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4:38
Today is Wednesday, January 14th, 2026.
4:41
We are live from the TVP Ultradome, the temple of technology, the fortress of finance, the capital of capital.
4:49
>> We have a smoke grenade, and it's not a sponsored smoke grenade.
4:52
We should have put a brand on there.
4:55
>> We should >> throw that smoke grenade, Jordy.
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Let's check out the new graphics.
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>> Easy use corporate cards, bell pay, accounting, and a whole lot more all in one place.
5:12
>> That doesn't work very well.
5:12
Well, >> you know about ramp.
5:14
Uh you also know about Microsoft who's making some waves because they jumped.
5:19
They were on truth social scrolling as they do.
5:21
Their comm's department was probably like, "What's going on?"
5:25
No, of course they were talking to the Trump administration.
5:27
>> Have you ever scrolled through social, by the way?
5:30
>> It's >> It's like five five ads for every one post. >> The ads are crazy. >> And they're crazy. >> They're crazy. >> Crazy.
5:38
[laughter] The ads are like are like, "Are you a real patriot?" Yes or no.
5:41
And no matter what you click, you just immediately go on to the next state like next phase of the funnel.
5:47
And then they'll just be like, "Gra, glad to hear it, Patriot. How about $200 donated?"
5:51
You're like, "Actually, 100."
5:53
And they're like, "200 it is."
5:55
[laughter] And you're like, "Okay, >> this is clear.
5:58
I'm clearly clicking an entire image that just has buttons there.
6:02
They're not actually buttons."
6:04
>> Uh, it's >> Well, they have Truth Social.
6:05
They have a Truth Social ETF now. >> Wait, what? What?
6:09
What's in the Truth Social ETF?
6:11
>> Invest in the Patriot Economy. >> Oh, okay.
6:15
Truth Social is really the uh going building everything everything.
6:21
>> Are they building nuclear power plants too now? >> What? >> I'm sure they are.
6:25
>> What a time to be alive.
6:26
>> Well, we have a lot of great folks joining the show today. Let's the linear lineup.
6:32
It's the system for modern software development.
6:34
Linear is building is a purpose-built tool for planning and building products.
6:38
And we have >> Brian Chesy from Airbnb. It's Chesk day. That's right.
6:44
We have from Robin Hood now, Aether Flocks.
6:47
He's the founder and CEO of that company. Space data centers.
6:52
Uh Gabriel >> from Noise, Alfred from Listen Labs, and of course capping it off with >> Mark Benny off.
7:01
>> Is the lightning round somehow sound?
7:01
We got Noise Labs and then Listen Labs. We need Signal.
7:06
We need the the founder of Signal on the show. >> Moxy Spike.
7:09
Well, I actually I I Moxy is going to come on the show >> today.
7:14
>> He's got a So, >> you got noise on the show.
7:15
We need signal, >> but he has a new focus LLM called Confer.
7:20
We're going to get him on the show. >> Awesome. Yeah.
7:22
No, I I I'm a huge fan of Moxy Marlin Spike.
7:24
Um >> and and I'm excited that to hear that he's coming on the show.
7:28
Um well, let me tell you about public.
7:30
com investing for those who take it seriously.
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They got stock, options, cryptos, bonds, treasuries, and more with all amazing customer service.
7:39
So, Microsoft I wrote about Microsoft and how they are negotiating the political backlash to AI data centers increasing power prices.
7:45
Uh Donald Trump posted on Truth Social.
7:49
He he and and the key the key line in here is really just that he says uh he you know he's talking to all the American tech companies but mostly he wants to make sure Microsoft is going first and they will make major changes beginning this week to ensure that Americans don't quote pick up the tab for their power consumption in the form of paying higher utility bills.
8:14
Um there's been a number of AI backlashes that have happened over 2025.
8:20
2025. uh you know the the the new technology came out everyone was there was a lot of excitement in 23 24 in 25 things got serious the numbers got really big the impacts got big and the stories about the potential risks to the rewards started cropping up uh
8:37
>> and one of the challenges is the early AI generated videos were pretty bad and so people were like these are bad my power bills going up I don't like this point now this move from Trump and Microsoft almost seems a little late because the videos are getting really good, [clears throat] >> right? So, I think people might start
8:52
So, I think people might start saying, "Hey, >> it's totally worth it. It's totally worth it."
8:56
Seeing those little You saw those those four cats on the boat.
8:58
That was >> I haven't seen that one. >> Pull it up, Tyler. We got to see that line.
9:03
Find the four cats on the boat.
9:03
We will get at some point.
9:06
Uh I did see a uh an AI video of people racing full uh full 18-wheelers with the boxes in the back.
9:15
You know how sometimes there will be real races with uh with uh >> Yeah. this video >> rigs.
9:21
>> See, I think most people would see this and say, "Can we get some sound?"
9:26
>> There's no Yeah, there's no amount of of uh power [music] bill. >> That's pretty fun. >> Okay, turn it off. Turn off the sound.
9:33
[laughter] >> But anyways, I >> Yeah, it's worth it. Worth it every clearly. Yeah. Yeah.
9:38
You see that and you're and you're like, "Yeah, I >> I think most people would see their power bill ticking up and realize that uh they're getting this content for free.
9:47
They they got to pay for it somehow.
9:49
There's no free lunch, of course. >> Yeah.
9:52
The the the power bill narrative is the one that I think stuck the most and became the biggest issue for AI companies to contend with in 26.
9:59
Um the water debate was sort of debunked pretty quickly.
10:04
Uh there were a number of just it sound seemed like mathematical errors in some of the reporting that was claiming that data centers used a lot of water.
10:13
And then you just talk to the data center guys and they're like, "Uh, yeah, we actually we do use a bunch of water, but then we recycle it and we just circle it circle it around and we actually don't dump it out and waste it."
10:21
And so you're just like, "Yeah, why would that's over?"
10:23
And then we're like, "But what about the power?"
10:24
Like, no, as soon as we use the power, the power's gone forever.
10:26
Like we trans we we we we use the power to generate and then we need more power.
10:30
So the power thing stuck around.
10:32
Uh there were other AI backlash narratives that were cropping up.
10:36
The oneshotting stories were very harrowing and a lot of people experienced someone who sort of went off the rails when GPT psychosis like that one felt real but it also seemed very preventable with aggressive guard rails.
10:50
The whole time it seemed like look these labs are as soon as they're made aware of this they're going to put a reality checker in the flow.
10:56
And so if you're 20 prompts deep >> Yeah.
11:01
>> Uh it'll just run an extra query and say does this seem crazy?
11:03
like does this seem like two crazy people talking to each other?
11:06
Okay, let's shut it down.
11:08
Like it was pretty simple.
11:08
And you can solve it just in software.
11:09
And when it's a product issue, you can solve it with a weekend hackathon. You can just lock in.
11:16
It can be one cloud code prompt for all I know.
11:17
You you can you can make the change to the app.
11:19
And I actually noticed this the Claude app has a pretty short context window like chat length.
11:27
[laughter] Like if you're if you're chatting with Claude and having it do I wanted it to pull the market cap for every single one of our sponsors and I was a couple prompts deep and it was just like this is you maxed out the context window.
11:38
You got to start a new chat which is sort of annoying but >> what was the market cap >> over five trillion let's go.
11:42
We have some breaking news today.
11:45
Uh but TVPN sponsors have been having a good year.
11:49
Uh obviously Google Gemini is a big piece of that but uh but we do have some we do have some very large companies supporting this show and we uh thank them for their support.
11:56
them for their support. We also thank the smaller companies that haven't raised a lot of money like Turppuffer Serverless Vector and Fulltech Search built from first principles on object storage fast 10x cheaper extremely scalable hey one day maybe it's a 10
12:09
trillion dollar company maybe it's the entire market cap I can see it >> um so uh the power one was tricky because with power uh you know the data seemed real on the actual price increases you looked at the power usage numbers and then you just See, demand is increasing. Supply is staying flat as it
12:28
Supply is staying flat as it always has been for decades in America.
12:32
We haven't been building a lot of power infrastructure.
12:34
When when demand increases and supply stays flat, we know what happens to prices. They increase.
12:39
This is basic supply and demand.
12:39
Uh yes, we can build nuclear power plants, but we had Scott Nolan from General Matter on the show yesterday.
12:44
He's working extremely hard on this.
12:47
He says, "Hey, we're going to be online in end of the decade." End of decade.
12:51
>> There's a lot of amazing folks.
12:51
We've had Doug Burnau from uh Radiant on the show.
12:55
We've had Isaiah Taylor on the show.
12:57
Uh, as aggressive as these founders are, >> they're trying to goitical this year.
13:04
That just means, think of it as testing. >> Exactly. It's still years away.
13:05
And so, uh, and then solar panels.
13:08
Solar panels uh, we can deploy those, but uh, that's still slow and that doesn't solve the base load power.
13:13
What if you want to use a deep research report in the middle of the night or generate a cat video at 2 a. m.
13:21
when the sun isn't shining?
13:21
Of course, you can do it somewhere else, but uh but it it doesn't solve. It's not a panacea.
13:26
And so, you got to build more power infrastructure. That takes time.
13:30
And I don't think very many Americans care about what the the the supply dynamic of power in America will be in 2035.
13:38
If just last month they saw their power bill go up by 20%. Yeah.
13:42
They're like, "This is hitting my pocketbook today and I'm upset."
13:45
So Bloomberg reported that a reported a 267% wholesale electricity price increase if you're near a data center.
13:54
So basically if you're within 50 miles of a data center, this is probably affecting you in some way.
13:59
Although it's there's a huge amount of variation.
14:01
Um, and it's now uh even even if you're, you know, like uh like even if you were able to pass that cost on to consumers, which is what's happening in the short term, it's starting to actually cause delays in data center buildout. So there's $64 billion. >> Yeah.
14:21
One one thing here that I think is worth noting is consumers if have have very real reasons to push back, right?
14:29
It's not like if they don't have a local data center, they can't use AI products, right?
14:32
Like it doesn't impact them at all.
14:34
Maybe there's jobs that come.
14:38
>> I'm kind of I feel like I'm missing out. I want one.
14:39
[laughter] >> I want one. There's empty buildings.
14:43
>> We did we did joke about moving the show to Abalene.
14:44
Uh but uh but yeah, it's very real thing.
14:48
It's not like, hey, you know, there's a new football stadium being built and suddenly you're going to be able to go watch. >> Yeah.
14:54
Like you could be a football fan, but even if you're an AI fan, you're like, I don't need it in my backyard. >> Yeah.
14:58
You're just like, I already have all the products.
14:59
And that's the big thing.
15:00
It's like >> power bill goes up.
15:01
Uh, you know, what do you get in return? Nothing. >> Aura. >> Aura.
15:06
[laughter] >> A nice view. A nice view.
15:08
If you're a data center appreciator. >> Yeah.
15:12
Well, uh, before we move on, let me tell you about Cognition.
15:14
They are the makers of Devon, the AI software engineer.
15:17
Crush your backlog with your personal AI engineering team.
15:19
So [applause] $64 billion in data center projects are currently held up and they face delays or cancellation because of opposition from local communities who say we don't want this data center because prices are going up.
15:34
Now there's a couple other reasons.
15:35
Some communities uh are still focused on the water issue.
15:38
Uh there's environmental impact questions.
15:40
Uh noise pollution during the construction process and even aesthetics.
15:44
There are some people who say not in my backyard.
15:49
I just don't want a big white square building.
15:52
>> Yeah, >> maybe it needs to look ornate.
15:52
Maybe it should maybe should have some, you know, aesthetics. Put some windows on it. Token cathedral. >> I don't know.
15:58
Um I don't know how big that that feels like a less less important one.
16:02
But there's a lot of communities that care about the the beauty of the community, the natural the natural beauty of whatever they have and the fact that it feels like homes and it feels like it feels like yes, there's a there's a Walmart there, but I know a guy who works there and I know the cashier and I go there and I walk in the data center. You'll never go in. They don't do tours.
16:20
There's no reason for you to go.
16:21
>> Walmart is employed and it's a it's a it's a product for the community. >> Exactly. Exactly.
16:27
So, even if the Walmart's sort of ugly, at least it has a brand and you know, okay, well, I can get something there.
16:31
It does something for me.
16:32
Whereas this data center, is it serving me Netflix? Is it serving me slop? I don't know.
16:36
My slot might be coming from somewhere else.
16:38
So, uh, interestingly, uh, the anti-AI issue is seemingly very bipartisan.
16:44
Data Center Watch, which is this uh research group, claims uh in the affected districts, the opposition is 55% Republican, 45% Democrat.
16:56
So, pretty much just across the board a bipartisan issue.
16:59
Um and you know, tech has obviously been worked very closely with Democrats in the past, worked very closely with Republicans more in the more recent history.
17:07
Uh but now they're facing >> Yeah.
17:10
And I think I think it's easy for people >> in tech to say, "Oh, you're just a you're these are lit. It's blah blah blah."
17:17
But it's actually not that. What's the incentive? >> Why do I want this? >> Yeah. Yeah. Yeah.
17:22
Especially because like it's going to get built somewhere.
17:25
It might it might as well not be in my neighborhood.
17:27
It's very it's it's the easiest nimi argument to make. >> Yeah.
17:31
>> Um so let me tell you about Crowd Strike. Your business is AI.
17:33
Their business is securing it.
17:35
Crowd Strike secures AI and stops breaches.
17:41
Um, so Trump picked up the story on Monday.
17:43
He says he's working with American tech companies to make major changes to ensure that Americans don't pick up the tab for their power consumption.
17:50
We're going to talk more about how that actually works out um uh in the form of higher utility bills.
17:56
Microsoft stepped up first and I think the first mover advantage here from a messaging perspective is pretty strong actually.
18:02
I think it's a very good move.
18:03
Now, uh to be clear, this isn't entirely new for the hyperscalers.
18:05
Google actually has a program called the clean tariff uh clean transition tariff where they overpay for electricity in certain markets, certain data centers, and Amazon uh pays a surplus above electricity costs already.
18:18
Uh but Microsoft is uh unique in the timing and in the volume of the announcement.
18:23
like it's a whole story in the Wall Street Journal and they've actually put uh a face to the program with Brad Smith who's the president and the vice chair of Microsoft uh giving quotes laying out a five-point plan.
18:37
He talks about a number of environmental issues as well.
18:40
He talks about water too that they want to be net zero on the water that they use.
18:44
In fact, I think Microsoft >> and that's such a that's such >> it's a lamp. It's a lamp.
18:47
Yeah, it should it should be a lamp.
18:48
Uh but it's still good to just say, "Hey, you know, I if that was a talking point that you were going to hit me with, we already got it sorted."
18:55
Um also, uh Microsoft is planning to be, I think, completely net zero on the carbon emissions by 2030.
19:04
And by 2050, they want to be so carbon negative that they will that as a company since the dawn of Microsoft in the 70s, they will have emitted negative carbon emissions over the entire life cycle of the company, which is interesting.
19:18
Um but um so Microsoft's exact language is they are committed to paying high enough electricity rates to cover the electricity costs of the data centers so that they aren't passed on to consumers.
19:30
Now a true free marketer is probably against this.
19:33
Why is one watt of electricity more expensive for one person or another?
19:40
If I'm watching Tik Tok and you're, you know, building the next and you're curing cancer, >> you know, on your laptop, >> why do you have to pay less than me?
19:49
Why are we putting a a value judgment on uh a particular use of a public good?
19:55
Most public goods like the roads cost what they cost, uh whether you're driving an ambulance or whether you're driving.
20:03
>> Zack Meyer says, "Would be cool to see a Microsoft liquid death collab for water that was used in a data center."
20:09
[laughter] >> Used water.
20:12
Somehow I I have no idea if the water that comes out of a data center is is drinkable.
20:16
Uh >> well, of course, you can just filter it.
20:19
>> Filter it again and then it'll be good to go the liquid death.
20:22
>> Um so, uh the the the the the diehard free marketers would argue that the government should stay out of supply and demand issues.
20:30
Let prices rise and there will be more of an incentive to build more power generation capacity.
20:34
Prices will stabilize naturally.
20:37
Uh but there are political realities and new capacity cannot be brought online in the blink of an eye.
20:44
It takes time to build these things.
20:46
Uh even if you're just going with uh natural gas, it takes time. There are backlogs.
20:50
At a certain point, you buy all of the natural gas turbines and then you need to be build more turbine factories.
20:57
That's why boom, supersonic is getting in the game.
20:59
Um and at a certain point, you know, you have to build more factories to build more factories and it does get slow.
21:04
And then there's also a capex consideration because if you're a if you're an electric if you're a a power company and you say, "Oh, great. The rates are going up.
21:16
There's a data center in my area.
21:18
They're going to buy a ton of electricity.
21:19
I got to bring a new power plant online. Uh, that's great."
21:21
And then you go to your team and you're like, "Okay, we need to put up how much money and where's that money coming from?
21:28
And we got to pay for Yeah, we're going to finance it, but we still have to pay for a bunch in the front and it's going to hurt e the interest payments on that.
21:33
we're not going to we're not going to be making money from this new power plant for a while.
21:36
So, we have to pay the interest.
21:37
So, we have to raise prices.
21:38
So, then prices do go up even if they are responding as fast as they can.
21:42
So, um so there's a there's a few different dynamics there that basically Microsoft and the big tech companies I think will be saying, "Hey, look, we want no excuses from power companies to ramp up production, ramp up ramp up capacity, and so we're willing to pay higher rates.
21:56
Hopefully, you can pass those uh th those that revenue on into bringing up capacity."
22:00
Um, so I think overall Brad Brad Smith is playing the game on the field.
22:05
Uh, and uh, the good news is that it feels like Microsoft, it seems like Microsoft can afford this.
22:10
So some numbers, electricity represents 40% of data center opex. Um, about seven 7.
22:14
5 million annually per major facility.
22:19
Now Microsoft has over 400 data centers.
22:23
Uh, and so energy is an is a significant line item.
22:28
I think like three billion a year in electricity, something like that. That's very rough.
22:32
Probably got to go to semi analysis for the real number, but uh this is back of the envelope stuff, but again, three billion in energy cost for 245 billion in revenue, Microsoft's going to be okay.
22:43
If they pay a 50% premium on all of their electricity across the entire portfolio, uh they were talking about a billion dollars of extra cost.
22:52
That's less than 1% of their operating income.
22:54
So this shouldn't be a you know a major rethink on the company.
23:01
It's uh but it is a big step towards um towards alleviating the political pressure and the fears of of uh higher energy prices.
23:12
>> Satya is simply the goat. He's my goat.
23:15
>> He does he does appear to be the goat.
23:17
Play that goat noise while I tell everyone about apploving.
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Profitable advertising made easy with Axon AI.
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23:27
Uh, >> no, I think it's I think it's super smart.
23:32
I think it was inevitable.
23:32
Trump uh needs this for the midterms.
23:34
He's putting pressure on everyone, right?
23:39
Credit card stuff, data center stuff.
23:41
We'll see more of this and uh yeah, being being the first mover ultimately only the first mover, the one that sort of like says like, "Hey, yeah, we're we're excited about this." Yeah.
23:51
>> Is the one that gets any credit, right?
23:54
doing this it they don't they're not going to get credit for it.
23:57
>> Yeah, it's a weird sort of game theory dynamic where uh it it this will probably wind up landing like a small tax on the entire on all the hyperscalers or all data centers as a as a as a broad like uninforced.
24:09
It won't be a true tax, but they will all be paying it because the political reality is necessitated.
24:17
Um but the but the first mover gets the good press cycle which is funny.
24:22
Uh it is uh it is from truth social to corporate concession.
24:27
Like that is the era we are >> pipeline.
24:30
>> Uh Tyler, what what was your reaction to this news?
24:33
>> Um you you're in favor of of data center subsidies, right?
24:36
Like you want the data centers to pay lower rates because it's more valuable to have >> governmentbacked data centers, >> electrical subsidies.
24:46
>> You got to feed Claude.
24:46
I mean, I I just think like this is kind of disappointing because it just it's telling me that like >> um >> if you imagine we have like a real free market. >> Yeah.
24:57
>> Uh there should be already insane incentives to build new energy supply. Yep.
25:01
>> And that's obviously not happening because energy prices would be going down. They're going up.
25:03
Y >> So it's like this is just like this is telling me that in the future we're not going to build nearly as much energy power as we want. Yes.
25:10
Or at least on any kind of like short-term scale. >> Yeah.
25:13
Um, >> it does feel I I think it feels like the energy market as a whole is is is at least in the short term much more zero sum than people thought.
25:20
It's there's a somewhat fixed pool of energy capacity and we're shuffling chips around the poker table trying to allocate energy effectively.
25:31
Uh, but it's the pie is not growing nearly as fast as people want.
25:35
which is why I was uh I was you know a big advocate for the theme of 2026 being energy and and uh and a lot of work being done across all different technologies unblocking all the different uh bottlenecks that exist to actually ramping supply so that prices
25:51
can neutralize and not and not be unaffordable because people do want to to to scroll Instagram reels and they want to watch AI slop and they don't want their bills to be through the roof when they go to charge their phone after watching four hours of Instagram reels. Uh
26:05
Uh >> uh Taiwan Semiconductor last week spent uh $200 million at a public auction to buy >> 900 acres of land adjacent to its existing Arizona property which will reportedly be used for the planned new facility.
26:20
So we're still waiting on this Taiwan trade deal.
26:22
Seems like as part of that uh TSMC will will expand uh uh their operations in in Arizona, which is very exciting.
26:31
and and they are basing their design for this off of uh Costco warehouses.
26:36
Nick here, uh the render here is uh is very sci-fi.
26:39
Uh I I've seen I've seen renders of their facility in Taiwan. It looks beautiful.
26:44
Seems like they're bringing some of that some of that aesthetic to Arizona.
26:48
Uh seems seems pretty cool.
26:53
>> This was an interesting exchange.
26:55
Somebody named uh Tom Leonard, candidate for governor in Michigan.
26:59
>> Uh he says, "This isn't a joke.
26:59
A friend of mine was offered 70,000 an acre for her farm by a data center company. 11. 2 million total.
27:06
This is what big tech is doing in Michigan.
27:10
>> Uh so anyways, somebody uh willing to basically overpay for farmland in Michigan.
27:16
>> Yeah, I remember on the University of Michigan campus, uh there's like these stickers and posters everywhere that are like stop the AI data center or it was stop the data center buildout.
27:24
>> And that's when you knew you had to drop out.
27:26
>> I was like, all right, this place is not for me. >> Oregon rejection.
27:29
You got to go back, take the take the fight to them.
27:31
Put up some posters that say yes on data centers. Put a data center in.
27:36
>> Subsidize the data centers.
27:38
>> Tear down the stadium. >> Yeah.
27:39
So, just just some context on that last exchange.
27:41
Matthew uh Zaitlin at Heat Map says, I think this is shared as an example of big tech doing a bad thing, but I don't know, man. 11. 2 is a lot of money.
27:51
The USDA says the average Michigan farm real estate value is $6,200 per acre.
27:57
>> So, they're paying over 10x the price. >> Yeah.
27:58
I mean, who know who who knows?
27:58
I mean, it's they could easily be paying a premium because of this >> uh land specific location or proximity to other projects that they have.
28:06
Uh but I wouldn't be s surprised if some some uh land maxers are going out and just buying up >> buy, you know, why wouldn't you try to buy up the farmland in in proximity to some of these other projects in hopes that uh in hopes that you somebody comes in?
28:22
I wonder how real this uh I wonder how real this text messages because I get a lot of spam text messages for business financing.
28:29
Oh, we'll invest in your company.
28:31
You just you just get like random spam all the time.
28:32
And you wonder if people are just throwing out like random numbers just for price discovery just to sort of like aggregate some sort of uh you know metrics across a whole pool of phone numbers and they're just sort of spamming it out.
28:46
Like if this person had said yes, what's the problem?
28:49
My wife got a spam text today that just said, "Uh, babe, I dropped my phone and it broke."
28:56
>> She immediately texted me and said, "This isn't you." Right. >> Oh, interesting.
28:59
Pretty an interesting interesting kind of like loop to get somebody uh and and to I I imagine send me $1,000 so I can get a new phone. >> Oh, sure, sure, sure.
29:09
>> Do you remember the text that Ben got?
29:11
He was asking him if you want to get stakes.
29:12
[laughter] >> Number spam.
29:15
That was the best spam ever.
29:18
It said, "Let's get steak tonight."
29:19
>> Let's get steak tonight.
29:19
I mean, [laughter] should have said yes. >> Yeah.
29:24
>> Did you respond and [snorts] just say, "I'm in." >> No, I just posted it.
29:27
I I should have responded, though.
29:29
>> Oh, missed missed an opportunity to to make a new friend.
29:32
>> Well, now is a great time to tell you about our newest sponsor, Cisco.
29:34
Cisco is critical infrastructure for the AI era.
29:41
>> They're building the foundation for AI powered enterprises.
29:42
We are very excited to be partnered with Cisco. >> It's truly an honor. It is. It is >> truly an honor.
29:49
>> Um, in other news, the stock market is down. The Dow falls.
29:51
Uh, weighed down by JP Morgan. Not good. Not good news.
29:57
There was a rocky quarter for JP Morgan and it weighed on the Dow Jones Industrial Average. Headline prices rose 2. 7 from a year earlier. 2. 7% according to the CPI.
30:06
Uh, this was in line with expectations and November's rate.
30:09
Core CPI, which excludes food and energy prices, also held at the prior month rate.
30:15
Now, overall, weren't things doing wait, where did they say here? I don't have this.
30:21
JP Morgan earnings investment fees both fall off.
30:23
JP Morgan reported that the bank's profit fell 7% in the fourth quarter, dragged down by a change from its deal to take over the Apple card credit card program and surprising slip in investment banking fees.
30:37
The investment bankers are not making enough money.
30:41
Still, the nation's biggest bank saw revenue increase for both the quarter and for the full year and was optimistic about the trajectory of the US economy and consumer.
30:49
Uh from Jamie Diamond, he said, "Consumers have money.
30:55
There are still jobs even though it's weakened a little bit."
30:58
He said on a call with analysts, I saw a great Jamie Diamond hype reel on Instagram reels the other day. It was fantastic.
31:04
Uh, in other news, the uh there's more details about that Apple Card uh deal that Jaime Diamond worked through. We should pull this up.
31:14
Uh, behind the unraveling of Apple's credit card partnership with Goldman Sachs after two years of negotiations, one of the biggest credit card deals of all time will see Goldman replaced by JP Morgan on Apple's credit card.
31:28
Before we read through this, let me tell you about Shopify.
31:30
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
31:39
So, in early December, a long delayed deal hung over a call between JP Morgan Chase chief executive Jamie Diamond and Goldman Sachs CEO David Solomon.
31:49
Executive, >> if you don't know David Solomon, >> you probably know him because >> DJ D Soul. >> DJ D Soul.
31:55
But he also runs a big bank called Goldman Sachs. Very cool.
32:01
>> Uh, executives of the two banks had been negotiating for months on trading the massive Apple credit card program and it's roughly $20 billion in balances, but the talks had stalled.
32:10
Privately, bankers on each side were blaming the other side for needlessly slowing down the negotiations. You're moving too slow.
