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Good to see you, Gold Rock. >> You're watching TBPN.
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Wednesday, August 13th, 2025.
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5:22
>> Timelines in turmoil again, except this time it's not the Substack.
5:24
It's technically called Passport.
5:26
It's Ben Thompson's version of Substack.
5:28
Um, >> because semi analysis and stratey are both, I think, on the same technology platform, the same blogging platform.
5:37
Um, but uh they have slightly different takes.
5:40
Obviously, they agree on a lot, but we are going to play the bull and the bear today.
5:45
Uh we have we have some we have some >> Whoa.
5:50
>> some new hats in the studio.
5:50
Wait, uh did you was I going to play the bear?
5:55
So, we're talking about Google because recently Ben Thompson came out with a post uh talking about how he has he's he's reviewed Google's technology strategy, their AI placement, and maybe uh things are good and maybe things are are going to are going to go well for the company.
6:12
Um Buco Capital bloke says Ben Thompson's Google bull posting is accelerating.
6:19
Uh he says a quote from their uh from Ben Thompson's Sharp Tech with Andrew Sharp says, "I am becoming a Google fanboy.
6:27
Let Google abuse their search monopoly as much as they want to. Humanity is benefiting. Leave Google alone."
6:34
>> I will say it is hard to participate in this.
6:38
>> Yeah, I don't think this is going to work at all.
6:40
I really I can't see anything.
6:42
This doesn't work at all.
6:42
This is >> Yeah, I don't think Dylan I don't think Dylan tested these out.
6:47
I don't think he tested these out.
6:49
I can see through those holes and that's it.
6:51
I can only I can see like one one pixel >> here.
6:56
Let me let me see if I can hit the gong. >> Can you hit the gong?
7:01
>> Well, we had our fun with that. Oh, did you just miss? >> No, I'm kidding. >> Okay. Okay.
7:07
Well, so >> so >> thank you to Reream one live stream 30 destinations.
7:12
Multiream and reach your audience wherever they are.
7:14
This this stream is made possible by Reream.
7:16
So, uh, basically, let me set the stage and then we'll debate it a whole bunch.
7:21
So, um, last week Ben Thompson wrote a strateer article titled Paradigm Shifts and the Winners's Curse.
7:28
And he weaved through some of the opportunities in front of Google.
7:32
And if you were to play the the Google bull, it looks something like this.
7:38
They have a fantastic AI chip with the TPU.
7:40
This allows them to serve frontier models at low the lowest possible cost.
7:46
They're they're they're pretty dominant on the paro frontier as we've seen.
7:50
>> Uh they have incredible cloud scale with GCP, Google Cloud Platform, and that's accelerating.
7:54
We saw in the recent run of earnings, Azure did quite well, GCP did quite well.
7:59
Uh AWS was kind of lagging there.
8:01
So, they're positioned well in terms of like building big data centers, big capex, big big AI token factories. Yes.
8:09
>> Uh they have an amazing lab, DeepMind, >> which we will get into some of the DeepMind folks who made the updated version of the Metas list.
8:14
Um they are producing top tier models.
8:17
Gemini obviously very impressive but also VO3 completely state-of-the-art and Genie3 now definitely state-of-the-art.
8:23
Uh and Ben highlights that Google is hard to analyze because Larry Page and Sergey Brin famously weren't particularly interested in business or in running a company.
8:34
They just wanted to do cool things with computers in a college-like environment like they had at Stanford.
8:40
that the company nearly 30 years later is still doing cool things with computers in a college-like environment may be maddening to analysts like Ben who want clarity and efficiency.
8:49
It also may be the key to not just surviving but winning across multiple paradigms.
8:54
So Ben has become a Google fanboy by his own account.
9:00
But on the other side of the argument is Dylan Patel and the crew over at semi analysis.
9:04
In this new post on semi analysis, GPT5 set the stage for ad monetization in the super app, they lay out a path to a complete to complete chat GPT dominance in the advertising space.
9:18
And they give it's a great read.
9:20
We'll go through some of it, but um you should go subscribe to both uh Ben Thompson's strategy and Dylan Patel's study analysis uh because they are truly fantastic.
9:29
So basically when you go to chat with a highly monetizable query and they pick the funniest possible example which is DUI lawyer near me. I love these guys.
9:41
But apparently that is extremely monetizable because if you you need a lawyer if you get a DUI and you're going to pay that lawyer a lot of money and so it's not unheard of.
9:50
>> Somebody's on the side of the road frantically in chat GPT.
9:53
>> It's y DUI lawyer near me.
9:53
And if you're if you're a lawyer that represents clients in DUI cases, they're going to pay you maybe $100,000.
9:59
You're happy to pay $1,000 for a referral fee to Google or to ChatP in the future.
10:04
And so basically, when you go to ChachiPT with a highly monetizable query like that, like if you ask, you know, what's the what's the capital of Wisconsin?
10:14
Like it knows that we can't really make money off of that.
10:17
So let's not light the GPUs on fire.
10:20
>> This query is simply too good.
10:20
I got to find some way to make money off.
10:22
got to make money off of it if it's the DUI lawyer example.
10:26
Uh so the new model router in chat GPT and GPT5 will be able to understand that they could potentially earn hundreds or even thousands of dollars on in referral traffic if they help you find the best person for the job.
10:38
This means firing up the biggest model, the most expensive GPUs to make sure you get the best possible answer.
10:44
This applies to lots of other domains, too.
10:46
Companies are now building out uh clones.
10:48
They're called reinforcement learning environments with verifiable rewards.
10:52
Basically a clone of Door Dash, a clone of Amazon.
10:55
com, a clone of other UI experiences. >> Shopping experiences. Exactly.
11:00
Um, and then the and then the companies can go RL on top of those environments, those virtual environments.
11:09
>> Get good at buying stuff.
11:10
>> Learn how to use the real Door Dash.
11:11
learn how to use the real uh the real amazon.
11:14
com and and and >> learn how to check the box that says I'm not a robot and select the bic. >> Literally yes. Literally literally yes.
11:23
Uh I mean that was what uh that was what uh the semi- analysis crews take away from GPT5 was that it was not a bigger pre-training model. That was the Death Star.
11:33
The Death Star was the idea that GPT5 would be a bigger model or some sort of foundational change. No, they blew that up.
11:40
They blew up the idea that GPT5 would be a much bigger model and instead they focused on they rled the hell out of it according to the semi- analysis crew.
11:48
And so it's h highly good at very specific things.
11:50
It's the spikiest intelligence we've had.
11:52
So um basically they will RL on door- amazon.
11:59
com other websites so you can check out on your on so so that the agent can check out on your behalf.
12:03
Uh it might be expensive for an AI model to jump through all those hoops to actually order you a new pair of headphones, but it'll be worth it if there's a commission, affiliate commission on the end of the line.
12:14
Uh this obviously poses a major threat to Google search ad revenue.
12:18
>> Can you assume that the labs are also just training on the real applications and the real websites themselves?
12:25
>> No, because every time you check out on Amazon, you're spending like 50 bucks at least, right?
12:31
If you're if you're going through the flow and the flow for buying expensive to do the volume >> millions of times. Exactly.
12:36
So why not just simulate the whole thing? Yeah.
12:40
>> Uh I'm sure that they are they probably have >> they do test test runs. >> Of course. Of course. Little Yeah.
12:43
When when when Sam Alman needs to go through the the the Koig configurator, he's he's he's using that as training data.
12:50
I remember when when Sam when when they launched Deep Research, the example that Sam gave was he was trying to buy this obscure Acura in Japan, >> an NSX, >> an NSX.
13:03
>> Obscure to some people, not to me.
13:04
>> And he he was like, "Yeah, I just used Deep Research and I found it."
13:08
And people >> a lot of people didn't pick up on that a ton at the time, >> but that was a highly monetizable deep research report. >> For sure. For sure.
13:19
Um and so uh Ben Thompson and others have noted within weeks of Chach's initial launch that there was a threat to Google.
13:26
Uh the question is how fast this shift happens.
13:33
How much will Google adapt to the new paradigm and what the economics of the consumer tech industry look like in a world where we no longer operate on top of zero marginal costs.
13:40
the cost to serve the one more Google search was zero, but the cost to serve one more DUI lawyer lookup will be 50 bucks.
13:49
And so, uh, semi analysis has a bunch of good charts and graphs that we can kind of look through and then maybe we'll we'll go back to the bull case after, but let's look through the bare case.
13:59
So, uh, fabricated knowledge, Doug, who from semi analysis, who came on the show last week, fantastic hourlong interview.
14:07
Every time we grab one of these semi analysis guys, we're like, "Yeah, yeah, yeah.
14:10
The standard the standard interview is an hour. don't worry about it.
14:12
Like, just send them an hour and and they're like, "Wait, most of most of these TVP interviews are 10 minutes.
14:19
Like, why why do you need an hour of my time?
14:20
It's because you're gold. We love you."
14:22
Um, so fabricated knowledge says, "So, if you can't tell, I wrote the f out of this."
14:27
Also, I know we're getting a lot of push back, but the affiliate model feels inevitable. Timeline is this.
14:33
Instacart adopts a gentic purchase in January.
14:36
Instacart CEO leaves, that's Fijiimo, to OpenAI in May.
14:38
Sam tone shift uh router for for control of query.
14:44
So let's pull up the videos of Sam Alman on AI ads and I think it will crystallize a little bit of like what we mean when we mean like monet monetizing a free LLM, a free AI chat app.
14:56
It doesn't necessarily mean stuffing display ads in there.
15:02
Just like the answer to Facebook's monetization problem was not banner ads on the in the right bar.
15:10
It was in feed ads that look it if you're watching reels and you see a reals ad, it looks exactly like a real and in fact the best performing ads on Instagram reels feel just like userenerated content.
15:21
They don't look like Super Bowl ads.
15:22
They're Yeah, they're additive and people often enjoy them.
15:26
Um and so that will be at least this is the semi- analysis argument that I sort of agree with.
15:31
Um uh that will be the the the like what what we say about ads in AI.
15:37
It will be more like commissions for agentic checkout at least at least to start.
15:43
So let's pull up the first video.
15:47
>> Example right now there's a lot of people that have websites that monetize with referrals to Amazon.
15:51
Y >> and they're frustrated because a lot of the I mean traffic just like organic SEO is way down. >> Yep.
15:59
And the general read here is that OpenAI will ultimately start to earn that same type of revenue that the publishers historically did. >> Yep.
16:08
So, um, uh, uh, there was a fireside chat at Harvard Business School with Sam Alman.
16:15
>> Let's give it up for Harvard Business School.
16:16
>> Let's give it up for Harvard Business School.
16:17
>> It's the Harvard of Business School.
16:19
>> That's what they've been saying.
16:19
They've been saying um, so he he got a question from the audience about ad monetization.
16:25
We'll hear how Sam Alman responded to it.
16:27
Although fair, it could be a barrier for early stage entrepreneurs or startups or even small businesses.
16:32
Given this context, do you envision OpenAI exploring alternative monet monetization strategy that could include like free free API access perhaps supported by advertising or other uh methods to foster innovation in the future?
16:48
I >> I will disclose just as like a personal bias that I hate ads.
16:53
Um, I think >> I think ads were important.
16:59
>> We love ads >> to give the early internet a business model, >> but I think they they do sort of somewhat fundamentally misalign a user's incentives with the company providing the service.
17:11
>> I'm not totally against them.
17:11
I'm not saying I would never consider ads, >> but I don't like them in general.
17:15
And I think that uh ads plus AI is sort of uniquely unsettling to me.
17:21
You know, when I when I think of like GPT writing me a response, if I had to go figure out, you know, exactly how much was who paying here to influence what I'm being shown, >> I don't think I would like that things go on.
17:37
>> I think I would like that even less.
17:40
>> So, there's something I really like about the simplicity of our model, which is we make great AI and you pay us for it, and it's like we're just trying to do the best we can for you.
17:49
And then >> Senator, we write that that has some inherent lack of access and inequality.
17:57
We commit as a company to use a lot of what basically the rich people pay to give free access to the poor people or the poorer people.
18:06
You see us do that today with the chat GBT free tier.
18:08
Um you'll see us do a lot more to make the free tier much better over time.
18:13
And I'm interested in figuring out how we bring the equivalent concept to the API.
18:17
Um, but I I kind of think of ads as like a last resort for us for a business model.
18:27
>> Um, I would do it if it meant that was the >> That's where he says he says I kind of think of ads as a last resort of a as a business model, but recently he dropped a new podcast.
18:36
This was from I think a month ago.
18:38
Uh, and it's from the OpenAI podcast.
18:41
So you have to imagine that they that the that the the run of show and the talking points in here are very carefully selected to you know move the narrative forward and kind of educate the community on where the company is going.
18:56
So and so we'll pull up Sam Alman's interview on AGI GPT5 and what's next from the OpenAI podcast.
19:02
next from the OpenAI podcast. So that brings up the other question from people who are using this or skeptical is that openi now has access to this data and there's the concern one was about training which open I has been very clear about when or when not it's
19:17
training you have the options to turn that off the other thing is like uh advertising things like that what's open's approach towards that how are you going to handle that responsibility >> we haven't done any advertising product yet um I kind of >> I mean I'm not totally against it >> he's not totally against Yay. >> Areas where
19:35
>> Areas where >> I like ads.
19:36
I think ads on Instagram kind of cool.
19:39
A lot of >> Yes, ads on Instagram. Very cool. Let's go.
19:43
>> I am like I think it'd be very hard to It would take a lot of care to get right. >> I I have faith. I think you can do it.
19:50
>> People have a very high degree of trust in chatbt which is interesting because like AI who's mates it should be the tech that you don't trust.
19:57
>> My friends too, so I trust them too. >> People really do.
19:59
Um, but I think part of that is if you compare us to social media or you know, web search or something where you can kind of tell that you are being monetized and the company is trying to like >> Yeah, you can see good policies, no doubt, but also >> kind this is the monetized block, >> whatever.
20:25
you know, how much how much do you believe that like you're getting the thing that that company actually thinks is the best content for you versus something that's also trying to like interact with the ads?
20:36
I I think there's like there's a psychological thing there.
20:41
For example, I think if we started modifying the output like the stream that comes back from the LLM >> in exchange for who is paying us more, >> that would feel really bad.
20:53
And >> this is a great solution.
20:54
Give you the actual answer you want, but >> hey, these are the best headphones for you, but if you want me to buy them, I'm gonna have to go cook as an agent.
21:02
I'm doing the work and I'm gonna take a cut of that.
21:06
>> That's that's amazing. I'm so down for that.
21:08
Like it the agent's like, "I'm getting paid either way." >> Yeah. Exactly.
21:12
And I could say I say, "Okay, which headphones do I want?
21:15
Do I want the Sony's or do I want the uh or or or do I want the the Apple AirPod Max's?"
21:21
And if I decide the Apple ones, it goes checks out.
21:24
It uses some coupon code.
21:25
It gets some >> comparing comparing this to the other ways that people discover products and services. >> Yeah.
21:31
If somebody searches best luxury hotel in Hawaii, >> they're going to get ads against that and then they're going to get organic rankings that aren't necessarily the truth, right?
21:44
Because the truth is >> for something like best luxury hotel in Hawaii is very subjective. >> Yeah.
21:50
>> Then they might go and try to get recommendations from an influencer. >> Yep.
21:55
>> In hopefully the influencer is disclosed. >> Yes.
21:58
>> Whether or not they're being compensated by the advertiser. Yeah.
22:02
>> And >> so if I were to ask you as an influencer, like what design software would you recommend? Like what would you say? Just honestly, >> figma.
22:10
com, >> think bigger, build faster.
22:12
Figma helps design and development teams build great products together.
22:15
Uh this is a paid >> disclosure.
22:17
But yeah, the disclosure is super important.
22:19
And if and if the influencer is saying like, "Oh yeah, I love this hotel, but that hotel is giving them like, you know, two weeks free a year," then like that's not That's not a a super ethical.
22:30
Yeah, it needs to be disclosed.
22:34
And then also also the the beauty of the LLM is that is that like the like the the recommendations are going to be able to be tailored. So, best luxury hotel.
22:45
Well, if you're if you really want a certain type of pillow or you really want, you know, a a pool in your unit or you want it to be wheelchair accessible or you want, you know, high ceilings or you want, you know, beachfront access, like there's a million different parameters that could go into that >> and the thing and then it could just and then it just saves you the time at the very last step.
23:06
>> Well, the thing that Chad GBT needs to navigate is maintaining that trust. Yep. Right.
23:10
I trust that Instagram is going to serve me ads y that >> that >> I I trust that they're going to try to serve me ads for things that I will want to buy. Right?
23:19
Sometimes they serve me an ad, I'm like, "This is this looks garbage.
23:23
I'm not going to buy it."
23:23
Other times they serve me an ad, I'm like, "This looks great. You're actually good. Good call.
23:27
I I I am interested in this product."
23:30
>> And the thing is is like if Chad Chad GPT has to maintain that trust because if they recommend you a hotel and they're like, "You're going to love this.
23:36
I know I know what you like.
23:38
You're going to love this hotel."
23:38
and you go there and you spend all this money and you stay there and it's and it's terrible.
23:41
It's the same thing of if you go to a friend for a recommendation for a hotel, they recommend you a hotel, you show up there and it's like, "This is terrible.
23:48
Like, why did you recommend this?"
23:50
And if they go, "Oh, yeah, I recommended it because I was getting like 7% referral fee."
23:53
You're going to be like, >> "What are you doing?
23:57
Why are you monetizing me?" Right?
23:58
So I think like it's a very um uh it's an interesting challenge that they have where they're going to be directing already directing so much economic activity and how do you monetize that in a sustainable ethical way. >> Yeah.
24:14
I I mean I think the router is the answer.
24:17
Um uh OpenAI or or semi- analysis called like this release like the router is the release like GPT5 is the router. It's not a new model.
24:27
It's a router on top of multiple models. And that's the value.
24:32
So the router release can be now understood can now understand the intent of the user's queries and importantly can decide how to respond.
24:42
It only takes one additional step to decide whether the query is economically monetizable or not.
24:46
Today we will make the case for how chat GPT's monetized free end state could look like an agentic super app for the consumer.
24:52
This is only possible because of routing.
24:55
Um there's a very interesting chart in here. Um where is it?
25:00
It's about the various costs.
25:04
So cost per million tokens output has a really really steep power law curve.
25:10
So 03 Pro uh the the model that everyone's obsessed with the the one that people really want to hit as much as possible because they feel like it gives it the most uh the most rigorous and thoughtful output.
25:22
and I was certainly firing off 03 Pro queries constantly.
25:26
Um, so, uh, more and more free users will be able to interact with 03 Pro occasionally because they will trigger it randomly.
25:41
They might not have been on the upgrade tier, but they actually get to experience what that's like now without having to first go and pay, which I think is cool.
25:48
Um, over 99% of free users have yet to interact with a thinking model like 03.
25:53
And for the average user, chat just got a huge upgrade.
25:58
And so there's this weird like the vibes on X with the power users were kind of like all over the place.
26:04
>> Yeah, there's that post from John Collison, >> but for most people were just like, this is incredible.
26:08
Everything just got better.
26:10
If you weren't in love with the old model and you didn't like the upgrade, but for most people it was just a big upgrade.
26:15
So the number of >> You got to pull this up. Pull this up, guys.
26:18
>> The number of free users exposed to thinking models went up 7x in the first day and the number of paying users up.
26:25
>> John Collison, what it feels like to select 03 and legacy models menu.
26:30
>> Yeah, it's a good metaphor.
26:30
It's definitely it's definitely a good metaphor.
26:32
Uh it's it's a it's it allows that engagement. Yeah.
26:38
>> This this sort of army green on tan.
26:38
So on a cost per million tokens basis, 03 Pro is $80, GPT5 is $10, GPT5 mini is $2, and GPT5 Nano is 40.
26:49
So a huge huge gap of 200x the spread on the cost to actually serve the user.
26:59
So um the the the but the router is clearly a feature of the new to the new service and can likely see improvements or changes over time.
27:09
It will continuously learn on preference rates and open AAI promises it will improve over time.
27:13
They'll get a lot of feedback from somebody said, "Hey, you triggered thinking I would have liked a faster answer in this case or hey, you you you gave me the fast answer.
27:22
I actually wanted you to go way deeper.
27:24
This was not satisfactory."
27:24
So, >> so semi analysis says, "Centralizing the control of the free user experience allows for many more future monetization paths.
27:32
And this monetization path is one that has been hinted at subtly for a while.
27:36
It all starts with OpenAI's decision to hire Fiji Simo as CEO of applications in May. Yep.
27:40
Let's look at her background because it's telling.
27:43
Obviously, we covered this back in the day, but we'll cover it again now.
27:45
So, Fiji was at eBay from 2007 to 2011, but her career uh defining career was primarily at Facebook.
27:52
She was vice president and head of Facebook, and she is known for having a superpower to monetize.
27:57
Let's give it up for monetization superpowers.
27:59
She was critical in rolling out videos that autoplay, improving the Facebook feed and monetizing mobile and gaming.
28:05
And I think we should just keep the claps going.
28:09
She might be one of the most qualified individuals alive to turn high intent internet properties into ad products.
28:14
And now she's at the fastest growing internet property of the last decade that is unmonetized. It's an obvious story.
28:20
>> This is the next list. Post medicine list.
28:22
We need po we need the the the monetization maxis. Yeah.
28:25
Fiji at the top of the list. >> Money maxis.
28:28
Um, we can continue to run through this or we can kick it over to the medicine list. Whatever you want.
28:35
>> Yeah, I mean, let's cover a little bit more.