32:19
JP Morgan had secured a discount on the balances, but to help cover potential losses, uh, they they've secured a discount on the balances.
32:27
We talked about this where normally these balances they trade at a premium because people expect them to be paid back with interest.
32:34
But in this case they were JP Morgan was going to get a discount but they wanted more protection in case the loans grew worse in case there were higher than expected defaults.
32:43
Um Goldman executives meanwhile didn't feel the need to bend much now that the Apple program was finally looking profitable.
32:54
Some executives on both sides had started questioning whether to walk away.
32:57
Diamond and Solomon got on a call on December 8th.
33:00
According to people familiar with the matter, they discussed why the Apple deal was taking so long to close and agreed to break the log jam to see the deal through soon.
33:10
People said [snorts] uh just before the new year, the banks finalized a deal that was announced last week, confirming the Wall Street Journal's earlier report.
33:17
A little patting on the back for the Wall Street Journal.
33:23
>> We're getting the scoop.
33:23
Uh, the deal brings two of the country's most influential companies together.
33:26
JP Morgan is adding the flashy program to its credit card lending operation and strengthening its connections to the trillion dollar tech giant at a time consumers are increasingly using phones and watches for payments and managing their finances.
33:41
Apple gets a new partner with a sprawling consumer base that is eager to build the card.
33:46
Goldman gets closure on its failed venture into consumer lending that has brought the firm billions of dollars in losses, a chapter it is hoping to forget.
33:55
Moving the Apple credit card was never going to be simple.
34:00
Card programs this big aren't put up for sale often and few buyers few potential buyers exist.
34:05
Apple is famously finicky about details and control including with its credit card.
34:12
Before launching the program in 2009 uh 2019, Goldman and Apple agreed to unusual terms that other banks bocked at taking over.
34:19
The interested executives were especially worried about higher than normal delinquencies and subprime exposure and wanted huge discounts to consider a deal.
34:29
Even still, almost nothing about the process of finding a bank to replace Goldman has been normal to begin with.
34:34
Goldman began looking to exit from the contract with Apple only a few months after it had extended its partnership with the tech giant to the end of the decade.
34:43
Apple and Goldman had discussions with larger and smaller credit card issuers American Express, Capital 1, Synchry, Barlays, and Satander as well as tiny fintexs.
34:50
Apple even debated bringing in private credit firms to help a smaller card issuing entity take over.
34:58
But it didn't go that way and they landed with uh JP Morgan. So very interesting.
35:03
Anyway, let me tell you about Labelbox.
35:06
Delivering you the highest quality data for Frontier AI.
35:11
[applause] >> Get in the box. The label box.
35:14
[laughter] >> The label box. Um, moving on.
35:14
Uh, OpenAI is going to be running another Super Bowl ad.
35:21
It's in the Wall Street Journal.
35:23
Open AI to run ad during Super Bowl.
35:26
Why don't we >> we need to watch last year's ad react to that and see what we think will change. What will stay the same? What will they do?
35:35
The artificial intelligence company behind the popular Chatty PT tool is set to broadcast a 60-cond commercial during NBC's broadcast.
35:44
>> All right, with sound. With sound.
35:45
>> Let's watch it with sound if we can.
35:45
The ad is the latest component of OpenAI's expansive marketing expansive marketing offensive which began last year with its first Super Bowl commercial.
35:56
>> Uh we don't have sound >> into Okay. >> Okay.
36:00
We uh the production team is telling us unfortunately we do not have the technology to play sound on a video. >> Let's work on that.
36:08
>> But uh it's uh if I remember the song correctly it's like like something like that. >> Really?
36:15
Is it is it a is it a licensed song?
36:19
>> Because you were thinking that they should they should license uh Creeds.
36:22
Can you take me higher for this next one? Right.
36:24
That was what you thought. >> Yes.
36:26
>> Can you take me higher?
36:30
>> And it's like to a higher plan. You're on the free plan.
36:32
Please upgrade to the $200 a month plan. Oh, we got it. Let's go.
36:36
We do have the technology. AGI is here. Okay.
36:39
So, there's a someone throwing a spear. We create fire. Then the wheel.
36:44
Then the wheel with spokes. Then the horse. The horse wheel. >> Man created.
36:50
>> We created the horse and corn. We created corn.
36:52
Maybe they should use a corn song. Freak on a leash.
36:54
That's the song they should license >> and an a nod to corn.
37:02
I mean, the motion design is incredible.
37:04
Like it is it is a very well done piece.
37:07
So they go inside the skeleton, build the 747, take a look at DNA, invent movies, TV news. That's us. They go to the moon.
37:15
Somewhat equally important. >> Create the internet.
37:20
>> And then you start talking to the computer. >> What bird is this? >> And now the merge. >> You got AI.
37:27
>> What do you want to create next?
37:28
>> And then you get the blue chat dot. >> Yeah.
37:31
So So I I love >> I love this. Yeah.
37:36
>> It was just not necessarily >> I didn't need a Super Bowl ad for me. >> Yeah.
37:40
I need a super ad for the Clydesdale crowd, right?
37:42
The people who are are are maybe on the fence about AI.
37:47
>> Um, >> but yeah, as a technologist, it has the aesthetics of like, wow, this is the coolest tech company ever.
37:54
>> And this is like this this has the vibe of Apple.
37:56
This has it has a lot of throwback stuff.
37:58
It It feels like high technology. It feels techy elite. It feels designed. It feels refined.
38:05
>> It's possible at the time they were like, "Look, we're growing so quickly.
38:09
We don't really need to run a Super Bowl ad.
38:10
Yeah, >> let's just let's just flex on everybody a little bit by running one.
38:15
>> I mean, there's a certain >> But this year, I expected to be much more pragmatic >> about what you can use to do to do something >> exactly how they want >> Yeah.
38:25
>> the average American to think about chatbt. >> Yes. Yes.
38:29
>> Where it integrates into their life, right?
38:31
>> And so, do you think it'll be one specific use case?
38:33
Like there's been OpenAI videos about chatbt helping you cook dinner and I actually got an odd email from a friend uh all about how he loves cooking with friends and how food is this important thing and then he was calling out the chatbt video on food being like I don't like this because it's it's taking away the one thing I like as a human and >> I actually had a funny using an LLM to to for for a pancake recipe last week >> and it completely.
39:03
The pancakes really did not work [laughter] >> like because it's it's it's basically taking the average of all pancakes.
39:11
>> You made a mid pancake >> and it just made the most like runny mid pancakes. Really bad. >> Interesting.
39:17
>> Uh I I I I don't know. It' be interesting.
39:19
I wonder if they try to do anything on the like anything on the um it's probably too early for commerce side.
39:25
You could see some of that, but maybe they want people to know commerce is coming.
39:28
Uh I could also see them trying to make it interactive somehow.
39:33
You could imagine like when >> you know maybe this >> when is [laughter] no no but I was going to be like ask like talk like like uh chat with chat chat like tell chat GBT you want to I don't know.
39:46
Well, well, it it could like they could sort of launch like Chat GPT Sports or something where you know you're like the demo of what it's showing you is that if you have chatpt as your second screen during the Super Bowl, you're going to pull up more interesting stories about the players.
40:06
You're going to pull up statistics.
40:08
You're going to be able to understand the the like add more context to your experience of Super Bowl watching.
40:13
Even like oftentimes if I'm watching the Super Bowl, I'll see an ad and I'll, you know, go and go to Google and say, "Well, what are the greatest Super Bowl ads of all time?"
40:23
And I'll wind up on some listical.
40:25
And Chachd, of course, can generate that type of stuff all the time.
40:28
You could filter and say, "Show me the best uh show me the best Super Bowl ads from tech companies back in the do boom.
40:35
I want to know about those." And you can go anywhere.
40:37
Uh, and that is the magic of Chachi PT.
40:38
Uh, there's a whole bunch of other ways that they could try and contextualize it.
40:42
They could try and be emotional, go with Chachi PT health.
40:46
Uh >> I wonder if they'll do anything on the dis with the new Disney integration like if they wanted to spark like another Studio Giblly moment is coming online.
40:54
Originally they said some in January.
40:56
So maybe the timing lines up.
40:59
That would be really wild.
41:02
>> Yeah, you get Darth Vader in there or something or >> I mean there's a lot of characters to choose. >> Characters. No, I was Yeah.
41:06
B I was saying like try to try to use a Super Bowl ad to prompt people to make >> go to >> go to Chat GBT turn yourself >> turn your Super Bowl party into a Disney themed thing.
41:18
Yeah, that that would be very good.
41:20
>> Uh yeah, surprise celebrity appearance or celebrity endorsement would be would be good.
41:25
Uh they they they've sort of shied away for >> Scarlett Johansson.
41:28
Maybe they can bring her back in >> reversal.
41:31
Reversal and getting her back on the team would be fantastic.
41:33
Um >> uh but but I expect that this will be this will be the AI Super Bowl.
41:40
>> You think there'll be even more ads? >> I'm sure there will.
41:43
>> So for context, tech companies across Enthropic Google, Microsoft, OpenAI, and Perplexity collectively spent 333 million on linear TV ads promoting their AI offerings in the United States just last year.
41:57
And that was up 43% from the prior year according to estimates uh from an ad tracker spot.
42:02
Uh they also shelled out 426 million on digital ads in 2025, more than triple their 2024 outlays. So interesting.
42:11
Digital is growing faster than linear.
42:14
That's I would not expect that.
42:16
I would expect uh the the digital to have been really really popular and then them to have just jumped into linear.
42:22
But I guess they've been >> Wait, are they talking about like streaming ads? >> Uh maybe. It's from sensor tower.
42:27
It just says digital ads, which I assume is Facebook, Google ads, all that sorts of stuff.
42:34
Uh, Anthropic kicked off its first major push into advertising in September and has been blanketing NFL, NBA, and college sports games with ads for its clawed chatbot.
42:43
It shelled out an estimated 16.
42:45
5 million dollars on linear TV ads in 2025.
42:51
Uh, despite boasting a base of over 800 million weekly users, OpenAI is, and that is such a stale people to download this app.
42:59
[laughter] >> What do you mean?
43:02
>> Like they they really can't.
43:02
I mean, they're not in the top 25 apps. >> Wait, which one? >> CL. >> Oh.
43:07
Oh, you're talking Claude. I I So, sorry. Sorry.
43:09
That 800 million weekly active users is for OpenAI for check.
43:13
>> No, I know, but I know I know.
43:13
So, they spent they've been spending money all over.
43:18
>> Well, you know, you know why?
43:18
You know why the the claude is not uh at the top of the app store charts?
43:23
It's because if you generate a deep research report on the iOS app, it will not read it to you out loud.
43:30
It doesn't have that functionality.
43:32
And that's clearly a gap that everyone has experienced and recognizes and and as soon as they run into that, they uninstall it and they don't recommend it to their friends.
43:39
So, if you're listening Anthropic, please add that functionality.
43:43
I want to be able to listen to deep research reports.
43:47
>> I just think how do they figure out how to get it?
43:49
How do they figure out how to become a real player in consumer?
43:53
because clearly they want to otherwise they wouldn't be spending that money.
43:56
>> I mean they need hooks.
43:56
They they you you need you need some viral flywheel like uh so the the chat GPT number 800 million weekly active users that feels woefully out of date.
44:05
It feels like they were well over a billion and they're just waiting to actually drop that press release at a at a key moment and now is not the right time to wow everyone with the real uh usage numbers.
44:16
But I I definitely think that they're beyond that.
44:21
This number is very stale.
44:21
Like we got this 800 million weekly number months and months ago and it must have grown.
44:27
Um Google obviously has a whole bunch of hooks into the Gemini ecosystem through Gmail and Google.
44:32
There's so many different entry points.
44:34
Claude as an independent app doesn't really have that.
44:38
that. Also I think just on a product sense uh chatbt I do think that the holidays were successful and uh it was not discussed on on X the tech elite and the tech you know like anyone who's like in tech was focused on claude code they were doing vibe coding projects they had
45:01
time off from work and time to lock in and play around with like the hottest new coding agent uh so people weren't People were people knew that Chachi PT could do images, but right before the holidays started, ChachiPT launched the image tab. And if you go to the image
45:15
And if you go to the image tab in the app, the most interesting thing there is that it's not just a prompt box. They have preloaded. Have you seen these?
45:25
Like it it will it will show you like retro anime.
45:27
Like it will show you it will show you like ideas like turn yourself into a bobblehead.
45:35
turn yourself into a sugar cookie or fisheye lens or ink work or pop art.
45:38
And so it's taking the work out of someone like most people in tech an image model comes out.
45:47
Studio Giblly thing happens.
45:50
Everyone's like what's the prompt? Okay.
45:52
>> It's too much to ask people to have an idea. It is.
45:54
>> We need to give them the idea and we need to make the image for them.
45:57
>> It it actually is too much.
45:57
It actually >> and then eventually when when you have your when you have your little uh sweet pee, whatever they're calling their new device. Yes.
46:06
>> It will just be generating images on the fly based on your day. >> Yes. Yes.
46:11
>> And then eventually you'll just be able to stay laying in bed all day long. [laughter] >> Yeah.
46:16
But I mean just from a product perspective, the chat GBT images tab is I think an important just growth hack which is something that they just have to do now because they're at that scale.
46:29
And I saw that people were generating images and then sharing them and they weren't screenshotting them or downloading them with some watermark.
46:39
They were clicking the share button in the chat GPT app and sharing a link to the chat GPT app that would show you the image in a preview if you shared it in iMessage or in or in a group chat.
46:49
Uh and that would onboard more people and those sorts of viral loops.
46:53
They they feel like oh the m the tech is so magical.
46:58
It just should it should just grow organically.
47:00
But yeah, it it already grew organically like the organic growth is is has was a billion people.
47:05
Now how do you get the next billion?
47:07
Well, you probably have to do some growth hacking and a product like images and chatbt with Disney characters and and links that beg you to install the app for yourself.
47:16
And Claude isn't quite there yet where there's an obvious thing that a huge swath of people can go to and then and then hook in and we can collaborate and I send you a link and then you install. >> Yeah.
47:28
The tough thing is like if you're spending all this money trying to drive consumer downloads. >> Yeah.
47:33
But then you don't have image generation at all. >> Yeah.
47:38
>> At what point why why don't they just even if that's not a priority for them? Yeah.
47:42
It still feels like a product that consumers really want. Yeah.
47:46
>> In their daily driver. >> Yeah.
47:48
>> And so at some point they may have to capitulate.
47:50
>> I mean I I don't know if they care about the the the app race at all the consumer app race.
47:54
It feels like Anthropic's been super focused on the enterprise, super focused on coding and that's been >> I know. I know.
47:59
They say that like >> all I'm saying is you can say that you're not focused on consumer, >> but you they run billboard ads all over LA. >> Yeah.
48:10
>> They're spending a lot of money on television. Yeah.
48:12
>> And so you kind of need to like make up your mind. >> Yeah.
48:15
You don't really advertise in NFL and NBA.
48:16
I mean, I guess enterprise buyers ad uh you know, watch those shows.
48:20
So 16 million, maybe it's worth it.
48:22
Uh but but but I agree with you generally.
48:24
Um >> their ad campaigns have been great. >> Yeah, >> that's it.
48:27
and maybe they just want to >> rub it in rub it in the face of the other labs.
48:32
They're also going public.
48:34
So they want >> they they they developing like real name recognition broadly I think is important.
48:39
But >> I mean, in theory, if they if they host a if they if they host Claude code in a virtual machine that you can access from a phone and have it write software for you, it should be able to go and, you know, set up an API with an image generator and generate you images.
48:56
And so you should be able to do that from the app.
49:00
Like cloud code, if I to if I ask cloud code to generate an image for me, it will figure out how to find an image generator, sign up for the API almost or at least I will give it the API key and then it will be able to generate images for me. Correct.
49:16
>> Um, yeah, it would ask you to like you would have to go generate the API key and stuff.
49:21
>> Yeah, >> but that's actually I'll try that right now. >> Yeah.
49:23
What what what happens if you just ask Claude code to generate you uh a picture of four cats on a boat or something like how does it actually work through solving that?
49:31
At some point it it it should it should you know prompt you to at least make maybe make a decision about which image generator you want to use and and at least ask for credit card information to pay for it.
49:45
Maybe it goes to a free image generator. I don't know.
49:47
Um, but the Wall Street Journal continues and we will continue after telling you about the New York Stock Exchange.
49:53
Want to change the world?
49:55
Raise money, raise capital at the New York Stock Exchange.
50:00
Um, selling to selling AI to the masses isn't easy, says the Wall Street Journal.
50:05
Due to sustained public fear about the technologies potential downsides, businesses have already cut jobs using AI task for tasks previously performed by humans and executives have articulated plans.
50:18
>> Why would the masses be scared?
50:18
Why would they be scared of this technology?
50:22
>> Half of US adults are more concerned than excited about artificial intelligence according to a spring survey by Pew Research.
50:29
That's a while ago, but >> only 10% say excitement outweighs their worry. >> Skill issue.
50:36
Just be in the 10%, right, Tyler? >> Yeah. >> Yeah.
50:39
Well, OpenAI's first big game ad positioned chat GPT as the next significant advance in human innovation, drawing parallels between >> Wait, this would actually this would actually be a great bit.
50:50
We should make an AI Tyler that we can go to >> and say >> and just we'll just we'll compare the two of you guys >> and this can this can just be a good uh barometer >> for AI progress.
51:04
How do you feel about that?
51:07
>> Um it could probably do a pretty good job cuz it's I mean it can already do like a talking head if you just put an image of me and then the voice you can clone.
51:14
>> I know but I don't think it would have your takes.
51:16
I don't think it would have your takes >> just say like or your or >> dwarash or >> it would say I'm sorry that's too controversial.
51:22
I can't hold that opinion.
51:24
[laughter] >> Uh well, OpenAI's first big game ad positioned Chat GPT as the next significant advance in human innovation, drawing parallels between AI and transformative inventions such as the light bulb.
51:37
More recent ads frame the technology as a relatable tool.
51:41
They feature people using the chatbot for everyday problems such as finding a recipe or searching for exercise tips.
51:51
Which way will OpenAI go in the new uh Super Bowl ad?
51:56
I imagine that they will go more uh proactive, more productive, more tangible.
52:02
There will be a human shot with a camera using the the app probably on the phone. >> Uh but we'll see.
52:09
Uh, in its ads, Anthropic has been positioning Claude as a partner for problem solvers rather than a threat to human intelligence.
52:18
Uh, yeah, why would you [laughter] why would you want to run an ad saying that?
52:21
Uh, this strategy anchored by the >> tele this is a Super Bowl ad concept.
52:23
We are not a threat to human [laughter] intelligence.
52:31
>> We are not a threat in >> don't worry about us. >> Yeah. How about a superis? >> We hear you.
52:36
We hear that you're concerned. >> Yeah.
52:38
Just just just saying this massive Super Bowl warranted.
52:40
Our Pdoom is actually really low relative to the true risk.
52:44
We think that the Pdoom should be low.
52:47
Everyone's like, "What are they talking about?"
52:49
>> 5% chance of annihilation by end of year.
52:52
>> Well, uh, if you're running the Super Bowl, you got to get on Reream.
52:55
One live stream, 30 plus destinations.
52:58
I want to be able to watch the Super Bowl on LinkedIn.
53:02
If you want to multiream, go to reream. com.
53:07
And I know the folks who have the rights to to the Super Bowl, >> SA really should push to get LinkedIn the streaming rights >> for sure.
53:15
Be a game changer >> for the Super Bowl. >> Uh okay.
53:18
So uh Gemini introduced a more personal Gemini today designed for you.
53:24
Personal intelligence they're calling it.
53:25
Uh personal intelligence draws insights from across your Google apps to provide truly customized responses for Gemini.
53:34
Learn all about it below.
53:34
They say, "Gemini already remembers your past chats to prevent to provide relevant responses.
53:40
But today, we're taking the next step forward with the introduction of personal intelligence.
53:43
You can choose to let Gemini connect information from your Gmail, Google Photos, Google Search, and YouTube history to receive more personalized responses.
53:52
Here are some ways you can start using it." Planning.
53:56
Gemini will be able to suggest hidden gems that feel right up your alley for upcoming trips or work travel because it'll know where you've stayed before, where you've been.
54:04
you'll know that I went to Austria and and recommend a different city, maybe. Shopping.
54:10
Gemini will get to know your taste and preferences on a deeper level.
54:12
Help you find items you love faster. Motivation.
54:16
Gemini will have a deeper understanding of the goals you're working towards. Look at your to-do list.
54:19
Privacy is central to personal intelligence and how you connect uh other apps to Gemini.
54:23
The new beta feature is off by default.
54:25
You can choose to turn it on, decide exactly which apps to connect, and can turn it off at any time.
54:32
Personal intelligence begins rolling out today as a beta to Google AI Pro and Ultra subscribers. That's me.
54:38
So, I got to turn this on.
54:41
I'm very interested in seeing um I I imagine that I will not be able to link multiple Google accounts because I have a personal Gmail and then I have a work Gmail and then I sort of want to integrate my old work Gmails that I think I have access to still because that says a lot about me even though I'm not really using that stuff anymore and I'm not actioning those emails.
55:04
Um, I could see that being important in terms of like building out a >> Yes, you were sick of switching between constantly switching between calendars and Chrome and having your personal calendar, work calendar.
55:18
Get ready to be sick of switching between LLMs. >> Yeah.
55:23
Uh, some of them have been have been surprisingly good at bootstrapping knowledge.
55:28
I feel like uh a few of the LLMs have been have surprised me by I'll ask a question and it'll just be like and here's the context for TVPN.
55:34
here's the TVPN angle and I'm like, "Oh, I forgot that I mentioned that to you or like you figured that out somehow or like yeah, you did something." I don't know.
55:42
The personalization is getting better.
55:44
Maybe this is the year when it really hits.
55:46
I know ChachPT introduced it as a concept a while ago, maybe almost a full year ago.
55:50
Uh, and it hasn't felt magical yet.
55:52
Pulse was cool, but it it I I never became like a daily active user of Pulse.
55:59
Um the the interesting question is like yeah is it is it a data source problem?
56:06
Is it an architectural problem or is it an actual like model level problem?
56:11
Are the models just not smart enough?
56:13
Do they not have enough data or are they not designed in the right way where they can actually go over all of your uh all of your information?
56:22
I was using the new uh Salesforce Slack bot that we're going to talk to Mark Beni off about at 2 PM and uh it was remarkably useful in Slack because I I'm not on Slack a lot.
56:33
And so I had a ton of notifications that had built up over months and I was able to go in and write a prompt or just talk to chat Slackbot and say, "Hey, like catch me up like what's been happening in Slack in this Slack workspace."
56:47
uh and it did a good job summarizing all the different uh key things where I was mentioned what was relevant to me.
56:54
Um I did pro it on what anthropic model it's using exactly and it's not using the latest and greatest uh 4. 5. It was using I think 3. 5.
57:04
It didn't seem aware of the latest models and also it didn't have the ability to search the web.
57:10
It didn't have the ability to to to act as like a fullfledged LLM.
57:13
You couldn't just ask it things.
57:16
It was it was very confined to Slack, but within that domain, it was pretty useful and it and it did help me like sort of get to like inbox zero in just like a couple minutes because I was able to just scan a digest of everything that's happening across all the channels instead of clicking through them, scanning, reading the threads, the going down the it was just able to be like here's the deep research report on it.
57:37
Yeah, I am waiting uh I'm waiting for the moment where people are like I'm not really interested in trying a new LLM that's hot because >> like having memory in the LLM and personalization is so important like waiting for that lock in moment don't think it's really uh you have some force lock in where a company is saying like we use this LLM
57:59
>> or or I mean vice versa where you know they're just it's just like yeah in the course of my day I use five different LLMs like on my phone I use Apple Intelligence and that's routing to Gemini and then I log into Slack and that's using the anthropic APIs, but uh it doesn't really matter because I don't care that they don't talk to each other. Uh like it's all it's all fine and
58:16
Uh like it's all it's all fine and they're and they and they work they they're good enough for the particular thing that I'm trying to do at a particular time.
58:22
That's another possible outcome here.
58:23
Uh Andrew Curran uh is is is summarizing some of the some of the news here.
58:28
Um saying that uh it includes Google Workspace.
58:31
Uh Google Photos is sort of interesting.
58:34
I wonder if that plays into, you know, nano banana.
58:36
You can have, you know, more suggested images.
58:41
Hey, do you want to touch this photo up?
58:42
Do you want to create some sort of holiday card?
58:43
Like what Chachi PT ultimately wound up doing with >> Go through go Google Photos and turn me into a dinosaur in every single set the GPUs on fire for sure.
58:55
>> Uh before we move on, Phantom Cash, fund your wallet without exchanges or middlemen and spend with the Phantom Card.
59:01
Um, >> uh, New York Times has some coverage today talking about, uh, IPOs of this year.
59:07
2026 may be the year of the mega IPO.
59:09
Not really new news, uh, for, uh, those of you listening.
59:14
SpaceX opening, Anthropic are going public.
59:17
Uh, they talk about, um, uh, Eddie Malloy from Morgan Stanley says, "We're going to get into a period of potentially unprecedented IPO deal sizes.
59:31
uh we are confident they're uh executable given the scale of these companies and the investor interest um uh in two decades I haven't seen private companies that are this meaningful and are this impactful said Jeremy Abson uh an investor at Irving investors not only are they bigger and more relevant but they're incredible companies with numbers that we haven't that we've never seen before ever.
59:53
Uh, I can't [laughter] I think they're uh I think everybody's excited to just get into these S1s.
1:00:01
>> Yeah, [laughter] >> I expect them to be uh extremely uh uh impressive numbers.
1:00:09
>> There's been a number of reports about like how bad the gross margins are, how much money they're losing.
1:00:13
Well, we're about to find out the real details.
1:00:16
>> It's going to be exciting times. Exciting times.
1:00:18
Um, so yeah, we'll we'll see.
1:00:20
All all the the geopolitical chaos, uh, you know, even even this this ruling around tariffs, which we didn't get today, uh, all this stuff is going to play into whether or not, uh, whether or not the window stays stays open. >> Yeah. Console.
1:00:36
Console builds AI agents that automates 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. Saks Fifth A.
1:00:50
>> Oh, >> Nean Marcus and Burgdorf Goodman filed for bankruptcy. >> Crumbling Sax guy.
1:00:54
You shop at Saks Fifth Avenue.
1:00:55
Have you shopped at Sakf Avenue?
1:00:57
>> I've never been a a >> department store guy.
1:01:00
>> Department Store guy ever.
1:01:02
>> You go straight to the Chrome Heart store.
1:01:03
>> You're You're the guy in line outside Supreme. >> Go direct.
1:01:07
>> And do they don't sell Supreme, right?
1:01:09
>> Maybe that's why they're going bankrupt. >> The hype beast move. >> Zero Chrome. >> Zero Chrome.
1:01:13
Um uh anyways uh they filed for bankruptcy protection late Tuesday.
1:01:21
Uh crumbling under billions of dollars in debt, a fring relationship with vendors and lagging sales.
1:01:24
The filing is the latest sign that America's luxury department stores once landmarks that served as immersive fantasy worlds for the wealthy and aspirational are becoming an endangered species.