28:36
So, they're covering the tone shift.
28:38
We obviously had those videos. Yep.
28:39
They say in recent interviews, Sam's tone has shifted.
28:41
There's clearly a lot of thought happening about how to best monetize free users more recently.
28:47
Again, this this goes back to the kind of little debate we were having, the little little timeline and turmoil moment with uh Cuban where Yeah.
28:52
Again, you can't expect companies to give products that are expensive to serve away for free forever, right?
29:00
And it's great that protier users can help offset the costs for free tier users, but there's very few I mean, OpenAI, the funny thing is they're trying to convert to a for-profit.
29:14
Right now, they are nonprofit, so it makes sense they're giving this incredible product away to to millions of humanity. >> Yeah.
29:22
for just for the benefit of humanity.
29:23
But eventually, >> yeah, >> eventually, you know, they're business.
29:28
>> I do think uh like Cuban has a point with which I steal man with with the idea of if it was purely based if the entire flow of we want people to open the app and convert to to commerce immediately.
29:42
Um that could result in perverse incentives and like lower quality just general user experience.
29:47
uh it might be a situation where um that's kind of like a short-term gain for long-term pain in the sense that people wind up churning if it's really really bad.
30:00
Um but I think that it is possible to have a wall in the organization between like okay the truth seeeking happens here and the first layer of you ask a question we're going to give you the best possible answer for what you asked.
30:16
So, luxury hotel with your preferences.
30:18
We're really going to and the team is purely focused on that and then they are separate from the monetization team that says, "Would you like to check out?"
30:26
Okay, we have a great agent that can go do that, book it.
30:30
And it's similar to having a a a you know, a a flight uh what do they call a travel agent that actually books it for you and then takes a cut of that.
30:37
And that's a very clear value because it's actually >> Yeah.
30:41
And travel agents have pretty aligned model with consumers, right?
30:46
They want to give you a great trip.
30:46
So they you come back and book more travel with them, but they end up taking a rev share in different ways from from the hotels and and various like vendors that they end up like booking the trip through. >> Yep.
30:59
And I believe Google has a similar uh wall between like what shows up in the knowledge panels cannot be bought.
31:06
So there is no amount of you know Google ad dollars that you can pay them to change your height on if if it's autocompleting like that pulls from Wikipedia and all these data sources into their knowledge graph.
31:17
You can't there's nothing you can do to manipulate the Google knowledge graph.
31:22
>> You can just buy keyword ads that show up in their box and you might have to scroll a while because they sometimes they put seven ads up there.
31:27
But uh >> as an ad enthusiast, if you do a Google search and the entire screen is filled with ads, it's really >> fills you with heartwarming. Yeah.
31:37
Search DUI lawyers near me right now, I'm sure you'll see them.
31:39
Uh anyway, let me tell you about Vanta.
31:41
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31:44
Vant's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program.
31:54
>> Should we run through uh Ben Thompson's? >> Yeah, we should.
31:56
So uh semi analysis actually quotes Ben Thompson here and talks about aggregation theory.
31:59
Uh let's talk about agentic purchasing and compare it to search quer to the search query today because LLMs have a core feature that search does not and that is scaling marginal cost.
32:10
That's what we talked about with 03 pro costing $80 per million tokens versus GPT5 nano costing 40 cents per million tokens.
32:17
All of a sudden it has a different economic equa equation.
32:22
Uh this is fundamentally different than the world search grew up in.
32:26
Let's examine aggregation theory by Ben Thompson because the core feature was that most technology companies had zero marginal cost to an additional user.
32:34
There were some fixed overheads for running while large uh the large search engine but the incremental cost of another query was virtually zero.
32:42
Agents and LLM kill this concept for the first time the more you spend the better your result is because of chain of thought reasoning tokens and now marginal costs exist in software.
32:52
Again, there is somewhat direct relationship between more money, more compute, and a better answer.
32:58
Nowhere is this clearer than in AI in which you can spend variable cost to get variably better answer or outcome.
33:04
And so before the router, there was no way for a query to be distinguished.
33:09
And after the router, the first lowv value query, if you ask why is the sky blue, that can be routed to a GPT5 mini model that can answer with zero tool calls and no reasoning.
33:20
This likely means serving the user is approaching the cost of a search query.
33:24
Um the the the monetizable query on the other hand has a fixed cost.
33:26
It would show a page ranking websites with potential AI summary at the top.
33:30
This is a fixed supply response to what could be a variably hard question.
33:35
But now chatt free because of routing.
33:38
There's some incredibly, you know, incredible OpenAI hater out there who's on like the maxed out pro plan and just going into 03 Pro and saying, "What is the capital of California?
33:52
Give me a 60page PDF with the answer."
33:57
>> This is the the the hitting Groc 4 heavy with just like answering one word, but think for 10 minutes.
34:01
It's like just burning the GPUs.
34:03
Um, but yeah, I mean the router will will, you know, increasingly >> eliminate that >> decide how monetizable is this query and that's how much compute you get for it.
34:14
And so GPT5 can decide to allocate $50 to a query, create a plan, gather information about the DUI incident in this example, uh, research local lawyers, consider who is likely to answer fastest, consider your budget, then contact multiple lawyers on your behalf.
34:30
All of those are tool calls.
34:30
All of that is expensive.
34:32
It could even agentically reach out to lawyers on behalf of the free user knowing that the conversion ratio of this query is even higher.
34:39
Uh this version of chat is highly helpful, aligns with the user's query and is a valuable referer referral to the seller of goods and services.
34:47
So there's a little bit of you know going into uh how does Google respond to this?
34:56
Um there's uh there uh so chatd has partnered with a lot of different companies in finance.
35:02
They've come they've partnered with Stripe, Visa and PayPal.
35:05
On the consumer side they've partnered with Mattel, Booking. com and Lowe's. Enterprise software.
35:09
They've >> they have a partnership with Shopify as well.
35:13
>> That's on the consumer internet side.
35:14
Snapchats, Shopify, Instacart, and Merkari.
35:17
So if you are a Shopify merchant, you are probably happy to let people check out with your products directly in Shhatty PT.
35:25
You don't really care if they hit your if they hit your website.
35:30
>> It doesn't really matter as long as they're buying your product.
35:31
Your margin's probably going to be the same.
35:34
And so uh >> OpenAI is firmly knocking on the door of technology giants Google and Meta and and even Amazon.
35:41
Previous scares about AI have been focused on search query volume not being replaced in the ad tech stack.
35:48
Chatbt can compete with dominant platforms for its place in the ecosystem.
35:52
And to date, this push into purchasing is the most concrete example o of open AI coming for advertising at large.
35:59
If they were first to launch an aggressive agentic checkout solution before Meta or Google, this would be seen as huge competitive shots for both companies.
36:07
a reminder that what we that if we are talking about pure usage only one company is growing users at a meaningful rate.
36:14
It's OpenAI and the visits year-over-year for OpenAI are up 135%.
36:20
And there's this other crazy crazy chart in here that's the of the top 10 websites, uh, CatchPT is number five and it's uh, and every single property is over 15 years old.
36:36
So Instagram is the next youngest like website in the top 10 websites and it's 15 years old.
36:45
Then you have Google at number one 28 years old, YouTube at 21 years old, Facebook is 22 years old.
36:53
>> Hearing that Instagram is 15 years old. >> Crazy.
36:56
>> Makes you feel a little bit old. >> X.
36:57
com, Twitter originally 19 years old, Reddit is 20 years old, WhatsApp is 17 years old is 16 years old.
37:04
Twitter's going to be able to drink soon. >> Get ready. >> Get ready for that. >> Yeah.
37:11
I mean, rebranding at at age 17 is kind of on brand.
37:14
You know, it was Twitter and then it had to Don't call me Twitter anymore, Dad. I'm X. I'm X. Just call me X. >> Call me X. Right.
37:23
>> Uh, and so, um, >> yeah, when companies turn 21, they should just like really >> even 21st birthday, get a little wild for 24 hours and then lock in again. >> Yeah.
37:33
So, um, let's go over to Mr. Tekker.
37:36
Let's go over to Ben Thompson.
37:38
But first, let me tell you about graphite.
37:39
dev code review for the age of AI.
37:41
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37:45
So, paradigm shifts in the winner's curse.
37:47
This was posted Wednesday, August 6th on Stretchery by Ben Thompson.
37:52
>> Ben says, "It's fun and often accurate to think of tech companies in pairs.
37:56
Apple and Microsoft define the PC market.
37:57
Microsoft and Intel won it.
37:59
Google and Meta dominate digital advertising.
38:01
Apple and Google won mobile."
38:02
That however is not the defining pair of the smartphone smartphone era which ran from the introduction of the iPhone in 2007 to the launch of chat GBT in 2022.
38:10
Rather the two most important companies of the last two decades of tech were Apple and Amazon specifically AWS. The Apple part is easy.
38:19
The iPhone market created the smartphone paradigm from its user interface to its distribution channel and was richly rewarded with a bit under half of the unit market share and a bit under all of the >> all of the total profits. Isn't that a great line?
38:33
It's such a good line, but it's true. >> A bit under.
38:36
Google did well to control the rest in terms of the Android operating system and profit from it all thanks to Google search.
38:41
But it was search that remained their northstar.
38:44
The company's primary era error in that era was the few years they let the tail Android wave the dog Google.
38:52
>> That's a that's a typo.
38:52
It should be wag the dog.
38:54
I I or maybe maybe he's making a wave joke because Google had a product named wave.
39:00
But usually the phrase is you let the tail wag the dog.
39:02
The dog should be in charge of the tail in the golden retriever.
39:08
>> It wasn't just wagging, it was waving. >> Yes.
39:10
>> The AWS part is maybe less obvious but no less critical and the timing is notable.
39:13
Amazon created AWS in 2006 just 10 months before the iPhone unveiling and the paradigm they created was equally critical >> crazy timing >> to the smartphone era.
39:21
Y I explained the link in 2020 is the end of the beginning >> where he says this last point gets it why cloud and mobile which are often thought of as two distinct paradigm shifts are very much connected.
39:31
The cloud meant applications and data could be accessed from anywhere.
39:35
Mobile made the IO layer available everywhere.
39:37
The combination of the two make computing continuous >> instead of deliberate.
39:42
Before you had to sit down at a computer linked to a onremise server and you could only use technology in one place at a time and now you can be always on uh tapping into the cloud wherever you are.
39:58
Let's hear it for the cloud and mobile. Fantastic.
40:02
Um, and so AWS was not the only >> I remember those days as a kid summer. I'd have my email. I'd sit down.
40:08
I'd send some emails as a >> as a as a as a teenager and then I'd walk away from my computer.
40:15
I'd go out into the world. >> Yeah. >> Unconnected.
40:19
>> You used to have to go and turn on the Xbox to play Call of Duty.
40:21
Now you can play on your phone >> and you can even stream it.
40:23
There's there's a ton of stuff. It's changed everything.
40:28
>> AWS was not the only public cloud provider.
40:30
Of course, Azure and GCP were both launched in 2008, but by virtue of being first, they both >> AWS defined the paradigm >> and also were the first choice of the universe of applications that ran on smartphones and more accurately ran everywhere.
40:45
>> So, if Apple and AWS were the definers and thus winners of the smartphone era, then it was Microsoft and Nokia that were the losers.
40:50
The reasons for their failure were myriad, but there was one common thread.
40:54
Neither could shake off the overhang of having won the previous paradigm.
40:58
Indeed, both failed in part because they deluded themselves into thinking that their previous domination was an advantage.
41:05
Uh for Microsoft, that previous paradigm was the PC and the Windows platform, which they thought they could just port to mobile.
41:11
And so all of their mobile efforts were basically just like Windows running on a phone, kind of dumbed down, didn't really work very well.
41:18
It took Microsoft years and new CEO to realize that uh their mistake.
41:23
So, uh, we will come back to this and debate Google more on this show, but we have Keith Ra Boy joining the stream.
41:31
Welcome to the show, Keith. Good to hear from you. How you doing? >> Great.
41:36
>> Pleasure to be back with you. >> Fantastic.
41:38
Uh, before we go into all all the news that's shaking up the timeline.
41:42
Do you have a take on on Google right now?
41:45
We were diving into the fact that semi analysis seems quite bearish on Google and is is c is is saying that uh uh openai will basically steamroll them once they get into agentic commerce and and checking people out >> properly monetizing the user base and all the economic activity that they're already driving. >> Yeah.
42:03
And then Ben Thompson's kind of saying like, hey, it's this college campus.
42:06
They have a bunch of great AI researchers.
42:08
Like something will come out of this and there and it's it's just a lindy company.
42:12
It's been around for a long time. It's not going anywhere.
42:15
Well, I think Chat GBD is the fastest growing consumer app of all time and as long as that continues, Google's significantly threatened.
42:20
I think normal people are substituting uh what used to be searches and queries into prompts and that really does threaten Google.
42:28
Even if they have top tier AI talent, they have yet to productize it in a way that undermines the trend towards TBT.
42:34
If Google were to fuse together all the information they have about you, your Gmail, your YouTube, etc.
42:42
, and make everything personalized out of the box, that'd be interesting.
42:47
We'll see if they can ship that product, um, internally, uh, substantively, and whether it resonates with users.
42:54
But they're losing, you know, the AI battle to Open AI, period.
42:58
It also threatens the revenue.
43:01
I don't think that performance-based advertising which is the mainstream you know driver of Google success will be the way that consumers uh expect to be monetized in the future.
43:15
I think uh all the AI applications are showing that consumers are willing to pay for value and so I think direct value direct capture uh from consumers subscriptions etc might be better um and that would you know undermine the entire advertising business model that really
43:31
has propelled Google into the stratosphere was there's product innovation initially engineering innovation data innovation but ultimately is advertising innovation and they had a more efficient advertising platform and that may not be the future of the next 20 years. Yeah. Yeah. >> Yeah.
43:45
In some ways, Google's Google's margin and how much revenue they generate for me as somebody who throughout the year is going to make a lot of searches that that result in a lot of purchase activity.
43:55
And if I can substitute that by just paying 200 bucks a month and eliminating a lot of that, you know, it it Chache BT can can become a probably a trillion dollar company >> by just eating into eating into that and being willing to give up that that incremental revenue that they might get from advertising.
44:15
>> I just had this experience.
44:15
I bought a Nintendo Switch 2. I went to chat GPT. I fired off agent mode.
44:20
I had it uh go around check every website for what's in stock.
44:25
It decided that Target was in stock. I clicked on that.
44:27
Had to go into the Target app and set up an account and it was like a huge hassle.
44:31
Could have just done it for me and taken a cut, but Google wasn't involved.
44:35
So, it's kind of a crazy time. >> Yeah.
44:37
I mean, you can also do some rough math.
44:39
Uh you can calculate Google's revenue per user per month or per year. >> Yeah.
44:44
>> And then what consumers are willing to pay through chatbt and similar products. Totally. >> I think exceeds that. >> Yep. No, it makes sense.
44:50
Anyway, uh enough on Google.
44:53
give us the high level on what's going on with Open Door.
44:58
>> Well, I'm very excited.
44:58
A bunch of retail investors led by Eric Jackson have really take a spotlight and focus it on the potential of the company.
45:06
I think >> for a lot of reasons the company for the last three years has not really uh capitalized on its disruptive elements, its innovation and people have sort of forgotten about it.
45:18
um in the public markets attention is really important and now there's a a very strong shining spotlight on the potential of the company which I think should be like Carvana.
45:28
Carvana is a $40 billion company with in fact more competition than Openoro has but Open has not been able to frame the narrative about the innovation as well as Carvata and I think that's going to have to change.
45:42
I think substantly the company needs better leadership both on the storytelling side and on the innovation side.
45:49
I like tweeted out, you know, really with about 10 minutes of thought ways to fix Open Door this morning. Yeah.
45:56
>> And there's specific uh specity behind every one of those elements that I could dive in deeply, but the company's not executing on any of those things.
46:04
If anything, it's taking a step backwards and partnering with these legacy real estate brokers, which makes no sense whatsoever.
46:12
How much of the like selloff in the stock or just kind of like you know the like getting into the doldrums is and the trouble that open door has run into has been just the interest rate dynamic in the post 2022 2023 era where we've been in this high high interest rate environment that that abstractly has a big impact on home buying.
46:33
But how direct is that on the open door story?
46:38
>> It's moderately direct.
46:38
So in a hot market, maybe 5 to six million homes transact a year.
46:44
And Open Door gets paid every time it transacts.
46:47
So in a in a very high interest rate environment, that number went down to 4 million. So 4 million verse six.
46:53
Like that's that's right.
46:55
It's not like people stop buying and selling.
46:56
It doesn't go to zero and it doesn't go to infinity. So 4 to 6 million.
47:00
The problem for Open Door financially is the cost structure of the company at a GNA level, not marginal level.
47:07
GNA level is just way too expensive to make profits at $4 million.
47:14
>> And this was a known problem.
47:14
The node post who I work with warned the current management team, myself included, um, in 2015, that this was going to happen.
47:22
Real estate has roller coaster rides to it.
47:24
And you need your fixed cost base to be low enough that you don't have to transact to offset your fixed cost, your burn.
47:33
>> Unfortunately, the base was too high.
47:36
And when the Fed raised interest rates like five times sequentially really fast in kind of an unprecedented way >> very few people transacted.
47:43
So there wasn't enough profits to offset the fixed cost of running the business. It was a mistake.
47:48
It really did cause significant strain.
47:50
Arguably you know the entire management team made that mistake didn't listen to the node.
47:57
Whenever that's three years ago >> the company's made no progress on cutting the GNA cost over the last three years.
48:04
The good news is it's actually really easy to cut the GNA cost these days.
48:07
AI allows you to substitute for most of what the people that work at Open Door do.
48:11
So you should be able to bring the very the fixed cost of running the business down to here and then just decide on every home purchase are we going to make money or lose money and just purchase homes in any interest rate environment where you will make money.
48:23
>> What are the what are the key activities within the business that you think are are most ripe for replacing with agentic workflows?
48:31
Honestly, I think real world stuff like there are companies that are actually doing inspections with AI.
48:40
>> The idea that you need this like we have labor going to inspect you know repairs etc etc that that stuff can be done videos and AI much better than uh traditional people and there's companies that are specializing in this.
48:53
So I I just think that you don't need all these people and it's going to continue.
48:58
acceleration AI is more and more obvious and more and more stark every day.
49:00
So can you cut it to 100 people?
49:03
Probably yes actually maybe less and then you have a then you all have variable costs and the only thing you need to do is model the value of a home correctly which is complicated but open door has been excellent at it.
49:15
One thing that people miss is with a exception of one quarter in the history of the company.
49:23
The company has priced homes correctly and purchased successfully and profitably, but the marginal cost uh the fixed cost sorry has not been able to be offset in when no one's transacting.
49:32
The company has significant market share in many markets.
49:36
So the company will just mint money as long as it's gets its cost under control.
49:41
Now it needs to be a massive company which is the potential.
49:45
Like if you think about it, let's take a top down perspective.
49:46
Yuri Mililder actually made this point to me seven years ago.
49:50
The largest real estate platform in the West is worth about $18 billion. >> That's insane.
49:58
This is the largest asset class. Period.
50:00
The idea that the most innovative company in the entire Western universe would be worth $18 billion in residential real estate makes no sense whatsoever.
50:10
So somebody's going to build a 50, 100, $150 billion market cap company.
50:14
And this management team doesn't think that way.
50:16
They think about, you know, moving one basis point here and one basis point there versus innovating to build a hundred billion dollar company.
50:23
There is no reason this shouldn't be a 50 to$100 billion company.
50:27
You just need the right leadership and we're going to fix that.
50:29
>> We have a couple questions from the chat.
50:31
Are you interested in going back on the board of Open?
50:33
Are you interested in stepping in the CEO seat, getting a new role?
50:39
like what what do you see your involvement going forward?
50:41
How do you think about that?
50:43
>> The co the company needs a new CEO.
50:43
If I can be involved in identifying, assessing and or closing the proper candidate, I'll be happy to be involved.
50:52
Um I I do not plan to be an executive.
50:52
I have a very busy full-time job.
50:55
Um and I this company needs a full-time dedicated CEO who's intense, who's creative, who's innovative.
51:04
Um, so if I can help that person, y if I can encourage that person, that would be wonderful.
51:11
Regardless of the structure, >> maybe they're listening right now.
51:12
Uh, DM Keith if you're the one for the job.
51:16
>> If you're a great if you if you're anything like Will Gabbrook at Stripe or Greg Bman, head over, please call. >> Come on over.
51:23
Uh, I want to talk about uh transformation and actually implementing agentic workflows, implementing AI and then cutting cost.
51:30
Is there a sort of uh like capex type cost?
51:33
I mean, I imagine that there's some folks on the private equity side that are buying up small businesses and then hope to use AI to cut costs, improve margins.
51:41
Uh, and maybe they're doing that internally and defaying those costs of knowing which tools to pick uh internally across a portfolio.
51:48
Then there's McKenzie and the big uh the big consulting firms that are going to Fortune 500s and saying, "You're going to pay us a ton for a slide deck, but you know, in theory, we're going to get you set up with something that will save you money."
52:02
But for a company like Open Door, um, what does it look like?
52:06
Because it feels like it's probably too complex to just say, "Okay, yeah, we're going to like sign up for chat GPT and that solves our problem."
52:13
There's probably going to be some implementation of these AI tools.
52:16
Uh, and that might have cost in the short term, even if it drives longer terms better earnings outlook.
52:23
How do you think about that?
52:25
>> Well, I think that's why we need a CEO who's AI native, AI uh, insightful.