1:01:35
Uh Jeffrey Van Raymon Don the former Neiman Marcus chief executive will return as Sax Global CEO.
1:01:44
He succeeds Richard Baker the chief executive and executive chairman who in 2024 orchestrated a $2.
1:01:49
7 billion acquisition by Sax of the Neiman Marcus Group which owns Burgdorf Goodman.
1:01:57
Uh Sax said it had secured roughly 1.
1:01:59
75 billion to help finance the company through bankruptcy, much of it coming from its bond holders.
1:02:03
Sachs said it intended to emerge from bankruptcy later this year and it expected to honor all customer programs, make payments to vendors, and continue to pay employees.
1:02:15
Saxs has brought in additional executives to help steward the company, including Darcy Pennock, former president of Burgdorf Goodman as president and chief commercial officer.
1:02:25
This is a defining moment for Sachs Global and the path ahead presents a meaningful opportunity to strengthen the foundation of our business and position it for the future.
1:02:33
Uh this is this is good messaging.
1:02:36
Trump was messaging around the Supreme Court ruling.
1:02:37
He said if they rule against us, we're screwed.
1:02:42
[laughter] I was like thought that he just was like if they if if they rule against the tariffs we're screwed.
1:02:49
[laughter] [clears throat] >> We're cooked. We're chopped in. We're cooked. ridiculous things.
1:02:55
>> Yeah, I mean >> I I feel like these stores are uh if anything uh just nostalgic, right?
1:03:00
Um it it really feels like an end of of an era.
1:03:07
Uh uh essence uh obviously uh went bankrupt earlier this year.
1:03:13
Uh in this case uh in that case too, founders are going to are going to actually maintain control.
1:03:19
So we'll see how they navigate through.
1:03:21
Uh but again, uh I just wonder, you know, as these stores shut down, like who who can even fill these spaces?
1:03:29
Like there's just not there's not companies that want to come in and occupy a bunch of this um a bunch of this real estate.
1:03:37
>> You got to get Rick Caruso in there.
1:03:39
He's like the master of this.
1:03:39
Like there there is something that's a little bit more durable about the mall that you go to for there's restaurants, there's a movie theater, there's a coffee shop, bookstore, escape room, probably laser tag, VR, maybe, maybe a sphere.
1:03:54
Um, but there's a few key stores that are anchor tenants, the Apple store, and there's electronics.
1:04:02
And then there are a few.
1:04:04
There's a Louis Vuitton store, a Coach store, Bautega store, and those brands want to own the entire realale experience. I think more now.
1:04:12
I don't I'm not I'm not sure, but it seems like, you know, as much as we joke about like the Supreme store having lines out front, like there isn't there is a deliberate strategy to that.
1:04:21
Like you control the full experience, not just a corner or a display table in a larger store.
1:04:29
So these like aggregator uh retail stores seem to be having a lot of trouble.
1:04:35
>> Yeah, >> it's not good.
1:04:35
Well, MongoDB, choose a database built for flexibility and scale with best-in-class embedding models and rerankers.
1:04:44
MongoDB has what you need to build what's next.
1:04:46
Um, Larry Ellison is being profiled in Vulture for New York Magazine.
1:04:54
Uh, it's a very long profile that we should read through.
1:04:57
Uh, first we should debate this story that we almost got to from Reddit yesterday.
1:05:02
Uh, are there any real candy innovations right now?
1:05:06
Uh, [laughter] r/ candy, which I didn't know existed.
1:05:10
Hey everyone, I'm curious to hear your perspective as candy lovers.
1:05:14
Do you feel like there's any real invnation happening in candy right now?
1:05:19
Are there any sweets, brands, or flavors that are new?
1:05:23
Uh, someone's been reading 0ero to one.
1:05:25
The stagnation stagnation theory has come to the candy industry.
1:05:30
[laughter] We're seeing progress in the world of bits, less so in the world of sugars >> of candy. Yeah.
1:05:35
Uh some people did make the good point that yes, there has been a phenomenal breakout success in the candy industry.
1:05:44
Do you know what I'm talking about, Jordy? >> No.
1:05:47
>> There's one really big winner recently and it is uh Nerds Gummy Clusters.
1:05:50
These Nerds Gummy Clusters.
1:05:53
I don't know where this got buried in this.
1:05:55
This went um this went very viral, I guess.
1:05:57
But uh Nerds was a brand of candy that had been around for a long time and was doing I think fine sort of like you know stagnant revenue and then they came up with this way to create like the Have you ever had nerds?
1:06:15
Are you familiar with this? Of >> course. >> Yeah.
1:06:17
It's like this like grainy like sand texture or something. I don't know.
1:06:20
It's like a bunch of little pellets and it's sort of like >> Are you mansplaining nerds? >> Yeah.
1:06:25
sort of like hard to wrap. I don't know.
1:06:26
It It's not It's not that accessible.
1:06:28
It's like you either dump it all in your mouth and then you just have a tunnel.
1:06:31
It's not a great user experience.
1:06:33
It's a little outdated >> really. >> I think so.
1:06:36
>> I thought it was fantastic growing up. >> You did? Yeah. >> Interesting. Okay. >> Nerd ropes, too. >> Yeah. Yeah.
1:06:41
So, basically what they did with the nerd rope, they they cut it up into these little clusters.
1:06:45
And this product has been selling fantastically well and has done very very well.
1:06:50
Um, and uh, there were also some there uh, yeah, there there's a bunch of people chiming in in the comments.
1:06:56
Uh, peelers, gummy mangoes.
1:06:59
Uh, there's a whole bunch of stuff.
1:07:01
There were even some companies that did uh, uh, like sugarfree candies that I think have done well.
1:07:06
There's been a number of uh, sort of new new startups.
1:07:10
Uh, there really isn't like a David's Protein Bar type of breakout success in candy that I'm familiar with.
1:07:16
Are you >> I love I love candy.
1:07:17
I just assume that it all wants to kill me. Yeah.
1:07:21
>> And so >> bring me the poison.
1:07:23
>> Bring [laughter] me the poison.
1:07:23
What was your favorite candy growing up? >> I don't know. That's a tough one.
1:07:28
Maybe Starburst, Skittles, the classics. >> Oh, wow.
1:07:32
>> Is there anything else? What? >> Hot tamales. >> Hot tamali. Okay. Interesting.
1:07:36
>> Tyler, what candy do you >> more of a chocolate guy? >> Chocolate.
1:07:40
>> I don't really like any kind. >> Interesting. Yeah. I I don't know.
1:07:42
I pick up candy from time to time at the airport. Uh something. >> Oh yeah, you do. >> Yeah. Yeah.
1:07:49
If we're getting on a plane, I like to have some candy hanging around.
1:07:52
But uh you know, the nerds gummy clusters.
1:07:55
I've had those on plane flights a few times.
1:07:56
But uh good to see that the candy community is coming out in full force in in support of candy innovation.
1:08:01
Well, >> uh I went and found this original post on r/ candy. And what do they say?
1:08:04
Uh the post seems written by chatbt m dashes. Uh all of it.
1:08:10
Uh and uh yeah, BA basically everybody's just uh nostalgia maxing.
1:08:19
>> Um >> what are they most nostalgic for? What do they like?
1:08:22
>> They're just saying uh they like the old school stuff. Willy Wonka candy.
1:08:28
>> Does A Reese's Peanut Butter Cup count as a candy or is that a chocolate?
1:08:33
>> I think of chocolate as a subcategory. >> Then candy. >> Oh, interesting.
1:08:37
>> I don't like Halloween candy.
1:08:37
I got to buy Halloween candy for Halloween.
1:08:40
>> Snickers came in there. Okay. Yeah. Snickers. Snickers counts. That's good.
1:08:44
It's also an ingredient that you could use.
1:08:45
Like you wouldn't say like a chocolate cake is candy.
1:08:46
There's something about the size.
1:08:50
>> Producer Ben wants a protein uh Twix.
1:08:53
[laughter] >> I wouldn't be surprised if that revitalizes the the candy industry.
1:08:56
Um anyway, let's move on to this story about David Ellison.
1:09:01
Um the the sun king of Hollywood.
1:09:05
Uh before we read through this, we'll tell you about Sentry.
1:09:09
Century shows developers what's broken and helps them fix it fast.
1:09:11
That's why 150,000 organizations use it to keep their apps working.
1:09:16
So, uh, with help from his billionaire father, Larry David Ellison is trying to become the biggest studio mogul in history.
1:09:24
Uh, one weekend in 2006, Dean Develin, a movie producer, was driving across Los Angeles to deal with an emergency.
1:09:31
His new movie Fly Boys had opened that weekend to reviews so bad that one of the stars has had abruptly checked into the hospital. What?
1:09:43
On his way to visit the actor, another potential crisis appeared on his phone.
1:09:48
I was terrified when the phone rang and it was Larry Ellison.
1:09:50
Develin said Devlin made a name for himself with a string of blockbusters in the 1990s.
1:09:58
Stargate, Independence Day, Godzilla. Wow, what a run.
1:10:00
Uh, but he'd struggled to come up with the money to make Fly Boys, a script about a band of World War I fighter pilots.
1:10:07
Then, in a stroke of luck, he learned that Ellison, the founder of Oracle and one of the world's richest men, had a college-ageed son named David, who was not only trying to break into Hollywood, but was also an amateur pilot.
1:10:20
David even had a nent film production company with an aerial name, Skyance.
1:10:25
Larry agreed to help fund the movie, which cost $60 million.
1:10:28
And Sky Dance was listed as a producer.
1:10:32
David, meanwhile, got a plum role alongside James Franco as a pilot named Eddie who can't shoot straight. Come on, Eddie.
1:10:40
Can we try the climactic fight scene? >> Eddie and Fly Boys.
1:10:45
>> Yeah, let's find uh let's find a David Ellison hyper rail or maybe just the trailer.
1:10:50
Uh, and do you see the uh the photo that Vulture chose for this is uh sort of a uh a collage, a rendition of David Ellison, but you know, they put him in the Royal Oak right there in the photo. You love to see it.
1:11:06
So, uh, Develin, let's Yeah, let's watch the Fly Boys trailer. I'd love to see this.
1:11:12
I I haven't I actually haven't seen this movie.
1:11:15
>> Looking back, >> we had no idea what to expect.
1:11:17
Franco, >> maybe this is the movie to watch this weekend. >> Nothing in common.
1:11:26
>> I can see >> except you wanted to learn to fly.
1:11:30
>> No, that's a cool shot.
1:11:35
>> Gentlemen, you have bravely volunteered to preserve freedom.
1:11:38
>> Captain tell you, >> we got to turn this into I think that's David, right? Six weeks.
1:11:43
>> Guy sure knows how to make friends.
1:11:44
>> All his friends out there, >> huh?
1:11:47
>> This is your quarters.
1:11:47
[music] French, you sure put on a nice war. >> That's him. >> Yeah. Wow.
1:11:51
>> Got any objection to move you could have made?
1:11:53
>> I heard it's good luck to rub your head.
1:11:54
I wouldn't do that if I were you. >> Sorry, fellas.
1:11:57
This room is reserved for killers.
1:12:02
>> Killer going to war in two days. Worried about me?
1:12:07
>> The Germans are moving towards >> I definitely saw this this movie as a kid cuz I just love I love playing. >> Yeah. Back by lunch. >> There he is. We'll be back by lunch.
1:12:23
>> This is pretty sweet movie for about 2001. >> Worth the 60 million. >> Hey, underpaid. >> Going anywhere.
1:12:30
>> Are they missing a zero?
1:12:30
Seems like a $600 million movie. >> Zero.
1:12:37
>> I'm going to turn this into a cult classic for for fans of of enterprise databases.
1:12:41
If you're if you're a fan of of hypers scale and data center buildout and data center construction like the rest of us be watching >> you gotta be a fly boys guy.
1:12:48
You got to get the original Fly Boys merch.
1:12:50
You gotta get the DVD copies.
1:12:52
You got to start collecting this stuff. >> Okay.
1:12:55
So Delin, he thought >> Delin thought he knew why Larry was calling.
1:12:58
Fly Boys had bombed at the box office and Larry stood to lose millions.
1:13:02
As it turned out, Larry wasn't all that stressed about the money.
1:13:04
He had spent tens of millions more just trying to win a sailing race. >> Sick.
1:13:08
He was however concerned about his son, the actor in the hospital. Wait. >> Whoa. >> Big.
1:13:15
>> The reaction to Fly Boys had so unsettled David that he was experiencing an episode of atrial fi fibbrriation.
1:13:23
Doctors had to shock his heart back into rhythm. >> Wow. That's crazy. >> This is bullish.
1:13:29
>> Yeah, >> this is bullish.
1:13:31
>> He he he was so upset about losing that he went he was hospitalized. >> That's crazy.
1:13:36
You think he's gonna lose Warner Brothers? >> Maybe not.
1:13:39
Maybe coming back and getting.
1:13:41
>> I think I think this is a guy you want. >> Yeah, this is good. Okay.
1:13:44
>> Um >> he was thinking that whole weekend, I just lost my dad a bunch of money. >> Wow.
1:13:50
>> He was upset about letting his father down.
1:13:51
Larry told Dein to make sure David knew he was still proud of him.
1:13:53
Fly Boys was the humble beginning of the Ellison's family's adventures in Hollywood.
1:13:58
After giving up on acting, David spent more than a decade building Sky Dance into a player in the blockbuster business, financing such hits as Top Gun Maverick. >> Crazy.
1:14:08
>> And Mission Impossible series along with a number of largely forgettable movies.
1:14:11
>> Have you seen Top Gun? >> Yes. >> Sick.
1:14:14
Have you seen Top Gun Maverick? >> No. >> It's good.
1:14:17
It's It's It's not as iconic as the first one, but it is a great ride.
1:14:20
What about Mission Impossible?
1:14:22
There's like seven movies in the series.
1:14:23
Have you seen any of them? >> No.
1:14:24
>> The first one's great. >> No.
1:14:25
Uh he was in other words a producer much like many others in in town.
1:14:27
Then last year David's father put up billions to help him buy Paramount, one of Hollywood's legendary movie studios and a company more than 10 times the size of Sky Dance.
1:14:37
This past fall, the Ellison set their sights on an even bigger prize, Warner Brothers.
1:14:41
At 43, David is now the first millennial, let's give it up for the millennials, to control a major Hollywood studio.
1:14:48
While running Sky Dance, he'd built a reputation as someone with an earnest love for the kinds of action-packed blockbuster movies he adored as a kid and the money to actually make them.
1:14:58
But his pursuit of Paramount and now Warner Brothers had revealed an empire building streak in line with his father, who is currently the fifth wealthiest person in the world. >> Mhm.
1:15:07
It's possible to sum up the divergent fortunes of the tech and entertainment industries over the past 20 years in the simple fact that when Fly Boys came out in 2006, Larry was worth 18 billion and couldn't afford Paramount which was valued at 22 billion.
1:15:20
By last year, the 6 billion Larry spent to help David buy the company barely made a dent. >> Wow.
1:15:26
>> Which briefly peaked in his fortune, which briefly peaked in September at close to 400 billion. Yeah.
1:15:32
>> Oracle, Larry's company, is is the world's most boring tech giant. disagree. Disagree.
1:15:35
It's It's um >> It's one of the most exciting to me.
1:15:40
>> Tell that to Chase Lock Miller Crusoe.
1:15:42
Okay, we'll see who's boring then.
1:15:45
>> Yeah, >> we'll see how boring Oracle is when we talk about Abalene, Texas.
1:15:47
Go to Abene, Texas, and tell me that Oracle's boring. >> Come on. Who's writing this?
1:15:52
Who's who's writing this?
1:15:55
>> Larry had long harbored more globe spanning ambitions.
1:15:57
Even before starting Oracle, he dreamed up a giant conglomerate he would someday build called Universal Titanic Octopus. >> [laughter] >> What? That's so sick.
1:16:07
>> Today, he keeps some of his wealth, which includes 98% of a Hawaiian island in an entity called Octopus Holdings LP.
1:16:15
In the past year, Oracle has become central to the AI boom, providing backend computing power for OpenAI and others looking to build LLMs.
1:16:20
In September, after Oracle reported a potential windfall of AI infused revenue, >> it stocks shot up so much that Larry's net worth increased by 89 billion in a single day.
1:16:32
That still was such a >> moment 15 Paramounts.
1:16:36
[laughter] Basically, you get 15 Paramounts in one day and you're like, "Okay, yeah, I'll take 10% of the gain from this day and buy a movie studio."
1:16:46
>> Uh later this month, the company is also set to acquire a stake in the American version of Tik Tok.
1:16:49
All of that combined with David's ownership of one and perhaps two major studios as well as one and perhaps two major news network uh networks Paramount own CBS and Warner owned CNN has spurred concerns that the suddenly omnipresent Ellison are building an empire that could dwarf even the >> Murdoch. Wow.
1:17:06
>> Uh what the Ellison's want with their conglomerate individually and together will affect the future of what appears on all kinds of screens.
1:17:11
And the relationship between father and son has provoked no shortage of psychoanalysis.
1:17:17
Larry divorced David's mother when he was young and the two became close only as David grew older and especially once he got into business.
1:17:23
David has always struck many people as his father's opposite.
1:17:27
Shy and competent, not a bombastic, worldconquering visionary.
1:17:32
David's ambition was initially as humble as making movies he likes.
1:17:34
Uh but the current climate has thrown him together with his father and shown him a path to something greater >> if he can pull it off.
1:17:42
Uh here I'll continue but first I'll tell you about Plaid.
1:17:47
Plaid powers the apps you use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and improve lending now with AI.
1:17:56
So last month, the Warner board spurned the Ellison's and Paramount's offer and agreed to sell its movie and TV studio to the HBO Max uh and the HBO Max service to Netflix, creating a potential streaming colossus.
1:18:10
the the true streaming octopus is forming under Netflix's reign.
1:18:16
The Ellison have continued to argue that their offer for all of Warner Brothers, including its cable networks, is superior.
1:18:22
Uh they [snorts] are currently attempting a hostile takeover and trying to persuade Warner Brothers shareholders to accept Paramount's offer instead.
1:18:29
The battle is expected to extend well into 2026.
1:18:31
Glad to be in the media business covering this because it's certainly entertaining.
1:18:37
Uh, of course, thanks to Dylan Buyers over at Puck for putting this on my radar by posting it on X.
1:18:40
Um, the battle is expected to extend well into 2026.
1:18:46
Some observers believe that acquiring Warner Brothers is in fact critical to Paramount survival.
1:18:50
Either way, now that he has made his move to become one of the industry's leading mogul, David Ellison is faced with proving to a skeptical Hollywood that he's up to the task.
1:18:59
David's mentors are Steve Jobs and David Geffen and obviously his dad. Those guys are ruthless.
1:19:06
killers, single-minded people with a different DNA.
1:19:09
A former Sky Dance employee who worked closely with David said on the record, uh, a former Sky Dance employee said, "David is a smart dude who is reasonably shrewd, but he's not that.
1:19:22
He's not the ruthless killer.
1:19:25
He's not the Steve Jobs, the David Geffin.
1:19:26
He's something else entirely."
1:19:29
During the Warner Brothers auction, the company gave code names to each of its suitors.
1:19:33
These are the code names. Netflix was noble. Comcast was charm.
1:19:38
Paramount was given the name Prince. Interesting.
1:19:42
>> One of the reasons David Ellison loves blockbuster movies is the way in which a spectacle can contain a more intimate story.
1:19:48
How a battle for an intergalactic peace or control of an empire can really be a story about a family.
1:19:54
He has often described the formative experience of seeing Terminator 2, Judgement Day as a child.
1:20:01
The fate of humanity was at stake.
1:20:03
But what David remembers is Arnold Schwarzenegger rampaging across the screen to protect a young boy who never knew his father. It's emotional. It's a great movie. Terminator 2. Have you seen it? >> No. >> Brutal.
1:20:15
[laughter] It's like one of the greatest movies. >> Should I watch it? So good.
1:20:18
It's >> Is that Is that what I should add? >> You should. You should.
1:20:21
And And truthfully, you can watch Terminator 2 without watching Terminator 1.
1:20:24
They have very different vibes, very different pacings.
1:20:28
Uh, you should watch both, but uh, Terminator 2 is just a fantastic movie. It's so so good.
1:20:33
And there's iconic like memes and gifts that I feel like you should know. I'll be back, you know.
1:20:40
>> Okay, soar and some of the chat actually put together >> what they put >> a film list for me. >> Send it to my DMs. >> Thank you.
1:20:49
>> Uh, Interstellar, Heat, Inception, Shaw Shank, Steve Jobs, American Hustle, Silver Lining Playbook, Almost Famous, The Talented Mr. Ripley, The Sting.
1:20:55
The issue is these are so so many movies you could easily be messing with me and just sprinkle in like 10 that are just like really bad movie.
1:21:04
I'm like well the boys said I had to watch >> I think that's uh notoriously one of the worst movies.
1:21:11
>> Um >> there's there's a lot there's a lot here's three three pages of movies.
1:21:14
So I promise I will do my best to watch all these.
1:21:19
It may take me >> multiple decades at my current pace >> but I'll work down I'll work down the list.
1:21:26
Uh well, so at the end of Terminator 2, David Ellison sitting in the theater, Arnold Schwarzenegger, not to spoil the story, but Arnold Schwarzenegger sacrifices himself in a vat of Molten Steel in front of the boy, and the 8-year-old David Ellison starts to cry. Wow.
1:21:41
Uh Larry wasn't around much when David was a kid, one of the only similarities in their very different childhoods.
1:21:48
Larry was born in New York City in 1944 to an unwed teenage mother who gave him up for adoption at 9 months old.
1:21:55
His adopted father, Lewis Ellison, was a Russian immigrant who took his last name at Ellis Island.
1:22:00
And a foundational part of the Larry Ellison story is that Lewis regularly told Larry he would never amount to anything. Wow, what a crazy thing.
1:22:09
Why did you adopt this nine-month-old kid just to dunk on him? This is so so bad.
1:22:14
But clearly [laughter] it it lit a fire uh in Larry and he went on to build one of the greatest tech companies in history.
1:22:24
Maybe Larry should write a book called Hardcore Parenting.
1:22:26
You know, people talk about soft parenting, right?
1:22:28
You want to, you know, >> uh, but hardcore parenting, it's like wake up every morning, tell your children, you'll never amount to anything. >> Crazy.
1:22:37
As a result, Larry likes to say that he had all the disadvantages necessary for success.
1:22:41
And colleagues at Oracle got the sense that Larry's seemingly endless ambition came partly from a desire to prove himself to his adopted father.
1:22:50
I'm not sure I would re recommend that everyone raise their children like this, Larry later said, but it certainly worked.
1:22:56
Wow, [laughter] that's crazy.
1:22:58
David's mother, Barbara Booth, was an or was Oracle's 10th employee.
1:23:03
He hired his mom when he needed a 10th employee.
1:23:06
And Larry's third wife, uh oh, David's mother, sorry.
1:23:10
Uh he uh Larry hired David's mother, Barbara Booth.
1:23:14
Um they they divorced shortly after David's third birthday and right after his sister Megan was born.
1:23:19
When Larry and his first wife tried couples counseling to save their marriage, Larry told the therapist that the very idea of love eluded him. I don't understand love.
1:23:27
I don't understand people bonding to one another. What is it?
1:23:29
Larry said he spent obligatory weekends with the kids and seemed to only realize later that a family was something he wanted.
1:23:37
One night, >> guy doesn't understand love, but has been is on his fifth uh marriage >> something.
1:23:44
>> He's like, I just I just need to get my >> reps marriage. [laughter] Yeah.
1:23:46
Larry called Booth to say he was lonely.
1:23:50
"You're never alone because you have the kids.
1:23:51
You always have a body," Larry said.
1:23:54
"I'm here by I'm here all by myself."
1:23:55
David credits his love of movies to his mother.
1:23:57
The family had a collection of 3,000 VHS tapes.
1:23:59
And David's ideal day as a as a child was to watch the Star Wars trilogy or all the Rocky movies back toback.
1:24:07
I did the exact same thing when I was a kid. It was fantastic.
1:24:10
I had Star the Star Wars trilogy on VHS was one of my prized possessions.
1:24:16
Quickly let me tell you about Lambda.
1:24:17
Lambda is the super intelligence cloud building su AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
1:24:24
Uh it wasn't until David became a teenager that he and Larry started taking flying lessons together that they grew close eventually staging mock dog fights over the Pacific.
1:24:39
>> These guys are dogf fighting each other. This is insane. >> Yes. bond with your son? >> Yes.
1:24:46
As a matter of fact, I do have that dog in me.
1:24:48
I I literally dog fight with my dad in planes that we fly over the Pacific.
1:24:53
David went on to compete as an arerobatic pilot, whipping barrel rolls, flying at 300 mph, just 15 feet above the ground, and pulling off his signature move, the davalator.
1:25:05
[laughter] He has a signature move. This is incredible.
1:25:07
After graduating from high school in 2001, David went to Pepperdine University as a prospective business major.
1:25:12
He hated it and he transferred to film school at USC.
1:25:14
He commuted from the beach in Malibu where he lived in one of the many homes Larry had purchased there on a $65 million buying spree.
1:25:22
His neighbors included Jennifer Aniston who was renting one of Larry's other houses.
1:25:26
For a senior thesis, David wrote, directed, and starred in a thriller called When All Else Fails, in which he plays a billionaire son who has to rescue his diabetic girlfriend from kidnappers before her insulin runs out.
1:25:37
That's an interesting frame for a plot.
1:25:39
Uh his girlfriend at the time, who was a diabetic, played the part.
1:25:43
According to people who worked on the production, David was respectful and eager to learn, if a bit oblivious to the ways in which he wasn't making an ordinary student film.
1:25:52
The budget was close to $100,000, and he shot part of it in one of his father's giant homes in the Bay Area.
1:25:59
When they ran out of film, David offered to fly his plane to Los Angeles to pick some up.
1:26:03
[snorts] Instead of graduating, David left USC to film Fly Boys.
1:26:05
He worked with an acting coach to prepare, but his performance didn't do any favors to a mediocre script.
1:26:11
David spent the next several years going to auditions and landed a few more roles from Devlin, the Fly Boys producer.
1:26:17
He played a bumbling assistant to a corrupt mayor on a TNT show and a shirtless drug addict who punches an FBI agent before leaping from the second floor of a motel in a TV movie.
1:26:28
Uh, his most significant screen time came in a runchy 2009 comedy called Hole-in-One in which he plays >> John, have you seen this? >> No, I haven't. Should I have?
1:26:37
Do you expect me to see every movie?
1:26:40
I [laughter] haven't seen every movie.
1:26:43
>> Um, and he plays a he plays the owner of a golf apparel company.
1:26:47
And there's a picture of him here in a sort of golf polo.
1:26:52
uh whose partner loses a bet that leads two nefarious plastic surgeons to give him breast implants, sending David's character on a quest to drum up enough money to help him get them removed. What a wacky plot.
1:27:03
[laughter] Only in 2009 are you making movies like that? That is wild.
1:27:09
Uh he delivers one of his first lines in the movie after a woman takes off her shirt. That was pimp.
1:27:14
He says, [laughter] "Wow, that is a phrase straight out of 2009.