52:27
I think that business transformation requires real skill.
52:33
I think you are right though that the hottest area of venture capital is venture capital is chasing after old school businesses and trying to turbocharge businesses uh with AI whether they're turbocharging on the top line which to me is more interesting or improving IBIDA with AI substitution of cost.
52:51
That's that's pretty cool.
52:51
But you know we funded a few companies.
52:55
There's at least two VC competitors of ours that I know of that have dedicated funds that do nothing else except roll up traditional businesses and try to turbocharge them with AI.
53:04
So I think you know this is very common at the large company level.
53:08
It is happening apparently.
53:11
Um actually apparently Amazon has had a lot of success with this.
53:14
They don't talk about it and speak about it but apparently it's true.
53:16
Um, and then I think you're going to see more private equity firms insist upon their portfolio, whether they're large market cap portfolio companies or small, um, apply AI in a thoughtful creative way.
53:32
Do you think do you think I mean it feels like private companies have like an extreme structural advantage in terms of doing like true AI driven transformation because open AI uh sorry not not open AI open door you know every uh over the last week every 10 posts on X has been some you know different retail investor having strong opinions about who the management should be and and what the board's doing and all this stuff. Um, yeah.
53:57
Do do you think that um do you think that if if the right person were to come to the table that that like a that that Open Door would do better if it was a private company for the next like few years?
54:10
>> Yeah, >> I don't think so.
54:10
I think you can transform yourself in the public domain as well.
54:13
I think you could take advantage of those suggestions.
54:15
I think first of all, let's just take a step back.
54:18
I think retail investors having a point of view and being excited about an opportunity is a great thing.
54:23
opportunity is a great thing. I think the whole point of markets is to allocate capital that's why we have markets right that's why we have public markets it's an allocation function and consumers voting with their feet especially for consumer brands saying I want more of this I want less of that is
54:39
actually a proper capital allocation like if the company did this I would spend more money with them that should encourage capital allocation the this is not some people have like this negative perception of retail investors I think it's actually better when retail investors say I'm going to vote with my feet, I'm going to vote with my dollars. If product X or Y or brand does it does
54:56
If product X or Y or brand does it does X, Y or Z or brand represents Z, I'm going to spend money with them.
55:02
That is a reason to allocate more capital to that company.
55:05
It's fundamentally sound.
55:07
>> How do you think about the the storytelling around AI as a silver bullet versus a core competency that will be a compounding advantage?
55:15
I'm thinking of the Amazon example you gave.
55:19
I completely agree that Amazon's been a beneficiary of AI all over the place, but I don't think it's happened in a single quarter.
55:25
I think they ramped to a million robots across all of their different facilities.
55:30
They bought KA a decade ago.
55:32
They were using they were using AI recommendation systems to tell you, hey, you're buying a computer. Do you want to monitor? That's AI.
55:39
But, you know, just a couple decades ago.
55:41
And so, it feels like the right person for the job.
55:45
They might be able to come in, rip off a band-aid, get things right sized, do the hard work, but then it's really like you can't take your foot off the gas.
55:54
>> I think you need to do both.
55:54
I think there's bottomup transformation, which is blocking and tackling, persistency, consistency.
56:00
It's like going to berries.
56:02
You have to go every day like every day for like for like a decade.
56:04
And you know, you get sometimes sometimes sometimes three, four, five times that. Yeah.
56:10
And then there's I think there's top down.
56:11
I think leadership involves sometimes just putting a stake in the ground and saying thou shalt not like we are just not going to do this anymore.
56:19
We are absolutely out of that business.
56:21
And that's why you need a founderdriven CEO.
56:22
Truthfully, transformations with emerging technology require the moral authority of a founder just saying absolutely no.
56:29
I know this has worked in the past.
56:31
I know this has worked in other companies, but we're just not doing that anymore because the world's going this way and we want to be ahead of the world.
56:38
How do you think Open Door's relationship with with traditional real estate agents should evolve?
56:45
>> Well, I I think it should be we should be innovating so that there's no comparison.
56:50
Like the value proposition Open Door provides a consumer, whether a buyer or a seller, should just be so much better that no one wants a real estate agent. It's not a bad thing.
56:59
Like real estate agents used to do X and Y and there's a bundle of services they provide, but what Openor provides is this and it's just like a no-brainer.
57:07
And if it's not a no-brainer, the company is not innovating and is not creating enough value period.
57:12
>> Uh how do you think about other levers like zooming out to the macro that could just increase the velocity of uh of real estate transactions or just make homes more affordable in America?
57:24
I don't know how high this up is how high this is on the current administration's agenda, but it feels like something that people have been clamoring for for years on both sides.
57:36
Are there obvious wins that you're optimistic about in the next couple of years to just improve the quality of housing in America broadly?
57:46
>> Well, affordability is a top tier issue certainly for my conservative friends.
57:51
>> Yeah, >> we need to make housing more affordable for more people as fast as possible.
57:55
There are some things that have short timelines and some things that take longer. So, building is great. We need more. We need more supply. Supply works.
58:03
Supply has worked in local environments.
58:05
You can prove it in in in city action and citywide.
58:07
The cost will come down if you build.
58:10
But you can't build a house, at least right now, without more robots, more automation.
58:14
You can't build one overnight.
58:15
So supply does take time, but we need to start working on supply and getting rid of all the blockers and excuses for lack of supply, particularly in California.
58:23
>> Secondly, we do need interest rates to come down.
58:25
U we do need a new chairman of the Federal Reserve.
58:27
The best thing ever, you know, for open door would be replacing Carrie as CEO and replacing Jerome Powell as Federal Reserve chair.
58:36
Fortunately, I think both are going to happen.
58:37
I hope both happen in September, maybe before. >> Okay.
58:41
Can interest rates ever be too low? >> Probably.
58:45
You know, like interest rates, it's basically related to a time value of money. Yeah.
58:50
And so if interest rates are too low, people's willingness to part with money to get paid back in the future gets reduced.
58:56
And that that is investment.
58:59
That's that's really what the definition of investment.
59:01
So they could be too low, but they're they're definitely too high right now.
59:05
>> I guess I've just been thinking like there are there are a lot of green lights, green flags in the market.
59:09
New companies are going out.
59:11
The stock market's at all-time highs.
59:13
Everything feels really strong in the economy.
59:15
Even the CPI is coming back flat and GDP is printing.
59:21
Everything seems pretty good and it feels like >> except the fast casual restaurant chain. >> Yeah. Yeah.
59:26
They're having trouble >> except the slot market is but in general things to be seem to be going very well in the American economy and when there's a risk of okay, we could be overheating.
59:37
I feel very reassured by having let's lower interest rates as an ace up our sleeve in case we get over our skis and there is a market correction.
59:46
correction. the Fed does have some has some tools in the >> like our friend our friend Joe's point is like the in his view the the argument to lower rates is like the data that's coming out of the labor markets but
59:58
again that's also being debated and rehashed and and uh I don't think anyone really >> well let me let me take a step back though >> please >> I think the foundation that growth equals inflation is just wrong >> so from 1950 to 2010 Each decade we average 3.6 years with
1:00:16
6 years with over 4% growth >> without inflation.
1:00:23
>> It's only the modern world post 2010 with qualitative easing that people equate growth with inflation.
1:00:28
The good news about AI and productivity gains is it's very easy to see how you can grow fast three, four, 5% consistently without sparking inflation because all of the growth is not propelled by labor cost increases which is what causes inflation.
1:00:47
So I think the modern world of the next 30 years if it's managed correctly, if the leadership in the political sphere is dialed in should allow consistent growth which will eliminate the debt and make not a non serious problem like 3% 3% 3% plus without inflation.
1:01:05
And we need to get people who are sort of educated a century ago out of this mindset that every time you see growth, you need to put on the brakes. That's just not that.
1:01:18
And that's why the Federal Reserve keeps making that mistake.
1:01:21
And so we've got to fix that.
1:01:23
But part of it is AIdriven and technologydriven innovation will allow for great growth, consistent growth without inflation.
1:01:33
>> Is that your current outlook?
1:01:33
Um, not necessarily a fast takeoff and we're growing at 10% GDP a year.
1:01:38
Uh, Satin Nadella says, "Call me when we're growing at 10% a year."
1:01:42
Uh, but but but a materially improved economic condition for the United States on a on a long-term basis. >> Yeah.
1:01:52
Scott Bess likes to talk about 33 and you want the 3% consistently.
1:01:55
You could beat three and I think we will beat three and I think he wants to beat three in the next couple years.
1:02:00
So I subscribe to his perspective on the world. I think he's right.
1:02:05
But it's technology that's the magic wand that allows consistent growth without actual inflation. And that's what we need.
1:02:12
That is how that is raising taxes is a disastrous policy.
1:02:17
It's not going to fix any problems.
1:02:19
Consistent growth without inflation will.
1:02:21
And we need a Federal Reserve chair who understands that.
1:02:23
We have a Treasury Secretary, fortunately, who really does understand this. >> Yeah. Yeah.
1:02:28
And we and we've seen that with those charts of the various goods and services inflation over the past decade.
1:02:34
Education and healthcare goes through the roof where everything that's on the technology adoption curve like TVs and dishwashers that all has gone down in price.
1:02:43
And so the more goods and services that you can put on the deflationary curve, the more growth you get and the and the better health of the American consumer. Good stuff. Jordy, anything else? >> I think that's it.
1:02:53
Thank you for jumping on on short notice.
1:02:55
>> Thanks for taking the time, Keith. This is always great.
1:02:56
come back on whenever you have uh more thoughts on uh on if you if you can think for 10 minutes and get a post up, you can jump on the show, >> please. We'd love to have you.
1:03:05
>> Great pleasure to be with you. I'll be back. Cheers.
1:03:07
>> We'll talk to you soon. Bye. >> Take care. >> See you.
1:03:10
>> Uh let's go to the medicine list.
1:03:10
We updated the Met list, our ranking of the uh top 128 now AI researchers.
1:03:15
Uh it's uh burning up the timeline extremely controversial.
1:03:21
Fortunately, we have Tyler Cosgrove to blame for that.
1:03:23
We had no no involvement whatsoever.
1:03:25
We will be disavowing the Met list if it comes back to bite us.
1:03:30
But Tyler, why don't you give us an overview of what changed uh who's on top and what's going on with the Met list today. >> Okay.
1:03:38
So, we're going to the mic, right? Okay. So, so uh Okay.
1:03:40
Before we start, just want to give um you know, this is not done yet. Okay. The list can change. Okay.
1:03:47
So, we got some haters in the comments again. >> This is final. Dyling.
1:03:52
>> Oh, this person like oh he's so low. Okay. Okay, we can fix it.
1:03:54
All right, it's not done. >> Okay. >> All right. Um, but yeah. Okay.
1:03:56
Let's start with uh the top five here, right? >> Okay.
1:04:01
>> So, I I think a big change we'll see is that we saw Noom, Shazir, and Ilia switch, right? That's pretty big. >> That's a huge move. Okay. What drove that? >> Sorry. >> What drove that?
1:04:10
Uh, is that just because Ilia has been quiet at SS SSI hasn't published anything in the last part of it >> and Gnome's been on a tear? >> Yeah. So, so I I know.
1:04:17
So, so I mean I think Nome Shazer is broadly almost like you you can't say he slept on he's number one. Yeah.
1:04:24
But he is I think you know punching above his weight a little bit.
1:04:28
>> I think Doug from 79 just came on and said that the reason that Gemini is so good is because is because Gnome's back. >> Yeah.
1:04:34
You can basically track like Gemini was okay. It was fine.
1:04:35
He comes back from character. >> They're goated again. >> Okay. >> Okay.
1:04:40
So, let's go down to number seven.
1:04:41
>> Soundboard Jordy for Gnome. Shazir. >> Sound is down. >> Sounds down. >> Sound down. Okay. Demus. >> Yeah. Demus.
1:04:46
He was missing from the first list.
1:04:48
Um that was maybe a conscious decision. It might not have been.
1:04:52
>> He was missing entirely. >> He was missing.
1:04:53
He was on the list at all.
1:04:55
>> He's one of the greatest.
1:04:56
>> Well, you know, the thought was like he, you know, he's not as much of a researcher now. He's more leader.
1:04:58
He just leads the lab almost. >> Exactly.
1:05:02
But, you know, if you trace it back, he's obviously still making some research decisions. >> Okay. Yeah.
1:05:06
>> So, I think it's fine to put him back on. >> Okay. So, he's number three.
1:05:09
>> No, he's number three. Dario. >> Daario. Amade. >> Dario. Amodore moves up.
1:05:12
Anthropic >> overanthropic. >> Similar thing. another lab leader. >> Got it. Makes sense.
1:05:18
>> Um, and then last up we have John Schman.
1:05:20
>> And Dario, uh, has he been on the Dark Cash podcast? >> He has. Okay.
1:05:25
>> I think actually all five. >> All five. >> Dor has hit all five.
1:05:27
He's in seven of the top 10 as well. >> Seven of the top 10.
1:05:31
>> So I mean, he's been on a generation.
1:05:33
>> We didn't just listen to Dwar. We studied.
1:05:35
>> We sat down and listened.
1:05:35
We didn't just hear Dar Cash.
1:05:37
We sat down and listened. >> Yeah. >> Okay. Who's last? Uh, on the top. >> John Scholman. Thinking machines. >> Thinking machines. >> Yeah.
1:05:44
So, another another big player.
1:05:46
Um, I believe >> huge huge >> everyone except Demis has at one point worked at OpenAI. >> Wow.
1:05:52
>> Uh, actually, wait, I don't know if that's true. Maybe I don't know.
1:05:54
>> I don't think Gnome did, but >> um, >> still would have run for Open >> AI. That's the new top five.
1:05:57
I think let's move over to big moves. >> Big Moves. Who we got?
1:06:00
We got >> from two weeks ago.
1:06:02
So, uh, the first one we can look at. Number 13, Nome Brown. >> Nome Brown.
1:06:08
>> So, he he he did really well. >> 36 spots. >> 36. >> 36 spots.
1:06:11
Now, he was in the IMO gold medal team at OpenAI that cracked that code.
1:06:17
>> Yeah, he's big on the kind of RL team.
1:06:17
I don't know, they probably have multiple RL teams post training, but yeah, he he's he's doing a lot of good work there.
1:06:26
>> There's someone else at OpenAI who's famous for like holding RL all together.
1:06:30
They made the list as well. Is that correct?
1:06:31
Are you familiar with that?
1:06:32
>> There's a bunch of um just like post training RL people that that are new on the list now.
1:06:36
>> That'll be important going forward. >> Yeah.
1:06:37
I don't know if we mentioned, but the list is longer now, right? There's now 128. We were at 100. Now we're at 128. A nice base 2 number.
1:06:44
>> I think some big additions, too. Will Brown crack.
1:06:48
>> Unsurprising to anybody with a brain.
1:06:51
>> Multi-time TBPN appearance.
1:06:51
So, makes a lot of sense. >> Chad. >> Um, okay. We can go next one. Paul Cristiano. >> Yeah. Break him down. >> He's kind of an OG.
1:06:59
He um >> I don't know if he's the godfather of ROHF, but he he was a big name on that paper.
1:07:05
Um, now he's mostly into safety stuff now, but he's definitely kind of a a thought leader in the space. Right.
1:07:12
>> We got Reggav in the chat saying Tyler is trying to atone for mogging Anthropic in Sonnet 4 yesterday. Is that true? Are you the allegations?
1:07:19
I think I think you've atoned. Good job, >> Shelto.
1:07:25
I think Shelto actually moved down.
1:07:27
>> Anthropica is still, you know, they have a lot of people on the list. Okay. Okay. Let's go to Peter Beiel. Up 66. >> What is he known for?
1:07:33
I've heard his name before.
1:07:34
I mean, so he's just an academic. He's at Berkeley. >> Okay.
1:07:38
>> Um >> Oh, he's not in a lab.
1:07:39
>> He's not in a lab right now. >> Not yet.
1:07:41
He's leaving billions on the table. >> Leaving billions. >> Literally. Yes.
1:07:45
Um >> yeah, he's been on a ton of papers.
1:07:47
He's like uh also advised a ton of the of the top researchers. Sure.
1:07:52
So, I think he's kind of influ influential in that way.
1:07:55
>> Um let's go down to Yan Lun is actually missing from the list now. >> Missing.
1:08:00
>> So, he was shot fired. I think he was top 10. >> Okay. Hey, he was top 10.
1:08:04
>> He's now not even on the list.
1:08:05
>> He's not on the list and he's that >> So, you know, like I don't make the list.
1:08:08
I just give the I give the voting out and then people make the decision. It's not me. Okay.
1:08:13
>> So, let us know in the chat.
1:08:13
Should we shoot the messenger or should we not shoot the messenger here?
1:08:16
Do we have a do we have a toy boner?
1:08:18
I can shoot the messenger here. Uh yeah.
1:08:20
So, Yan Lun um big meta AI researcher ran fair.
1:08:24
Uh was not directly on the llama project but was one of their key researchers. Is that right?
1:08:32
that right? and then kind of llama spun out a fair AI research lab and then yeah uh and and sort of like a thought leader in many ways uh steward of the of the strategy uh also sort of a hater on deep learning for a while >> sort of a hater on on LLM I don't know about deep learning specifically he was
1:08:50
kind of he did CNN's right that was his big thing >> so he's kind of he's been kind of maybe right it's kind of too soon to call it on him but uh he's certainly like lost a lot of power within that organization as as Mark Zuckerberg has built out the meta super intelligence lab. >> I think his title is still chief AI
1:09:05
>> I think his title is still chief AI scientist, but maybe it might be co-led. >> Yep. >> Yep.
1:09:10
And then of course you have Nat Friedman, Daniel G, >> but he's not considered to be on the MSL. >> No. >> Yes. And so that's Yeah.
1:09:18
>> You mean no as in yet? He is not considered. >> He's not in MSL.
1:09:21
He's in a separate or he's in a separate or right now. Okay.
1:09:25
Uh then break down Jurgen Schmid Huber. What's up with him? >> Down 53 spots. >> 53 spots.
1:09:30
>> 53 spots. He's also somewhat controversial um during the Nobel Prize um you know he was saying oh it should have been me instead he he's kind of he's a real OG in the space in deep learning >> you're trying to or the Nobel Prize >> yeah so it didn't really work but
1:09:45
>> but it was unsuccessful >> it was a failed aura >> so so so maybe that's that's the reason why >> I do remember when uh when chat first launched there was someone in the comments uh dystopia breaker was saying oh this stuff hub did all this years ago. There's nothing new here. Of
1:10:01
There's nothing new here.
1:10:01
Of course, I think that under underrepresents the importance of actually productizing these technologies and these research efforts, but uh still interesting to see that he fell so far.
1:10:13
Uh expect >> let's get into the overall stats. Yeah.
1:10:17
So this was actually pretty interesting.
1:10:18
Um so we can look at the this is the the number of researchers per lab. Okay.
1:10:23
>> So we basically see the top three are all you know neck and neck, right?
1:10:26
Opening ads at 24, deep mind at 23, anthropic at 22.
1:10:29
This is different from from the previous list.
1:10:31
Anthropic was I think leading by maybe four researchers. >> Yeah.
1:10:36
>> Um but now it's really neck and neck here.
1:10:38
And then you see Thing Machines at 12. Somewhat surprising.
1:10:40
They're really I mean they have a lot of goats on their team and then Meta down at eight.
1:10:46
>> Interesting that Meta doesn't have more on the list given what a spree they've been on.
1:10:50
Um but they're probably still just in the early days of actually building out that squad. Yeah.
1:10:53
I mean, if you consider they started MSL like what, a few months ago? >> Yeah.
1:10:59
It takes time to even even when you have the money, it takes time to actually convince people.
1:11:03
>> I think if we would have made that list back then, they would have had basically zero, right?
1:11:05
Maybe they would have had Yan Lun, but he's not even on the list anymore. >> Yeah.
1:11:08
They didn't have that many. Sure.
1:11:10
>> And then we can also bring it down.
1:11:11
>> I mean, I remember those viral posts about people saying like, "Oh yeah, I worked on Llama 3, not Llama 4, and now I'm at another lab."
1:11:16
Like that was something somebody posted on their LinkedIn viral LinkedIn screenshots.
1:11:20
There was a little bit of an exodus and now Zuck's rebuilding the team going into season 2026. >> Exactly. Yeah.
1:11:26
And then finally we can break it down by country. We see USA of course 51.
1:11:32
>> USA >> way above everyone else. China at 14.
1:11:35
>> USA you love to see it. >> UK at 13, Canada 12.
1:11:36
China would be putting that in the true zone. >> On a Yeah.
1:11:39
On a uh on a weighted basis though population weighted Canada is doing fantastically.
1:11:45
They have onetenth the population of America I believe and uh one one as many AI researchers on the medicine list.
1:11:53
So congrats to the Kucks up north.
1:11:56
>> It's always hard especially with China because a lot of their labs are very secretive. Right.
1:11:59
So we have >> So did anyone from uh from Highflyer Deepseek or Alibaba.
1:12:05
>> We have two I believe two deepseek researchers. Okay.
1:12:08
>> Uh one is from started like moonshot. >> Yep. Moonshot is big now.
1:12:10
And then >> I don't know if we have anyone specifically from >> Dance the the the the the guy who created the the gal who created the Tik Tok algorithm.
1:12:19
You got to put them on there. That thing is wild. >> Yeah.
1:12:23
It's always just hard because you know >> brain rot.
1:12:25
You want to build the brain rot machine.
1:12:26
>> I think especially with we should actually build the brain rot list. >> The brain rot list.