1:27:17
No one uses those words anymore.
1:27:20
Uh that slang has fully died.
1:27:22
Uh his acting career more or less came to an end a few years later after he wrote a script called Northern Lights about a pilot friend of his who had died.
1:27:30
Taylor Lner signed on to play the lead but dropped out after finding David had written a role for himself. Rough.
1:27:38
>> What what did Taylor have against David?
1:27:40
I guess he was like, I don't want to act with them or something or I don't want to be in I I mean, you know, it's like in F1 there's always like the oh is who is this person do they deserve the seat or you know are they there for the because they just have the money and so you know you you sign up for this you you're in this role the movie bombs and
1:27:57
it's seen as you know a black mark on your IMDb resume I suppose >> anyway before we move on let me tell you about Vanta automate compliance and security vanta is the leading AI trust management platform Um, while David inherited a love for movies from his mother, it became clear that if he wanted to stay in the business, he needed to think more like his father. David wanted to be an actor.
1:28:17
David wanted to be an actor.
1:28:19
And when that didn't work, he was like, "If I'm not going to be on screen, I'm going to be the biggest guy in the room."
1:28:24
A person who knew him at the time told me, the writer of this uh vulture piece, uh Larry's friend, David Geffin, introduced David to Skip Britain, a legendary Hollywood lawyer who had represented Pixar, which was co-founded by Steve Jobs, who was Larry's best friend.
1:28:42
Britain helped David make a business plan for building a production company and learn to navigate the web of agencies, producers, and studios in Hollywood.
1:28:50
David wanted Sky Dance to make the type of movies he loved, movies with explosions. Let's go. Finally.
1:28:53
Like the last the last Hollywood producer understands how to get in.
1:29:00
>> So, you know how Truth has their ETFs, their Patriot ETFs?
1:29:03
I think they got to get Paramount Paramount Guidance in there.
1:29:08
>> Because this movie studio committed to Explosions. Explosions. Very American. >> Yes. >> Something there.
1:29:15
>> So, Andy Kesler was an investor who worked with David to raise money for Sky Dance early on. And they had uh a rule.
1:29:23
They said he swore to me no romcoms, no touchy feely emotional Oscar bait, just explosions, but funding the Hollywood dreams of the 25-year-old failed actor son of one of the world's richest men was a tough sell to investors.
1:29:39
Will people show up to these movies?
1:29:40
And Larry ultimately made the point moot.
1:29:43
In 2010, he stepped in to provide almost all of the initial $150 million David was trying to raise, according to multiple people with knowledge of the company's finances. Their timing was good.
1:29:52
The late as Hollywood was royal by the financial crisis and Paramount, the studio behind the godfather and Titanic was struggling movie was uh was the struggling movie making arm of the Redstone family's viaom cable TV empire.
1:30:06
Deutsche Bank had bailed on an agreement to fund Paramounts movies and the studio needed cash.
1:30:12
When Larry's funding for Sky Dance came through, David signed a deal to co-inance Paramounts Movies, which meant he would help fund production in exchange for a share of the profits.
1:30:23
David had initially considered partnering with Relativity Media, which would later collapsed in a fiery bankruptcy.
1:30:28
While co-inancers often get stuck funding risky projects, Paramount's desperate state opened the door for David to negotiate his involvement in some of the studios biggest franchises like Star Trek and Mission Impossible.
1:30:39
The first feature film, David Back, a Cohen brothers remake of the western True Grit. I've seen that. It's a great movie. Have you seen it? No. >> No.
1:30:48
[laughter] Went on to make two $250 million, but they couldn't get a dime out of Jordy Hayes, apparently.
1:30:54
[laughter] And it earned 10 Oscar nominations, but couldn't get Jordy to throw it on streaming on one random Sunday night.
1:31:03
Uh, his sister Megan followed him into the industry, co-inancing True Grit and launching her own company, Annaperna Pictures. Oh, I didn't know that. Interesting.
1:31:09
Anna Perna has been on a run that I think they also have an interactive division.
1:31:12
Well, although that might not be related. I'm not sure.
1:31:16
Uh the sky dance thesis, according to a person that worked closely with David, was that Hollywood wasn't prepared for the overwhelming economic force of a Silicon Valley billionaire throwing around his wealth and ambition.
1:31:24
Plenty of dumb money came into town, but producers and talent mostly viewed it as something to take advantage of.
1:31:29
Money in Hollywood is not appropriate appreciated.
1:31:33
Uh the person said this was an opportunity to reverse that, to make Hollywood treat money with respect.
1:31:37
We got to respect the dollar in Hollywood.
1:31:42
>> Nicholas Cage was was Yeah.
1:31:45
>> Uh he famously said, uh, "I do not [snorts] chuckle when I get a big check.
1:31:50
I have respect for the dollar." >> That's right.
1:31:52
>> D uh Cage, Nicholas Cage, uh shortly after signing the deal with Paramount in 2009, a person who knew David then said that he had declared, "We are going to buy Paramount one day."
1:32:03
He called his shot in 2009. Well, here he is. He did it.
1:32:07
Uh, David proved to be a savvy enough operator, negotiating better terms with Paramount when his deal came up for renewal and working hard to pick up the quirks of a job that involved everything from managing the egos of talent to negotiating debt facilities with JP Morgan.
1:32:21
He would sometimes tell colleagues about an instructive conversation he'd had years earlier about running a company in Hollywood.
1:32:28
at the premiere of Steven Spielberg's Minority Report starring Tom Cruz.
1:32:31
He walked up to congratulate David Geffen who had produced the movie through his company DreamWorks.
1:32:38
As David told it, Geffin shook his hand. Steve is getting paid. Tom is getting paid.
1:32:43
How much do you think DreamWorks is getting paid? Geffin said.
1:32:47
He held his hand up in the shape of a zero.
1:32:50
DreamWorks was making a relative pittance on the movie, an early lesson in the confusing economics of the business, >> where a poorly structured deal could mean even a hit might generate little for the company that produced it.
1:33:03
It was always in the back of David's mind.
1:33:05
On Minority Report, everybody got paid except for DreamWorks.
1:33:10
A former Sky Dance executive said, "Have you seen Minority Report?
1:33:13
That is one of my favorite movies of all time.
1:33:16
It is a fascinating, fascinating movie. It is amazing. It's not on the list. sci-fi.
1:33:21
>> It's not on the list that the chat made. >> Add it to the list. Add it to the list.
1:33:25
Minor Report is fantastic.
1:33:25
Uh really great vision of what the future of VR and augmented reality could look like.
1:33:32
Has a whole bunch of other interesting sci-fi elements.
1:33:34
Tom Cruz obviously puts off a put puts on a masterful performance, but the the interactive how they interact with computer technology is is remarkable uh in that.
1:33:42
Anyway, let me tell you about Finn.
1:33:45
ai, the number one AI agent for customer service.
1:33:47
If you want AI to handle your customer support, go to fin. ai.
1:33:53
>> Okay, I think we're running out of time.
1:33:55
Chesy is going to join in a second.
1:33:55
Um, >> there is some funny dialogue happening. I'll fill you in.
1:34:00
Uh, the Koshi market, will Elon win his case against Open AI?
1:34:07
>> Was at a 36% chance this morning. >> What's it doing now?
1:34:11
>> He asked, "What are the odds looking like?" They responded.
1:34:12
Uh, now Elon is posting, "I've lost a few battles over the years, but I've never lost a war."
1:34:23
>> Elon said that >> just posted this. [laughter] >> Oh my god. >> Absolutely. Insane. >> Scorcher.
1:34:28
Well, uh, we have Brian Shasky, the co-founder and CEO of Airbnb in the Reream waiting room.
1:34:33
We're bringing him in the TV show.
1:34:35
Brian, great to see you again. How are you doing?
1:34:38
>> Hey guys, good to see you.
1:34:38
Thank you for having me back on. >> Of course. You're welcome anytime.
1:34:40
It's great to be here with you.
1:34:42
Uh first kick us off with the news.
1:34:44
You've been acquiring talent, building the roster. You have a new CTO. How did it come about?
1:34:50
Tell me about this person.
1:34:53
>> Yeah, so like you know obviously a couple years ago um I started asking around like who are some of the best leaders in AI and I started meeting people and one of the names that came up over and over was this guy named Ahmed Ald.
1:35:05
And he was head of generative AI at Meta.
1:35:08
We met and I I just was completely blown away by him.
1:35:11
Um, you know, not only was he at Meta and he essentially created uh led the team that created the llama models have been downloaded a billion times.
1:35:19
There's been over 60,000 derivative models.
1:35:21
Um, but he was also at Apple.
1:35:23
He actually joined Apple out of college, worked on the original iPhone in 2005, led a lot of the multi-touch technology.
1:35:28
He um led the autonomous uh technology group that was the self-driving car project at Apple.
1:35:36
So, he was somebody at the frontier.
1:35:36
He really understood both Frontier technology but he also understood that like kind of Apple design craft which I think Airbnb also was really passionate about and we just really hit it off became friends and as my current CTO we were talking about handing the baton to somebody we thought it would be really great. >> Yeah.
1:35:52
How are you thinking about design in the era of generative AI these apps are amazing and the fun and the models like you see the benchmarks you you use the models and it's it's magical.
1:36:03
It's like you know we created fire.
1:36:05
Uh, and then one rough edge, one button that doesn't quite work the way you expected it.
1:36:12
I was lamenting the fact that I was using clawed and I couldn't get a deep research report to read it out loud to me.
1:36:19
That feature is in one app and there's different features there.
1:36:21
How do you >> Yeah, it feels it feels very notable that even in all the leading LLMs, there's still so many rough edges in the product.
1:36:30
>> Part of that is like a new new product paradigm.
1:36:31
We're kind of figuring out what the the edges are. All right.
1:36:35
>> Yeah, maybe there's all sorts of metaphors.
1:36:37
You know, I I remember when I was a kid, >> um I had I I think I got like a compact computer and I was running MS DOSs and we're kind of more in the MS DOSs phase of AI.
1:36:49
Um you know, I don't I I think I not to belittle the interfaces, but the chatbot is not the endstate interface.
1:36:57
The current chatbot is not the end state interface for AI.
1:36:59
I mean, think about your phone in your app.
1:37:00
Um do you want to chat to get the weather?
1:37:03
or do you want a chat to like do most of the functions? The answer is no.
1:37:07
And so I think the the the future AI interface will have a reference to chat, but it's probably going to be much more visual.
1:37:15
Most people aren't completely text- based.
1:37:17
And I I do think there's been a it's kind of like we've been iterating the engine of the car, but we haven't really redesigned the car.
1:37:24
And so the chatbot is really a pre-AI interface that we've plugged onto this incredibly powerful engine.
1:37:32
And so I think what we're trying to do is think through like what are where can we take this interface?
1:37:37
What is the like multi-touch reference for an age of AI?
1:37:40
And we're not going to do this overnight.
1:37:42
We're not going to be the only company doing this.
1:37:44
But I really think like the models are even more powerful than people realize because we have hardly harnessed them.
1:37:51
And if you look at where they're going to be in a year or two, we really want to like skate to where the puck is going and do something really really cool.
1:37:57
So I totally agree with you.
1:37:57
And I think the other thing I'd say is I'm on the board of Y Cominator and I think the last I checked 87% of the companies are enterprise companies per batch.
1:38:11
>> People aren't >> I know we're we we go and we meet with every batch and uh to have them on the show and and we're always trying >> hey every we want every consumer company to come on because often times Yeah.
1:38:22
often times they give you >> and and the interesting thing is all of them all these founders started doing consumer businesses.
1:38:28
You asked them they're doing Minecraft servers and flipping sneakers and stuff.
1:38:33
So they actually have some consumer >> DNA >> but they end up really >> So you're you're bringing up a really good point.
1:38:40
I joined Ycomir in 2009 and that was not like a two years after the iPhone was introduced and almost every startup was a consumer company and enterprise is awesome and I think it makes complete sense why AI is starting with enterprise cuz the models are not cheap to run.
1:38:56
You can basically vertically integrate any business and completely automate the workflow.
1:39:00
It's going to revolutionize how we do work.
1:39:03
But the point is that the biggest prize is consumer because that is what's going to reach daily life for billions of people.
1:39:09
And I think a lot of people are a little bit a lot of entrepreneurs are afraid to go into consumer.
1:39:12
That's the biggest thing we've heard. They're afraid.
1:39:15
Um partly they're worried that like OpenAI or Google are going to like essentially eat their lunch and vertically integrate.
1:39:20
Um the other concern is consumers just hard.
1:39:22
You know, it's a little bit more of a hitch business.
1:39:26
Distribution's a little more mature because of the app store.
1:39:28
There's not really new distribution channels in the same way.
1:39:32
At the same time, we are in the midst of a revolution.
1:39:34
And more than just a couple chat bots have to be the way that you interface with the world.
1:39:40
And I also, this might be self- serving to say, but I also believe this independently.
1:39:45
>> I don't think we're going to use just one agent.
1:39:48
>> I don't think we don't have just one person in our life.
1:39:50
I don't think we're going to have just one agent in our life.
1:39:52
I don't think we'll use thousands, but I think there's going to be some level specialization that's going to help.
1:39:57
And we like there's going to be too much specialization where I wouldn't download that agent or use that agent.
1:40:02
But I I think even if you want a meta orchestrator whether it's Claude or Gemini or Chetch BT specialization is going to help even within consumer.
1:40:11
So we want to do some really cool stuff within traveling and living. >> Yeah.
1:40:16
>> Yeah. What what advice do you give to the 13% of Y cominator fan founders that are going after uh consumer at least for now or at least in at this moment is it hey keep your burn really low run a ton of experiments stick it out because it
1:40:34
feels like part of the reason why 87% wind up in enterprise is because businesses are just throwing money at them they're saying yeah you're doing consumer but if you come solve this one really small problem for me and build this API for me I'll give you a contract. I'll be your first customer.
1:40:46
I'll be your first customer.
1:40:48
It's very easy to get the money flowing on the business side potentially.
1:40:50
Uh but what how can you actually make it as a consumer founder when there is a big prize but it might be a harder road. >> Yeah. So many thoughts here.
1:41:00
I mean one of the things that Paul Graham taught us and Gary Tan teaches which I think is very effective is use other Y cominator companies as your early adopters.
1:41:08
Hence why a lot of companies go into enterprise.
1:41:11
If you have an artist company don't go to like Boeing to try to use your service.
1:41:14
go to a young startup and work your way up to the large companies.
1:41:17
And so they've developed this incredible ecosystem where thousands of companies are adopting each other's tools and they bootstrap each other.
1:41:24
And that's actually been part of the explanation for why Y Cominator has so successfully created so many enterprise companies.
1:41:31
But when I was in Y Cominator, we got everyone to use Airbnb.
1:41:33
And so in other words, like we have a huge alumni network.
1:41:36
I would tell people that are going into consumer, number one, don't be afraid to do AI consumer.
1:41:40
It might fail, but like investors aren't going to hold it against you that a startup failed.
1:41:46
They're gonna like a a founder who's failed is more fundable the next time than someone who's never started unless they really blew it. Yeah.
1:41:53
>> Because you have experience and I think that's what's so great about this.
1:41:56
Number two, you got a lot of early adopters within Y Comer who are normal people too. They have daily life.
1:42:00
I would agree to keep your burn rate low. Um I would pick a niche.
1:42:04
I wouldn't pick a niche that's too narrow.
1:42:06
So like maybe like AI to do something incredibly narrow is going to get really really difficult for somebody to want to like change their workflow and behavior.
1:42:14
But just think about all the parts of daily life that are kind of annoying.
1:42:18
And maybe pay attention to like your sister, your significant other, your children, like whoever's in your life and just look at their life and ask like how could their daily life be a little bit easier?
1:42:30
And I would just go for it.
1:42:30
I mean and by the way like >> the app store is mature.
1:42:34
That's a little bit of an issue.
1:42:36
At the same time, the top apps in the app store are AI apps.
1:42:40
So, if something is truly great and truly breakthrough, people will seek it out.
1:42:44
And I do think my prediction is I is that AI is going to revolutionize consumer applications in the coming years.
1:42:51
And they might not be apps, they might become agents.
1:42:53
Agents might be the new apps.
1:42:54
We have to figure out what that means.
1:42:56
What's the new platform paradigm?
1:42:57
It's probably agents, not apps. But we'll see.
1:43:01
>> But ultimately, I think that's the big takeaway here.
1:43:02
And so what we're going to do is we want to really innovate on the consumer experience.
1:43:06
We want to inter integrate we want to interface on like what does consumer interfaces look like in the age of AI.
1:43:11
Um and I think they should evolve past the current design paradigm and we'll see where it goes.
1:43:18
>> Yeah, it would be I'm not expecting to open the Airbnb app and see a blank text box purely like there's so much more that you can do.
1:43:25
Have you thought more about uh the Airbnb app is is unique I think because it's not this uh reactive people are opening it 10 times a day.
1:43:35
There is an intention and there's probably a lot of value in understanding uh okay this person they like to travel around the holidays.
1:43:42
They're opening the app in October.
1:43:45
Let's think that through.
1:43:47
agents and LLMs can probably work through a customer's history, their preferences, just do better recommendations, what you're surfacing them.
1:43:56
How how much have you thought about uh being proactive about reaching the customer with something that's more tailored? Uh what's been working?
1:44:04
Where do you see it going?
1:44:08
>> Yeah, I mean so many things.
1:44:08
One of the other problems with consumer have to keep coming back to it is there's a business pro model challenge, right?
1:44:17
like these models are not cheap and so there's probably one of three ways you can make money in consumer.
1:44:20
You can put ads in your chatbot, you can pay a subscription or you can do essentially transactions.
1:44:26
Well, Airbnb luckily has the business model.
1:44:28
We have transactions and our transactions are pretty high dollar transactions.
1:44:31
So, we actually have the really the business model going for us.
1:44:35
We also have a lot of data.
1:44:35
Um, we do about 50 billion searches a year on Airbnb.
1:44:40
That's nothing compared to Google, but 50 billion.
1:44:42
So that's that number of times somebody's typing in something to a Airbnb search box.
1:44:48
So we actually do have quite a bit of data about people, their preferences, and we can bring it in.
1:44:53
And so and part of what we want to do is if the interface is a little more chat-like, again won't be per se a chatbot exactly like OpenAI, but if it's a little more of a turnbyturn chat-like connection, you're going to get a lot more information from people.
1:45:08
And I think you know the one benefit of the current chatbots are they have memory and so you're putting a lot of context in the window.
1:45:15
Um and I think memory by the way is something I think we're going to want to technically innovate on because the chat bots still are stateless and so you're essentially the prompt is putting in this kind of you know obviously a lot of your memory.
1:45:29
So, I do think there's going to be an an area around how can everybody understand people's preferences, learn more about you, understand what you care about, and just be really thoughtful like what's your bucket list, who are you traveling with?
1:45:42
One of the other things every can be really good at is the majority of trips have multiple people.
1:45:45
Most chat bots are single player mode.
1:45:47
They have collaborative tools, but most people are not chatting with multiple people.
1:45:51
Most people in Airbnb are searching for an Airbnb with multiple other people.
1:45:55
So I think another thing we really want to do is really be great at like understanding two people they have totally different preferences.
1:46:02
How do we help them figure out the right choices for them?
1:46:04
So a lot of collaboration tools I think going to be really important.
1:46:08
But I think at at our heart what we want to do is really build out these robust profiles deeply understand people and give them what they want in the real world.
1:46:17
>> How are you thinking about the challenges of generative AI imagery in Airbnb listings?
1:46:21
I can imagine there's sort of a risk of uh what is it called?
1:46:26
catfishing where someone takes a photo.
1:46:28
It is their house, but they said, "Hey, like patch up the walls and you know, let's let's change the lighting and make it look a little bit warmer, a little bit nicer."
1:46:35
And there's probably a little bit of that. That's fine.
1:46:36
You know, if you took it on a phone, you want it to look nice, but you want it to represent the actual experience.
1:46:41
How are you thinking about the challenges with that?
1:46:45
>> Yeah, I mean like it's really interesting, right? Like I don't know.
1:46:46
I saw on Twitter yesterday like the Stranger Things where like you can turn your face into someone else's face.
1:46:51
And so what this really means is the like know your customer authentication.
1:46:55
A lot of it is like you know you do a selfie and an ID or you do a video.
1:46:59
A lot of this stuff now AI can get around.
1:47:01
And so I mean we should remember AI stands for artificial >> and so we're now starting to live in a world where if you see in a screen it might be artificial.
1:47:10
And so I think authentication is going to be critical.
1:47:14
And one of the best authentications is in the real world.
1:47:16
I mean we're going to be pretty soon living in a world where you don't know something's real unless you've seen it in the real world.
1:47:20
unless we have authentication.
1:47:23
>> One example of the way can solve this for example is we do have a network of professional photographers over 5,000 around the world.
1:47:30
In fact, we built an ondemand professional photography network before Uber even launched where you hit a button and if a photographer shows up and takes photos your home and advantage of that is those photos are by Airbnb and so if we took them a customer would know those are authenticated photos from us.
1:47:46
That's just an example of something that is possible.
1:47:48
But I do think like solving this, is this real?
1:47:53
Is this authenticated is really important.
1:47:54
So we're gonna have to have something we're gonna have to have technology solutions for it. >> Yeah.
1:47:58
>> What's your latest thinking on integrating Airbnb with various LLMs?
1:48:04
Like how how are these conversations going into Yeah. What kind >> Yeah. I'm interested.
1:48:09
I think I think last time I was on I said they weren't ready. >> Yeah. Yeah.
1:48:12
Um and I I my view, you know, um we chose not to to launch with ChateBT.
1:48:18
They launched with Expedia booking and the reason why wasn't like like I I was a huge fan of that project and um gave Sam some advice on it and stuff and I think it's awesome.
1:48:27
I would love to show up on Chat GBT.
1:48:29
I would love to show up on Gemini.
1:48:31
I'd love to show up on Claude.
1:48:32
I don't Here's the thing.
1:48:34
I don't want to be the first. I want to be the best.
1:48:36
Like we want to have the best integration, not the first integration.
1:48:39
There are some limitations.
1:48:41
90% of people book an Airbnb send a message to a host ahead of time.
1:48:43
You have to have a verified ID.
1:48:45
There's just some things we need in integration for Airbnb to have a really good integration. We'd love that.
1:48:51
By the way, the traffic coming from Chat GPT converts higher on Airbnb to a booking than the traffic coming from Google search. Yeah.
1:49:01
>> So, actually various like e-commerce brands have been reporting this too.
1:49:05
Like the traffic is super high intent because people are informed. >> Yeah.
1:49:10
So I get I get this question is asked to me often as an existential thing as in are you going to partner with them or not and are they going to kill you and is there going to be no app in the future and my answer is there probably are no apps at some point in the future.
1:49:22
They're probably agents that's there's probably some platform like paradigm.
1:49:26
We're probably designing agents.
1:49:28
I don't know for sure but I think that we're going to exist on those platforms but I also think specialization is going to matter.
1:49:33
I don't think there's just going to be a few chat bots and they do everything and you are separated from every application.
1:49:40
That's going to be true of some apps and that's going to be true if you need like maybe a commodity, but there are going to still be reasons to work with different agents or different applications.
1:49:48
I think some specialization will make a difference.
1:49:52
what are the big uh what is your super one sec one thing one thing I appreciate about your framing of like we don't want to be first we want to be the best is because I think uh other CEOs in travel that are not tapped into Silicon Valley that aren't on the board of Y Combinator
1:50:08
feel this pressure to be like I have to prove that I'm like at least trying to be AI native whereas I feel like you don't have any like there's no ego around like can we build great products with AI it's simply like yeah we're going to but like I don't need to I don't need to prove it by like rushing into something. >> I remember I appreciate you saying that.
1:50:25
>> I remember I appreciate you saying that.
1:50:26
I remember when the metaverse launched I had uh somebody who didn't on my team that was not >> metverse.
1:50:31
You mean the the idea of the metaverse? [laughter] >> Yeah. Yeah. Sorry. When Yes.
1:50:34
When it was announced Mark Zuckerberg like what's our metaverse strategy?
1:50:38
And I I remember like other companies like we have to have a metaverse strategy and it's like that is definitely like what someone usually would say if they're not really steeped into it.
1:50:47
So, you know, I think it's important that you're you do something really really well, but I don't think you want to be first to signal we care about AI. That's kind of vanity.
1:50:56
You don't need to do that.
1:50:56
And so, when it's ready, we'll do something great and we want to add value to customers.
1:51:02
And that's kind of all that really matters.
1:51:04
>> Uh, if you were running Apple, what would your AI strategy be? >> It's a big question. >> Oh, wow.
1:51:10
[laughter] I would um I I um I would say that like the devices should be completely built from the ground up.
1:51:26
AI native, AI first, probably not even AI first, AGI first.
1:51:30
We should ask ourselves what is it going to look like in a few years.
1:51:32
It's probably going to be fully agentic.
1:51:36
These devices are going to be able to work while you sleep and you should work backwards from that.
1:51:39
These devices and the paradigms haven't changed since the advent of AI.
1:51:43
These are pre-AII devices running AI.
1:51:46
So my question is what would it look like if you designed it from the ground up knowing what we know today?
1:51:50
It would probably look pretty different. >> Yeah.
1:51:55
>> So less Gen Moji, more [laughter] actual hardware, >> more hardware.
1:52:00
>> We are we are in the midst of a revolution obviously.
1:52:01
I mean I don't want to be like saying what everyone already knows.
1:52:06
>> But here's what I do want to say.
1:52:07
>> Like >> the everyday life of the average person has barely changed in the last 3 years. We're on Chachi a lot. We're on Gemini. We're on Claude.
1:52:15
People listening are much more technical than the average person.
1:52:19
They're doing unique things, workflows.
1:52:20
The average person's still mostly living the life they live three years ago, using the same devices.
1:52:24
The world hasn't finally made the shift yet.
1:52:28
It hasn't funnel made the shift.
1:52:28
It won't make the shift until daily life has changed.
1:52:32
And daily life doesn't change until the devices have changed, the operating systems have changed, apps become agents, and we're all living in a completely natively consumer AI world.
1:52:42
And we're not using chat bots, at least not today's chat bots.
1:52:44
We are still living in the DOSs era of AI and we need to move into the multi-touch era.
1:52:51
>> The chat is begging us to ask you for an arm routine.
1:52:53
Is there a dedicated arm day?
1:52:56
Are there any particular machines that you recommend? Free weights.
1:52:59
What is the secret to those arms?
1:53:04
>> Oh, thank you very um [laughter] so well well first of all like genetically I have better arms than shoulders or chest.
1:53:10
So that's just one thing.
1:53:10
But I actually don't have an arm day.
1:53:12
I used to do a 5day split where I do back, legs, chest, shoulders, arms.
1:53:16
I now do um arms with shoulders.
1:53:19
So, I'll usually do two exercises of biceps, two exercises of triceps, typically a compound freee movement and a machine movement.
1:53:27
So maybe like a dumbbell curl followed by like a hammer strength cable with like a a V a rope rope or V bar and then um triceps always doing a push down with a cable and then maybe like a French press or skull crusher depending what we all call it.
1:53:45
>> Okay, that's a good >> I like to call them skull crushers.