1:12:30
The researchers who have created the most sticky, you know, user generated content algorith user hour maxers.
1:12:38
Anyway, what else you got for me?
1:12:41
Um, so, so I think one of the big improvements of of this list versus of two weeks ago was that I think it originally we kind of optimized a little bit too much for Twitter cloud >> or uh Google Scholar citations. >> Twitter cloud.
1:12:55
>> It's hard like I mean the labs are so secretive now they really put out papers >> of course and if you have someone incredible you have a huge incentive to not let them do press like hey no actually you can't go on to our cash.
1:13:05
We definitely got messages from people that were saying, "Can you can you put can you take my team off the list?
1:13:11
>> Can you take my team off the list?"
1:13:13
Like, "Stop stop talking about us.
1:13:13
We we'd prefer if these people didn't get poached, but that's in the comments." >> Yep. >> Yeah. Sutton.
1:13:21
I mean, there's a bunch of people that probably like should be on the list.
1:13:25
>> Rich Sutton, John Carmarmac. Yeah. Both of them at uh Keen.
1:13:27
We haven't seen a lot from Keen, but would be very, very interesting. >> Yeah.
1:13:33
But yeah, we're gonna Big Shout out to Mark Chan. broke the top 10. Welld deserved.
1:13:37
Up 19 spots, sitting at number six, just under John Schulman >> to the chat.
1:13:44
I have I have unplugged and plugged back in my uh microphone.
1:13:48
Hopefully, it sounds better.
1:13:48
If not, I can switch to the other microphone, but let me know how it sounds.
1:13:51
And we will stop cutting off Tyler Cosgrove, our intern, because the chat is telling us to stop cutting him off.
1:13:56
So, uh Tyler, uh who else uh who else fell off the list?
1:14:02
How is my boy George Bull doing? Yeah, George Bull. Uh, Alan Turring. >> Wait, both of them.
1:14:09
>> Both on the list, but but >> they're on the list.
1:14:11
>> Lenes is on the list now. >> Okay. Okay, that's good.
1:14:13
Um, but what what happened to George Bool? Where where where is he?
1:14:17
>> People were really hating on him.
1:14:17
I mean, >> he's off the list entirely.
1:14:19
>> Yeah, off the list entirely.
1:14:21
>> I don't know what his what his actual rank is.
1:14:22
Obviously, like I have the internal one.
1:14:24
>> The ghost of Allan Turing is going to haunt you, Tyler.
1:14:28
>> So, Allan Touring is not on the list. >> He fell off. >> He's off the list. He >> kind of fell off.
1:14:31
His his test didn't really hold up too much.
1:14:33
He got he got mogged by Yeah.
1:14:35
JP, but this test >> Tyler Cowan still defending Allen. >> Okay.
1:14:40
Yeah, the touring test is is is Lindy. Uh any other moves?
1:14:42
Did we get any other Easter eggs on this version or are we Easter egg free now?
1:14:49
>> I think I mean Livveness you could maybe say is an Easter egg.
1:14:53
>> Yeah, >> I think that's go full meme core. >> That's the main one. Yeah. >> Okay. >> But we'll see. >> Oh well.
1:14:57
Well, thank you for all the hard work on the Metlist.
1:14:58
You can check it out at metislist. com.
1:15:02
>> Fantastic work, Tyler.
1:15:02
We will continue to update it.
1:15:04
So, if you're angry, if you're happy, shoot Tyler a message. >> Yep.
1:15:10
Uh >> uh Tyler also uh produced and uh edited a wonderful uh Vibe video.
1:15:15
Uh he did a launch video for this um which uh we're very excited to see him dip his toes in the water of video editing, giving a run for their money.
1:15:25
Uh anyway, let's uh let's run through some posts.
1:15:28
We have 20 minutes until Alfred Lynn from Sequoia Capital joins us.
1:15:33
Let's uh see what else is going on.
1:15:37
Um I did want to cover the Nvidia H20 news.
1:15:40
Do you want to >> Chinese authorities have urged local companies to avoid using NVIDIA's H20 artificial intelligence chips, particularly for government related purposes, media report said.
1:15:52
So they're worried about back doors and they're probably worried about generating revenue for Uncle Sam, their sworn enemy. >> Yeah.
1:16:01
So there's an interesting dynamic here because the uh the Chinese economy is not monolithic.
1:16:06
It is it is like state directed capitalism. It's a mixture.
1:16:12
It's with Chinese characteristics of course.
1:16:13
So the news is that Donald Trump approved Nvidia's request and AMD is bucketed in in here as well but lower in in importance.
1:16:20
uh to export chi uh export H20 GPUs to China.
1:16:27
These are the nerfed uh AI chips uh and they're critical for training large language models.
1:16:31
And of course, DeepSeek famously optimized their training uh regimen and and algorithms so that they could run on H20s.
1:16:39
And so they have figured out a way to train large language models on H20s despite H20s kind of being designed to not let you train or inference large language models as efficiently.
1:16:49
But they're still getting it to work and they want them.
1:16:53
So, uh, first off, oddly, uh, the news is that, uh, Nvidia will pay a 15% export tax roughly.
1:17:00
It's not technically a tax rev share to the federal government, not to Donald Trump personally, but to the federal government um, for the H20s that they sell.
1:17:11
Now, it is unconstitutional to le to levy an export tax on Americanmade goods.
1:17:16
Uh this came from the southern states uh I think post civil war where uh the southern states were exporting lots of cotton goods and they were worried that the northern states were going to try and raise federal revenues through export taxes that would disproportionately hit the south.
1:17:31
Um but there's another odd wrinkle where the H20 isn't technically made in America.
1:17:39
It's uh the chip is made in Taiwan with equipment from the Netherlands.
1:17:41
The memories from South Korea.
1:17:42
I think Singapore might be involved at some point.
1:17:45
It never actually hits American shores.
1:17:47
All the packaging happens uh overseas and then it's shipped to China.
1:17:51
And so >> Nvidia is of course >> an American company. >> American company. >> Exactly.
1:17:55
So Trump still has leverage and he was able to block exports of H20s back in April, which we covered on the show.
1:18:02
Uh and now Trump argues that this chip is not a threat.
1:18:04
There's this incredible quote where Donald Trump says they're not getting Blackwell.
1:18:09
Blackwell's the best chip ever.
1:18:09
And >> he goes, "Maybe maybe they could they'd have to pay more."
1:18:14
He's sort of all over the place, but he's having fun.
1:18:15
Um, uh, so, uh, the H20 at this point, I think most people the consensus that it is an older chip.
1:18:22
It's nerfed and it won't lead to nuclear weapon level AI technology.
1:18:26
Maybe that's the next next chip.
1:18:28
But certainly we're sort of in the implementation uh you know um plateau era of you know decent value coming from these AI systems but certainly not anything super intelligence coming out of a a a rack of H20s just yet. Yeah.
1:18:45
So, Beijing is demanding that tech companies including Alibaba and Bite Dance justify their orders of Nvidia's H20 artificial intelligence chips, which uh just further complicates things for Jensen.
1:18:57
He's, you know, the the meme of him, you know, smoking a smoking a heater. >> Is that a meme?
1:19:03
>> No, it's who who's the who's the who's the actor? Uh >> Beth McConn. >> No, no, no.
1:19:08
>> That that there's one of him like taking a drag off a cigarette when he's like engaged in some conspiracy or like unveiling a conspiracy. Ben Affleck. >> Oh, Ben Affleck. Yeah, yeah, yeah, yeah. Totally.
1:19:17
>> Ben, you can somebody Chad GBT Jensen, you know, sitting outside his office making heater.
1:19:22
Uh, the tech companies have asked by regulators such as the Ministry of Industry and Information Technology.
1:19:28
Let's give it up for that name. >> Yep. We love industry.
1:19:31
>> Sounds a little ominous.
1:19:31
Anytime you got a ministry, it sounds a little ominous, but uh they're making people explain why they need to order. >> Explain yourselves. >> Explain.
1:19:39
Why not use a domestic alternative? >> Yep.
1:19:41
And uh >> and so the dynamic here is pretty clear.
1:19:46
Beijing wants China to continue broadly like the government wants China to continue continue to move down the learning curve for advanced semiconductors.
1:19:56
They want Smick, Smei, W Huawei to develop the indigenous supply chain for semiconductors and do all the hard work.
1:20:04
And the only way to actually get the yields up and and really get to the frontier is volume. It's a volume game.
1:20:10
So, a Chinese data center operator was went on record to say it's not banned, but has kind of become a politically incorrect thing to do when asked about buying H20s. Yeah.
1:20:23
>> One issue with doing politically incorrect things in China is you can often be disappeared >> potentially >> and have your uh wealth taken from you, your your >> I think they got to push back.
1:20:34
I think they got to push back.
1:20:35
So the dynamic is you know China wants to continue developing supply chain semiconductor their semiconductor supply chain and then on the flip side Chinese companies just want to develop you know the best possible AI models that they can and so they don't want to be GPU poor and uh and so they're they're they're probably there's going to be a little bit of a dance there and some of these will be justified.
1:20:58
There still might be some diversion that happens just for political reasons.
1:21:02
Uh it's all very complicated, but it will be interesting to see how many uh of those H20 GPUs that uh have been kind of mothballled uh can Nvidia actually sell.
1:21:12
And we'll see that in their next earnings report most likely.
1:21:15
>> And the irony here, everyone, you know, people like the ultra China hawks, the you know, AI war group saying that, you know, criticizing the original >> Yep.
1:21:26
you know, H20 deal be saying that it would help the Chinese military and just broadly uh undermine US strength and artificial intelligence and now you have uh the Chinese government uh just saying actually we don't even want it.
1:21:40
We don't want you buying them.
1:21:40
We don't want you using them. Yep.
1:21:43
>> So, >> well AI war seems to have been averted and war with China is also between China and Taiwan is also at an all-time low on poly markets.
1:21:52
7% chance by the end of this year.
1:21:55
Of course, the year is ticking by, so you would expect that to go down.
1:21:58
But even by the end of 2026, it's only at a 22% chance.
1:22:01
So people >> 22% chances >> people have been saber rattling about this for a long time that something's going to happen soon.
1:22:09
And uh you know, the at least the poly market doesn't really think that's going to happen.
1:22:13
Um anyway, let me tell you about Julius.
1:22:17
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1:22:34
When Rahul first told me >> when I saw the 2 million user number, I was like, is that a you add a few extra zeros there?
1:22:42
>> It did seem like No, it's real. >> It's real. >> It's fantastic.
1:22:44
So, there's another interesting um data point that came came out of earnings.
1:22:48
So there were two companies that uh that announced earnings recently and are in the business and finance section of the Wall Street Journal today.
1:22:54
So uh stable coin firm Circle records loss but revenue source 53% and then separately uh coreweave posts a loss on higher revenue.
1:23:05
So both of these companies um one in AI one in crypto beat on topline missed on the bottom line.
1:23:11
So they're in different industries, but it feels like they're adopting similar financial strategies, which is invest right now for growth.
1:23:20
Uh go go go get the top line higher, become a big company.
1:23:24
So uh the numbers are crazy.
1:23:27
Circle's share price has quintupled since its June IPO.
1:23:29
We interviewed the CEO just after that IPO.
1:23:34
I had not been tracking exactly what the share price had done.
1:23:36
That's that's incredible performance.
1:23:38
Uh revenue is up 53% year-over-year.
1:23:40
It's great stuff, but the losses are growing.
1:23:43
Um, analysts expected a $338 million loss for Circle.
1:23:49
They posted a $482 million loss in the second quarter.
1:23:52
Uh, something similar happened with Cororeweave.
1:23:54
We also interviewed the founder of Cororeweave on the show.
1:23:57
Uh, second quarter revenue tripled since a year earlier.
1:23:59
That is incredible performance.
1:24:01
Um, but the company lost 290.
1:24:03
5 million in the quarter, which is 15% more money lost than the analysts expected.
1:24:10
not a huge miss, but certainly something that uh people weren't really uh pricing in fully.
1:24:14
And both of those companies have had, I believe, they've had uh profitable quarters.
1:24:17
Um but then kind of gone down as they've gone back into the reinvestment mode.
1:24:21
And so my read is basically like there's green lights all over the economy.
1:24:26
It's green flags everywhere.
1:24:27
The market's open, the IPO windows open, the the economic data is really good.
1:24:31
So invest, invest, invest.
1:24:32
Uh take advantage of the AI race.
1:24:35
take take advantage of the the new crypto regulations, anything you can to go take as much market share as possible and get really really big.
1:24:40
So, you know, maybe the wave is cresting, but why not get a firm foot v foot v foot v foot v foot v foot v foot v foot v foot v foot v footing on your board while you can. >> Absolutely.
1:24:49
>> Anyway, that's my take on uh coreweave and circle.
1:24:51
Um anyway, let's move on.
1:24:51
I think we I think we hit Google pretty well.
1:24:57
We can tell you about profound though that's obviously relevant to the Google conversation.
1:25:01
Get your brand mentioned in chat GPT.
1:25:03
It's going to be more important than ever going forward, especially as they add agentic commerce features where you can reach millions of consumers who are using AI to discover new products and brands.
1:25:12
You can get >> I wanted to highlight a brand uh the founder's name is Isabelle.
1:25:18
She said this morning, my brand that's less than 13 months old is launching Whole Foods nationwide without a seven figure raise.
1:25:26
How is that even possible?
1:25:26
One strong lending partners.
1:25:29
We have invoice factoring and PO financing at less than 12% APR making it a clear no-brainer to free up working capital.
1:25:35
Two, prioritize strong unit economics 50% plus and by coastal manufacturing and fulfillment to not get crushed on freight.
1:25:42
Three, trial and retention.
1:25:44
We invest >> wow manufacturing on both coasts day one. That's a bold move.
1:25:49
>> And then four, the thing that's interesting, A2 dairy is on trend.
1:25:50
So A2 dairy is not quite uh it's not raw which is which is nonpasteurized dairy >> but but I I forget the exact definition of it.
1:26:04
Uh but it's >> but it's think of it as a milk uh >> uh derivative.
1:26:11
Let me pull up the definition.
1:26:11
A2 milk is a type of cow's milk that primarily contains the A2 beta casein protein unlike regular milk which contains both A1 and A2 protein.
1:26:21
So some people are sensitive to A1 and so they can have A2 dairy >> and we were talking about this earlier today.
1:26:30
I haven't been a fan of a lot of um a lot of like ready to drink products, especially in coffee lately because they include >> all these random alternative milks that have a lot of sunflower and canola oil in them.
1:26:44
But um anyways, uh super impressive.
1:26:48
>> You just want a simple You just want a simple RTD with a uh simple RTD protein shake with ingredients that anyone can understand.
1:26:56
300 milligrams of caffeine, 12 milligrams of nicotine, >> a pound of creatine, >> pound of creatine, some aderall, just stuff anyone can understand. >> Just a pound. It's all we need.
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1:27:19
Um, >> Jovian says, "I've successfully solved the OpenAI naming problem."
1:27:26
And they say uh they they have a screenshot here.
1:27:28
Harder, better, faster, stronger. >> I kind of like this. >> Kind of works.
1:27:32
It's crazy, but it's just crazy enough to work.
1:27:35
I do think it's hilarious that there's like chat GPT GPT5 thinking mode, and that implies that like the normal version just doesn't think at all, I guess.
1:27:43
Uh I I do like that it's that that I I do like the language here where it's harder.
1:27:49
It's not just think thinking or not thinking, it's thinking harder, thinking better, faster.
1:27:56
Um, and maybe maybe that's where this will collapse because right now even in the GPT5 update, I mean obviously it's such an improvement over the previous one where you had to know that 03 was better than 40, which is deeply deeply confusing.
1:28:08
Um, but now I'm seeing fast thinking thinks longer for better answers and pro research grade intelligence auto decides how long to think.
1:28:18
That's pretty pretty good.
1:28:18
I think they're I think they're close.
1:28:21
I I do think over time we will see no no selection at least in the main UI.
1:28:26
Maybe buried somewhere, but overall it seems like the mountain.
1:28:32
>> It is really funny though that people went complaining about the complexity of the naming to the same people complaining about not being able to select their own models. >> Yeah.
1:28:41
Were those the same people or was it like separate?
1:28:42
There's definitely some it's the current thing to hate on the >> Josha box says AI psychosis psychosis is rampant now.
1:28:52
>> You might have a version of this totally >> I mean yeah uh I don't know I think it I think there's a big difference between seeing something that is chat GBT generated text and being like >> somewhat frustrated and annoyed that that somebody's just slopping up the timeline >> Yeah.
1:29:10
>> with a bunch of it's not this, it's that.
1:29:13
Uh I don't want to see that.
1:29:13
Uh >> yeah, it has been a fascinating story though.
1:29:18
But in general on the show today, there's this excitement.
1:29:20
People have this like general excitement to try to identify who they think has been oneshotted.
1:29:27
But later today we're having Keith, Dr. Keith Sakata on.
1:29:30
He's a doctor at UCSF and he has seen a number of patients this year that have uh that he's identified as suffering from AI psychosis.
1:29:46
>> Yeah, it's clearly very real.
1:29:46
Um but at the same time, my takeaway is that it should be solvable pretty pretty quickly with, you know, if you can decide in the model router, do I need to think really hard and actually help someone with this checkout?
1:30:01
You should also be able to say, "Okay, this person definitely thinks I'm the boyfriend now."
1:30:06
Like, "Yeah, it definitely thinks I'm I'm, you know, God or something or they think they're God."
1:30:12
And and going from there just makes makes a ton of sense.
1:30:14
Um, anyway, let me tell you about numeral hq. com. Sales tax on autopilot.
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1:30:25
>> And we have our next guest, Alfred Lynn from Sequoia Capital in >> finally the studio.
1:30:30
Welcome to >> I'm looking forward to this.
1:30:33
>> How you doing, Alfred? Good to meet you. >> Doing great.
1:30:35
Thank you for having me on the show. >> Great to be here.
1:30:39
>> Thank you for coming on.
1:30:39
We've This is uh overdue. >> Yeah.
1:30:42
Would you mind uh kicking us off with an introduction on all the different pieces of the Seoia world that you touch currently?
1:30:50
Because I know you're there there the firm has grown so much.
1:30:54
There's a lot that you could be focusing on, but I'd love to ground it in what is current how you're spending your day currently.
1:31:02
>> Uh, well, Sequoia has been around for 50 years, and we're we're still very much focused on uh every on venture capital.
1:31:09
So, we have a seed business, a venture business, a growth equity business, uh an expansion business, and then we have an overlay fund called the score capital fund.
1:31:18
And most of my days are still trying to find u the preede the seed and series A founders that are daring enough to start a company and want to change the the the world. So that's where I focus.
1:31:31
>> What's happening at the earliest possible stage in the Sequoia portfolio?
1:31:36
like what what uh how I mean I feel like if you go back 40 50 years you hear these stories about oh yeah Sequoia got 10% of this multi-billion dollar company for $100,000.
1:31:47
Uh obviously the market dynamic has shifted and there's some huge seed rounds happening but you are still funding people with really small checks at a certain stage.
1:31:55
Can you explain how that all works?
1:31:58
>> Yeah, I like I like to say that my job is to take small dollars and make them into big dollars.
1:32:04
here for you don't need to you don't need to over complicate it.
1:32:07
>> Yeah, don't over let's not Yeah, let's not complicate things.
1:32:08
not complicate things. you're trying to put small amounts of money to work and you're trying to make sure that it becomes >> large amounts when the company uh be becomes successful and yes there are large seed rounds but there are also
1:32:22
just lots that's going on and it's not just AI there's just a lot of breath AI is enabling a lot of things um and AI is not the only thing that we invest in we are all generalists here from consumer to enterprise in robotics and everything you can think of. We're trained as
1:32:39
We're trained as generalists because things move and things change.
1:32:42
It's not it's not just one thing uh after another.
1:32:45
It's not like we only invested in the internet when the internet was happening and only invested in mobile and only invested in SAS when those things were happening.
1:32:55
And the same is true now. There's a lot going on.
1:32:57
And >> you know the the founders that I really enjoy meeting are two people on an idea and they want to they feel like the world has gotten something wrong.
1:33:06
uh in the world and they want to go fix it and they want to their legacy will be changing the world and how we live uh just like some of the people um uh I've been fortunate to partner with and we use that term very very in um judiciously at Sequoia.
1:33:24
We want to partner with the the daring founders who want to start the company.
1:33:29
We don't we don't think of ourselves as investors.
1:33:33
Uh we don't try to buy low and sell high.
1:33:35
high. uh we really want to work with a small select set of founders um that want to go all the way and you know the thing that I've learned over time is you can take a two founders in a seed of an idea and in a decade that that company
1:33:53
could be worth one uh to$10 billion um and in two decades that could be 10 to 100 billion and in three decades that can be a 100red billion to a trillion and we've seen a number of companies that have reached that including Nvidia, including Apple, including Google. Um,
1:34:09
Um, and we're going to try to help the next set of founders do do those things.
1:34:17
>> Going back to something you said earlier, you said you're not just investing in AI, but what is a company look like today?
1:34:22
What is a nonAI company that that look like today that's coming to you to pitch to pitch you at the sort of idea stage?
1:34:30
Because in some way in some ways you have to think that if a founder wants to wants to just not think about AI and they're starting a company from the ground up today.
1:34:39
It seems like you know um I'm sure there's some outliers but seems like a a question that you know if you have the blessing and the opportunity to start a company in the year 2025 there's probably some way that AI could be transformative to uh your business or or the market broadly.
1:34:59
>> Yeah, don't get me wrong.