1:53:46
They sound a lot more hardcore than totally. Yeah. Yeah.
1:53:49
You know there's heavy metal press.
1:53:50
>> We don't know how to name exercises like that. >> We don't.
1:53:53
>> The world's become soft.
1:53:53
It really [laughter] has the best.
1:53:55
I do think I do think generally if you're like under 40 >> for sure you should be doing almost entirely compound movements and free weights and dumbbells and barbells.
1:54:04
You know, I'm 44, so I think transitioning to some more machines is good just because the tax it puts on your joints, but I still try to put in free weights.
1:54:16
Are >> are you using any AI in the gym?
1:54:16
Are there are you tracking movements or or an asking question?
1:54:24
I'm a nutrition and I have a >> I have a trainer um he was a former Mr. Universe. He competed in Mr.
1:54:29
Olympia so he I let that I let him do that.
1:54:32
Um he is he is he is um but I my diet and my supplements are um very much like I put everything into AI and I get like I do I do things I don't know if it sounds eccentric but like I'll get blood work and they'll give you a PDF and you can put the PDF in a chatbot and it'll tell you like to analyze it and it can even tell you what supplements you need based on your blood work.
1:54:55
It's probably something everyone should do.
1:54:57
It's not that hard and so like I don't get I don't go out enough so I don't need more vitamin D.
1:55:03
the blood work said that so I take a vitamin D supplement >> because I'm not I'm like inside working a lot so stuff like that. >> Yeah. Yeah.
1:55:09
>> Have you been surprised uh seeing the explosion of peptides?
1:55:14
>> I wouldn't have imagine a world where you know people are clamoring to do like actual >> injection >> injections uh and given given how popular it was.
1:55:23
I mean, it's in the bodybuilding world, there was always like a divide between how hardcore you were, which was like, are you like natural or are you going to >> are you natty or not? >> Yeah, natty or not.
1:55:33
And now nobody's natty anymore, seemingly. >> No one's natty.
1:55:37
Um I'm I'm not surprised.
1:55:39
I I'm I'm surprised actually a little bit how much the tech community has embraced fitness.
1:55:43
I mean, like when I came to Silicon Valley, I was like slightly self-conscious about like wearing long sleeve shirts cuz I thought if I wear a short sleeve shirt, people think I'm a mithead and therefore an idiot.
1:55:53
And people just didn't really lift weights in like 2007, 2008.
1:55:58
>> And I I I really think that like everyone's come around probably to just the science that like nutrition and weightlifting is good. It's good for longevity. It's good for your mind. You'll live longer. You'll feel better.
1:56:08
And honestly, weightlifting is far superior to cardio.
1:56:10
You should do both, but weightlifting is far superior.
1:56:12
or increases bone density.
1:56:14
It's just you can only do one thing, you should do lift weightlifting.
1:56:18
And um so I'm I'm really excited to see people actually embracing this.
1:56:21
I mean, one of the things I learned about bodybuilding that I think is very much consistent with Silicon Valley is I was like, you know, I was like 120 lbs in high school. I played hockey.
1:56:32
I remember I broke my leg and I had to do physical therapy.
1:56:36
And um through my physical therapy, I said I'm going to like I want to learn about like my body.
1:56:40
And there wasn't a lot of information on the internet.
1:56:43
So, I'd like go to the Barnes & Noble and read as many books as possible.
1:56:46
And I learned something about bodybuilding.
1:56:48
And that was if I can change my body, I can change my life.
1:56:51
And it was about control.
1:56:51
And it was about this idea that you don't get in shape in one workout. It's 1% a day.
1:56:55
And frankly, those are the lessons I learned with Silicon Valley.
1:56:59
There's it's not about one idea.
1:57:00
It's about grinding every single day, year after year with consistency.
1:57:05
And overnight successes take thousands of days actually, typically.
1:57:08
And so I think there's a lot of lessons from bodybuilding that I brought to Silicon Valley. >> Yeah. No, 100%. It's a really Yeah.
1:57:14
It's it's a really important frame of mind and we appreciate you sharing all of that with us.
1:57:20
We know we have a hard stop, so we got to get get them out of here. >> Oh, hard stop. >> Yeah.
1:57:25
But thank you so much for taking the time.
1:57:26
>> We have time for one more question. >> Enjoy.
1:57:27
I I hope to be back soon, guys.
1:57:30
Thank you for having me here. >> Awesome. Awesome. Great to see you.
1:57:32
>> We appreciate having you on the show.
1:57:33
We'll talk to you soon, Brian.
1:57:33
Have a good rest of your day. >> Goodbye.
1:57:36
>> Wanted to ask him about uh Super Bowl ads. Oh yeah.
1:57:39
>> Specifically like how how they're thinking about I I know they've run an ad in the past that they they haven't been a annual >> spender on that front, but >> well they do those annual uh uh showcases sort of like the WWDC style.
1:57:54
You wouldn't expect it from Airbnb because they're not necessarily introducing like a new iPhone, but uh Brian's been very outspoken about uh putting the whole team on an annual cadence, a rhythm of releasing all of the information, packing packaging everything up, getting everyone to, you know, rush towards one deadline.
1:58:09
Uh it's an interesting way to run the business.
1:58:13
>> Uh we got cut off on the Sun King of Hollywood about David Ellison and Vulture.
1:58:17
Uh I encourage you to go read it.
1:58:19
>> Yeah, you should go read it. It's a very long piece.
1:58:20
It goes on and on and on.
1:58:22
Uh, so many great stories.
1:58:24
>> You should go check it out in Vulture.
1:58:25
>> I'm glad that we know that the the father and son are dog fighting together.
1:58:30
>> I mean, some great some great writing from Reeves over at Vulture.
1:58:32
Matthew, go check it out.
1:58:35
First, >> before we go into that, let me tell you about graphite.
1:58:38
Code review for the age of AI.
1:58:41
[applause] Graphite helps teams on GitHub ship higher quality software faster.
1:58:44
Matthew McConna is taking a novel legal approach to combat unauthorized AI fakes.
1:58:48
Trademarking himself >> actor plans to use trademarks of himself saying all right all right and staring at a camera to combat AI >> fakes and the print headline is actor is not all right with AI fakes. I love it.
1:59:04
Over the past year, over the past several months, the Interstellar and Magic Mike Star has had has had eight trademark applications approved by the US Patent and Trademark Office featuring him starring, smiling, and talking.
1:59:16
His attorney said the trademarks are meant to stop AI apps or users from sim uh from simulating McConne's voice or likeness without permission.
1:59:25
An increasingly common concern for performers.
1:59:29
Maybe we'll have to get a trademark on you're watching TBPN so we will get paid when someone generates a deep fake of us.
1:59:36
Uh the trademarks include a 7-second clip of the Oscar winner standing on a porch, a 3-se secondond clip of him sitting in front of a Christmas tree and an audio an audio of him saying, "All right, all right, all right."
1:59:49
His famous line from the 1993 movie Dazed and Confused, which I know you haven't seen, but I don't think I've seen Dazed and Confused either.
1:59:58
Tyler, have you seen Dazed and Confused? >> Uh, no.
2:00:01
>> Yeah, just a little bit before all of our times.
2:00:04
Maybe we got to lock in and watch that.
2:00:06
Uh, is there anything else in this uh Matthew McConna piece?
2:00:07
What else is he doing here?
2:00:11
>> He says, "My team and I want to know that when my voice or likeness is ever used, it's because I approved and signed off on it.
2:00:16
We want to create a clear uh perimeter around ownership with consent and attribution, the norm in an AI world."
2:00:23
So, >> uh, lawyers lawyers finding a way If you do pay Matthew McConnA like Salesforce has for an advertisement and you want to run it on connected TV on streaming TV, you got to go to vibe.
2:00:36
co where DTOC brands, B2B startups, and AI companies advertise on streaming TV.
2:00:40
Pick channels, target audiences, and measure sales just like on Meta.
2:00:46
>> Uh yeah, this is interesting.
2:00:46
Um I it doesn't seem like >> they're going to trademark this and then go to Chatbt and say like, "Hey, you want to license my likeness?"
2:00:57
It feels like he realizes the value of like doing a handful of big deals with a sales force. Sure.
2:01:05
>> And probably wants to keep keep doing that. >> Yeah.
2:01:08
It' be interesting to see if every all talent needs to go and >> trademarks.
2:01:13
I mean certain at a certain level.
2:01:15
Uh, I wonder what his to what his total all-in cost for all of those trademarks is.
2:01:19
It's not super cheap to file a trademark. We've done it.
2:01:20
Uh, you know, it's not nothing.
2:01:22
It's not it's not a billion dollars, but um uh what did uh what did Rune say?
2:01:28
He replied to the deciphering of the uh the Rune Elves vague post.
2:01:34
Rune said, "The elves have left for Valinor."
2:01:36
Uh and Boaz Barack says, "Our internal models are so good they can decipher Runes posts."
2:01:41
There's Oas who is a computer scientist uh at Harvard and Open AI.
2:01:48
Uh and Run says, "After a vague post gains a certain level of mystique, I lose the ability to correct misconceptions. I'll let them have it."
2:01:57
And Brandon Girl says, "I was just made aware of John's theory that you were literally just watching Lord of the Rings and live tweeting."
2:02:02
No one no one looked to see if he had tweeted, you know, Gandalf has reached the Shire.
2:02:07
The sh the fireworks have started in the Shire.
2:02:12
They're having breakfast in the Shire.
2:02:13
No one No one checked on that.
2:02:13
So maybe that's the next one.
2:02:16
>> Uh speaking of OpenAI, I have some uh breaking news.
2:02:18
They partnered with Cerebras. >> Oh yeah.
2:02:21
>> So there's uh 750 megawatts worth of like capacity over [laughter] >> it's a big Oh no. >> That is massive news.
2:02:31
[laughter] That is massive news.
2:02:33
Well deserving of the flashback.
2:02:35
Um yeah and uh and it seems like s uh Cerebrus is uh on an absolute tear post Grock deal.
2:02:42
Uh there are there are a ton of rumors swirling about about financings and and uh and uh IPOs and it seems like they're in a great great place.
2:02:53
Uh do we know anything more about the partnership between OpenAI and Cerebra? >> It's in the journal. >> Okay.
2:03:00
>> Multi-billion dollar agreement.
2:03:01
>> I think 10 billion >> 10 billion. >> Yeah. Through 2028. >> Wow.
2:03:04
So >> that's very exciting.
2:03:06
I'm very interested to see how they how they integrate it.
2:03:08
Are they running 40 on it?
2:03:11
Are they >> Yeah, I assume I mean it's definitely I mean not definitely but I would be very surprised if it's going to anything besides just like uh inference, right?
2:03:18
Um >> yes, but but what are they inferencing?
2:03:21
Because they also do Sora video generation.
2:03:24
That's a different model that might need different silicon at a certain point.
2:03:29
OpenAI is working with Broadcom on custom chips.
2:03:32
They're co-developing stuff with Nvidia.
2:03:34
They're working with AMD.
2:03:36
There might be an Intel deal at some point. Who knows?
2:03:39
Like um they they they obviously they use every part of the semiconductor supply chain and uh and how Cerebras fits in.
2:03:46
It doesn't feel like it's just like, oh, OpenAI now runs everything on Cerebras.
2:03:51
It's probably a particular piece of the model architecture or a particular model.
2:03:59
Maybe when you go to a deep research report or do some reasoning, it needs to be faster.
2:04:02
I I'm not exactly sure where they would be taking advantage of it, but it is exciting for them.
2:04:06
I don't know that certainly certainly >> raising one on 22 billion is the rumor.
2:04:14
So they're doing the meme. Remember the meme 2021?
2:04:16
It was like the classic round was like one on 20. Yeah.
2:04:18
Uh and uh but they're of course doing it at at an M.
2:04:24
Uh and also I mean good news for uh the the Open AI folks.
2:04:27
You know they have the 1. 4 trillion in deals.
2:04:29
So they do another 10 billion deal. It's just 1. 41.
2:04:35
>> And at that point, you just round down.
2:04:36
It still rounds down to 1. 4. So you're still good. It's a rounding error.
2:04:38
It's a literal rounding error.
2:04:40
You're good at this point.
2:04:43
>> Plant says every guest on CNBC is like, "Yeah, we are concerned with uh the end of the global order and death of US institutions, but we are looking forward to doubledigit EPS growth this year.
2:04:52
So we want to remain focused on that." >> H brutal. >> Yeah. >> Real.
2:04:59
It's a it's a tough time to be uh navigating politics and business, but uh we're having fun in the trenches.
2:05:07
>> We uh we already covered this one earlier.
2:05:08
Elon said, "What are the odds looking like on will Elon win his case against Open AI?" Yes. >> Cali says 36% chance.
2:05:18
>> Let me tell you about Figma.
2:05:18
Figma make isn't your average vibe coding tool.
2:05:21
It lives in Figma, so outputs look good, feel real, and stay connected to how teams actually build, create, codeback prototypes and apps.
2:05:30
>> Tyler was joking around earlier.
2:05:30
He was saying, "I'm going to move to Oakland." >> Oh, yeah.
2:05:37
>> And become a resident for the chance of being a juror in the trial.
2:05:41
>> I feel like there's a there's a plot of a movie with that where, you know, you you try, you know, that if you really are a crazy corrupt lawyer, you try and get a plant on the jury.
2:05:49
Uh they're making an OpenAI movie.
2:05:52
Maybe they should make a second movie about this.
2:05:55
The the story of Tyler sneaking his way on the journey [laughter] and and and the whole time you're just like you're just like, "Look guys, we got to we we got to settle this in a way that maximizes the total amount of compute in the United States and ultimately delivers AGI as fast as possible."
2:06:10
And everyone's like, "What are you talking about? Someone's guilty here."
2:06:16
>> Uh skilled AI has secured. >> Okay.
2:06:18
So this market is the market's low volume, but it's now up to 57% chance >> that Elon wins. >> Yes. >> Interesting. Yes. >> What's at stake?
2:06:27
What like if if Elon Musk wins, uh what does that do?
2:06:30
Is that just a settlement?
2:06:32
Is that just some monetary penalties?
2:06:34
Does Elon have the st have the chance of getting equity in Open AI?
2:06:38
Because at a certain point, if you convert it to a for-profit and you can just have a settlement where he gets 10 billion in stock, it doesn't really change the structure.
2:06:47
he doesn't get a board seat.
2:06:48
That's kind of a that's kind of a non-issue even if he wins.
2:06:50
But then there could be the nuclear option where he wins and he uh and he gets control and gets a board seat or gets a majority stake.
2:06:59
I mean, if you run back the clock and you look at how much he donated, if you if you weight ownership by nonprofit donations, which is a crazy thing to do that's I don't think on the table, um you you would wind up with a very very different control structure.
2:07:11
But um it is it is an exciting time and I'm sure the court reporting will be fascinating.
2:07:18
I wonder if there will be cameras in the courtroom and if we'll get more testimonies every just uh somebody sketching, right? >> Maybe.
2:07:25
[clears throat] Yeah, we might just get the the the court the court uh >> have we figured out why they still do sketching? >> Um it is fascinating.
2:07:35
I think >> is it just for fun?
2:07:38
I think it's just it has aura. It has it has motion. Like there's nothing.
2:07:44
>> I love how the person sketching can just have so much ability to make the person look cool or really >> I mean a photographer does too.
2:07:53
>> Not as much not as much leeway as you picking your nose and then you look like a fool.
2:07:56
Or they can catch you from a really great angle with perfect lighting and you look like a hero.
2:08:00
They can frame things up.
2:08:02
Just saying if Tyler was sketch artist just be mogging. >> Yeah.
2:08:06
>> And it'd be hard to catch him lacking.
2:08:08
>> Well, didn't they do that with SPF? That is a old time.
2:08:10
That's what I'm talking about.
2:08:13
>> Yeah, [gasps] they just gave him the gigad filter on >> Maybe that's because let's pull up this courtroom uh sketch.
2:08:20
>> Yes, we have our next guest in >> Oh, we do.
2:08:21
That's probably more important.
2:08:23
>> Let me tell you about Gusto first.
2:08:23
It's the unified platform for payroll, benefits, and HR built to evolve with modern small and medium >> cameras are just not allowed. That makes sense.
2:08:32
But but I'm saying why don't we like is that not a rule that we could at one point say like, okay, we can have one camera in the court. >> I don't know.
2:08:40
Maybe there's a a lobbying group. Maybe there's a union.
2:08:41
Maybe it's just the way people like it.
2:08:43
Big sketch, big pencil, big colored pencil.
2:08:48
>> Uh well, we have our next guest.
2:08:48
[music] Welcome to the stream, how are you?
2:08:53
>> How are you, >> gentlemen? How are you doing?
2:08:55
>> Oh, you gave us a preview of the wrist check.
2:08:57
What's on the wrist today? >> Oh, yeah.
2:08:59
I I figured this was going to happen.
2:09:01
[laughter] Um, >> the liquid FP on today. >> Whoa. There we go. That is beautiful. Fantastic. And what's behind you? >> The T30. >> T30. Very nice. And what's behind you? The liquid nitrogen.
2:09:13
You're doing serious business.
2:09:15
>> Yeah, I got a I got a few tanks of liquid nitrogen behind me, which uh were actually like making a ton of ruckus a couple of minutes ago. >> Oh, really?
2:09:22
And [laughter] I'm I'm I'm glad they're not anymore.
2:09:23
Yeah, they were like hissing and making all kinds of noise.
2:09:28
>> So So you're you're fully funded.
2:09:28
You have a lab, you have a team, you're building. What are you building?
2:09:32
What's the first product?
2:09:34
And then I'm sure I'd love to go into the far future, talk about data centers in space.
2:09:37
And then I also want to go back and talk about your career at Robin Hood since this is the first time on the show. >> Yeah. Yeah.
2:09:44
I feel like it's been a long time coming. It has.
2:09:46
So yeah, what are we what are we doing here?
2:09:47
So start out by telling you guys about Aether Flex. >> Yeah.
2:09:51
The mission of the company is to build a power grid in space.
2:09:53
And the core idea behind this >> when I started it a little less than two years ago now was that collecting electrical power or collecting power in orbit was this like really special and important energy source that had not really been thought of as such.
2:10:09
>> And the reason is because if you place things in the right orbits, they're going to be illuminated by the sun.
2:10:12
The solar panels are nearly continuously. >> This is sunny, right?
2:10:16
We learned this term yesterday, Scott Nolan.
2:10:18
sunsync >> or the more specific one is called Dawn Dusk orbit >> which is also sometimes called the Terminator orbit. >> Oh, Terminator Orbit. I like that.
2:10:28
We were talking about Terminator 2 earlier on the show. >> Terminator orbit.
2:10:33
>> The Terminator orbit sounds like the one I want to be in.
2:10:34
Uh so what yeah, what is special about the Terminator orbit and then how does that uh lead into the whole strategy for the business?
2:10:43
>> The thing that's cool about it is is that it's always facing the sun or nearly always facing the sun.
2:10:46
So [clears throat] if if this is the Earth, right, and and the camera is the sun, then it sort of follows this orbit, >> if that makes sense.
2:10:54
So it's kind of passing over sunrise and passing over sunset always. >> Oh, okay. Okay. Got it. >> Yeah.
2:11:02
And the benefit of this is is if you take a solar panel, which is the cheapest form of energy as we know it today on Earth, >> problem is it's not terribly useful because it's very intermittent.
2:11:11
it produces peak power for an hour or two in the middle of the day.
2:11:16
If you take those same or very similar panels and you put them in orbit, they're going to be producing power 247 at nearly peak power.
2:11:26
>> So, you just get so much more energy production out of effectively the same panels.
2:11:31
>> And also, lower Earth orbit is actually kind of an interesting place to build electronics applications.
2:11:35
So I started the company out with the goal of making energy and space a commercial business.
2:11:44
And a little bit more on that.
2:11:44
Um the idea was that the reason space isn't a bigger part of people's lives dayto-day is because it's like for for the large part of history been mostly a government thing, right?
2:11:57
Where is in one shape or form funded by the government or there's government pricing that kind of drives what the activity there is.
2:12:03
But if you can find new ways for people to actually make money doing it, >> then you'll attract more young people to want to pursue those careers and you'll just make space a more commercially relevant part of day-to-day life.
2:12:18
>> So if the applications of space today are like earth imaging, telecommunications, defense, and internet, >> what's that next thing?
2:12:26
And my thesis was that energy would be the next thing. Mhm.
2:12:32
>> A little analogy to uh the past company that I I started. >> Yeah.
2:12:37
>> Uh um the core idea when we started Robin Hood was that if you thought of mobile as a platform >> is like back in 2012 2013 era then the applications that were built on top of it were like photo sharing maps, >> email ma you know like they were mostly digital services like that.
2:12:58
And the thesis that we had was that the next industry to sort of natively exist on this platform was going to be financial services. And that's Robin Hood.
2:13:12
>> And the idea here is is that low Earth orbit is a platform. Yeah.
2:13:15
>> And that energy is the next vertical of the economy that's going to natively exist there.
2:13:20
>> So >> yeah, how much of the energy do you think will stay in space just be routed around?
2:13:25
Obviously, there's new narratives about what you can do in space with data centers and whatnot, but uh versus uh beam the the energy collected on the solar panel down to Earth uh via a laser, something like that.
2:13:38
I've seen uh there's reflect orbital that's just doing mirrors.
2:13:42
There's a whole bunch of people that have said, "Hey, there's cheap and abundant solar up there 247 in these orbits.
2:13:47
Let's get it down to Earth."
2:13:50
Where how are you thinking about where the power should be used? >> Yeah.
2:13:54
Well, I think our our view on it is is we want to have electrical power in orbit and you can use that for two applications. Yeah.
2:14:01
>> You can kind of think of the two applications that we're building >> as almost like appliances that you plug into this new fangled energy grid. >> Mhm.
2:14:09
>> And the first one is actually getting they're doing sub subco component assembly like right next to me right over there. >> Yeah.
2:14:15
>> So behind this uh this this container is our clean room which kind of goes on for a long ways back there.
2:14:21
where the first satellite that's going to space is hanging out right now.
2:14:26
>> Um, so that first thing is basically the appliance that plugs into the energy grid >> and then beams power down to places where there's no power grid.
2:14:35
>> So the use for this is going to be places like >> DoD applications, excuse me, excuse me, Department of War.
2:14:42
>> Yeah, Department of War >> applications. >> DOW. >> Yeah.
2:14:45
where there's no energy grid where you can basically provide um resilient useful power >> where there's a contested environment and [clears throat] stuff like that. >> Yeah.
2:14:56
>> The other application is is rather than beaming the power down to the ground and doing things like powering artificial intelligence data centers, the more natural thing to do is cut out all those energy losses and take the chips and put them directly in orbit. >> Yep.
2:15:09
>> Because they don't actually, >> in the grand scheme of things, they're not the things that are the heaviest part of this. >> Yeah.
2:15:15
So that's the galactic brain and that's actually where a lot of our efforts are right now.
2:15:19
>> Yeah, that's exciting.
2:15:19
Um I remember when we first talked about this like years ago, uh thinking, you know, the natural reaction was going to be, oh, what does this finance guy know about space?
2:15:30
If there, you know, if there's like the math is so important and if you get one number wrong in the spreadsheet, maybe the the economics don't work and it's 10 years out instead of two years out.
2:15:40
Uh but of course you have a you have a math background, so I know you did the math.
2:15:43
Matthew, I know you crunched the numbers, but I'm interested to know how did you actually crunch the numbers to understand that now is the right time with the amount of funding you're going to bring in to the orbital launch costs to the value of what you're doing up there to the materials, how much a solar panel costs.
2:15:59
There's all these different variables.
2:16:01
They all have to synthesize into something that eventually makes profit within somewhat of a venture timeline, I imagine.
2:16:07
What was the actual process?
2:16:10
Were you talking to a team?
2:16:11
Were you in an Excel sheet?
2:16:14
Were you just asking an LLM to sort it out for you?
2:16:16
Like, how did you do the back of the envelope to know that now is the right time that the economics can actually make sense on a reasonable timeline?
2:16:25
>> Well, I did what any rationally minded person would do is I made a big old spreadsheet. >> There we go.
2:16:29
[laughter] Here for spreadsheets. >> I love it.
2:16:34
In all, in all seriousness though, um like I I kind of make this joke with people sometimes is when I started doing this, for all intents and purposes, I was a finance bro. >> Yeah.
2:16:44
>> You could make the argument that was arguably perhaps the archetype of the finance bro in some ways. >> Yeah.
2:16:50
>> Um but in in all seriousness, like I you know, I was approaching this as a novice, as a student of the field. >> Sure.
2:16:57
And the cool thing about this is is that artificial intelligence has made the learning curve dramatically dramatically, you know, easier to cross >> because the hardest thing about physics I remember cuz I studied physics and math in college was you sometimes get like a textbook and you're trying to like learn a new subject, you end up sometimes just getting stuck in the first chapter of it because you don't know the formalism.
2:17:21
like you're you have to you in order to learn these things you have to learn them in the language that they're written >> obviously. >> Yeah.
2:17:30
>> But the difference is now you can just ask questions as you understand them and you know artificial intelligence will kind of meet you there.
2:17:38
So it's been a huge accelerate in learning >> sort of the ins and outs of doing it.
2:17:43
But beyond that look we're a team of like 30 people.
2:17:45
We've got um optics experts.
2:17:48
We've got folks from JPL.
2:17:48
We've got folks from SpaceX.
2:17:50
We've got folks from uh the uh what's it called?
2:17:56
Lawrence Livermore National Lab.
2:17:58
>> So, we've done pretty deep foundational work in understanding kind of how all the components work together, what the economics of them are, asking questions like [clears throat and cough] what is the raw cost of this, right?
2:18:13
what is the cost to buy a component versus what's the cost to manufacture it from raw ingredients, you know, and if you see the delta in any one of these things being too big, you kind of know you have to ask question why. >> Yeah.
2:18:28
>> Um, but to kind of answer the question that you started out with, right?
2:18:30
The goal from the beginning was how do we down cost this down?
2:18:34
How do we make this as close to the sort of theoretical minimum cost?
2:18:39
And if we do that, does this make sense?
2:18:42
Does this make sense at bigger scale?
2:18:44
And I think that there's a path to doing that, >> you know, but the cool thing about it is the path starts with actually showing that you can do this.
2:18:55
>> So, and by the way, you guys should come out when we do this.
2:18:58
>> So, we're going to have a demonstration this summer.
2:19:00
Um, ideally, because we have two satellites going up that are actually going to beam power down from space. >> Wow.
2:19:07
So, we're going to have a something between a scientific conference and like a mini Burning Man [laughter] in the desert.
2:19:15
Uh where we'll where we'll show what this looks like in real life.
2:19:18
>> Yeah, that's that's remarkable speed.
2:19:18
I feel like uh the modern space company uh VA did a little bit of this where it's like if you're going to be taken seriously as a space company, you got to get up into space quickly.
2:19:30
start get up there, get the experience, do something, iterate, start the process instead of, you know, 10 years of, oh yeah, we're going to go one day, but it's got to be the perfect system.
2:19:40
Uh, you know, Vardo went up and back and I think there were a whole bunch of chaos that happened in space, but they learned a lot and it obviously improved the second, third, and then already the Varta launches have become kind of old news.
2:19:53
Oh yeah, I guess they're up and back again.
2:19:55
That happened and it just becomes part of the business.
2:19:58
So, uh, I I love that you're moving so quickly there.
2:20:00
uh talk to me about >> those guys were inspirational for me in that regard.
2:20:04
[clears throat] Like I talked to I talked to Will Buy a ton um in the early days.
2:20:08
>> I once called him my space sherpa.
2:20:11
>> Uh >> and I think for that exact reason I think they went from concept to real thing in space.
2:20:16
Doesn't have to be perfect.
2:20:18
Doesn't have to be the exact version of the thing that you're going to be doing forever and ever. >> Yep.
2:20:23
>> But like you're much better off just demonstrating it. >> Yep.
2:20:26
in year one, year two, year three rather than waiting 10 years because the odds that the thing doesn't work are still pretty high. Yeah.
2:20:35
>> You might as well get it out of the way early. >> Yeah.
2:20:37
You got to blow some stuff up if you're working in the aerospace industry broadly. >> Yeah.
2:20:41
You got to be comfortable make you got to be comfortable like having stuff not work and iterating from there, right? >> Yeah. Yeah.
2:20:47
>> What uh what kind of weird groups are coming out of the woodwork to try to help uh try to get you guys to help them do data center stuff in space?
2:20:54
because there's a lot of different types of groups that seem like they have an incentive to just do something like a space data center just to just for narrative purposes, right?
2:21:04
I mean, this whole thing kind of like heated up because >> uh you had a handful of SpaceX investors really start to get uh excited about it.
2:21:15
Uh but I imagine you've got some kind of strange pitches because like you guys are working on this problem broadly and people are like, "Hey, do you have power?
2:21:22
I want to put some chips up."
2:21:24
>> Yeah, we're cooking some stuff. Stay tuned on that.
2:21:26
We got some we got some good stuff we're cooking up.
2:21:28
Um I will say though, I think the credit for this goes to Bezos who was looking just like very professorial in that talk that he gave last fall where he was like data centers in space might happen in the 2030s and then just everybody in the world was like no we're actually going to do this in the next 5 years. >> Yeah.
2:21:47
Um, I will say though that there is something kind of interesting to this point, which is that I think a lot of people in the space industry see this data centers in space concept as one of the first novel ways to make money in space in kind of a long time.
2:22:01
I would say in in about a decade.
2:22:03
And >> I think that that that's an important point and like one to kind of pause on for a second because the reason space isn't a bigger part of our lives is because we haven't really figured out how to like justify people working on it in mass numbers in my opinion. >> Yeah.
2:22:22
And and Starlink has been a big a big part of uh >> Starlink I feel like is the best example of like hey if you just build the capability of going up and down a lot then you can build a lot of other capabilities telecom being one of them.
2:22:38
Uh one thing I'm curious about is how how has it been like building and running this company versus Robin Hood?
2:22:45
You've sort of like done the meme of like make your money in finance and then work on the thing that like you really want to work on.
2:22:51
Uh, of course, uh, I'm sure you really wanted to work on, uh, on Robin Hood as well, but, uh, is it like, you know, at the same time, like you have, uh, so much to prove, right?
2:23:03
Like you needed, you want to you want to, uh, do something at Robin Hood scale or bigger, right, which is a high bar.
2:23:11
Uh but then at the same time there's maybe more I would hope like some element of like even just like calmness because you're like uh it's not so existential as I feel like early companies are where it's like I need to I just need to like I need to make something in this world. >> Yeah. >> Yeah.
2:23:29
A couple of thoughts on this.
2:23:29
You kind of kind of hit the nail on the head.
2:23:32
This is something I think about pretty often cuz at the on the one hand starting companies and doing things at early stages when they're not really figured out is kind of my happy place. So I do like that a lot.
2:23:42
At the same time it's like kind of a brutal reminder of like when you're in the early ages of starting something, it's actually pretty damn hard because [snorts] you have all the problems of like a small company in my case all over again, right?
2:23:56
my case all over again, right? where you've got like you've got an you know a function within your organization where there's like one person working right and that person for whatever reason leaves >> right and then you're like well got to
2:24:09
rebuild that thing from scratch and so there's like a lot of those kinds of growing pains where you're like >> there's nobody here that's doing that I got to go out and hire a recruiter and then that person has to go out and recruit the person that's going to do the thing. So, [clears throat] in many
2:24:24
So, [clears throat] in many ways, it's like um it's really hard.
2:24:29
>> Yeah, >> I guess that's what I'm trying to say is like it's a reminder that starting companies is actually not that easy.
2:24:35
>> Yeah, you get you get better, but it doesn't actually get easier because then you if it's easier, it just means you need to be doing more and more and more and more and and pushing yourself even even further.
2:24:44
>> I also did um do something that I didn't have >> a ton of professional experience in, which was kind of the point, [clears throat] right?
2:24:52
I wanted to do something that was net new because it was intellectually very interesting for me, but at the same time, and not to throw shade at anybody out there that's building an enterprise SAS company, right?
2:25:03
Like that's this is like new company on absolute hard mode. Um, >> yeah. Yeah. Yeah. >> Yeah.
2:25:11
I mean, like there just is the reality that in enterprise software, uh, you can get a customer to pay you pretty quickly if you build something that works.
2:25:19
in in hard tech and anything that requires government approval or real science and R&D like the money is just going to be further down the road and so that's going to require more risk. That's just a fact.
2:25:32
>> When people talk about progress in space or really any human domain, there's this general sentiment that okay this thing this thing that we want to do is really hard but uh robots will be able to do it in like a few years.
2:25:46
So, uh, and and, uh, you're you're looking a little concerned, which is why I wanted to ask, [laughter] what about the process so far?
2:25:54
I'm sure you've been pitched by various robotics companies that want to help uh, speed up processes internally or or help with the work that you're doing.
2:26:04
Is there anything that that's really adding a lot of value today?
2:26:06
Uh, and >> there's not a lot of robotics going on here.
2:26:12
>> No, this is like >> that's what I figured.
2:26:13
like >> just fire up the welder.
2:26:17
>> It's not to say It's not to say that that's not going to happen.
2:26:19
By the way, there is a welder I think either in the corner or it got moved back to my garage.
2:26:26
>> Have you picked up any new skills?
2:26:26
Can you use a blowtorrch now or are you are you learning this stuff or I mean I imagine you have a team but every once in a while you know you want to take the you want to take the crane for a spin.
2:26:36
>> Sometimes you got to do it yourself. >> Exactly. >> Yeah.
2:26:39
I mean I'm I'm really good at opening boxes.
2:26:41
>> Okay, [laughter] there you go. That's good.
2:26:44
Now, >> I joke around with the team about this sometimes.
2:26:46
I'm like, "Yeah, I left >> a software company to start a hardware company, but somehow I ended up with a job that's emails and spreadsheets." >> Yeah. Yeah, of course. Of course. >> Um, >> exactly.
2:26:57
>> No, but it is fun because I do get to >> I mean, my background is in physics, so I get to think about the actual physics of it pretty often, but we have >> a team of people that's actually doing assembly and doing a lot of the hardware design.
2:27:10
>> Um, but I get to live vicariously through them. Yeah.
2:27:13
>> Um, >> and I can't I can't show you this right now, but literally there is assembly happening >> like on and off.
2:27:18
You'll see people walking behind me.
2:27:21
>> Um, they're like carrying boxes and stuff in there. Yeah.
2:27:24
>> For for the first satellite that goes up. >> Yeah.
2:27:26
Uh, when we watch tours of Abene, Texas, and see data centers, there are a lot of people buzzing around.
2:27:33
It feels like uh you know even if you just get an offtheshelf like NVL72 Nvidia rack uh there's people that are maybe doing wiring or dealing with uh cooling issues or a variety of things a chip that's you know died and you need to replace it that all feels really hard to do in space.
2:27:51
Uh I heard one pitch that uh was sort of making the case that wafer scale compute could be more popular in space because you want the entire model on one chip that's just in one satellite.
2:28:03
You don't want to put a NVL72 up into space or whole rack.
2:28:08
You're just going to have more problems uh in space.
2:28:10
And so it's going to live on one sort of complete system.
2:28:14
We asked the CEO of Cerebras if this was in his forecast and he said no I'm not really interested in in the next three to five years and then he went and did a $10 billion deal with open AI.
2:28:22
So uh he he kind of denied that that was on the road map but what do you think the shape of like the compute workload or the compute hardware that you will eventually put into space or or any company would put into space.
2:28:35
What what will be the norms?
2:28:36
will be the norms? what will be the you know the the the full like we we have uh we very much coalesed around like one rack and AMD and Nvidia they all work within rack scale architectures what will be the equivalent on a satellite
2:28:52
bus that is compatible with a starship or a SpaceX rocket uh like what will the shape of the compute stack be in space >> yeah the way that I think about it is in terms of the workloads and the energy draw or workloads and >> there's versions of this in the future
2:29:11
that are more ambitious right where you say we'll get to much much bigger scale integrated power levels per satellite >> but I think the from my perspective the right starting point is to say what can you do right now in terms of satellite size power envelope per satellite and
2:29:29
can you solve meaningful problems with that right because if you're trying to do something brand new like this you want You want to you want to sort of like you want to have a conscious approach to how you take on risk, >> technical risk more specifically. And if
2:29:42
And if your idea is predicated on making something that's like, you know, the size of 10 football fields on day one, you might want to see if there's a way to do it much smaller at like satellite sizes that are common place.
2:29:56
So the the thought process is is that we'll start out in the next 18 or next 12 to 18 months or so with demonstration missions >> culminating in a firstofits-kind satellite from us that has [clears throat] let's say the 10 to 20 kilowatt electrical power draw that powers a set of 8 to 10 interconnected GPUs that can host a model and do inference on it.
2:30:23
So inference I think is the primary initial use case for this.
2:30:28
There's the idea of like could you do um training with this or could you do stuff that requires massive interconnectivity >> and it's possible I think I think the orbital mechanics of it might be challenging if you're trying to connect 100,000 GPUs together. >> Yeah.
2:30:46
But you don't want to start there because it's it's kind of interesting because we kind of ran into the same problem when we were working on um power beaming from space where the old versions of that concept called for >> um one gigantic satellite >> that would beam power down with microwaves and it a byproduct of the frequency of light and the aperture sizes that you would need.
2:31:09
that thing called for like satellites that are like 1 to 5 kilometers in diameter, right? Like that's too much.
2:31:17
Like if you if your demo mission is a kilometer wide satellite in space, let me give you a little hint.
2:31:25
You're probably not going to get funded for that.
2:31:26
Like there's there's probably not funding out there >> to like spend a billion dollars on something that may or may not work for the first time. Mhm.
2:31:35
>> Um, >> are you That's kind of Are you feeling any uh any push back yet or push back coming on the horizon around like space junk blotting out the sun?
2:31:44
It it's annoying when I'm stargazing.
2:31:46
Is that something we need to worry about?
2:31:49
Is that something you should be worried about?
2:31:52
Even if the worries are unfounded, you need to get out ahead of from a messaging perspective.
2:31:56
like how a lot of the AI data centers probably should have been talking about recycling water a year ago.
2:32:03
So that never became an issue.
2:32:05
It did and then it got debunked, but uh it still was something that you know took over the news cycle for a few days at least.
2:32:13
>> No, I think it's a good point.
2:32:13
So [clears throat] on space junk in general, I think a couple of things.
2:32:19
>> You have to look at space and realize that it's going to get commercialized >> and that might happen this year.
2:32:23
It might happen five years from now.
2:32:26
>> It might happen 10 years from now.
2:32:28
But I think that there is an inevitability that as humans exhaust or really push the the boundaries on like the resources on planet Earth that we're going to look to space to do more stuff there.
2:32:41
>> So I think my starting point is there's going the civilization that we want to build has a massive footprint in orbit.
2:32:48
And so the question is is how do you design these satellites and how do you design these mega constellations that are you know I hope in the next 10 years putting gigawatts or more power up so that actually works and doesn't create massive problems with things like the Kesler syndrome >> and we think about that from the beginning.
2:33:06
We think about the sort of component choices that we have to make sure that as we're de-orbiting them that they're made with components that can demise on re-entry.
2:33:14
And there's a lot of work that's actually going into this already to make sure that you know there's this what's it called where you can basically disambiguate the space that your satellites are in.
2:33:27
That being said, there is space junk out there.
2:33:31
There's actually a lot of effort to sort of identify where it is, to track it, and to do orbital maneuvers to make sure that you can protect your spacecraft against it.
2:33:42
>> But again, like space is really big. >> Yeah. Sorry, Gordy.
2:33:46
>> Uh, any plans to go to space yourself? Blue Origin.
2:33:49
It's It's got to be a little bit weird like working on something.
2:33:53
It's like working on like a restaurant, but you never actually go there, you know?
2:33:56
Like, >> Jared Isaacman's been he's really I feel I feel very confident with him at the helmet at NASA given that he's been to the the thing that he's in charge of.
2:34:04
We got to get you up there. What's the plan? >> He's a good dude. He seems very fit, too.
2:34:10
He seems like he's like um seems like he's he's he was able to survive that and had the build for it.
2:34:14
Um [laughter] I gotta tell you guys to be totally honest because he space. Yeah.
2:34:21
>> Oh, you think the space did the fitness for him?
2:34:23
In that case, count me in.
2:34:25
>> It's a miracle [laughter] up there. That's funny. >> Um one last question. Oh, yeah.
2:34:30
>> In all seriousness on this one, >> um >> can you imagine how upset your stomach would be in space?
2:34:35
Like, can you imagine the pressure changes and like gh >> [laughter] >> You're going to >> That's my reaction.
2:34:42
We're going to let >> leave the data centers there. Okay. Last question. >> The data centers.
2:34:47
>> The the Chevy Corvette ZR1X just posted a 0 to 60 time of 1. 68 seconds.
2:34:54
It goes uh 1/4 mile time of 8. 675 seconds.
2:34:59
Can we call it a supercar?
2:34:59
Is America back in the supercar game?
2:35:05
What's your take on the ZR1X? I think I think so. Okay. But I'll I'll say this.
2:35:10
Um >> I don't think people give a about that. >> Okay.
2:35:14
>> I think what people care about is is the car fun to drive.
2:35:17
And what they should do is they should make that thing with a manual. >> Oo.
2:35:21
>> I think that's >> You guys know I love cars, right? >> Yeah. Yeah. Of course. Of course. >> That's a good take. >> Yeah.
2:35:26
Sort of a uh a Chevy Corvette ST would be the move. Something like that. >> Yeah. >> Yeah.
2:35:32
The that Corvette's really cool.
2:35:34
It's based on a or they it was like inspired by the 458 Ferrari. >> Yeah.
2:35:39
I mean, there's a lot to like about it.
2:35:40
They set the the the speed record for American cars.
2:35:42
I really like how they have the the Chevy executives driving it on the track, setting the records, the employees themselves.
2:35:48
They don't just hire some.
2:35:51
I think that's really cool.
2:35:52
I mean, that's equivalent of like sending an Aetherflux employee to space, you know?
2:35:55
It's like it's a little bit of a gimmick, but it just feels like oh, they really take it serious. >> Yeah.
2:36:00
I don't think it's a gimmick at all.
2:36:01
It's like way cooler to be like one of their employees. Yeah. What you saying?
2:36:05
>> They want to do a gimmick.
2:36:05
You know what would be a really good one?
2:36:06
Put a manual in that thing. >> There we go. Back to the manual. Yes. 100%. I completely agree.
2:36:13
>> Do you see uh any predictions around uh yeah, just just cars uh supercars with manual transmissions?
2:36:19
It feels like there's certainly a lot of enthusiast interest, but it's it it feels like potentially one of those things where >> uh the TAM is actually just like you take like people that will buy a supercar and then like people that will buy a manual supercar because you get into this you start running this calculation of like okay >> uh I'm getting this car and then and then I'm on a hill in San Francisco.
2:36:44
[laughter] Maybe I'm Sam Alman.
2:36:44
I pull up on a hill and maybe I drive stick, but I'm in a $4 million car and it's [laughter] starting to slide back.
2:36:56
>> Sam Alvin stalls F1 on [laughter] on on Gary Street or something headlock.
2:37:01
>> So, but the the thing that I am bullish on is like more more analog controls in cars.
2:37:07
>> Uh, anybody that's owned a Ferrari loves the the how the buttons get all sticky.
2:37:12
>> [laughter] >> I may or may not have been dealing with some sticky buttons this morning. >> No, it's brutal. >> Sticky.
2:37:18
The sticky button thing is is truly so funny.
2:37:20
They're like, "Yeah, like we made these and all after a few years, everything is going to feel like a kid was eating candy in the car."
2:37:26
And if you want to replace it, it's going to be [laughter] >> Yeah.
2:37:31
You go to turn the volume knob and like the volume knob like comes off on your head and you're like, "This is disgusting."
2:37:38
Um, [laughter] >> I got to tell you guys, like >> the fact that there are not too many manuals that are being made today, it it >> like and I love cars.
2:37:47
>> It le it just takes people like me out of it, right?
2:37:50
I'm just like >> if you make a manual, I'm in.
2:37:51
But otherwise, >> there's plenty of cool old cars out there.
2:37:56
there. Um >> well one exciting one exciting thing that that I've been thinking about is I feel like >> uh in 15 years from now it is not unreasonable to imagine that it is illegal to drive a car yourself on the roads like at some point autonomous vehicles will become so safe >> and driving a car yourself is so
2:38:20
dangerous as it you know one of the the number one causes you know motor vehicle accidents being the number one causes of that car manufacturers will start making insane enthusiast cars that are effectively track only because you have some percentage of the population that's just like they're not buying a 911 to like use as a daily. They're like I love
2:38:40
They're like I love cars so I'm going to get this like you know something like uh they're making like a W1 track only edition, right?
2:38:45
And I could see like track only cars having like a real renaissance.
2:38:53
>> That'd be interesting.
2:38:53
Yeah, >> that kind of stuff is happening already.
2:38:56
But I will tell you this, while such a thing might happen in California, >> Florida man will never stand for that. [laughter] >> I agree.
2:39:03
>> There will like Texas will never stand for that.
2:39:06
There are parts of this country that simply will not >> from their cold dead hands for sure. >> Yeah, for sure.
2:39:12
>> But like Florida, man's not down with that. >> I don't know.
2:39:14
I just feel like uh I I I see it.
2:39:18
But at the same time, eventually, you know, you these >> the safety the safety data is going to be overwhelming for perfect self-driving cars in a decade.
2:39:28
Like they're just never going to get >> it will literally be like moms against self-driving, but they're talking about driving. >> Yeah. Yeah. Yeah. Yeah.
2:39:37
>> But but that it's so dystopian though, >> right?
2:39:40
I'm not saying I'm excited.
2:39:40
I'm not saying I'm excited about it >> because >> because cars also I mean if I'm going to wax politic here for a second on cars like cars are really important.
2:39:48
They represent freedom in my opinion, right?
2:39:52
They represent the idea of like being able to have the the freedom to, you know, explore the world, the geography of the of the landscape of everything around us, right?
2:40:02
It's the feeling of like the wind in your hair, the the way the steering wheel feels in your hands when you go over a patch of road, right?
2:40:09
like the way all these things feel like it's not just about transportation.
2:40:12
It's not just about the feeling of power for me.
2:40:17
I think it is like the embodiment of freedom.
2:40:20
>> Um totally and the idea of like >> going through a sort of like technological course and a course of human history where we make that freedom illegal.
2:40:30
Man, that's I find that to be super dystopian. >> Yeah.
2:40:34
Let's hope it doesn't happen.
2:40:34
You can still ride a horse around if you want on many streets.
2:40:37
We might see a resurgence in uh >> yeah stay with the horse.
2:40:43
Stay with the >> people are like I want to live within horseback distance of my office.
2:40:49
>> Give that horse a manual.
2:40:49
[laughter] >> But I don't think I don't think this is going to happen.
2:40:53
I don't think this is going to happen in the next 10 years. >> Okay. >> You know. >> Okay.
2:40:58
>> We'll have you back on and we'll we'll and we'll see what happens.
2:41:00
We'll check in in a decade.
2:41:01
We'll check in next month when there's some amazing news.
2:41:04
Well, like California, California, there's some uh there's some like mileage tax that they're working on where you'll be allocated like a certain number of miles and pass that point.
2:41:15
[laughter] >> Pass that point.
2:41:15
It's like you're going to pay your odometer tomorrow.
2:41:20
>> Leave it to California to come up with all these brilliant ideas. >> Who knows?
2:41:23
>> Well, thank you so much for taking the time to come hang out with us.
2:41:26
>> Come back on as you have these uh launches, announcements. Always welcome.
2:41:32
>> Yeah, we'll talk to you soon.
2:41:32
We'll have you guys out, too.
2:41:34
>> Have a good rest of your day. >> Goodbye. >> 11 Labs.
2:41:37
Build intelligent real-time conversational agents.
2:41:39
Reimagine human technology interaction with 11 Labs.
2:41:45
>> Uh C, we have some we have a small piece of news and then we'll bring in our next guest.
2:41:48
Uh CBS is preparing a new segment called Whiskey Fridays with Tony Dopu Dopu Peel.
2:41:55
I can't pronounce the last name.
2:41:58
Uh, some staff [music] were only first made aware of it because they encountered CBS testing set designs of a faux stock R >> brought to you by >> Jack Daniels.
2:42:08
>> Uh, so they saw Cheeky Pint Cheeky Pint >> and they were like, "We got to have a Cheeky Pint at CBS." >> Okay, Cheeky Pint. Great concept.
2:42:13
They got the faux ball Friday. >> They're hanging out.
2:42:17
It's casual, but they're not drinking.
2:42:20
So, what if you did Cheeky Pint with whiskey?
2:42:24
>> Wait, is this a re This cannot be a real photo.
2:42:26
This is has to be fake update.
2:42:28
Here's what it >> here's what it may look like, okay?
2:42:31
Because that makes no sense to just put a news desk in that type of uh set.
2:42:36
Anyway, we'll have to tune in.
2:42:36
We'll have to uh give it our review.
2:42:37
But until one Friday comes because we were just talking about cars.
2:42:47
>> Uh this post here from CDTV, the goose says, "Remember when Quo flexed driving 60 miles hour?
2:42:54
I [laughter] go a mile a minute, skirt.
2:42:59
>> Yeah, that's actually quite slow on most freeways [laughter] where the speed limit 65 and most people are going 85.
2:43:06
Uh 60 might be time to speed it up, Quo. Let's step it up. Let's step on the gas.
2:43:13
Let's get you into a ZR1X hopefully.
2:43:15
Anyway, let's bring in our next guest, Gabe from Noise.
2:43:17
He's the CEO and we got some fantastic news. Thank you for waiting. >> How are you doing? Welcome.
2:43:25
>> Good to see you, dude. >> Good to see you.
2:43:26
>> Absolute pleasure, gentlemen.
2:43:28
>> It's great to be here.
2:43:29
>> First time on the show.
2:43:29
Kick us off with an introduction on yourself and noise.
2:43:33
>> And get the gong ready.
2:43:34
>> I will I will warm up the gong. >> Yeah. So, my name is Gabe.
2:43:36
I'm one of the co-founders of Noise.
2:43:38
Um, we started this project maybe at the start of 2025 when we started building it.
2:43:43
But the idea is to build this trading platform for relevance, right?
2:43:47
So, can we give users the ability to long or short trends, brands, ideas, and have these markets kind of be rooted to uh social data in a way?
2:43:57
So, you know, when you combine the trading activity and you combine the kinds of things you're seeing on Twitter or Tik Tok or Reddit, you kind of end up with this uh objective measure of cultural relevance for different types of brands or trends.
2:44:10
And uh for many reasons, we think that's extremely important for where the world is at today.
2:44:14
But maybe we can jump into those uh that you guys. >> Yeah. So maybe Yeah. May maybe an example.
2:44:19
So like uh we when we started covering Leubu, we were like this must mean it's about to be over and I think it was like I think just a lot [laughter] of the stock at least has sold off a lot in that situation.
2:44:32
There's a public company associated with the product.
2:44:34
So that that >> you can track Google trends but uh yeah walk me through more of how you pull out signal from all the noise around a brand there's so many different data points that you can use to track so like Google trends is a good example >> Google trends uh in an era where people are spending more time in apps more time in and all these things like social relevancy how much something's being talked about >> uh is uh there's less signal there. >> Yeah. Yeah. Yeah. What's the process like? >> Yeah.
2:45:04
>> Yeah. So Google trends is you know if you were to look at a market on noise let's say it's cloud code or it was labu you would see something structurally similar to Google trends >> the problem with that is you know like 20% of the information that is going into Google trends is what actually matters in today's world right what was
2:45:21
saying uh you're seeing things on Tik Tok on Instagram on on Twitter um so the Lubu one's interesting we basically uh we partnered with Kaido first so they were doing this already for the crypto industry specifically So they were building social graphs on Twitter and they were able to tell you you know how much relevance does poly market have versus call sheet in that industry. How much relevance does um you
2:45:42
How much relevance does um you know AI compared to DeFi have and then you can see kind of how that relevance changes over time.
2:45:50
What we care most about is kind of the market component of it which is you know it's great like you can get a snapshot of where attention is today.
2:45:57
You know can you really trust it?
2:45:59
That's that's something to discuss as well.
2:46:01
Um, but we want to use markets that have kind of this forward-looking nature.
2:46:04
Um, and how basically all these different types of industries make decisions based off of trends and resource allocation, right?
2:46:10
Um, so where are trends going to go in the future?
2:46:16
Where is relevance going to shift?
2:46:16
We're talking about movie theaters.
2:46:18
If you're talking about, you know, is claude is anthropic still going to be as important as it is today in the AI industry in 20 by the end of 2026.
2:46:25
These are all like extremely interesting questions, right?
2:46:29
Um, so yeah, >> if you're pulling uh if you're if you're using signal from social and uh and these markets get to some amount of scale, there will become an incentive for uh market participants to try to game it, right?
2:46:45
I can think of somebody spinning up a bot farm and and talking about Leubu millions and millions of times in a inorganic way.
2:46:52
How have you guys thought about like parsing through all the noise and trying to find like real signal? >> Yeah, for sure.
2:47:01
Um, it's a good question and it's often like one of the number one questions we get, but we pull from a variety of sources and I'd also add that um the relevance on noise is very much market based.
2:47:15
market based. So it satisfies the criteria of any other market which is you know if the relevance of let's say claude or movie theaters or peptides is going to go up it's because people are inherently putting capital behind those positions right they're longing it um and those are good questions but I think you the best question that we could try to
2:47:34
answer right now is is social media data alone today a good measure of relevance a good measure of understanding the shared interest of the world our bet is that you know Markets are probably the best coordination mechanism for these kinds of questions and we just need markets to be a little better about reading where genuine interests are and where those trends are uh than social media data alone. So is it a solved
2:47:57
So is it a solved problem? No.
2:47:59
We'll continue to basically build in that direction, but uh it's definitely interesting.
2:48:05
>> What uh what are some rising trends that you guys are thinking about building markets around for this year specifically? >> Yeah.