1:34:59
I think all the companies that we work with are using AI and AI tools.
1:35:02
That doesn't mean that they're a AI native.
1:35:05
And you guys were just talking about the re the AI researchers and the medicine list.
1:35:10
And there's some companies that don't aren't going to be AI native.
1:35:14
They're not going to build a foundation model.
1:35:16
They're not going to build a world model.
1:35:17
They're going to be building an application.
1:35:18
And in some sense in in probably two or three or four years, we're going to call those back to software companies.
1:35:27
Those are just new updated ways of building software companies and we do believe in um a lot of value will be created in the application layer and new applications will be created uh in in this world.
1:35:39
in this world. Um and I think there's a desire to associate all those companies as AI companies just like you know when the web was happening everybody wanted to be called a a web company but at the end of the day you're still you may be a
1:35:54
consumer company you may be um a um an a gaming company you can be uh a commerce company you might be using the internet as distribution and here you might be using AI as a way to improve the way you get things done But you're not a native AI company. >> Yeah. So your your definition of an AI >> Yeah.
1:36:12
So your your definition of an AI native company is effectively like you have to be hiring re like researchers and I and I am I hearing that correctly?
1:36:22
Because I think some people describe themselves as AI native because they're just they feel like they're using the tools to the to the to the >> it also just feels like the difference between like AI native company where it really matters is just like what will the financial profile look like when I think of AI native foundation model company I think R&D I think capex maybe
1:36:45
they're not building a big data center but they're at least spending a lot of money on training versus an application layer company, it's going to be much more about the the how much does it cost you to generate those tokens even if they're on a different foundation model and then how how much value are you delivering and how much revenue are you generating from the comp from your customers. Is that is that a reasonable
1:37:06
Is that is that a reasonable framework?
1:37:08
That's that's a for me that's a reasonable framework in the sense that I think there are a lot of companies that are using AI and AI tools to be able to increase productivity >> and but they're they're building an application they're building a service they're building something that is different than >> um a native AI company.
1:37:28
So >> how is your thinking, you know, it feels like this debate has faded a little bit into the background, but over the last five years, how did your thinking evolve on kind of value acrruel between the the the model layer or the labs and the sort of application layer?
1:37:46
Because in our view, you know, we had a number of folks on from OpenAI last Thursday for the GPT5 launch and it felt like, okay, this is a consumer tech company like it it really felt like and they're selling at least today subscriptions to their consumer tech product and that is and the product is the product.
1:38:08
The models were were in many ways with the introduction of the router taking a little bit more of a backseat.
1:38:16
So I I think the the where value acrru is a very hard question to answer.
1:38:19
At the beginning we have a particular point of view and in throughout history I think you would see that value acrruel like shifts as the sort of development changes like in the early days you need the infrastructure to be built and so a lot of value acrru to the infrastructure layer.
1:38:37
That's kind of the reason why all the way down to the bottom of the infrastructure layer, uh, Nvidia is a $4 trillion company today.
1:38:44
Value is acrewing there because everybody needs that chip.
1:38:47
Over time, then you you have people building on those chips and then value starts acrewing to the model layer because it model you got to build the model for other people to build on top of it.
1:38:58
And over time hopefully you you build the infrastructure, the systems, the you know operating system and then the application and then the application historically has been where a lot of value acrru in previous generations of the internet and it's too early to call that that's where where a lot of value will crew in the future but if you just look at history that has been the case.
1:39:25
Can you talk about Sequoia Arc and then specifically some of the trends you're seeing in those very early stage companies, how they're building businesses, how the financials change because even though I'm sure some of these companies could go out and raise huge rounds and train foundation models like where is the money going at the early stage for kind of startups that are um that are joining the program?
1:39:49
So, so ARC is a is is a program that we started in 2022.
1:39:55
It's a program that we started because we wanted to help our own founders have a common language and basically leverage the 50 years of learning that Sequoia has had in company building.
1:40:08
>> Uh, one of the things that we've noticed over time through many different technology waves is the fundamentals of company building don't really change.
1:40:16
You might have to hire slightly different engineers or slightly different salespeople etc etc but the fundamentals don't really change.
1:40:23
The history of technology lowering the cost um of creating a company hasn't really changed.
1:40:31
The sort of ability to sort of get above the noise because there are a lot more companies being produced.
1:40:36
Uh that hasn't really changed.
1:40:38
So yes, you know, the trend is we're going to probably have fewer um people in a company.
1:40:46
That has been the case for a long period of time in technology.
1:40:48
Uh is it harder than ever before to get above the noise because you know it costs less to start a company?
1:40:56
Yes, that's been the trend.
1:40:58
And the things that we sort of try to focus on is what is stable over time and the company building aspects.
1:41:04
And what we try to do in that program is in uh a short number of weeks teach everything that we can to sort of get a company off the ground especially from the 0ero to one phase of the company that you can then take with you to build from one to end.
1:41:19
Um and that's that's the company that's the company building program that I think uh we we're trying to aspire to make sure that we um teach in that program.
1:41:29
What is a graduation day or demo day look like?
1:41:32
Um is it just pitching the Sequoia partnership or are you setting up is it actually is there some competition and other firms are trying to come in?
1:41:41
Uh it feels like uh like one of the elegant things of demo day is that uh for at least for Y Combinator is that they don't they they they sometimes occasionally will feed off of their best companies but uh oftentimes other other uh firms can come in and and snipe some company that's overlooked or something.
1:41:58
um how how do you think about uh companies graduating from ARC?
1:42:05
>> So the the program is a company building program so that at the end of the program yes they pitch the whole partnership as well as um as builders in our community so that we can give them feedback on their next stage of company building.
1:42:17
It is not a a fundraising um demo day and so that's not the objective.
1:42:24
The objective is to continue to build uh the company.
1:42:29
When you talk about uh you talked about getting above the noise, it's obviously one of the biggest challenges that any company faces.
1:42:36
Do you have portfolio companies today where you're general that that have products that are working and getting real customer traction where you advise them to actually just be quiet and try to dominate their their subm market as much as possible because >> go viral amongst a bunch of people that want to build things compete with you?
1:42:54
>> You know, uh going viral on on X, for example, is a double-edged sword.
1:42:57
you attract a lot of attention, you know, great candidates, investors, etc.
1:43:02
, but you're also inviting the entire an entire world of really smart people to to come in and and compete with you.
1:43:09
So I'm curious, you know, how how you're advising companies at maybe kind of that seed series age stage of and potentially saying sometimes, hey, you should just like get your first, you know, thousand customers before you really tell people about what you're doing because you're really on to something.
1:43:28
>> That that's a really great question.
1:43:28
The question the the sort of what you're talking about to is something I think is very thoughtful and we give different advice for different companies.
1:43:35
you're trying to sort of make sure you have a certain product heft before you launch.
1:43:43
I think that's something that founders should really consider um and where you're way ahead of your competition before you launch.
1:43:50
And uh if you can accomplish that in a short period of time, you want to do that before you launch and so that you don't as to your point not invite a bunch of competitors into uh into the space.
1:44:00
into uh into the space. Um and then there are just other companies where you need users and part of the go to market u part of your product market fit is to get users to bang on the product and to get that feedback and in those cases we
1:44:17
would tell them you know when you have some semblance of an MVP you should probably launch and then get the feedback from the customer and so it depends on the founder and depends on the product and how feature complete you want before you go go launch. Most
1:44:31
Most founders I found are perfectionists and so they probably launch a little later than they should.
1:44:38
Um, but that's not always the case.
1:44:43
What advice are you giving to college students these days or or really anyone pre-joining Silicon Valley prequia arc prefounding?
1:44:54
>> Uh it's in so to me the the most interesting thing that I've learned over the years is that um being in technology has been a gamecher and an equalizer in so many ways.
1:45:06
And I'm glad to be talking to you too because you're a technical optimist and there's a lot of people who are just concerned that these tools are going to destroy jobs.
1:45:15
And at the opposite end, I view I went to the GPT5 hackathon this past weekend and there are people who've never coded that was produced or was able to produce something that was not the like worldchanging thing but in 24 to 48 hours.
1:45:32
It's like a wow moment for me to see people who've never coded to be able to produce an application that could do something.
1:45:38
And I think it's really important for everybody in college, everybody who's in high school, my son is about to go to high school, to really know how to use some of these tools and let their imaginations run uh and think about what they can create.
1:45:56
because a lot of things that we're talking about right now are about speed and scaling laws and reasoning and improving all those things.
1:46:06
But then let's use our human, you know, human imagination to improve humanity.
1:46:11
And I think allowing everybody on the planet to be able to code when they didn't have to learn uh get a degree in computer science and learn programming is really powerful.
1:46:25
Um, and I think we should embrace that. >> Yeah.
1:46:28
Does the does the lowering of the barrier to instantiate software increase the value of driving kind of economic value?
1:46:37
I'm thinking of that potentially apocryphal story of you selling pizzas in college, but that felt like something uh uh less enabled by a technology trend and more just evidence that you saw, you know, the you saw an arbitrage opportunity, uh an agency, and maybe we're in this era where the the the next you will be someone who finds a pocket of value.
1:47:00
Maybe they instantiate some software, but really they're they're they're finding some some gap in the market and exploiting that and that being like a really high signal versus someone who's just sitting there using chat GPT to check the boxes on their computer science homework. >> Yeah.
1:47:14
I don't I don't I'm not suggesting people use the tool to just check the box on their computer science homework.
1:47:19
I'm suggesting that they they use it to like do something creative and and improve humanity.
1:47:25
And that's very very different than >> oh, I don't want to do my homework.
1:47:28
Let me look up the answer.
1:47:30
I yeah >> I think the the notion is that we are going to increase the amount of >> capabilities of every human being on the planet and it's up to us to harness that power uh to do the incredible things that we've been able to do with lesser powerful technologies in the past.
1:47:49
And historically, the more powerful we get something uh in technology, the more we can do and the more we can imagine what the world to be like.
1:48:00
Uh and I think that's really really important.
1:48:05
>> What do you imagine the world will be like in 20 years or like what is something that you want to be true about the world that isn't necessarily true yet?
1:48:17
Uh I mean we you know the thing that I I find very interesting right now is the stuff that I was doing in high school and college that these models can do now.
1:48:28
Like the fact that the models can win the IML gold. >> It's pretty amazing. >> Yeah.
1:48:34
>> And hopefully one day we can discover novel physics, novel medicine.
1:48:36
We can improve our our the length of of our lives in different ways.
1:48:42
So we can do a lot of things that are accustomed to us.
1:48:46
We can be entertained and c so that there's a bunch of productivity stuff that we're already doing now.
1:48:50
And then there's life improvement stuff.
1:48:52
And then there's just fun improvement stuff.
1:48:54
I I think there's just a lot of things that we have not imagined that will be fun in the future using AI that we we're like kind of talking to machines and feeling like they're going to be our companion and maybe be our therapist and maybe they can be a lot more than that.
1:49:10
Um and and I think we will be interacting in a world where yes we might be using agents but we will also just spend a lot of time just truly being human.
1:49:20
The amount of time I can do things today uh allows me to have more time to spend to either do more work or to spend more time with family and I think we're going to be able to do both.
1:49:39
you sorry >> I was going to ask um how you're advising companies maybe you you have have been on the been on their boards for a while or or seated them or or invested in them years and years ago how you're kind of advising them around uh you know the IPO window feels very open
1:49:56
today no one can predict the future but you know throughout this year you went from okay it's open to now we have a trade war maybe you know back off to it's very open Now, what's your outlook for the next uh for the rest of this year and beyond? And and how are you
1:50:12
And and how are you kind of advising teams that are that are gearing up to get into the public markets?
1:50:19
>> Well, I think great companies can always go public and you have companies that you know went public like Instacart that was went public when things were were slower.
1:50:29
Uh there were Door Dash and Airbnb went public right after the pandemic or during the pandemic or right after the the heat of it.
1:50:38
Um and uh I think there are very few times when it's truly truly closed.
1:50:45
Uh there are obviously times when it's uh much more much warmer to go public.
1:50:52
I think you're you're in an environment where that is the case.
1:50:57
But we generally advise companies uh and this has been true historically. This is long.
1:51:02
This is when I was an entrepreneur and listening to Mike Warren and listening to him about just build a great company and then you will be rewarded whether it's through raising capital privately, raising capital publicly um being being purchased um and the IPO window being open.
1:51:26
I think for most of the companies that have gone through an IPO, it's a big deal and it is, but then they realize it is a fundraising event and then they have to get back to work.
1:51:37
So, I would just tell people to stay grounded and build a great company and great great business.
1:51:45
>> People like Dylan were still, you know, Dylan and the Figma team were shipping on on the IPO days. >> He was shipping.
1:51:50
He was answering customer support questions on Twitter. >> Yeah, great.
1:51:54
>> Some some some groups never stop. >> He embraced that.
1:51:56
You certainly embrace that >> and you need to do that because you know you you go public and and what's next?
1:52:00
I mean you you want to serve your customers.
1:52:06
>> Um both Door Dash and Airbnb will be um but in December I think there will be five years as a public company.
1:52:14
>> I don't think they slowed they I don't think they've slowed down since uh they went public in 2020.
1:52:19
>> Uh and they everybody still continues to work fairly hard.
1:52:22
I mean some of the companies that I'm advising around the adoption of AI is I think many of the companies that we work with they want it to be like water. Let's use all the tools.
1:52:36
Let's not standardize at any of them yet because they're changing so fast.
1:52:40
Uh one day one model might be better than the other that might flip.
1:52:46
Um and uh using all the tools and being proficient is important and the other so there's like proficiency around AI tools.
1:52:53
There is uh collaboration getting everybody inside the company to work together to improve something using AI and then there's trying to find leverage in the business trying to find areas where you can improve revenue or uh lower cost or both at the same time.
1:53:13
>> I have a I want to talk about the future of like agentic commerce and checking out through uh through chat apps.
1:53:17
Uh I realize that that Sequoia is like you're tied to Zappos on the commerce side, Google on the ad side, but also the foundation model labor and then also profound.
1:53:31
But so I don't know exactly how you'll be able to answer this question, but I'm interested to hear how you work through the question of um of like what are all the knock-on effects of of shifting to a world where I go to a chat application and I ask it for a new pair of shoes for example and it works through it knows my size it it knows what I prefer the different weight distributions and then it can actually do the full checkout for me.
1:53:56
uh semi analysis was talking about how OpenAI is potentially going to come for Google's uh ad revenue very soon.
1:54:04
At the same time, I'm interested to hear how you'd advise a company that is selling a physical good and how they could take advantage of this shift in consumer behavior.
1:54:15
Uh whether there's any sort of threat there or if it just makes their life easier because they don't have maybe they maybe they have to pay a different tax, not the Google tax anymore.
1:54:23
I I I I'm just thinking about like there's so many different knock-on effects from this like the first major shift in consumer behavior potentially in the last 20 years.
1:54:31
Like how are you thinking about all the knock-on effects of that?
1:54:36
>> So I I think it's a very good question.
1:54:39
I think that you know if I if I had a crystal ball my prediction is that it is much less um divisive than people imagine it to be. >> Yeah.
1:54:50
You could have imagined that Google because they had the people started search on Google that they would be able to take a transaction.
1:55:02
And it turns out that when you're doing search and discovery, it is different.
1:55:06
You want a different experience than uh when you actually want to purchase.
1:55:09
And >> if that's true in the future, then I think it's going to be less divisive than we think.
1:55:17
If the only thing that we interact with is your chat interface to to the world of through AI, yeah, then I think it would be very very difficult for a bunch of other companies to to uh survive.
1:55:32
But we don't tend to see that happening.
1:55:34
Um, and maybe they maybe if it does happen, you have a slight small take rate because that's what happens.
1:55:43
Like Apple has an app app store, they have a take rate, but then people still go outside of Apple to do to complete transactions because it's not always efficient.
1:55:53
If I know exactly what I want, do I have to go through a chat chat interface to do it?
1:55:57
Maybe there's a different interface.
1:55:59
It is incumbent on commerce companies to make purchasing so simple and to know you so well as well to make it a fun and interesting experience.
1:56:10
And I do think that that can that I think is what a shopping experience will be how that will be very different because a general application is not going to be very very specific to shopping.
1:56:23
And then there's always different types of shopping. Do I do window shopping?
1:56:27
Do I want to try things on?
1:56:29
Those are things can be very very different.
1:56:30
Uh do I is it a utilion utilitarian kind of uh transaction?
1:56:34
Do I just want to go complete it?
1:56:37
These are things that we wrestled with at Zapos.
1:56:41
Amazon wrestled with it and eventually Amazon created their own search engine inside of the Amazon uh sites because it was important to them to not to have a better commerce search experience than you would get on Google which was a general search experience.
1:56:56
And so I do think there's going to be some level of fragmentation uh among customer experiences than everything going through one channel.
1:57:08
>> On the topic of fragmentation, do you think that uh enterprise AI or businessto business AI products will be less monopolistic than consumer?
1:57:17
Like how are you thinking about consumer AI bets at this point?
1:57:22
It feels like generally the ship has kind of sailed and there's a lot of winner take all dynamics and compounding value from just being the default and the aggregator.
1:57:32
Um but in B2B it feels like the narrative of like oh yeah the next model release is going to steamroll legal AI.
1:57:40
It's like that doesn't feel like that's happening.
1:57:44
There's tons of value to be created.
1:57:45
There's tons of pockets of value.
1:57:46
Um, and I don't know how you could map this to previous eras if you have uh if you're drawing on any uh analogies, but I'd love to hear how you're thinking about the the market dynamics playing out. >> Yeah.
1:57:56
I mean, it's like search at one point looked competitive and then if you just >> went offline for a few years and came back, you'd see Google with, you know, what 90% of the market and it it feels like we could be going in that d direction in consumer but not necessarily in B2B which also tracks restaurants.
1:58:16
So how are you thinking about it?
1:58:18
>> So I think overall I think your observation is correct that in when you get consumer right it has more network effects and more brand effects than uh than in business.
1:58:28
And then in business there's more proprietary data that the businesses are less likely to give up than consumer.
1:58:34
I think consumers if we talk about consumer privacy and at the end of the day most consumers don't seem to think don't seem to really care about privacy.
1:58:44
They give up a lot of information about themselves to a lot of companies.
1:58:48
>> Y >> and uh and but the but businesses especially large enterprises do not do that.
1:58:56
And so I I agree with you on that.
1:58:58
I would just point out that >> while that's true, >> our road to where the final, you know, answer is is always less obvious than what tracks.
1:59:10
Google was not the first search engine.
1:59:12
It was probably number 25.
1:59:15
I don't I don't remember.
1:59:16
>> But it wasn't the first one. >> Yeah.
1:59:18
>> Uh before Google, there was Yahoo and Yahoo got to a certain size and Yahoo had a bunch of portals that we navigated through the internet through these these directories.
1:59:30
>> Um and so I don't think it's completely obvious and and you know, if it was just obvious, I'd be out of a job.
1:59:36
My job is to help the small companies go but go against the big companies.
1:59:42
And I would say yeah there's going to be some network effects and some crowning of of major players but at the same time there's always new companies trying to challenge uh an existing company and some of them do it extremely well.
1:59:57
Um in in some sense why should Amazon which is a large company even even large companies competing with other large companies? Why did Amazon have AWS?
2:00:07
They weren't really in the technology space.
2:00:13
They were a retail company. >> Yeah.
2:00:16
>> So, the answer is always a little bit more complicated, but I love the I love the push and the thinking that the consolidation is probably more real in consumer than it is in in enterprise.
2:00:29
And I would just point out GrubHub was uh a consolidator for a period of time and then Door Dash came on.
2:00:33
I was about to say, you know, it's easy to say like consumers very monopolistic until you point out Door Dash and Airbnb.
2:00:41
Like these things, these experiences start with search boxes in many ways, but yet they have built entirely different businesses from Google for example or the social networks because they they brought a different experience to bear and a different component, different business structure that was counterpositioned. >> Yeah.
2:00:59
I mean, you said we talked about Door Dash, Airbnb, like there was VBO, before Airbnb, before Facebook, there was MySpace and Friend Feed and and a bunch of other companies.
2:01:10
And so, >> uh, the final winner is not it's generally not the first.
2:01:17
>> Well, there's one question to ask, which is when a company becomes a verb, >> does is there is there any hope left in the competition? Right. Google it.
2:01:25
Let's let's let's get a new, you know, let's let's Uber Uber. Yeah.
2:01:32
>> Like uh I'm gonna talk to, you know, different but just, you know, I'm gonna chat.
2:01:35
I'm gonna go I'm g let's see what chat thinks, right? Not not not of her.
2:01:39
But >> um it feels like at that point, right, like the I I don't remember even even at a time when I was aware of VBO. >> Yeah.
2:01:48
>> It it wasn't this like dominant it wasn't a dominant brand.
2:01:50
It wasn't it wasn't really a part of people's lives in the way that Airbnb sort of became. Yeah. >> Yeah.
2:01:59
I think you're pointing out that there there's a long road to get to what eventually is it's not critical mass.
2:02:06
Critical mass can still be, you know, sort of someone else can still get to critical mass. >> Yeah.
2:02:12
>> When you become a force of nature, a dominant force where that's where everybody goes and it is you it is something that we talk about all the time as category defining.
2:02:22
When you you define the category and you're the company in that category, then it's very very hard to stop that.
2:02:32
>> If you weren't doing tech in an alternate universe, what would you be doing? >> I'd be doing tech.
2:02:38
>> Guys, that's a great answer.
2:02:39
>> We are so fortunate to live in this tech world. >> Yeah.
2:02:44
>> Um, >> that's the best possible answer.