2:48:14
Uh, I really indie rock music.
2:48:14
I think people aren't really noticing this, but it's it's been on the rise for the last 18 months.
2:48:24
>> My prediction is this is coinciding with uh this return to in-person meta.
2:48:26
Indie rock music is probably the best kind of music for that. >> Um, so that's one. We see Claude Code.
2:48:32
I think one of the interesting things is with noise is you kind of get to see where echo chambers are breaking, right?
2:48:41
because claude code was kind of this thing in Silicon Valley that took over the entire timeline and everybody assumed you know nobody's using chatb at this point that these open AI products are basically in the dust but um the things that we were seeing is the
2:48:56
engagement and and the kinds of interest that people have in chatb is still higher than claw uh no matter what so um when you actually compare these things side by side at a very global level it's interesting to see uh where these trends are actually at >> Yeah. >> Yeah. How do you think about relevancy >> Yeah.
2:49:11
How do you think about relevancy to particular sub communities or niches?
2:49:17
Because we were reading this piece in Vulture about uh David Allison and we were joking that they they were saying that Oracle is this sleepy no-name company that makes a lot of money but it's not known or it's not popular.
2:49:28
And in us it was like in the headlines all last year.
2:49:32
We were following it very closely.
2:49:33
We know everything about the about the company.
2:49:35
Uh, and so but but at the same time I understand where the vulture writer is is talking about in the sense that like Oracle is not a company that >> they're like Oracle the sailboat company. >> Yeah. Yeah.
2:49:46
Like if you stop someone on the street they might not be talking about Oracle where they might know about Leubu.
2:49:51
So how do you think about someone's stock rising relative just to their niche? >> Yeah.
2:50:00
Um, one of the most interesting things that we found when we launched our beta >> Mhm.
2:50:05
>> in summer of last year was that people were kind of, you know, we kept seeing uh maybe 40% of the users that we had invited onto the platform using it every single day, every single day.
2:50:15
Consistent time patterns and we were like, you know, why the hell are you using this so much? Right?
2:50:21
So, we're trying to talk to these people and part of it was they were they wanted these niche trends to be part of their daily news cycle, right?
2:50:29
They wanted to see how the relevance was changing based off things that they really cared about.
2:50:32
And mind you, we're talking about some projects in in the crypto industry that people don't really know your audience probably doesn't even know exist.
2:50:40
>> Um, and it was about kind of engaging with other people who are also interested in those things or have differing opinions about those things.
2:50:48
Um, and basically creating communities around these niche trends.
2:50:50
So, uh, yes, it's interesting.
2:50:55
>> Yeah, >> more interests are becoming niche over time.
2:50:57
Um, but still the echo chambers and seeing where you're actually at is is something crazy.
2:51:03
>> We love we we love an echo.
2:51:04
>> We love echo chambers.
2:51:04
We celebrate echo chambers. >> Give me the lead. Who led the round? How much did you raise? >> Paradigm 7. 1 million. [music] >> Great hit. With authority. With authority. >> Congratulations.
2:51:21
>> Thank you so much for coming on the show. Great.
2:51:23
Great to finally have you on the show, Gabe. Uh excited to cheers.
2:51:28
>> Excited to track noise on noise in the near future.
2:51:32
>> We will talk to you soon.
2:51:34
>> Have a great rest of your day. Bye.
2:51:35
>> Gemini 3 Pro, Google's most intelligent model yet.
2:51:38
State-of-the-art reasoning, next level vibe coding, and deep multimodal understanding.
2:51:42
Um we have our next guest already in the reream waiting room.
2:51:47
We have Alfred back on the show for the second time from Listen Labs.
2:51:52
He's the co-founder and CEO. Welcome to the show. How are you? >> Thank you so much. I'm excited to be here. >> I'm excited. >> Welcome back. I love the energy. We're fired up. Fired up.
2:52:01
[laughter] And we got a we got a special We got a I mean, real quick, >> reintroduce yourself for people that missed the first appearance.
2:52:08
Um, and then we'll get into these special deliveries that you got for us. >> Amazing. Yes. So, I'm Alfred.
2:52:14
I'm the CEO of Listen Labs.
2:52:17
What we do at listen is an AI that speaks to thousands of people and tells you what they want and why.
2:52:23
And this helps you develop better products or fix your marketing campaigns.
2:52:27
And what you have in the room with you is some incredible products that have been developed using lesson. >> Um. >> Yes. Yes.
2:52:33
So take us uh what what is this? How are you involved?
2:52:36
What happened with this crazy? >> Did you want John?
2:52:39
Did you want John to wear this?
2:52:42
>> Who are you talking to?
2:52:42
You didn't talk to me about [laughter] this, but somebody's >> going to put them on. >> Yes. Who's who's happy?
2:52:47
[laughter] >> Um, you know, products are all about finding the right audience.
2:52:53
Um, and so, um, these are shorts from Chubbies, which has been one of our early customers.
2:52:59
And they used Listen to test their prints, test their fitting.
2:53:02
And um actually one of them they developed a new entire new product line for kids uh kids shorts where they used listen to interview hundreds of kids and they figured out like the liner in the shorts that they had previously were very uncomfortable.
2:53:19
>> Oh very >> maybe maybe something for you to wear. >> Yeah. Very very fascinating.
2:53:22
>> Yeah. Very very fascinating. uh what maybe 10 years ago >> what what are some of the challenges with consumer brands when it comes to un like really understanding your customers because I think with >> uh you know with with a SAS company early stage SAS company you can almost
2:53:38
you can just talk to all your customers many's probably a power law where there's one customer who's providing 80% of your revenue in the first couple >> whereas whereas with consumer brands you could go talk to 20 customers and then like you could get like terrible signal because you just happened to to pick incorrectly. >> Yeah, totally. >> Yeah, totally. >> Yeah.
2:54:00
>> Yeah. Yeah, I mean like you in the olden days you were stuck in this paradigm between you could use a survey but then you would get a ton of people not really paying attention >> and they would answer your your questions uh but you wouldn't get like rich deep insights and you could then have one-on-one interviews but as you
2:54:16
said if you have thousands of customers it's really hard to do them at scale and so with listen you get the best of both worlds where you have an AI talk to all of your customers and then you can figure out the nuances like which segments work which don't and people are much more honest talking to an AI than talking to a person uh is something that we found out. So you get kind of their
2:54:36
So you get kind of their feedback is more driven to how they actually will behave in the future.
2:54:43
>> I have a company that uh that I'm going to email and tell them to use listens.
2:54:46
I don't know them at all.
2:54:49
It's this company they make uh sound machines for kids. Oh.
2:54:54
>> And I've had multiple of them.
2:54:54
I don't know why I've had multiple of them because both of them uh when you're trying to adj if you just like touch the thing in the wrong way it triggers like a motion thing and it just starts playing music.
2:55:04
[laughter] >> Like it literally I went I was I was messaging >> quietly >> I I I felt bad.
2:55:10
I was messaging the the support after uh a week ago saying like please let the CEO know that your product makes >> uh uh bedtime worse a disaster and I will buy another >> I will buy another one but as soon as you fix it but you need to fix it I I'll give you the I'll give you the third chance.
2:55:30
>> Um and that that just seems like an incident where they shipped a product and then they're it sells well because it's in demand but they're not actually paying attention to like how people experience Do do you feel like you're able to pull out that emotional response from like you you interview a hundred people, they're all like, "It's okay."
2:55:45
And then there's that one person that clearly found a fatal flaw with the product, is animated about it, they're aggressive, they're emotional, maybe they're screaming at the AI, maybe they're being rude, you censor the expletives, but you know that there's emotion there. It's valuable. Good. Good on you.
2:56:02
Uh and uh and you're able to give that more weight.
2:56:05
like how do you think about balancing out all the different uh the different emotions that come through in responses because sometimes they can get collapsed in AI models. >> Totally. Yeah.
2:56:14
I mean the CEO of Sweet Green I think was on the on TBPN talking about this how like surveys miss the outliers.
2:56:21
Uh yeah, that's the protein bolt um that they developed using lesson.
2:56:25
But um like the the other methods of collecting feedback miss the kind of the crucial pieces of feedback that really matter and it's often about like one or two or or a couple of people that are part of your segment that will drive most of your revenue and they will be much more animated and care much more.
2:56:45
And so the AI is able to detect kind of their emotional um the way they show up emotionally as well as kind of the nuances of um how they answer the question.
2:56:55
We have something called uh response quality.
2:56:57
So the AI can rank how well this person kind of answers the question and how much they know about their product.
2:57:04
So it's able to kind of surface those outliers to you and then like give you actionable recommendations.
2:57:09
What is the actual workflow like uh in general in order to actually start talking with customers through listen?
2:57:17
Uh I imagine it's also different with um like a kids product line with chubbies like how do you actually facilitate getting a >> a parent to allow their their kid to talk to a robot? Um I'm very curious.
2:57:32
>> Yeah, of course you need um the parents of concerns but u it's essentially four steps.
2:57:36
steps. So you start by asking your question and which could be you know SAS tools also use it like replet so they could ask how how should we what should we change in our product if you compare us to lovable and then listen will go and recruit that audience for you so
2:57:52
we'll find replet users as well as lovable users and we have 30 million people in our database so we can find like pretty nuanced um recruits and then listen will go and have video calls with them where they could potentially also share their screen. So you can have
2:58:05
So you can have thousands of those video calls and then the AI will kind of analyze those and give you recommendations of what to do. >> Mhm. >> Makes sense. >> Uh take me back.
2:58:15
We didn't really talk about your your uh your earlier career the first time you were on the show. Uh B fake image app.
2:58:24
What was the story there?
2:58:26
Uh [laughter] how did you build it? How did you scale it? What was the value prop?
2:58:29
And how did you wind up selling it too? >> Yeah, for sure.
2:58:33
Um, so we we my co-founder and I we built this AI consumer app um which was essentially kind of giblify.
2:58:40
You could giblify yourself.
2:58:42
You could do this kind of image prompts back >> style transfer almost. >> Yeah.
2:58:48
>> And the real use case was creating Tinder profile pictures of course.
2:58:50
Um and so it like blew up on Reddit.
2:58:53
We were on the front page of Reddit and we had 20,000 downloads in one day.
2:58:56
And that was the inspiration behind listen because we had these many users and we were experimenting with LMS at the time and thought it would be interesting to let an AI talk to our users and it turned out to be really useful.
2:59:08
So we were like why are we making this shitty app like let's just sell this thing and >> and then we actually ended up in this limbo state where it did work for us but it still took us 18 months of >> like making the product perfect um before it became useful.
2:59:24
And that's something I've learned that like being early looks the same as being wrong.
2:59:30
>> Um, and a lot of people we talked to told us they've already built the product that we were building and it didn't work.
2:59:36
And so we had so much rejection.
2:59:38
Um, but now since we launched 9 months ago and when I was last on TBPN, we've grown our revenue 15x.
2:59:44
We interviewed million people. Let's go.
2:59:50
Raised 100 million in total now. So, let's go. >> There we go. >> Congratulations.
2:59:58
>> I'm still trying to get used to the energy of, you know, I'm Swedish.
3:00:00
I'm I'm trying to amp it up, but >> No, I mean, this is night this is night and day from the last time. You you're fired up. I love it. >> Great.
3:00:08
>> Uh what's uh what what's next?
3:00:08
Just just scaling uh on the on the customer side, hiring the >> whole Fortune 500. You got to get them all. >> That's right. That's right. Got to collect them all.
3:00:17
>> Sweet green, Google, Nestle, Skims, Microsoft.
3:00:20
There's a couple going after 500 companies one at a time.
3:00:23
But we have like hiring is the number one priority and uh we're trying to do these tricks to stand out.
3:00:30
We did the the billboard.
3:00:32
I don't know if you saw that where we had >> uh you know one one thing we've learned learned is that there's so many companies growing really fast raising a ton of money and so you just got to communicate your culture and get people excited to join.
3:00:45
And so we made this billboard that had just black text on on white where that led to a puzzle, an engineering puzzle.
3:00:53
And that made it much more attractive for folks to try to join the team because they realize we're a team of like competitive programmers and and puzzle hunters overall. Puzzle hunters. Love it. >> Yeah. Yeah.
3:01:05
Mike Isaac in the New York Times wrote a whole piece about how like how obscure billboards are in San Francisco.
3:01:11
It's like a few people talking to each other. Very in-group.
3:01:15
But I love when people do uh fun stuff with Billboard. It's always great.
3:01:17
Thank you so much for taking the time.
3:01:21
>> So great to have you back on.
3:01:21
I'm sure you will be back on this year with the amount of momentum you guys have.
3:01:25
Uh and looking forward to it.
3:01:28
And uh yeah, thanks thanks for this thanks for this protein max bowl. We'll we'll split it.
3:01:33
We can each still get like 50 g of protein.
3:01:35
[laughter] >> That's plenty. That's plenty. >> Plenty. We'll talk to you soon.
3:01:37
Have a good rest of your day. Goodbye. >> Cheers. Railway.
3:01:41
Railway simplifies software deployment.
3:01:44
Web apps, servers, and databases run in one place with scaling, monitoring, and security built in.
3:01:50
Uh TJ Parker asked a question.
3:01:50
He said, "Why are there not a hundred times more weird consumer AI things going on?" Nikita Beer answered.
3:02:01
He said, "Hold that thought until Dom Hoffman launches."
3:02:07
And Dom quote tweeted and just said, "Sup."
3:02:09
Of course, uh Dom is the creator of Vine >> and his company is called Sup.
3:02:16
>> Oh, I didn't know that.
3:02:18
>> So, but it was a it was a good response. Dom created Vine. >> Yeah.
3:02:21
Uh and and a number of other things.
3:02:23
Uh a fantastic creator on the internet has has created a bunch of like fun moments on the internet.
3:02:27
I've been following his career for a long time. I enjoyed Vine. Were you ever on Vine?
3:02:33
>> Uh I was on it, but I never I never I never like fell in love with >> I created the skits, so I add it on Vine. No, not really.
3:02:40
But I I was actually experimenting with the Vine format very seriously and I would do these like hyperlapses and infinite loops.
3:02:49
You could do this this fun format where you would take a little like basically an image as you went around your house and if you ended at the start it would be an endless loop and Vine was very good about endlessly looping videos.
3:03:01
So you could do all these cool fun things with it.
3:03:03
Uh I had a lot of fun with that format. It was great.
3:03:05
Uh, did you see that Havana syndrome is real?
3:03:10
>> Apparently, this is crazy.
3:03:10
I Smith says Havana syndrome was real and we got the device that causes it.
3:03:16
>> Conspiracy theory that turned out a number of months ago, the US captured a weapon that has been associated with Havana syndrome. >> Uh, Havana syndrome.
3:03:22
Let me >> disputed medical condition.
3:03:25
Starting in 2016, in about a dozen overseas locations, US and Canadian government officials and their families reported symptoms associated with a perceived localized loud sound.
3:03:38
The symptoms lasted for months, including disabling cognitive problems, balance problems, dizziness, insomnia, and headaches.
3:03:48
Havana syndrome is not officially recognized as a disease by the medical community.
3:03:51
Uh but apparently uh there is reporting in CNN now that there's a device.
3:03:57
>> Well, there have been a bunch of real investigations into this because it's happening all over the world.
3:04:00
People are like, I feel terrible. Why do I feel terrible? I'm hearing things. I have a headache. I can't balance.
3:04:08
>> Uh and so this was just a great mystery.
3:04:12
>> CNN now reports the device linked to it was purchased by Homeland Security in the waning days of the Biden administration.
3:04:18
And DoD has spent a year testing it.
3:04:20
It has Russian components and fits into just a backpack, >> which is scary.
3:04:27
>> Will a defense tech startup build one and go through why combinator? [laughter] Who knows? Stay tuned.
3:04:35
>> We might see someone commercialize this technology any day now.
3:04:38
Uh Tyler, >> I want to see um someone if they're building it, I want them to use it on themselves like uh Jake Adler at Pilgrim. >> Oh yeah.
3:04:47
>> Cuts his leg openings. >> Prove that it works.
3:04:49
>> He shoots the VC with the I'm so dizzy.
3:04:51
I got to write you a term sheet.
3:04:53
[laughter] Uh Als says that jobs exist because important people want to have large pyramids of people reporting to them.
3:05:01
Even if the pyramids do nothing useful, AI will not change this. Oh, interesting. Fake jobs.
3:05:06
Um in other jobs news, uh there's an opinion here.
3:05:10
Our brightest minds are disappearing into finance, management, consulting, and corporate law.
3:05:16
And uh is this one of Marinetti says no we are using our best minds to allocate resources optimally. How terrible.
3:05:26
>> Of course we love finance, management, consulting and corporate law.
3:05:28
These are all valuable pieces of the economy. They are important.
3:05:33
Salesforce who we have the CEO of joining us right now.
3:05:36
Mark Benoff is in the ream waiting room and we will bring him in to the CBP Ultra. Mark, how are you doing? >> He's back.
3:05:45
>> Great to see you guys. back for round two.
3:05:47
I prepared for this interview. I prepared for this.
3:05:50
I prepared for this interview.
3:05:52
I went >> No, we loved it. We loved it.
3:05:53
I I will say it was one of the most fun conversations we've had all last year. >> It's amazing. Amazing. >> Really? >> No. Yeah.
3:06:02
>> Well, then you guys are just not having enough fun in your life. I'm your biggest fun. >> Here. Here it comes. Here it comes.
3:06:06
The >> Don't sell yourself short. >> The blogging starts.
3:06:10
Uh, but I prepared for this interview by going to Slackbot.
3:06:15
uh now powered by Anthropic and I asked what is the single best Metallica song.
3:06:21
>> It said master of puppets. Agree or disagree.
3:06:25
>> Okay guys, I know that you are this isn't at the tip of your tongue.
3:06:27
So I was ready [laughter] and I was going to flip it for your partner so you can he can get all the the words cuz you know we had some issues last time.
3:06:36
Let's go through the details.
3:06:38
>> Are you going to say name your tune? >> Yes.
3:06:42
It was not a great moment for your show.
3:06:46
>> It was a rough moment. It was a rough moment. >> It was rough.
3:06:48
>> Are you gonna sign that?
3:06:48
Are you gonna sign that and send it to us so we can hang it in the rafters? >> I'm not. It's mine.
3:06:53
You [laughter] can get your own. >> Metallica. com.
3:06:57
We run it actually on Salesforce. We run. com.
3:07:02
>> You can get to your Metallica album on there and all the other good stuff that you need to kind of >> Okay.
3:07:06
So, I'm going to I'm going to give the I'm going to give my uh uh recap of John using Slackbot this morning because >> he this was an ASI moment for John.
3:07:15
He was like, I was very pleased with it.
3:07:20
>> John uh we do the show all day long.
3:07:23
There's a lot going on in Slack and so catching up is >> is tough.
3:07:28
>> This absolutely nailed the summary.
3:07:30
Immediately found something that was like very >> actually interesting, important.
3:07:32
We're like, whoa, we missed that.
3:07:34
I probably truthfully had about like 200 notifications across 15 different channels as they build up and it basically put together a deep research report of every little item, picked it out when am I mentioned and it was exactly what I wanted to catch up and then I went to it and I asked okay clear all of the notifications.
3:07:51
[laughter] It couldn't do it but it gave me the shortcut shift escape and it didn't it in two seconds. So I was very satisfied.
3:07:58
How has the response been from your customers?
3:08:02
>> Well first of all well there's the response of my customer right there.
3:08:03
I would say I'm so excited that we could finally get this out of the shop and into people's hands.
3:08:10
I've been using it myself for months.
3:08:13
>> Yeah, >> it's completely changed my life.
3:08:13
I think it will change your life.
3:08:15
I think it'll change your show.
3:08:17
I think it's going to make everything better >> because, you know, we we've we've talked a long time about prompt engineering in AI.
3:08:24
You know, when you're writing your prompt, you're kind of coming up with your question.
3:08:26
Now, you really see the power of context engineering.
3:08:29
that is it's looking at all the data about your show and everything you guys have ever said.
3:08:35
It can even read your DMs and then it's coming in and it's saying, "Hey, right here, this is what you need to ask Mark Benny off this question.
3:08:42
This is going to this is the zinger for him."
3:08:45
>> And that's the prompt you could give it, which is, "Hey, based on everything we know about Mark, everything that's ever happened in the show, everything that's happening inside Slack now, plus everything that Enthropic knows, everything that everyone knows, what's the zinger for Mark?"
3:08:59
and then it's going to come up with it. >> Yeah.
3:09:02
Uh talk to me about the uh the the the tone and the speed.
3:09:07
I noticed that uh it responds like an LLM.
3:09:10
It's giving me a few paragraphs.
3:09:12
It's not acting like a person who might respond with on it and then okay, here's what I found and then it's like six different messages.
3:09:21
Do you is that intentional?
3:09:21
Do you like the the the tune or do you see it evolving to your style over time?
3:09:30
Where does all this go in terms of the the flavor of Slackbot's personality powered by >> This is really different than our last interview.
3:09:37
We're going deep in product.
3:09:39
Okay, so number one, >> we love it.
3:09:40
[laughter] >> Number one, every company is going to have a customer agent and an employee agent.
3:09:45
And that's why we've been working on agent force to build the orchestration layer, the observability layer so that companies can get out there with their agents.
3:09:53
And that's what I've been so excited about.
3:09:55
Then all the apps like Slack is only one app we make.
3:10:00
We have a whole bunch of apps like Tableau, our salescloud, our service cloud, marketing, commerce, and and on and on and on.
3:10:07
We have a whole family of apps that help you run your business.
3:10:10
and then a huge set of data uh capabilities including Informatica, MuleSoft, our data 360 layer that let you federate and integrate your data which means that it's going to find all the data in your company and bring it together.
3:10:24
>> Now what you're not seeing yet in Slackbot, but what I have >> is that you just you just hit a button and it connects to all your Google sources also >> and it connects to all >> you're keeping the good stuff for yourself.
3:10:36
this a fast takeoff scenario and [laughter] you're like we're keeping this for ourselves.
3:10:40
We can't let it we can't let it out.
3:10:43
>> I my like I was at a conference for the last two days, really cool conference in Honolulu, Hawaii. Okay. >> Um I live in Hawaii.
3:10:49
So I popped over to Honolulu and it was called the Honolulu Defense Forum.
3:10:54
And there's so many of my customers there. It was really cool.
3:10:56
But I didn't have time to get briefed on all these customers.
3:10:59
So I'm doing the briefing myself.
3:11:02
I just say to Slackbot >> in real time, I'm meeting with this customer.
3:11:07
Tell me everything about the customer.
3:11:09
And it's not just getting the experience from the public web, >> but it's also then looking at all my proprietary databases and saying, "Boom, here you go, Mark. You're ready."
3:11:19
And the prioritization, I I think you're going to have a great experience.
3:11:25
I want to hear your exact feedback after you kind of get into it for a few days because it's changed how I work. It's awesome. >> Yeah.
3:11:32
I I had a I had a great experience.
3:11:33
I didn't feel like I needed a smarter model.
3:11:35
It did seem like I was on claude three, not four, five, which I've used and is great for some.
3:11:43
>> You want to know why you feel that way? >> Why? Yeah. Why?
3:11:45
>> Because you're getting the data from Slack.
3:11:48
>> You have so much data about your business or what you know your show your everyone >> that you that's what you've been missing in all of your prompts. Yeah.
3:11:56
you're when you go on Anthropic or you go on Gemini or OpenAI or whatever you use. Yeah.
3:12:03
>> You know, it doesn't know anything about you.
3:12:05
It doesn't have your context.
3:12:05
It doesn't have your data.
3:12:07
And that's what I mean context engineering. It knows you now. It really does.
3:12:12
It knows so much about you, your company, everything you guys have done, what you've built, this great show you have.
3:12:19
>> And now it's able to really tell you, and you should like ask it like, "Hey, what are the three things we should do to, you know, increase viewership?
3:12:24
what are we gonna what should we be doing to you know increase our revenue make us more profitable what is my priorization for the week try like because it knows so much about your company now because of the huge investment you've made in Slack >> you're going to get a great outcome I'm really confident and you know I don't know if you've seen some of the videos that Mr.
3:12:45
Beast has been doing >> but he is really in it to win it on this and he runs you know his whole company >> people talk about Mr.
3:12:53
beast like like he's this consumer guy, but this guy loves enterprise software entrepreneurs as an entrepreneur. >> That's true. >> Oh, he's amazing.
3:13:02
The first time I ever talked to him was a couple years ago.
3:13:05
He goes, >> I am going to be like Steve Jobs.
3:13:08
I am going to be >> like Larry Ellison. I am I'm like, what?
3:13:15
He's like, yeah, I want to be one of the great entrepreneurs of all time.
3:13:20
>> So, he really has a mental model that's super unusual.
3:13:23
Well, he runs his whole companies on Slack.
3:13:25
So now he has the ability to kind of >> get to a new level by bringing AI in because when you take AI data and the app together as you see >> you get a tremendous outcome.
3:13:37
AI by itself the models great fantastic but they're commodities at this point. We all know that. >> Yeah.
3:13:44
>> The data sets >> those are commodities on the consumer side but not your data set.
3:13:49
>> The only one who has your data set is you. And then three, the app. You've chosen Slack. Thank you for that.
3:13:54
And so now you put one, two, and three together and bam, you are ready to roll.
3:13:58
You know, you can now sleep with one eye open. >> There we go.
3:14:05
Uh give us a Super Bowl preview.
3:14:07
What What's What's been exciting in the past that you've done?
3:14:10
What do you want to do in the future with the >> What's your most memorable Super Bowl? Let's start there.
3:14:14
[clears throat] >> I think there is going to be some pretty cool stuff coming from us uh for the Super Bowl.
3:14:20
I'm not going to give you all the secrets, >> okay?
3:14:23
>> I may have already given you some of the secrets, okay?
3:14:25
>> But I don't think I can give you any more of the secrets because it is going to be astonishing what we're doing and everything that we just talked about somehow serendipitously.
3:14:33
Maybe you guys already know. >> Yeah.
3:14:36
>> You know, but everything that we just talked about, take all of that and make it into a Super Bowl ad over the last 10 minutes and I think you're going to have something astonishing. >> Yeah.
3:14:44
Well, what do you think about uh uh model pickers selecting the model that I want to use?
3:14:49
How much of that should live with the end user?
3:14:52
I go to Slackbot and say, "Hey, I want to use Opus or I want to use 45 versus uh your team deciding what makes sense for that overall uh you know, infrastructure that you've built and then it's below the surface and I don't really care as a as a user."
3:15:10
>> Well, you're already using a whole synthesis of models. >> Okay.
3:15:12
Because Salesforce h makes we make a lot of our own models. Sure.
3:15:17
>> We use uh we use all the all the major vendors >> and we bring it all together to get what you need to be successful.
3:15:23
We don't want you to have to worry about that.
3:15:27
>> We want to just deliver a great I want you hit Slackbot and it just says boom here we go.
3:15:33
>> And I don't want you to have to think about those things.
3:15:35
I want to make it just great a great experience.
3:15:36
And I want to help you grow your business.
3:15:38
you know, I want to help you grow your customers.
3:15:42
I want to help you service them.
3:15:44
I want to help you make your employees more productive.
3:15:46
That that's what I'm excited about.
3:15:50
>> You guys have uh insane scale as you look across the the the Yeah.
3:15:54
To to put it to put it uh lightly. >> It is. It is crazy.
3:16:00
>> Uh but specifically, have you been surprised by any industries that are resistant to AI?
3:16:04
like just blanket saying like ah we're >> well there's so much dark things to AI that it freaks everybody out.
3:16:10
I mean I mean how to know how dark do you want to go?
3:16:15
Like we can go >> let's go dark.
3:16:16
I mean we were talking there was the journal had a statistic earlier.
3:16:19
They said only 10% of adults are excited about AI.
3:16:22
>> I don't think that's as dark as I would go.
3:16:24
I would say the rate of suicide that I saw with kids this year because of AI that was the one of the worst things I've seen in my life.
3:16:32
It was very reminiscent of kind of what we saw with social media, kind of this unregulated technology dramatically impacting families in the most horrible way possible.
3:16:45
I watched an episode on 60 Minutes a few weeks ago on character AI and I could not believe what I was watching.
3:16:53
>> And I think that that dark part of AI, the unregulated AI, because we know AI is kind of, you know, it's inaccurate.
3:17:01
It's, you know, it's very kind of unwieldy.
3:17:03
We don't know how these models work.
3:17:06
>> And to see how it was working with these children and then the kids ended up taking their lives.
3:17:11
That's the worst thing I've ever seen in my life.
3:17:15
>> So that's the darkest part of AI.
3:17:15
And I think we have to be careful.
3:17:20
You know, tech companies hate regulation. They hate it.
3:17:25
You hear that all the time except for one regulation they love, section 230. Yeah.
3:17:29
>> Which means that those companies are not held accountable for those suicides.
3:17:35
>> So those social media companies or in this case now the AI companies that that's not they basically say, "Oh, we're protected by section 230.
3:17:42
We're a platform company."
3:17:44
They they will quickly run to that regulation.
3:17:47
But the reality is is highly unregulated in every other area.
3:17:52
So, this is kind of a moment.
3:17:54
I Sorry, am I going too dark? No, >> I'm sorry. You said go back.
3:17:57
We We have these kind of conversations.
3:17:59
We've talked about all this stuff and uh in general, >> I I wrote I wrote about this in our newsletter last week, which is that why would the why would the average America the the the all the interviews that all the lab CEOs have done have just resurfaced over the last couple years?
3:18:19
Maybe they did the interview five six years ago talking about how uh the classic line from Sam is uh you know AI will lead to the end of the world but there's going to be a lot of great companies created in the meantime and so when people I saw that exact video
3:18:34
yesterday had 100,000 likes on Instagram right so like that is everyday people just seeing this and being like >> okay I like they maybe like Chad GBT but they're like I I like my job more or I like you know living in this world and being a human. So, I think we have a re
3:18:50
So, I think we have a re there's a real like narrative problem with the industry uh right now and it's going to be >> and if we're not about protecting our ch children, what are we about?
3:19:03
>> So, let's just start there.
3:19:03
And because we now have evidence of what happens when it's fully unregulated and because we have the evidence of this huge horrible situation, >> we have to take action.
3:19:17
And I think some countries, you know, have taken a lot of action, especially when it comes to things like social media.
3:19:22
You know, if you're in Singapore, you can't use social media if you're under 16 years old.
3:19:28
So it's like it it it will eventually get taken care of.
3:19:32
But we live in, you know, in our world here in the United States, we're we're very much like, oh, don't regulate technology because we got to keep the innovation going at all costs.
3:19:42
We got to keep the growth happening at all costs. And I'm >> Yeah.
3:19:46
So what's the real solution? So I get it. >> Yeah. Yeah.
3:19:49
What what like what what's a pragmatic approach here?
3:19:51
Because when it at the same time LLMs can have some negative externalities.
3:19:56
We've talked about the example of like, you know, if if grocery stores were invented last year, all the headlines would be like this guy just went insane in a grocery store and that would be a huge story, right?
3:20:08
Or like this person was murdered in a grocery store.
3:20:09
That stuff happens, but like we don't it doesn't get written about every day.
3:20:14
It's not because of the grocery stores.
3:20:17
>> It's just because >> and at the same time AI from an education standpoint, all the focus is on people like not writing essays anymore, but there and there's very little writing on like, hey, this, you know, uh, you know, a 15-year-old might like teach themselves like physics through using an LLM.
3:20:35
And maybe that's amazing, right?
3:20:37
So, it's like uh cuts both ways.
3:20:41
>> Well, I own a media company, too.
3:20:41
Not as exciting as yours. It's called time.
3:20:45
>> And in my little media company, we're held responsible for the content that we write and what we say.
3:20:50
Oh, by the way, you are too.
3:20:54
>> But in the case of this technology providers, they are not.
3:20:57
>> So, I think step one is let's just hold people accountable.
3:21:00
Let's reshape, >> reform, revise section 230 and let's make let's make it let's try to save as many lives as we can by doing that. >> Yeah.
3:21:09
Who uh who are you looking to uh in terms of leading the messaging around uh around AI safety? Do you like Daario?
3:21:18
>> Oh, I'm turning it over to you right now.
3:21:20
Uh >> I'm passing this over to you guys. >> Okay. Okay. Yeah.
3:21:26
>> You guys can make this part of your narrative and take it forward. >> Yeah. Yeah, it makes sense.
3:21:28
Uh what about in in the workplace?
3:21:30
Have you had to uh contend internally with the idea of someone uh confiding in, as silly as it sounds, confiding in Slackbot about a problem that they're having with in an HR context and how that might be a new territory, a new surface area for you to deal with?
3:21:48
>> Yeah, we need to talk about Slackbot safety.
3:21:50
>> I mean, it's it sounds silly, but really, if somebody goes and and they're like, you know, my my boss said he's going to fire me next week. I'm overstressed.
3:21:57
I'm thinking of doing something crazy.
3:21:58
You're in this but bizarre scenario for the first time in perhaps your entire career.
3:22:05
>> We are and I think in two areas.
3:22:05
First of all, as I mentioned, every company's going to have a customer agent and you've seen like there's 10 since we've spoken like 10 20 30,000 companies.
3:22:12
spoken like 10 20 30,000 companies. I don't even know what the exact number is today of companies deploying agent force for their customers and we've seen these amazing agents emerge like olive you know William Sonoma site or we're going
3:22:26
to see one emerge next week at the world economic forum in Davos called EVA and every c company has an agent to work with their customers to make them more successful and when we deploy those agents we have a tremendous uh architecture to create the guard rails to help prevent crazy things happening. You know, we don't want, you know, we've
3:22:47
You know, we don't want, you know, we've seen this where customers try to come along and have kind of cyber sex experience, you know, with these agents on these websites like, "No, no, that's not going to happen, you know, on the William Sonoma site.
3:22:59
[laughter] >> You're that's not what we're going to use the turkey baster here for." Okay.
3:23:04
>> So, we we have a whole different approach.
3:23:08
That's >> And so that level of guard rails is super critical.
3:23:12
And on the employee side, we h we're doing exactly the same thing.
3:23:16
We have to kind of, >> you know, put those tools together and work with our partners, but also do a lot of deep engineering work to make it as as great as we can.
3:23:23
And that core platform, Agent Force has all of those capabilities built in. >> Okay.
3:23:29
On the on the employment side, has AI rethought your thinking about employment planning, how many people you need to hire, the scope of the organization?
3:23:39
Has it been a roller coaster or do you feel like you've been on one trajectory or the trajectory has changed?
3:23:44
Have you been processing just AI making uh your employees more effective potentially?
3:23:50
>> Yeah, what a great question.
3:23:50
I would say that, you know, we have about 80,000 employees now and we'll do a little over 41 billion this year in revenue.
3:23:55
We're now the number one enterprise software right we're now the number one >> enterprise software company in AI we just passed 11.
3:24:08
1 trillion tokens >> like crazy >> so are you are you surprised are you surprised that companies are not getting valued on token generation yet they're such big numbers you know we we >> I am I think I mean We're probably number one or number two on the token side.
3:24:29
Um, that's probably has to do with our relationship with Billbo Baggins, but otherwise we've got this figured out. Okay.
3:24:36
I would say what we have to do when we think about employment.
3:24:40
To get back to your core question, >> um, I've changed the employee mix.
3:24:46
>> I, uh, this year we hired more than 20% more account executives.
3:24:50
There still needs to be people like me and you who go meet with our customers to really explain all of the intricacies and nuances of the technology.
3:25:00
There's a lot of false narratives and people playing the market and saying things about AI that are not true, especially in regards to the enterprise.
3:25:09
And we have to go explain it and talk to it and build the relationship and show them and prototype and deploy.
3:25:16
And so those people are more valuable than ever and more important than ever to us.
3:25:22
On the engineering side, I've held my engineering headcount mostly flat this year >> because I've gotten so much productivity increase.
3:25:30
I probably have about 15,000 engineers and >> they're more productive than ever. I'm so proud of them.
3:25:36
Look at what we just delivered for you guys.
3:25:37
You know, they're like doing great.
3:25:39
And um we need to go go even farther. >> Yeah.
3:25:43
>> But you mentioned Enthropic.
3:25:43
You know, we own about 1% of Enthropic.
3:25:44
we own about 1% of Enthropic. I would say that you know those coding tools uh you mentioned cloud code other things cursor we use that inside we do things to have a more efficient more productive engineering organization and we it turns
3:26:00
out we've reduced the number of cos to one because of [laughter] slackbot we can do more because uh we can deploy that AI technology the cos did uh I mean you've spent your entire career in technology did this did the chatbt moment did the AI I boom. Uh, were you
3:26:15
Uh, were you expecting it or did it hit you like a flashbang?
3:26:20
Was it just was it just a just a massive flashbang that just hit you like a ton of bricks?
3:26:27
[laughter] >> Hit me like a ton of bricks.
3:26:29
Um, I would say >> we have a flash.
3:26:34
In fact, I had to use it.
3:26:38
>> 10 years ago, I had the nastiest dream about AI and so I started a whole AI initiative at Salesforce called Einstein. >> Okay.
3:26:44
and we became the number one enterprise AI.
3:26:48
>> And so we were building models, doing these things, making all it happen.
3:26:50
I always believed that this time would happen, but it was more about predictive AI and machine learning and machine intelligence and these kinds of things.
3:26:59
And it was it, you know, we still use all that, by the way, to make this work.
3:27:03
>> And then when the large language model emerged and prompt engineering emerged and by the way, you may or may not know, but I'll give a little credit to my engineering team because they deserve it.
3:27:12
But prompt engineering actually emerged out of Salesforce research >> and then fantastic >> all of these companies you know have new companies came along to say we're just going to focus on the large language model and it's been a huge incredible success story.
3:27:27
>> So um I am just so impressed with what's happened in the last three years but it's just another core part of our infrastructure now and I think you see that in Slackbot.
3:27:38
So yeah, >> getting back to Slackbot, it was just a seamless upgrade for you today.
3:27:43
>> Sure, >> you have Slack. We added Slackbot.
3:27:44
When we added Slackbot, we added >> all the AI and all the data capability.
3:27:51
And now actually in the new version of Slack, you're going to see a lot of new CRM capabilities as well.
3:27:55
You'll be able to manage your customers information without even having to go to Salesforce.
3:28:01
>> You will be able to manage your service organization. But here's the secret.
3:28:05
Salesforce is behind the scene in doing all of it. Let's go.
3:28:07
>> And at some point, if you want to upgrade to the bigger, more advanced adult versions of all those things, you'll be able to do that, too. >> Okay.
3:28:13
I I I want to talk about that because uh we've we've talked to a lot of companies where they they have a single product there, a point solution, but because of AI, they're able to add on other surface area.
3:28:22
Everyone's bleeding into everyone else's territory.
3:28:27
Everyone's expanding right now.
3:28:27
What is it like running an organization where you might have two products that are now bleeding into each other?
3:28:33
And like how do you have to go and play tiebreaker a lot?
3:28:38
Do you have a pattern for this?
3:28:40
Like how do you how do you work through all that? >> I love it.
3:28:42
I I think everyone should, you know, innovate and create and compete with each other, especially inside the company. Yeah.
3:28:50
>> Some people stay in their lane, some people don't.
3:28:52
I'm not going to interfere with that.
3:28:53
You know, we have these tremendous leaders like running Slack or >> our sales product.
3:28:58
Our sales and service product are 10 billion dollar products each.
3:29:02
each. They are the some of the largest products in the software industry and the new versions are incredible, but the new versions are all Slackbot first and you haven't seen them yet, but if you want to get a demo later after the show,
3:29:14
>> you'll see Slackbot and Slack sitting on top of Salesforce and that boom, you can have all this incredible productivity, but it's the lineage of Salesforce coming forward into the present moment reality of these unbelievable new advancements in AI. Yeah. Yeah.
3:29:29
>> And that is what I've been working on.
3:29:31
So, a Slackbot first world, the ability for every company to have a customer agent, an employee agent, uh the agent force layer, the all these incredible family of applications we have.
3:29:41
We just bought a company called Informatica, by the way, for like $9 billion.
3:29:48
>> And it was >> kind of an incredible acquisition. All right. Well, there we go.
3:29:52
But I love I always love the company. Yeah.
3:29:57
>> But you know they've done things in their new technology that for AI if you don't have your data right you don't have your AI right.
3:30:04
Remember the reason why Slackbot is working is we have all your data in there normalized.
3:30:08
And so it's able to take all your data and give you really cool answers.
3:30:13
Well every company needs to normalize their data.
3:30:17
So that's why we bought Informatica.
3:30:19
Everybody needs to integrate it together.
3:30:21
And then you have to go and connect to all the other data sources in the enterprise like snowflake or datab bricks or big query or red shift or even IBM mainframes. We call that zero copy.
3:30:33
So our system goes out grabs all that data in all these other places brings it together like it is for you already in Slack >> and then everything sits on top of it and you get this really powerful AI experience.
3:30:44
So that's what's going on.
3:30:46
That's what's exciting for me every single day. >> Let's talk about M&A.
3:30:49
Uh you talked about Informatica.
3:30:51
There's uh you know the SAS apocalypse has been widely reported.
3:30:56
I'm sure you look at some charts and get a little get a little >> I'd rather not look at the charts. I can't figure them out.
3:31:02
I mean our revenue and our profitability and cash flow go up and then the the stock is all over the place because people think >> there's some weird end of SAS.
3:31:09
But I would just ask you guys did did did Slack become a lot more valuable for you today or less? >> Way more.
3:31:18
way more way and I'm not talking about that.
3:31:20
I'm talking about you looking for value.
3:31:21
You've done so a ton of M&A like you must look around at at companies that you feel like are oversold.
3:31:30
>> I think there's a lot of incredible opportunities right now in the market >> and um you you if you were not looking at look we do about 15 or 16 billion in positive cash flow a year. We're going to use that.
3:31:43
We're going to buy back some We're going to buy back some stock.
3:31:48
We're going to do some dividend action, too. >> Fantastic.
3:31:51
>> You know, but what else are we going to do with our cash?
3:31:53
I think we should buy some companies also, you know, because I love organic innovation, but I love inorganic innovation, too.
3:31:59
I bought about 100 companies.
3:32:02
>> Give us a give us a give us a a threeinut M&A master class.
3:32:04
There's a lot of companies whose market caps have inflated.
3:32:08
They've got a bunch of cash on their balance sheet.
3:32:10
They're, you know, 1% of the size of Salesforce, but maybe they're starting to think about M&A.
3:32:17
What have you learned about how to do it well in a few minutes?
3:32:20
>> And this is the last question.
3:32:21
>> You got to, you have to innovate.
3:32:23
Innovation is our core, one of our core values.
3:32:24
What are our core values?
3:32:24
Trust, customer success, innovation, and quality, sustainability.
3:32:28
Those are our five core values.
3:32:30
We can talk about any of those, but when we talk about innovation, we talk about organic and inorganic innovation, right?
3:32:36
Organic is those 15,000 engineers making Slackbot. It's 100% organic.
3:32:43
>> But then, well, actually, but it's not because we bought Slack.
3:32:46
Remember five years ago when I bought Slack? Because I love Slack.
3:32:50
I thought they did such a great job.
3:32:52
I thought it was a one-time trade.
3:32:54
I don't think anything was going to replace it and I thought I could make it a lot better.
3:32:59
>> I thought I could put it on top of all of our products.
3:33:01
I thought it could be a user interface for the future.
3:33:03
I thought AI would be incredibly benefited by the data inside Slack.
3:33:09
We just proved that to you with Slackbot. >> So, we bought Slack.
3:33:13
Well, it was a huge purchase at the time.
3:33:16
One of the biggest ever in the software industry.
3:33:18
I think it was like $25 billion. >> Our biggest. >> But guess what?
3:33:23
The value that it's provided now it's, you know, it's not a subbillion dollar company like when we bought it.
3:33:30
It's a multi-billion dollar company.
3:33:32
I think it's like almost $3 billion or more.
3:33:33
or I don't have the exact number in front of me, but you can just go, "Wow, this is like incredible the value that Salesforce and Slack together provide."
3:33:44
>> And that's what I'm looking for.
3:33:44
Or Informatica plus Salesforce together or Mulesoft.
3:33:48
I mentioned we bought it when it was a $300 million, >> you know, revenue company and, you know, now it's a huge multi-billion dollar software engine as well.
3:33:58
So we have so many of those and our job is to buy them and make them work.
3:34:04
Not all of them are going to work.
3:34:06
Acquisitions are very risky.
3:34:08
You got to be really careful, you know, and then you can have it all worked out and it still doesn't work out.
3:34:13
But it's worth it to take the risk because innovation is risky and organic and inorganic innovation you have to do both.
3:34:21
And >> what is a good what is a good one hit rate?
3:34:25
What is a good hit rate at at scale?
3:34:27
you said you bought something around a hundred companies.
3:34:28
Uh but for uh when you're talking like with your M&A team like how often are you okay with them just you know and the company just swinging and missing?
3:34:41
>> I have such a cool team there because not only do they that do that they also run a $5 billion investment fund.
3:34:44
You know we have invested in so many amazing companies and taken so many amazing companies public.
3:34:53
We just sold Whiz that we helped start to Google.
3:34:58
>> We took we helped grow Snowflake and took it public and made one I think we made a billion and a half dollars on that.
3:35:03
I think we made a billion half dollars on whiz.
3:35:07
>> I think we have now about >> you know a point of anthropic which is a few billion dollars or so. >> Fantastic.
3:35:15
>> I you know and it was started you know when it was a tiny company.
3:35:17
So we love investing number one.
3:35:20
We love buying things and we think all of that is innovation. >> I love it.
3:35:27
>> And it's all in one big innovation bucket.
3:35:29
And I'm, you know, but we're trying to do something that others have not done is we're trying to innovate in the enterprise at scale. >> Yeah.
3:35:37
>> And that is the hard thing because look, as I said, we have 80,000 people and more than 41 billion and we're starting going to start our next fiscal year out on February 1 and it's going to be a it's going to be a massive year bigger than that.
3:35:50
So >> I'm like going, "Whoa, these numbers are huge."
3:35:54
But I've got a huge dream.
3:35:54
I'm trying to go as fast as possible, you know, to 100 billion in revenue, but while maintaining this incredible profit.
3:36:02
Oh, we're one of the most profitable enterprise software companies, too.
3:36:04
We're delivering more than 34% margin this year.
3:36:08
>> I have I have one last question coming last question.
3:36:11
Are dreams an underrated Ares underrated source of uh business alpha?
3:36:17
You said you said you had a had a had almost a nightmare about AI and that started Einstein.
3:36:21
Do you look for signal in your dreams?
3:36:25
>> I I pay attention to my dreams.
3:36:25
I pay attention to my my visions, my insights.
3:36:33
And you know, Salesforce started because I was swimming with a pod of dolphins outside the the coast of Hawaii where I live.
3:36:40
>> And I was in about a hundred dolphins and I was one with the pod.
3:36:42
And when I was one with the pod, all of a sudden in my mind, I saw this vision of what Salesforce could look like.
3:36:48
And I came into Larry Ellison and I said, "Hey, I think I'm going to quit my job."
3:36:52
And he gave me $2 million and we started Salesforce. And that was that. That was 26 years ago. >> It's amazing.
3:36:59
Well, thank you so much for sharing the story with us. >> Thank you, Dolphins. >> Thank you, Dolphins.
3:37:03
Thank you [laughter] to the sound. The sound is amazing. Look at that. >> Thank you, Dolphins.
3:37:11
>> Thank you for coming on the show.
3:37:11
Take care of the dolphins.
3:37:15
>> We will talk to you soon.
3:37:15
Have a great uh super fun.
3:37:19
The chat's calling him the Steve Jobs of AIDNED.
3:37:22
I think he's a strong candidate. >> Strong candidate.
3:37:27
>> Always great to chat with Mark hanging out with Mark. >> Um what else we got?
3:37:32
>> Uh there's there's a few posts.
3:37:32
There's some uh breaking news.
3:37:34
Andre Carpathy has been on a following spree on X.
3:37:37
This is why you come to this show.
3:37:40
He followed Jacob Rinttoaki, friend of the show.
3:37:44
He followed Eric Glimman, the CEO of RAMP.
3:37:46
Andre Karpathy is uh making the rounds.
3:37:50
Uh and Jacob Rintamaki says, "You know, I still think it's funny that the guy who ran Tesla's full self full self-driving program. His name is Car Path E.
3:38:00
It's a good It's a good nominative determinism for path. >> It's always there.
3:38:05
>> Although he's working on education now, so we're going to have to rework the the nominative determinism to figure out how that works.
3:38:10
Uh, in other FSD news, uh, Tesla says, uh, Elon says Tesla will stop selling FSD after February 14th.
3:38:16
It will only be available as a monthly subscription thereafter.
3:38:20
So, February 13th, you go in, you buy the full self-driving. It's a onetime purchase.
3:38:27
Then he's going he's going uh subscriber mode.
3:38:29
Probably good for the >> uh somebody here is uh in Google just searching, I'm a kitty cat. Where is my owner?
3:38:39
My bowl is empty [laughter] and the AI overview pops up.
3:38:42
It sounds like you are very hungry and miss your owner.
3:38:46
Since you can't find your owner right now, you might want to meow loudly near their usual spots to get their attention.
3:38:53
Check the common areas of your home like the living room or their bedroom in case they are sleeping or relaxing elsewhere.
3:38:59
I'm really glad that the AI overview and Gemini powering it are are uh open all species.
3:39:03
It's not it's not humanist.
3:39:07
It's not focused on humans exclusively.
3:39:10
It's uh >> it embraces the the kitty cat inside of all of us.
3:39:16
I suppose I started saying yes to all the apps that can track me prompts.
3:39:20
The internet is now noticeably better with more relevant and less spammy ads.
3:39:24
Apple did us all a disservice and and misplaced emphasis on privacy.
3:39:29
He says, "Get into the targeted advertising flow.
3:39:31
You want to see good stuff?
3:39:34
Hit yes on this app can track me.
3:39:37
Let them target you with the best possible ads.
3:39:40
>> Well, speaking of targeting, Hermes is allegedly stalking their clients.
3:39:42
A Glitz investigation has revealed that Hermes employees are googling clients home addresses to determine whether they have a prestigious enough address to be deemed worthy of a Birkin or a Kelly.
3:39:56
Mez is also allegedly scrutinizing clients social media accounts and the content they post.
3:39:59
After a quota bag is purchased, they continue to monitor for resale activity, which if detected, >> results in an immediate blacklist for the client. >> No surprises there.
3:40:10
>> I think OpenAI should do this with their device and they sell those.
3:40:12
They should they should say, "Oh, you know, you know, there's a quota, there's an allocation, we'll try and get you in, but uh no problem.
3:40:21
>> We're really not using chat GPT all that much, and the questions you ask aren't that interesting."
3:40:25
So, you know, I don't think we're going to be able to get one for you.
3:40:28
And oh, by the way, you know, AirPods, we were debating, is the Open AI device going to cost a h 100red bucks, 300 bucks.
3:40:34
I think they got to do like 30K.
3:40:36
I think it's got to be like 30 G's.
3:40:39
>> Yeah, >> it's got to be >> add a zero.
3:40:40
Why not >> add a couple zeros?
3:40:42
>> Yeah, >> add a couple zeros.
3:40:42
And then make it a huge hassle. Make it Oh. Oh.
3:40:45
Well, how many Chat GPT Pro subscriptions have you bought for your friends and family?
3:40:50
How much money have you spent with us?
3:40:52
What's what's your purchase history with us before we get you one of these devices?
3:40:56
You need to make it elite. This is the key.
3:40:59
>> Have you ever consumer electronics?
3:41:02
>> Have you ever churned from Chat GBT? Yeah.
3:41:03
Well, you're going to the back of the list. [laughter] >> Yeah. Yeah.
3:41:05
What was going on in in November?
3:41:07
We see that you you you tested Claude. Uh yeah. Yeah.
3:41:10
You're not getting the device.
3:41:12
You're not getting the what's it called? Sweet Pee. Sweet.
3:41:17
>> Ben Mullen at the New York Times >> says, "What AI generated PR pitches are doing to reporter inboxes everywhere is a catastrophe. Brutal."
3:41:26
>> Uh you're absolutely right.
3:41:28
Uh yeah, this is crazy because the the challenge is >> uh they can like it used to be, >> you know, from our side >> even even maybe a year ago like if someone was like really enjoyed this segment where you were talking about this this that like actually seemed like they watched it and now you can just >> easily get that from Gemini or wherever.
3:41:52
So, it's a disaster, but fortunately, Nick is there just chopping emails down, dodging >> uh PR lasers.
3:42:01
>> Maybe the last piece of news, uh Mike Kger, the co-founder of Instagram, who joined Anthropic two years ago as chief product officer.
3:42:09
He's changing roles to co-lead an internal incubator dubbed the labs team.
3:42:14
I could see him cooking up some really cool stuff.
3:42:16
He of course in between Instagram and Anthropic worked on a news application called Artifact that was sort of a precursor to Pulse.
3:42:26
It was it was at it was like almost at the perfect time but AI wasn't quite there and I could see him doing something really interesting.
3:42:33
Obviously he's good at going to from zero to one in a consumer application.
3:42:37
If there's some new surface area for uh you know a an an AI tool and app I wouldn't bet against him.
3:42:46
So, congrats to him on the new role. >> One final post.
3:42:49
Freya >> says, "So fascinated by this product."
3:42:54
And it is uh in some type of booking.
3:42:57
Looks like it's in the Booking. com world.
3:42:58
And it's a get $500 if it rains on three days of your 9-day trip. Only $26.
3:43:06
So, >> we're bringing gambling.
3:43:09
>> Now, this feels like a prettyable >> straightforward uh >> This is just Freedom's first company, right?
3:43:15
>> Climate [laughter] insurance. Not really.
3:43:16
I mean, he was selling to farmers, but yeah, it is sort of weather and whether futures and insurance crop insurance has existed for a long time.
3:43:24
Uh, and yeah, this makes sense.
3:43:24
But are we getting out of here?
3:43:29
>> The bomb has been planted.
3:43:29
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3:43:31
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3:43:53
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3:43:56
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