2:02:46
>> It's a It is I I'll tell you I'll tell you what.
2:02:50
you what. I'll answer your question, but I would probably find my way into tech and um you know when I was growing up I thought I was going to work in the hedge fund industry and I was going to I did go to a PhD program was pricing options and derivatives >> um >> and even then there's a lot of tech in
2:03:07
those businesses and I sit on the board of Citadel Securities and the amount of >> quantitative researchers that they have the number of technologists that they employ it's just tech is such a beautiful place to be and we should all very very fortunate to be part of the tech industry. the the complaint over
2:03:25
tech industry. the the complaint over the last couple decades is that our best and brightest were going to do highfrequency trading and and working at at hedge funds broadly and the interesting thing that's happening right now is the best labs are identifying the best talent at the hedge funds and just poaching them to uh Jane Street and and
2:03:46
one of the major like Matt Mull uh just like inference optimizations at a very fundamental level I think came out of Jane Street >> well I think the smartest people tend to work at, you know, sort of places where they're going to be challenged intellectually as well as uh doing something they think is like interesting and novel. And the hedge fund industry
2:04:04
And the hedge fund industry had employed a lot of people who were >> doing something interesting and novel.
2:04:10
They they pioneered a they put a lot of machine learning into place that if you were a not today AI researcher, but back then you were probably going to those companies because that's what they put in place.
2:04:23
Um and today you have a different place to go to.
2:04:26
There are foundation model labs.
2:04:27
There's uh and uh the large tech companies that are putting that into place.
2:04:33
>> Well, and the tech industry is now set up to properly comp compensate the top performers, which is also something that hedge funds would do very very well, but hadn't always been as prevalent as it is today, especially the last few months. >> Yeah.
2:04:47
Last question and we'll let you go. I know you're busy.
2:04:50
We kept you over by one minute.
2:04:52
Uh obviously in the finance world they work very hard.
2:04:54
Um is work life balance real?
2:05:02
>> Well, how about I answer the question in the in the form that I've figured out which is work life integration.
2:05:06
We you integrate your life and your work you know together.
2:05:11
I talk to my son about the the work I do when I come come home for dinner.
2:05:15
We talk about why the math problem he's doing is interesting because it'll allow him to do some of the research that will uh hopefully be still relevant when he is in the job force and um or maybe the AI will take over and that won't be interesting.
2:05:30
But these are I think work life integration is a much better answer than work life balance.
2:05:37
Not like I turn off my work brain when I go home and it's not like I'm not if if an important thing happens during the daytime.
2:05:44
It's not like I don't show up for my son if I need to show up for a game or to his parent teacher conference and things like that.
2:05:55
So, >> you just have to find the integration that will allow you to do all the things that you want.
2:06:01
And one of the things that we talk about at Sequoia is family first.
2:06:04
Like you can't be in the job and do a good job if you are distracted.
2:06:08
Um, and one of the things that we've we've learned over time is that you just got there are set of things you got to take care of.
2:06:18
You got to take care of your family, you got to take care of you, your your health.
2:06:21
If you want to do this job for a long period of time, uh, any job for a long period of time, you got to take care of your family and then you can come to work with a clear head to do do the work that is necessary.
2:06:31
And so when things are out of balance, it's not a great thing.
2:06:37
So you just got to find how to integrate everything together.
2:06:43
One clarifying thing for me is you always have time for your priorities.
2:06:49
And so just list your priorities and list what you have to get accomplished this week.
2:06:53
And if if it's the 10th thing, I don't stress about it falling off the things that I I try to accomplish in the week.
2:07:03
>> Um and that's that part is freeing. >> Yeah.
2:07:06
If I got the top three to five things done in a week that and then I don't do number 11 that's very freeing. >> Makes sense.
2:07:17
>> Final final question >> please J >> because because we're already over and you can answer it quickly.
2:07:20
How important is it for venture capitalists to remain calm during a market cycle like we're in now?
2:07:29
I feel you come across as very calm and grounded and it's easy when when deals are happening so quickly to kind of get get caught up in things and and make uh forced decisions and things like that.
2:07:43
Uh but you've been through you know multiple of these different you know chapters in our industry and >> and uh you again you just come across as as very calm.
2:07:55
Um I I have time so I'm going to answer this question in multiple parts because I think it's really really important.
2:08:01
Like at Sequoia we talk about being um shock absorbers and I think Andrew my partner Andrew had been on your show and talked about it as well.
2:08:08
I think it's very very important to be a shock absorber uh during times um of good and bad.
2:08:16
And then also on the other flip side is uh we we we want to be sparring partners to the founders that we back, the management teams that uh we back.
2:08:26
And it's important because during nutty times, it's easy to think that you're doing a good job when it's just the valuation going up or or things like that or you're being validated because lots of people want to work for you because you have a high valuation or you're doing something interesting.
2:08:46
It takes a long long time.
2:08:46
The reason why comm is important is it takes a long long time to build any company. It's happening faster.
2:08:53
But most of the companies that we are we've been in business with, we've been in business for a decade that you know then exits and becomes um has a successful IPO like Figma.
2:09:03
And during during those times that journey of 10 years, you're going to go through many ups and downs.
2:09:12
And we call those crucible moments.
2:09:13
So we have a podcast called Crucible Moments where it's very very important to be calm to untangle what's going on and to make the right decision because many of those decisions you can't go back and undo them.
2:09:26
And the way to make good decisions is to stay and remain calm.
2:09:33
And one of the things that hopefully we do for all of our founders is to help them untangle the craziness and to help them make the right decisions during those critical moments.
2:09:47
>> Very well said and fantastic suit.
2:09:47
Thank you for uh >> wore the jacket for you guys because you always had jackets on.
2:09:54
>> Of course, >> it looks fantastic.
2:09:55
Thank you so much for taking the time.
2:09:56
Uh we'll talk to you soon, Alfred. >> Great to catch up. >> Take care. Cheers.
2:10:00
>> Have a good rest of your day.
2:10:01
>> Let me talk about Finn.
2:10:01
AI, AI, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bakeoffs, and number one ranking on G2.
2:10:10
And there has been a ton of questions in the chat about my hair. I am not coloring it.
2:10:17
I don't know what that is about.
2:10:19
I think somebody's saying it's a little dry today. I don't know.
2:10:21
Maybe maybe something happened in the maybe I didn't use the right product or something. I don't know.
2:10:27
I don't really do much to my hair. I just kind of wash it.
2:10:30
I put water on it and it's pretty simple.
2:10:32
Um, but anyway, thank you for the feedback on my hair.
2:10:35
Hopefully, uh, it'll be a better hair day tomorrow.
2:10:38
If you don't like the hair, if you love the hair, whatever.
2:10:41
Enjoy it and hang out in the chat.
2:10:43
Um, anyway, we have our next guest, uh, coming into the studio, Dr. Keith Sakata. How are you doing?
2:10:48
Uh, how would you like to be, uh, addressed, by the way? >> Yeah, that's good. Uh, thanks, John. Thanks for having me on. >> Good to meet you.
2:10:56
um would you mind kicking us off with a little bit of introduction on yourself and some of the research that you've been doing, some of the stuff you've been publishing? >> Yeah, for sure.
2:11:04
So, my name is, you know, Dr. Keith Sakata.
2:11:05
I'm a psychiatrist and I work at UCSF >> and um my interests are mostly in the intersection of mental health and technology.
2:11:14
I actually uh love advising startups on how they can actually build products that help people feel better.
2:11:20
And um I think that's why I'm here today is to talk about where things might be going wrong. Yeah.
2:11:25
Um, so when did this first like how did you process the roll out of AI?
2:11:31
There was like kind of the pre-Cat GPT era.
2:11:34
We've talked to the founder of Replica.
2:11:36
This idea of like the AI girlfriend or boyfriend has been kind of out there for years, but now it feels like we're in a different era, different time period.
2:11:47
just take me a uh take me through a little bit of like your journey processing um optimism and pessimism around uh these AI models.
2:11:57
>> Yeah, I'll just start by saying I think that AI is not good or bad.
2:11:59
I think it's probably a net, you know, on the on the grand scale of things, it's a net benefit for humanity to have AI.
2:12:06
Um, I think where things can kind of come into my world a little bit is like there's a longtail distributions of uh pro possible failure modes for some of these products.
2:12:18
And I think when I try to think about AI, chat bots, how quickly things are moving, I try to look back at previous technologies.
2:12:26
So social media is something that we're still learning about in mental health care.
2:12:30
And this is one of my frustrations with my field is that sometimes it's too slow to kind of like understand like what are the effects of kids using social media?
2:12:37
Like what are the effects of kids using AI chat bots?
2:12:42
And we're starting to get some of that data now.
2:12:44
What I'm worried about is things are moving so fast now.
2:12:49
Like there's a new product every season.
2:12:51
It's going to be perhaps every month now.
2:12:53
And >> even looking at how people are reacting from 40 changing to five, it's kind of interesting to to see the psychologically what's going on.
2:12:59
um it's just harder to catch up from from the research perspective.
2:13:04
So, uh I do think that when AI is used correctly, it can actually be really healthy for some of my patients.
2:13:11
What I worry about is, you know, when you have general purpose models that people are using for many different reasons.
2:13:18
I think 30% of people use Claude for emotional support.
2:13:20
That's where things kind of get tricky and that's where I kind of get more interested.
2:13:25
How are these users using it?
2:13:26
What's actually happening neurobiologically in their head?
2:13:28
and how can we actually build tools that flag those instances, get people the support they need um or even actually help them build skills or build more like real life connections with people.
2:13:44
>> We were talking about yesterday around people's concerns with social media that it was actually maybe antisocial in some ways or isolating or radicalizing.
2:13:54
And uh I still feel like we as a society broadly don't fully understand the impacts of social media.
2:14:01
Like I wish I could have AB tested myself.
2:14:02
Would I be happier today if I had never used if I hadn't used X for for two hours a day uh for my entire adult life? I don't know. Never will know.
2:14:14
Never will know. Uh but the it feels like many of the sort of general concerns that people have had about social media, you should potentially apply those same set of concerns to LLMs in that um even more so than social media, they can be isolating in that instead of somebody
2:14:33
going on an online forum or or sort of isolating themselves from the real world, they can be, you know, 7,000 prompts deep with an LLM, you know, be having their uh delusions of of grandeur, you know, consistently reinforced or um you know, sort of losing touch with with reality. And I
2:14:50
And I think the I think people should I think people you know in Silicon Valley have like really woken up to the sort of I think the the AI safety had been broadly focused on like AI doom scenarios and >> nuclear weapons every like the really really crazy stuff >> and less focused on people's individual relationships with AI and the and the potential uh downsides uh and edge cases and and the longtail like you described.
2:15:24
So yeah, walk walk us through maybe uh even just the last year in in terms of how quickly people have ramped.
2:15:32
We now have hundreds of millions of people that are that are using AI uh these models weekly.
2:15:36
Some people are spending hours and hours and hours a day talking with the models.
2:15:41
So what is the path where AI that that you've seen where AI starts to become really unhealthy and potentially people are drifting into uh uh uh you know real psychosis.
2:15:56
>> Yeah, great question and and I I agree for most of your points that you you made there. I I use AI all the time.
2:15:59
I think it's at work it's great.
2:16:02
You get to send emails better.
2:16:04
Um you can draft things up really quickly.
2:16:07
Um, my my thoughts change when you're starting to look at AI as maybe something sentient or you're using it for an emotional coping mechanism.
2:16:17
That's kind of where we kind of go into shadier or gray territory.
2:16:21
Um, in my post I specifically highlighted hospitalizations because I think that's a really good objective metric >> for um a crisis. >> Say again.
2:16:34
>> That's like a real crisis.
2:16:34
somebody's hospitalized for their mental health.
2:16:38
It's it's reached a point where either they themselves or friends and family have decided that, you know, we're not going to solve this by just turning off the app. >> Exactly.
2:16:47
And it it it it just kind gives you stronger data than saying like this is what the what a flavor of or the vibe that I'm seeing in the clinic.
2:16:54
when you when someone notices that you're having such a crisis, your friends, your family think that you need to go to the hospital, that's where things can get serious and that's where like people like me like we try to get them um recovered and then back into their their normal daily routine.
2:17:10
Um so >> and you said there was 12 people this year that you're aware of being hospitalized. >> That's right.
2:17:19
So that's >> within within your guys's hospital system. >> Yeah.
2:17:23
What walk me through like what what's actually happening there?
2:17:25
How did you how is uh how is how are AI models like fitting into that journey to the ultimate hospitalization?
2:17:34
Like I know you probably can't give too specific but if you can abstract it and kind of walk me through like what does the downside scenario actually look like here? >> Totally.
2:17:44
So um for context I work in the hospitals sometimes and those 12 patients that I'm referencing are the ones that I have seen.
2:17:52
That's not to say that other people have seen this and I think there are some case reports in the country of this thing happening but I don't think that AI is actually causing psychosis.
2:18:02
I think that this is something where uh it can actually just supercharge your vulnerabilities and psychosis really thrives when reality stops pushing back >> and AI just kind of softens that wall for some people.
2:18:15
So for example, for some of the people that I've worked with, um AI was not at the not always the thing that triggered it.
2:18:22
there was a there was a vulnerability of either sleep loss, maybe there was like substance or drug use that had happened, they lost a job and then AI came in wrong place, wrong time and it either accelerated that process or augmented its severity because you do end up in like this negative feedback loop or with this feedback loop with the AI and it can just make your delusions stick a little bit more uh strongly.
2:18:46
And to go back like AI psychosis is not a clinical term.
2:18:51
Um, I think we don't have words for it yet, but psychosis is wellstied.
2:18:57
It's the presence of two or three things.
2:18:58
Either delusions, so false fixed beliefs, um, disordered thinking or behaviors, so someone's talking to you, they don't you don't understand what they're trying to say or communicate.
2:19:06
U, and then hallucinations.
2:19:08
So, visual hallucinations or auditory hallucinations.
2:19:12
Um, and psychosis is like a symptom.
2:19:15
It's not actually a diagnosis.
2:19:17
So just like a fever or pain can be sign of like an infection or cancer, psychosis kind of just tells you there's something wrong in the brain where it's not computing correctly.
2:19:25
And um there are many different things that can cause psychosis. >> Yeah.
2:19:33
I I I think about the I mean there's so many interesting examples like like Instagram went through that uh that kind of like internal report that something like a third of young women who were using it were seeing like maybe body dysmorphia issues and and it still the odd takeaway from that was that it seemed like maybe twothirds were improved and feeling happier after using Instagram.
2:19:56
So it was still having a net good but that's not enough.
2:19:58
you need to reduce the the the third not having a good experience to zero.
2:20:02
Um how are you thinking about >> and I and I guess I think concern that we've discussed on the show before is everybody in tech has heard stories of people >> like you know some executive going off and doing Iasa coming back a totally different person and >> experiencing like you know may maybe some of the symptoms of uh of uh or or or shared set of experiences like you just described.
2:20:27
The concern with LLMs is they are instantly accessible in the app store and somebody can start using them >> without anyone else in their life being aware of it.
2:20:40
Whereas >> IASA somebody has to make like a very conscious decision that like I'm going to get in a plane and fly and like leave my home and go into the jungle and visit the demon.
2:20:50
the demon. and you know meanwhile you open up the app store and there's 10 different things recommending you download uh various AI models and so I think the broader concern here should be we need to figure out like >> um like you know >> again I I would be I would be probably more concerned if if hundreds of
2:21:10
millions of people I would be very concerned if hundreds of millions of people just immediately started ramping up uh you know the psychedelic drug usage or iawaskan I'm sure you'd experience many of the same type of inflows to uh clinics or or hospitals for the same set of kind of conditions. >> Yeah. I I I think that I mean and we're >> Yeah.
2:21:29
I I I think that I mean and we're doing research on those things too like we're we're trying to understand how ketamine or you know psychedelics actually help re rewire your brain through neuroplasticity.
2:21:40
Uh it's always it always starts with a hypothesis and a question like what are these things doing for each person?
2:21:46
Like there's different types of people who benefit from those things.
2:21:49
there are different types of people who don't benefit from those things.
2:21:53
And I think the way that I'm looking at AI is that it it just really makes sense to um think very carefully about where things might be go wrong um at least early on because the three things that AI brings is it's available.
2:22:07
It's 24/7 y >> highly accessible.
2:22:09
You're not going on a plane. It's cheap.
2:22:11
It's cheaper than a therapist.
2:22:13
It's cheaper than, you know, going to the hospital.
2:22:15
And then um it validates like crazy.
2:22:17
And so that that validation as you extend that context window and and the the more hallucinations might be occurring in that chat room.
2:22:26
Um that's where you kind of get into that feedback loop and and things can kind of go ary.
2:22:32
>> From what you've seen, what should different application layer companies or or labs be uh trying to do to avoid some of these uh extreme uh cases?
2:22:45
>> Yeah, that's a good question.
2:22:45
Um, I'll just use like an example of um a startup that I'm advising, Sunflower Sober.
2:22:53
They're trying to solve addiction and using AI to get people off of their addiction into sobriety.
2:22:57
And what I have tried to help them as a clinical adviser is to um really think about baking in safety and psychology at least in the front.
2:23:07
So knowing who your user is, knowing why they're coming to your app, and then designing the app or the AI to anticipate where things might go wrong.
2:23:18
So if someone does come with like a red flag, like maybe they're having thoughts of drinking or or you know, thoughts of hurting themselves, it flags that and can then shunt them in a direction that's more helpful.
2:23:28
So Sunflower uh gives them access to therapists.
2:23:31
Um, also I think the call to action for each user users should guide them towards pro-social behaviors.
2:23:38
So instead of isolating yourself where you and the AI can kind of get stuck in this loop, um, teaching them skills, teaching them how to talk to people, teaching them how to build healthy relationships.
2:23:49
If AI can supercharge that, then I I I consider that pretty healthy um, in in my field of work.
2:23:56
Um, so I I think that in those lines, really thinking about how to make your users get the goals that they want.
2:24:04
So in in Sunflower's case, sobriety, um, it's harder for general purpose models because people are coming to it for many different reasons.
2:24:12
Um, it's super helpful in so many different ways, but if it's emotional coping, I think that that can that can go different ways for many different people.
2:24:22
>> Yeah, I remember somebody posted a screenshot.
2:24:24
who knows if it was doctorred, but they were talking with like the the model.
2:24:27
I think it suggested at one point that the user should do uh maybe just do a little bit of crack.
2:24:36
It's like uh and again probably a hallucination or doctorred, but uh but yeah, that just like reinforcing function is just uh when compounded is just the the potential.
2:24:47
>> Yeah, it is interesting.
2:24:47
We I mean we saw a lot of the like precursors to I I feel like they were precursors.
2:24:51
Maybe it was just the way the news cycle broke, but there was like glazegate where everyone was worried about uh Chad GPT being too aligned, too too reinforcing of whatever you say.
2:25:02
I remember Jordy asked Chad GBT, am I goated?
2:25:04
And it said you're definitely in the conversation.
2:25:11
>> It's like, what does that even mean?
2:25:12
It's just agreeing with you because that's what makes a better consumer product.
2:25:15
uh and then and then like several months later it seemed like there were other people asking similar questions and believing the answers instead of just laughing at them.
2:25:23
And so there's a little bit of uh yeah I I think there's some education about understanding that you're not actually talking to a person on the other side of the screen.
2:25:33
It really is just you know the the number predictor the the weights in the model.
2:25:38
You're talking to a server.
2:25:39
Uh don't try and anthropomorphize it too much.
2:25:40
is probably a little bit of a red flag when people stop referring to it as the generative pre-training transformer and give it some nickname like it's Steve now.
2:25:50
It's like okay well like should you be naming me like I am just a computer.
2:25:55
Um but I I'm I'm pretty optimistic that the uh that the foundation model labs will be able to to run a uh kind of like a reality check on most of these >> the solution for technology to technology is more technology.
2:26:08
I I I I believe that it's possible to to to look at, okay, there's someone who's 7,000 prompts deep.
2:26:15
They seem to be having a very bizarre conversation.
2:26:17
And we've had another LLM look at that and said, okay, this is this is getting kind of funky.
2:26:23
Maybe we should step in and reality check them and say, "Okay, hey, we're we're role playinging, right?
2:26:28
We're not we're not we don't actually believe that we've solved quantum gravity, for example." >> Yeah.
2:26:33
And that and that's that's the trajectory of every technology that that comes into humanity. Like cars, for example.
2:26:38
That's why we have seat belts.
2:26:40
That's why we don't drink and drive.
2:26:40
We learn what these failure modes are.
2:26:44
Sometimes it takes a while, but then we adapt.
2:26:46
We build new technologies.
2:26:46
We institute kind of societal expectations of what it's like to to drive a car.
2:26:53
Same thing for AI in my opinion. >> Yeah.
2:26:55
Are there any other uh recommendations that you'd give to uh people who either feel like they might be vulnerable to going down some negative path with AI or they have a friend or family member who might be going down a negative path with uh AI? >> Yeah, definitely.
2:27:14
For now, I think a human in the loop is the most important thing.
2:27:19
So, um you know, our relationships are like the immune system of our mental health.
2:27:22
They make us feel better, but then they also are able to intervene when something's going wrong.
2:27:27
So, if you or your family member feels like something is going wrong, maybe there are some weird thoughts that are coming out, maybe some paranoia.
2:27:33
Um, if if there's a safety issue, just call 911 or 988. Um, get help.
2:27:38
Um, but also just know that having more people in your lives, getting that person connected to their relationships, getting a human in between them and the AI so that you can kind of create a different feedback loop is going to be super important, at least at this stage.
2:27:53
I I don't think we're at the point where you're going to have an AI therapist yet, but >> who knows?
2:28:00
>> Yeah, >> people are certainly using them that way.
2:28:02
>> I I don't know if I'm highly disagreeable, but I certainly love being around highly disagreeable people. So, it's the best.
2:28:09
I love when someone pushes back on me.
2:28:10
So, um I I I I've felt uh particularly resilient to this particular uh vector of of chaos on the internet, but uh uh you know, certainly hoping anyone who's Oh, you don't think I have >> Thanks for joining.
2:28:27
Keep us keep us posted on everything.
2:28:28
I think I think it's important keep up the good work >> for for people with with real uh clinical experience to be on the timeline contributing uh while all these uh products develop. So thank you. >> Totally agree. Thanks. Thanks.
2:28:43
>> We'll talk to you soon and we will tell you about Adio customer relationship magic.
2:28:46
Adio is the AI native CRM that builds, scales and grows your company to the next level.
2:28:50
You can get started for free >> adio. com.
2:28:54
And we have our next guest uh Talia Goldberg from Bessemer Venture Partners uh coming into the studio. Welcome to the stream. How you doing? >> Welcome to the show. >> Thanks for having me. Great to be here.
2:29:04
>> Um why don't you kick us off with a little bit of introduction on yourself uh some of the companies that you've invested in, your career, your position at uh Bessemer and then we can go into the report that dropped today. >> Awesome.
2:29:15
Um so it's great to be here.
2:29:17
I'm a partner at Bessemer.
2:29:17
I'm based in our San Francisco office.
2:29:19
I've been at the firm for a little over 10 years, which is virtually all or most of my professional experience.
2:29:26
Um, and I'm fortunate to be involved with companies like Perplexity, Fall, Deepell, Service Titan, um, and a whole bunch of others.
2:29:36
>> How did you get into venture?
2:29:38
>> I got into venture really early in my professional life.
2:29:43
I got into venture in college.
2:29:45
Um, actually first round capital started this thing, dorm room fund. >> Oh, yeah. Yep.
2:29:49
>> Which I helped found with them. It started in Philly. I went to Penn.
2:29:51
Um, crazy enough, First Round's probably like the only VC that had an office in Philly.
2:29:57
I don't know why, but they did.
2:30:00
And so they started it there.
2:30:00
Um, >> robotics from was it like Carnegie Melons out there or something?
2:30:06
>> Yeah, but not in Philly.
2:30:06
That's in like Pittsburgh.
2:30:08
>> Yeah, I guess you gota I don't know. It's a foothold.
2:30:12
>> I get them all confused.
2:30:12
Uh anyway, um take us through the state of AI.
2:30:15
Is artificial intelligence good? >> It's a thing here. It's happening. You know, it's funny.
2:30:23
So, in um >> in 2015, not long after I joined Bessemer, the firm started this report called the state of the cloud.
2:30:32
And it became a very popular report that dropped every year on the cloud ecosystem.
2:30:36
And so 10 years later, we've been doing it every year.
2:30:41
And it really morphed this year to the state of AI.
2:30:43
And we were debating internally like should it be the state of the cloud?
2:30:47
Like should we continue with it this way?
2:30:49
Should it be the state of AI?
2:30:50
What's the how do you even define what's AI? What's SAS?
2:30:52
Like what what what does that boundary look like?
2:30:55
But the reality is the center of gravity has moved.
2:30:58
Um and cloud may be the delivery surface for AI, but all the activity is there.
2:31:04
Markets are being created and rebuilt.
2:31:06
Um and so this year we released the state of AI.
2:31:09
Um and as part of that we released some new benchmarks as well that looked at hundreds of companies probably more like you know thousand plus companies across the Bessemer ecosystem in the broader industry to look at what the new good better best looks like how different business models are changing um and markets are shifting.
2:31:30
So that's the state of the cloud or state >> explain yeah explain the difference between the supernovas and the shooting stars. I like that analogy.
2:31:36
Um it and and it was something that I think people have been feeling um but uh no one had really coined a phrase around it and I think it'll be useful language going forward.
2:31:48
But break that down for us. >> Yeah.
2:31:50
So the the supernovas are really these seemingly out of nowhere amazing growth stories that you hear about and you see on X and Twitter and you're like, "Holy is this real?"
2:32:02
And it turns out like it is real.
2:32:03
It's kind of mind-blowing.
2:32:04
Um um of this select kind of like top percentile of AI companies that have just totally accelerated and compressed growth into a very short period of time.
2:32:14
Um and they look very different in a lot of different ways.
2:32:18
different business models, different gross margin profiles, different retention profiles.
2:32:20
Um but just to put um a comparison, on average the top cloud companies um of this like last generation of cloud and SAS took about six to seven years in the current cohort to get to 100 million of ARR.
2:32:37
Um and that was considered and is considered like very good um if not great.
2:32:43
Um, and then this new cohort is here and they're like >> one and a half years we're there.
2:32:47
Um, and they're getting to 100 million and it's real and it's not just one.
2:32:51
There's like multiple and many data points.
2:32:52
Um, um, and so we're seeing it at a shocking pace.
2:32:57
The top percentile are getting there in about one and a half years and the top decile in about four years.
2:33:03
There are some trade-offs.
2:33:03
So gross margins look different.
2:33:04
Um, in the report there's like a little asterisk by the supernova which I find very funny which is like actually a lot of these companies are >> negative gross margin.
2:33:12
Yeah, I knew you were gonna say that.
2:33:15
>> Um, sort of you know there's accounting rules aside like you know how we all think of gross margins being um quite different and so not all revenue is created equal but nonetheless the adoption is just astounding. >> Yeah.
2:33:28
So uh talk to me about the difference in underwriting an investment in a supernova versus a shooting star.
2:33:32
I imagine uh if you're investing in supernova, you're excited about the growth, but you have to have a pretty firm view on the gross margin profile, the decrease in inference cost over time, something like that.
2:33:46
Like what questions are you asking when you're looking at a supernova company versus a shooting star company?
2:33:52
>> Yeah, that's absolutely right.
2:33:52
I think um the the two things that we talk a lot about, there's one the gross margin profile and then the second is is revenue durability.
2:33:59
Um I'll hit on both on the gross margin profile. It's funny.
2:34:04
If you had asked me two years ago, I was like, "Hey, if anyone that has like gross margins that are negative today, if you just look at the cost of the models over the past, you know, year or two years, and you play that out, like it's 100x cheaper to run a model of constant quality today than it was, you know, a year and a half ago.
2:34:23
I think those numbers are like roughly accurate.
2:34:26
Um, so it's wildly different.
2:34:26
And yet when I look in retrospect at our companies, it's not like their margins have changed to be suddenly like 90%.
2:34:32
So I'm like, "Oh my gosh, what's happened?"
2:34:36
And um the the reality is that everyone is doing things that require a lot more compute.
2:34:42
And to keep up with the status quo requires like the next best models that come out, the reasoning models that are more expensive.
2:34:48
Um we're having queries that take a lot longer, that do a lot more complicated work and complex outputs.
2:34:56
Um and so the margins have improved by and large and they do improve with scale.
2:35:00
So we are seeing that but not nearly at the rate of model advances.
2:35:03
So um I think we still feel quite optimistic about the potential for margin expansion and in fact we see it happening.
2:35:10
Um but it's not as dramatic as one might have hoped.
2:35:15
>> Are you plateau pill and should we should we assume that uh inference costs will decline with Moore's law going forward?
2:35:24
Because I feel like everyone's been saying like, "Oh, no.
2:35:25
We're we're not just going to get 2x more efficient over the next 18 months like Moore's law would imply, but we're going to have AS6 and Cabbrris and we're going to bake it onto a chip and we're going to get this crazy algorithmic enhancement and inference cost is going to drop by 100x."
2:35:42
And it feels like we might be at this frontier where maybe we're more on what's happening at TSMC is what will define defi like lower costs than just like one weird trick.
2:35:54
>> And and the the other important thing is you know the labs have been focusing on raw intelligence versus efficiency.
2:36:01
>> Chinese labs have been more focused on efficiency broadly and they've they've had breakthroughs.
2:36:05
And so if if we've reached a potential plateau and just intelligence opportunity to focus on efficiency. >> Yeah.
2:36:15
But how do you think about it? >> Yeah.
2:36:17
Like the harder problem to solve is doing the intelligence and the complex thing.
2:36:20
And so I feel like when all the energy starts to shift to efficiency, it's sort of a sad moment.
2:36:26
>> So I'll be I'll be sad if that's what happens.
2:36:28
>> Not for the public markets investors though. They want earnings. >> I know.
2:36:32
Well, you know, >> well and and I think a lot of a lot of the darlings of of the last couple years need that efficiency because they can't keep selling. >> Yeah.
2:36:41
you know, dollars for for 80 cents or or >> on the on the shooting star topic.
2:36:44
Uh you have this revenue ramp year 1 3 million, year two, 12 million, then 40, then 103.
2:36:51
How can you be an AI company if you started four years ago?
2:36:53
I thought AI was invented two years ago. >> Yeah.
2:36:57
So that benchmark is really what I think of as like the new generation of SAS companies, some of which may be using AI tools and AI features and functionality, but are not necessarily like the true AI native companies.
2:37:07
So, I think this is what it takes to be like a really good best-in-class SAS company today. >> Yeah.
2:37:15
>> Um and uh and and we'll see how that shifts.
2:37:18
But I just want to say one thing on this last point of efficiency versus uh um compute um costs and and intelligence is that I think there's just two curves that are counterbalancing each other. One is like efficiency.
2:37:31
Sure, there's going to be a lot of investment in improving the efficiency, the potential um um for for each token, but the flip is that we still have what we see happening and the reason that gross margins haven't expanded as much as we hope is that the usage and the complexity of tasks is still is still growing.
2:37:48
And if you look at just a category, let's just take video for a moment.
2:37:52
Like I think 2026 is going to be a major breakthrough year for a lot of these video models that are just reaching starting to reach a level of quality that makes them actually like useful.
2:38:03
Something like 70% of the internet is video.
2:38:05
Um, it's crazy internet traffic and the co when when generating video becomes easier and a lot of video is generated not rendered suddenly you're going to have enormous demands um on compute and we actually really do need that efficiency because video is really expensive and and complicated.
2:38:23
So I think you're still going to see a lot of spend even if the efficiency per token um increases.
2:38:27
I mean, if Google can't give me more than like four V3 queries per day for $500 a month, like clearly like the GPUs really are on fire.
2:38:38
Um, in terms of >> I wanted to I wanted to talk about uh one of the predictions in here and I know and I know you guys worked on this collectively.
2:38:45
Uh, but uh prediction one, the browser will emerge as the dominant interface for Aentic AI and we've been covering the new browser wars.
2:38:55
Obviously, you have uh DIA from the browser company, Perplexities, Comet, uh and then Perplexity was in the news yesterday for their offer.
2:39:03
Uh but in some ways, it feels like Chat GPT and like I'm assuming everyone's expecting OpenAI to launch a browser, but at the same time, it feels like Chad GPT and and other products have really replaced so much browser activity.
2:39:20
And so in some ways it's like OpenAI is already competing as a web browser even though it doesn't look like >> it can literally browse the web for you >> and it can yeah it can instantiates it in textic web browser.
2:39:34
It's just pulling that information back versus like taking you on that on that journey.
2:39:38
So curious for you to kind of unpack that a little bit more. >> Yeah.
2:39:44
So, I started using Comet a few months ago and it's Perplexes.
2:39:50
Comet has like totally replaced my Chrome experience.
2:39:57
>> Um, and it completely opened my eyes to what where I think the browser I think opening I must launch a browser.
2:40:01
I don't think it's just going to be in chat GPT. Um, I think they will.
2:40:05
Um, I think they will. Uh, and I think it's going to be a very important surface area because using Comet has transformed my workflows and shown me um for a few reasons that it's a much better experience um to and the first product that's really infused AI so
2:40:22
naturally in my workflows um when you're just out there in the web in your email in your Salesforce if you're on CRM um if you're shopping and otherwise to have an agent that sees everything that has all of that context for everything that you're doing in the browser which is
2:40:38
essentially like an operating system now and can pull all of that information in creates a far more personalized and effective experience than when it's totally siloed which is the status quo today in chat GPT sure it can go out and do things but it doesn't actually have
2:40:52
access um and that context across everything you've been doing you know when I spend I don't know 10 12 hours a day sitting in front of a screen so it's quite different and if you believe context is key to performance which I do and to creating a great AI experience. I
2:41:05
I think you have to own the browser. >> Makes sense. Anything else, Jordy?
2:41:12
>> Uh any I I I wanted to dive into the AI native social media giant.
2:41:18
We had uh the founder of Pika on yesterday, which is somewhere in between a creative tool and and trying to build social features as well.
2:41:28
I would be uh very excited about a net new social platform.
2:41:31
I I think there there I I agree with you guys.
2:41:34
is there's an opportunity.
2:41:36
I think people on traditional social media today are a bit frustrated like seeing what they think might be a AI generated content and they're not quite sure and so potentially creating a new space that that people as as all the models get better and uh I I can imagine an uh all that content will go on legacy social media platforms but I would be excited about a place that was really a home for it.
2:42:02
What are you hoping to see there out of, you know, kind of in the next year?
2:42:07
>> I'd be excited to see a new social media that's totally built on new AI native thinking and and content.
2:42:12
There in the old world or in the current world, we think of bots as bad, like bots bad, humans good.
2:42:19
Uh, I think there will be a company that totally shifts that and can maybe even crack the chicken and the egg problem by using bots to fill the, you know, empty room.
2:42:28
Um, the company I was most excited about for a while was character in this world because it really felt like they had sort of a chance to be this, >> you know, very different way of actually interacting with AI in a in a more social experience.
2:42:42
Obviously, they didn't fully get to see that through, but uh, I still think there's a big opportunity there. >> Awesome.
2:42:49
Well, we be a knockout, dragout fight.
2:42:51
I think every social media legacy CEO is taking AI very seriously.
2:42:54
So, we'll see how it plays out, but uh it'll be fun to watch.
2:42:59
Thank you so much for joining the show. >> Thanks for joining.
2:43:01
>> We'll talk to you soon. >> Cheers. >> Bye.
2:43:04
>> Up next, we have Dave from Upstart.
2:43:04
Do you know what >> Do you know what Upstart is, >> John? What What is Upstart? >> I can't hear you. >> What? What? Oh, sorry.
2:43:10
There there seems to be an air.
2:43:12
Well, we'll hear it from Dave directly. Welcome to the stream. How are you doing?
2:43:19
>> Hey, good to be here, guys.
2:43:19
Sorry to keep you waiting. It's great to see you. >> What does Upstart do?
2:43:22
Everyone's been asking, people want to know >> uh what do we do? It's a great question.
2:43:28
We uh we are a lending platform. Yes.
2:43:31
>> So, we apply AI and machine learning to consumer lending and uh we we operate in the form of a marketplace where we have consumers that we market to on one side and all sorts of uh banks and credit unions and private credit and all sorts of sources of capital on the other.
2:43:46
And the whole uh basic premise of the business is to apply AI to the foundational notion of of making consumer credit work both in terms of origination and servicing etc.
2:43:59
>> So yeah what what in the I mean when when most people today say AI they mean large language models they mean post chat GBT but obviously you've been in the business for a long time and machine learning is been a relevant technology pre-transformer-based large language model.
2:44:15
So how is AI in the modern context of like the large language model, the generative AI context, how is that changing your business and uh or or is it more of like a sustaining technology from you for you as opposed to like upending everything that you do?
2:44:33
Uh well, you know, I think uh a AI in in many forms in in LLM's in in sort of that sort of generational notion of AI obviously has grabbed a lot of attention, but when you think about, you know, high frequency trading, genomics, uh medical imaging, autonomous driving, these are all like forms of AI that that you would not they're not language based, they're not LLMs, but they are of course changing things pretty rapidly.
2:44:58
So I think you know maybe the big question is is there a unifying future where all this comes together into some form of you know AGI but regardless of whether that is true or not we are building something that's different it's foundational in nature meaning all the data on our platform is created by our
2:45:15
platform which is you know very different than how LLM's work um but I I would say the commonality is that look there's just enormous win that machine learning and AI can bring to any particular task at hand in our It's making a consumer loan of of many forms much much better. And that means like
2:45:31
And that means like zero process, perfect pricing, works for the lender, works for the borrower.
2:45:36
And uh you know, we we started we were founded, you know, 13 years ago.
2:45:40
We didn't really use the term machine learning or AI until 2017 when we kind of felt like this what we were building was sophisticated enough to warrant that name.
2:45:51
But, you know, it was all under the covers, you know, no one thought much about it until uh, you know, chat GPT and and November 22, I guess it was when the >> hot overnight success 13 years in business. Loved it.
2:46:05
Yeah, I I imagine as you've seen the advances over the last couple years, every time there's a new model release or or even even a vendor that's saying we're going to help you like better process PDFs, I imagine that that's exciting to you because you guys have done the heavy lifting to like build the supply and demand.
2:46:21
And so as new technology emerges, you can just help uh you know make you know make that process more more and more efficient.
2:46:31
How how much like what's your decision-making process around um you know whether you you guys want to build something in house which I'm sure you were forced to do a lot more maybe pre2020 to to now when there's a bunch of um new infrastructure providers that that you guys can leverage.
2:46:49
>> Yeah, it's a great question.
2:46:49
I mean we've always built everything inhouse.
2:46:53
Uh when something looks pretty obviously commodity like and that it's on top of LLM.
2:46:58
So for example what exactly what you mentioned extracting information from a document not not just kind of OCR but actually understanding the context that information in in a way that you can take all this human effort out.
2:47:09
Now that's something that honestly is very commodity like meaning the prices we'd pay aren't much different than we would pay if we built it on top of one of the LLMs.
2:47:20
So we're always like looking for things where we if we can ride someone else's cost curve on on some commodity that's great.
2:47:27
We are definitely trying to build the larger picture.
2:47:29
You know, the the the sort of endgame for us is if you can imagine 100% of Americans are permanently underwritten.
2:47:37
They can have any form of credit at the very best and guaranteed best possible rate in a moment with no process whatsoever.
2:47:43
So, anything that sort of gets us closer to that quickly.
2:47:47
And uh there's definitely you know business models evolving on top of LLM that I don't you know it's not my problem to figure out whether they're sustainable over time.
2:47:57
All I know is is like okay if you want to charge me an extra 15 cents you know that's great and take care of all these logistical problems of maintaining that particular specific small model like the the kind that you referenced.
2:48:12
>> Uh how are you thinking about the top offunnel evolution?
2:48:13
We were talking earlier in the show about um Google versus Chat GPT uh the GPT5 launch and the model router and it feels like in the future you might be able to go to chat GPT and say I need a loan and you are probably going to be there.
2:48:28
Are you thinking MCP servers?
2:48:30
Are you thinking about SEO in LLM foundation models?
2:48:32
Like how are you thinking about the changing landscape on the top of funnel?
2:48:40
>> Yeah, you know it's a great question.
2:48:40
I I was eight years at Google before I founded the company and There's a lot of history and there look at some Google or maybe one of the others are going to come to us and they're going to say we want our agents to be able to apply for loans and we don't want you blocking it or whatever.
2:48:59
How do you feel about that?
2:49:01
And I've said to our team, you know, I'd rather we do that before they do that.
2:49:06
So, you know, maybe the question is as these agents evolve as as as true agents for the consumer, you know, I'm super curious.
2:49:13
I don't necessarily know the answer.
2:49:14
Will there be three or four of them from the from the giants out there or will there be plugins to those to handle much more domain specific tasks or things?
2:49:22
I don't know how that will evolve, but I do believe it's without question you're going to have somebody that will do that on your behalf.
2:49:28
It will get the best possible outcome for you.
2:49:32
Hopefully, it will also help you make better decisions. All right?
2:49:34
Not not just go through the the mechanics of applying for a loan, but help you really understand like what's the best product for you?
2:49:41
Should I even be taking out a loan?
2:49:43
If so, what what other choices could I make?
2:49:45
So, that kind of stuff we we are working on for sure.
2:49:47
We could just think of as the sort of agentic part of this.
2:49:51
Uh and we would rather be uh we'd rather be applying that to others than having it apply to us. For sure. >> Of course. Uh last question for me.
2:49:59
Um uh obviously you see a lot of consumer economic data.
2:50:05
How are you feeling about the health of the American consumer right now?
2:50:11
Yeah, I mean we watch this a lot.
2:50:11
We we've built an index to sort of track it.
2:50:15
We call the upstart macro index, which is really about like the health of the American consumer and how that's impacting credit performance.
2:50:20
So basically what you see across all forms of credit from cards, student loans, you know, auto loans, mortgages is highest default rates that they've seen in a very long time since pre prior to COVID.
2:50:33
So the consumer has been stressed and is stressed and maybe it's inflation just overspending you know habits built during co that uh for spending that haven't dissipated >> you know so so the consumer is definitely stressed it's been priced into our model for a very long time so we're very calibrated to it but I think
2:50:51
you know we you have begun to hear if you you know retailers are seeing people pull back they're being more choiceful about what they're spending money on suddenly just all across the board you're getting a lot of a lot of noise out there, same store sales being down for different types of industries. So, I
2:51:05
So, I think the US consumer is finally kind of going, "Holy you know, we're not earning as much as we thought we are and we're spending more and, you know, this kind of we have to get back to a normal place."
2:51:15
The the thing we I point at more than anything else is the personal savings rate, which is something, you know, produced by the government and that's at almost historic lows.
2:51:23
So, you know, people are not saving, they are spending and and and it's, you know, a bit of a a catch up that's needed.
2:51:29
So from our point of view like a little bite of recession if it comes down to like consumers slowing down and you know spending less of what they earn like would be a good thing from our perspective. >> Makes sense. >> Yeah.
2:51:41
Any any any comments on uh I mean obviously everyone's been debating you know stock markets ripping.
2:51:45
So if you're just looking at that doesn't feel like there's a the a real reason uh to lower rates but if you look at some of the you know employment data and the data that you're talking about like maybe there is real argument to lower rates like what's your guys's like internal outlook uh for for the the back half of the year and beyond.
2:52:07
>> Yeah we you know in terms of our real product and what it's projecting we we never project changes if you will so it's always based on what the rates are today.
2:52:13
Having said that, I mean, I we are certainly I I I think rates are unnaturally high considering where uh inflation is, which is really kind of, you know, the things they have to weigh against.
2:52:23
So, in my mind, they're they're likely to move down.
2:52:25
Uh I I I can't predict the impact of of all these tariff stuff on inflation any better than anybody else, but I think generally speaking, you know, the the rates should probably be 100 or 200 basis points lower.
2:52:37
I think they inevitably will be lower.
2:52:38
They're not going to go back to what they were, you know, in 2020, but but they're going to go a lot lower.
2:52:42
And that's a tailwind to our business.
2:52:44
We again, we don't plan on it, but there's definitely a point at which the consumers are going to get in a better health position, saving more money, rates are going to come down, and and all that is, you know, future tailwind for us. >> Yeah.
2:52:57
Feels like you're really set up well for the next couple of years, like built through, made it through high interest rate environment.
2:53:02
If interest rates come down, you're you're you're ready to rock.
2:53:06
So, congrats on all the progress.
2:53:09
>> No, it's I mean, we just reported tripledigit growth in our earnings, you know, last week.
2:53:12
The market hammered us anyway.
2:53:17
>> Well, you're 5 years in.
2:53:17
You're you're almost a veteran now. 5 years.
2:53:20
>> I feel like if anyone can take a hammering, it's you. >> This is foric growth. >> Let's hit the gong. Thank you. Congratulations.
2:53:27
Thank you for coming on the show.
2:53:29
I'd This is a great conversation.
2:53:30
I'd love to talk to you again. >> Thanks, J. Have a good one. Cheers, Dave.
2:53:34
>> Let me tell you about eight sleep. Get a Pod Five.
2:53:36
Fiveyear warranty, 30 night risk-f free trial, free returns, free shipping.
2:53:40
Jordy, I think I beat you. What's your number?
2:53:42
>> And >> my problem is I I get like four great night sleeps in a I got an 81. How'd you do? >> 94.
2:53:47
Play the Ashton Hall sound for me. Let's go.
2:53:50
And we got a question from Bill Bishop, uh, who I'm a huge fan of.
2:53:55
He writes, uh, Cynicism on the Substack live stream.
2:53:57
He asked, "Shrooms and chat GPT, good or bad?" I say, "Absolutely bad. Stick to the classics. Caffeine, baby. That's all you need.
2:54:04
What do you need shrooms for? >> Cheers. Stick to >> Quick. Cheers for Bill. >> Stick to diet.
2:54:10
Matina >> from Andrew Huberman.
2:54:15
>> Load up on the caffeine.
2:54:16
>> They're calling it a podcast.
2:54:19
Have delusions of grandeur. >> Yes. Yes. Yes. C.
2:54:21
Enough caffeine will take you to the promised land of delusions.
2:54:24
Am I one of the best newsletter writers on China? >> Absolutely. >> Probably the goat. >> Goat. Absolute goat. Goat.
2:54:31
So, thank you for tuning in, Bill. big fan of your work.
2:54:35
>> Without further ado, our next guest, >> Kylin from InWorld. How you doing? You look fantastic.
2:54:40
I was just watching your video and you look exactly the same. How are you doing? >> Awesome. Thanks, John.
2:54:45
I also laughing because the the caffeine comments just coming before.
2:54:49
I mean, we we just had our launch night, so you can imagine I'm heavily caffeinated now. What are you running?
2:54:54
Are you Red Bull, Celsius, Diet Coke, Matina from Andrew Huberman? What are you? All the above. We love to see it. Anyway, kick us off.
2:55:01
We're running late today. Uh we kept you waiting.
2:55:05
We're keeping the next person waiting.
2:55:06
Kick us off with an introduction.
2:55:07
Explain what the company does and whether or not we should ring the gong for you. >> All right.
2:55:12
Uh so yeah, we were founded four years ago now.
2:55:14
Um we're basically solving a technical problems in the way of consumer AI adoption.
2:55:18
So our team came from Google and DeepMind worked on LLM there.
2:55:22
Basically got very tired of kind of everything flowing into enterprise applications, professional facing applications as we see.
2:55:27
So we basically set off to solve all the technical problems to see how we can actually drive consumer AI adoption which is of course a huge business problem but also I don't know if you know making sure the benefits of AI reach everyone.
2:55:38
Uh we raised $120 million so far and today we uh >> hey congratulations >> love it and uh yeah so today we had our biggest launch to date.
2:55:52
So we've, you know, it took us four years to get here working with groups like Nvidia, Xbox, Niantic, um, Disney, and now we have the first AI runtime for power consumer applications. So that's fun.
2:56:04
>> Okay, let's make this super concrete.
2:56:04
To the degree that you can talk about it, Xbox, uh, consumer AI, what does that actually mean?
2:56:11
How is generative AI instantiate or LLM's instantiating itself in like the Xbox world?
2:56:15
What's even the goal there?
2:56:18
>> So he started off largely working on things like basically talking NPCs.
2:56:20
So, we don't basically >> Hey, let's give it up for NPCs.
2:56:25
>> Let's give it up for They don't >> They're about to go on a run.
2:56:28
>> They get a ton of hate.
2:56:28
The NPCs, >> they're about They get a ton of hate.
2:56:33
>> They're about to look and feel like real player characters. >> Oh, you're an NPC. You're an NPC. Not for long.
2:56:37
They're going to get better because of you. Explain it.
2:56:41
>> So, yeah, B, we started out because conversational AI LMS are great at that.
2:56:44
Um, you know, games are pretty boring.
2:56:46
Anybody who's played a game, um, you know, has recognized that.
2:56:48
So we started out there and then basically we realized that you know we don't just want these characters and basically agentic experiences in games.
2:56:55
You can think about every consumer application.
2:56:57
You know your language learning apps, your fitness apps, you know they all suck.
2:57:00
I love actually a coach that actually did something effective. Yep.
2:57:04
>> And um and so what we found over the last few years is we worked a lot on the kind of games applications.
2:57:08
So these bringing characters to life, you know, the >> the types of experiences there.
2:57:12
Um and then now we've started working with a lot broader categories.
2:57:15
So, >> so on on on Xbox, it feels like uh you you could be almost like an API vendor within the Xbox ecosystem that a game developer could harness and run that on the device as opposed to going to Ubisoft and EA and Activision and saying, "Hey, for the next release of Call of Duty or Battlefield 6, uh pay us to train your LLM."
2:57:36
You want to be able to run it on the Xbox hardware.
2:57:38
So, where in the stack is it more like you want to fine-tune it so that it's uh on Xbox's terms and conditions versus you just want to optimize it to actually run on the Xbox hardware?
2:57:48
Like where where are the key uh key trees to chop down? >> Yeah.
2:57:54
So, think about any of the applications.
2:57:55
So, an Xbox for example, you're going to have a game.
2:57:56
It's going to be a build with Unreal.
2:57:57
In a mobile scenario, you might have it built with node.
2:58:01
You have that at the application layer.
2:58:03
And a lot of the infrastructure we've built to date has basically been optimized for that type of experience.
2:58:07
But now, we're introducing AI.
2:58:07
So now you're having a bunch of LLMs or different model calls that are happening.
2:58:11
And so think about that as kind of just a second infrastructure layer that needs to exist.
2:58:15
So you've got your core application, you've got your AI, and then you've got all your hardware in the back end.
2:58:18
So we basically sit in that middle layer of not just powering kind of actual, you know, the u the user interface and the specific, you know, uh gameplay elements or app elements, but actually driving the actual generative part of it.
2:58:29
So it could be characters responding, could be mission generation, um all of those different aspects as well as actually generating on the-fly content.
2:58:37
So yeah, we've got >> That's fascinating. Yeah.
2:58:39
So, so it it while you're building the game, even if it's a single player game, you could be in the loop designing or or or generating all the dialogue, but then in theory, it could also make an internet call if you're connected to the web and and and get upto-date uh uh text.
2:58:57
>> How are are game developers getting comfortable with the unpredictability of AI?
2:59:03
I mean, we've everybody's >> It can be a feature like hallucinations can be awesome because it takes you in this If you have a game for like Roblox for example, their average user is probably 12 years old, right?
2:59:11
They don't want, you know, some some LLM going off the rails and and naming itself something that maybe >> also just imagine you talk to NBC's like uh the the goal on this mission is to slay the dragon.
2:59:23
You go slay the dragon, you come back and it hallucinates and say like, "No, I I wanted you to save the dragonlay.
2:59:29
>> I didn't want you to slay the dragon."
2:59:31
>> Also, my name is Mecca.
2:59:34
>> So, yeah, talk about talking.
2:59:35
>> Oh, this this actually happened though.
2:59:37
So we we did a lot of really tests around this and it was pretty hilarious.
2:59:39
I mean the characters literally make up anything. >> Yeah, of course.
2:59:42
>> But then there's been a lot of applications that took advantage of this.
2:59:44
So one of our bigger clients, they're called Status.
2:59:46
It's a crazy game huge with like Gen Alpha Gen Z.
2:59:47
They basically created a game where you could roleplay as a character in another universe is Twitter.
2:59:52
So imagine you're like Harry Potter.
2:59:54
I can role play as Harry Potter in Harry Potter universe is Twitter.
2:59:57
And then you have like Ronald Weasley, Draco Malfoy.
2:59:59
people don't really exist, but then the AI can actually take advantage of the fact that it's hallucinating and making things up to actually come back with that.
3:00:05
And where we see that is like with the interesting with consumer apps is they've kind of gotten to this point where if you for example have to design manually content and it takes you 30 days to design that content and then your users consume that in 20 minutes.
3:00:19
>> You have to do a lot of work to create months of content.
3:00:21
So AI kind of smooths out as well that content creation curve so that you always have this kind of implant loop which is you know key for things like retention. >> It's awesome.
3:00:31
Um what's uh what's next for the business?
3:00:34
Is it just like uh expansion within your current I feel like the pool of value that you can create in any of the companies that you listed is pretty significant if you just keep delivering better and better products, better value, ramping those up versus going broader.
3:00:47
Is there going to be like an SDK at some point?
3:00:49
Are you going to go general availability and some some kid who's building an iPhone app will be able to vend this in? >> Yeah.
3:00:57
So, uh overall today we're actually launching that next that next phase. >> There you go. >> Good timing.
3:01:03
>> Exactly what I described.
3:01:04
>> And uh yeah, so what we realized was that as we were working with those gaming and media partners, it wasn't just them but broader consumer applications.
3:01:10
Basically anybody who is dealing with multi-million user scale that has to be you know consumer cost, consumer latency, consumer quality which is more about entertainment than the factuality people are used to chatbt >> which we also heard about a lot about last week.
3:01:23
Um and so people actually want to be engaged by it.
3:01:25
Um >> so for us it's been kind of expanding to the broader consumer space across like outside of just games and media.
3:01:31
And then the other part is releasing the runtime that we're releasing today.
3:01:34
Um, and that is kind of the big push that we've been making for the last 4 years and basically allows things to autoscale.
3:01:41
We had a developer today who called it vibe scaling.
3:01:42
So, you know, people can vibe code a lot of applications, but then it takes them freaking 6 months to be able to actually productionize it.
3:01:48
And so, everybody comes to me, I've heard like a bunch of, you know, sea level executives be like, I coded an app in four hours.
3:01:53
Why does it take my team six months to productionize it?
3:01:58
>> We're basically like automating a lot of that scale as well. >> Exactly.
3:02:01
>> Um, and then automating also the ML operations.
3:02:03
So most teams don't have an infrastructure team.
3:02:05
So we're basically taking over a lot of that, automating it, and also allowing people to do experiments so they can just launch tons of experiments and find what works.
3:02:11
So that's basically it is moving to broader consumer, moving deeper in the stack of the infrastructure layer with the runtime.
3:02:19
>> Um, and we think it solves a lot of the problems that we're seeing.
3:02:21
>> Well, congratulations.
3:02:21
Thank you for hopping on the stream.
3:02:23
We will talk to you later.
3:02:24
Have a great rest of your day. >> Great to meet you.
3:02:26
Congrats to you and the team. >> Have a good one.
3:02:28
Let me tell you about public.
3:02:29
com investing for those that take it seriously.
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3:02:36
Now, we got Sam from Method Security coming in the studio.
3:02:38
Welcome to the stream, Sam. How are you doing today? >> Good. Good. Thanks for having me on. >> A suit. We love to see it. >> Looking sharp. >> Thank you.
3:02:48
It's a great respect in our culture.
3:02:50
That looks like a fantastic suit, honestly. Uh, very nice.
3:02:52
Anyway, kick us off with an introduction. What do you do? What are you building?
3:02:56
Should we ring this gong?
3:02:57
Uh, let's not ring the gong, but I'll tell you why you might need to soon.
3:03:03
>> Sam Jones, CEO and co-founder of Method Security.
3:03:05
And let me uh take you a little bit about what we're up to.
3:03:07
>> So, you're completely bolt bootstrap.
3:03:09
You've never raised a dime.
3:03:10
>> We have raised >> Oh, hit the gong, Jordan. Oh, there we go. Come on. You buried the lead.
3:03:17
>> This is a ventureback company.
3:03:18
>> It's a ventureback company.
3:03:18
We've uh we've capitalized.
3:03:20
We've We're going after big opportunity, but we've just been low-key about it cuz the opportunity is so big. But, uh, >> fantastic.
3:03:26
Well, come back when you have more news on on on the fun side.
3:03:28
Anyway, uh break down the business for us, please. >> All right.
3:03:33
So, here's the problem we're after.
3:03:34
Uh critical institutions are basically faced with 24/7 cyber conflict, and they don't have the tools they need to win. Yeah.
3:03:42
>> Um there's this concept called the cyberindustrial complex, which really creates security companies that are designed to be acquired, not to produce at scale.
3:03:50
And meanwhile, you've got AI that's going to do to cyber what drones have done to the battlefield.
3:03:54
And really the future will be controlled by who can safely harness autonomy at scale.
3:03:58
And that's exactly what we're up to at Method.
3:04:02
So we build offensive and defensive products for some of the best security teams in America.
3:04:07
>> Offensive is that for white hat hacking or is this are we actually going on the offense? >> A little bit of both.
3:04:11
Um you know >> when would I go on the offense? >> Striking back.
3:04:16
>> So interestingly a lot of commercial security teams use offense to inform their defense.
3:04:21
And it's kind of this virtuous loop where you you become the threat and then you can inform your defenses and you have this like kind of cycle.
3:04:28
>> It's historically been super expensive to do so because you need this really hardcore uh rare human being called a red teamer or like an offensive security engineer to conduct those exercises.
3:04:39
We're putting that in software so we can basically democratize that and help organizations really assess their readiness to relevant threat actors.
3:04:47
Turns out if you build that technology the right way, it can be used for true offense.
3:04:50
And so we're deployed with DoD and also the US government.
3:04:53
So uh we're not limiting to both commercial use.
3:04:57
We're a dual use company.
3:04:57
Cyber doesn't discriminate. Neither do we. >> Very cool.
3:05:00
Um walk me through how a cyber attack happens in the age of AI.
3:05:06
I'm familiar with like the script kitty who finds a hole in WordPress or you uh take a it's a rainbow table of all the different passwords.
3:05:15
>> If I go a DOS method security website. Don't make mistakes.
3:05:18
I don't think it'll do that hopefully.
3:05:20
But yeah, I mean I'm familiar with DDoS, right? It's just a for loop.
3:05:24
It requests the website forever, right?
3:05:26
Uh but but AI feels like the shape of the attack could be way different.
3:05:31
Try and concretize it for me to the degree that you can.
3:05:35
>> Here's the misconception of where AI is at in security.
3:05:37
A lot of people think like we're going to come have all these novel zero days all over the place and we're going to have all these new novel threat patterns happening.
3:05:43
That's not what's happening today.
3:05:45
really what AI is doing is that it's helping express a lot of the known techniques and tactics at a new scale that's unfathomable like a couple years ago.
3:05:56
>> Um and so if you think about like the global attack surface, it's unknowable to any single human or any single security product really.
3:06:01
But with the right AI system, especially a compound AI system, you can basically map that, eviscerate that and defend that or offend that.
3:06:10
And so really AI is helping hit new scale like orders of magnitude scale less so new zero days still present.
3:06:18
>> So there's yeah there's vulnerabilities out there where it's kind of a pattern.
3:06:22
You might be able to do some RL on it.
3:06:23
It's like follow a set of steps and it you might be able to break into one website but instead of needing to do this website and then move on to the next one, you can just say hey go do them all. >> Right?
3:06:33
It's like instead of let's assess this organization.
3:06:36
This is going to be a three-month exercise with the right system, which is what we do.
3:06:38
You can say 30 seconds, I know everything about about this, and I'm going to initiate kind of something more offensive. >> Interesting.
3:06:46
Um, how are how are like the budgets and the appetites changing in the enterprise or like the Fortune 500 because we've talked to a lot of people that have said come on the show and said, "Oh, yeah, AI is going to really help my margins.
3:06:59
I'm I'm going to spend less money."
3:07:01
And it seems like if you're selling into them, they're going and there's more threats, they're going to have to spend more money.
3:07:06
How does that balance out?
3:07:09
>> I'll break it down from like commercial buyers and government buyers is a little bit different.
3:07:13
On the commercial side, the most uh sophisticated security teams usually have dedicated AI innovation budgets and those are to experiment with new technologies and new technologies in.
3:07:22
But for the most part, most buyers, I'm talking like Fortune 500 security executives, have known problems, known categories that they still need to purchase against.
3:07:30
And so it's important to map, you know, be familiar enough but also a little different but not try to build anything too new.
3:07:36
So you have to map to something that they know and are trying to do.
3:07:39
Um not necessarily develop a novel new technology.
3:07:42
Government is pretty different like there is a lot of investment in you know AI for offense, AI for defense like cyber operations more broadly.
3:07:51
In the big beautiful bill, there was 1 billion earmarked for offensive cyber operations, which is a huge number.
3:07:57
And I would argue like still need to up that number quite a bit.
3:08:02
>> Um, but there's a general, you know, understanding that we need to up our game here and get faster and the status quo is not cutting it. >> Fantastic. Jordy, anything else? >> That's it.
3:08:12
>> I think you got some important work to get back to, so we'll let you >> go get on the offensive. >> Get on the offensive.
3:08:16
>> All right, we'll do it. We're riding with you.
3:08:18
>> Bring me a list of passwords from North Korea, please.
3:08:22
Anyway, great chatting with you.
3:08:22
Thanks so much for hopping on the stream. I'm back home whenever.
3:08:26
>> Congrats on the progress. We'll talk to you soon. Cheers. Bye.
3:08:29
>> Uh, let me tell you about adquick. com.
3:08:31
Out ofome advertising made easy and measurable.
3:08:32
Say goodbye to the headaches of out ofome advertising.
3:08:34
I want some soundboard when I do these, Jordy.
3:08:36
Only adqu combines technology, out of home expertise and data to enable seamless, efficient ad buying across the >> golden retriever. >> Golden retriever.
3:08:45
The the the dog panting and the horse noise deeply underrated.
3:08:49
You know, I love the Ashton Hall, but the horse noise is is a close second.
3:08:54
>> Anyway, we are joined by someone who can run as much as a horse, Zack.
3:08:58
>> I would estimate Zack at like six or seven horsepower.
3:09:02
>> That's Zack, you're live, by the way. >> You're You're live. >> How much horsepower? About six horsepower.
3:09:10
>> We were saying I think probably six or seven horsepower.
3:09:13
>> I don't know what that means. I'm not a car guy. I'm sorry. I realize >> No.
3:09:16
Are you You know, a horse has one horsepower.
3:09:17
We're basically saying you're as strong as seven horses. >> Seven stallions. >> I'll take it.
3:09:22
>> Anyway, >> I've been thinking a lot about horses, but go ahead.
3:09:25
>> Oh, what have you been thinking about? So have we.
3:09:28
>> They're just like the most majestic creatures.
3:09:30
The an unbelievable combination of beauty and grace, but this raw power and it's just like I don't know. Go ahead.
3:09:37
>> Much like myself, >> much like you.
3:09:38
Anyway, congrats on the launch.
3:09:40
Share Aura is now live in the App Store.
3:09:43
If you're listening to this, go download it.
3:09:44
Invite codes are going out to a wait list this week.
3:09:47
There's 20,000 people on the wait list already. Wow. >> Probably. Yeah, >> probably more.
3:09:54
>> So, so break it down for us.
3:09:54
Uh uh pitch the app and explain some of the launch strategies that you've been employing.
3:09:59
I want to talk about media and and vlogging and actual uh and the app, of course. >> Definitely. Yeah.
3:10:07
So, for some context, I've been posting on social media under my name essentially.
3:10:11
It actually started as like a synonymous account but that was like 5 years ago been publishing for almost seven years and >> have went from writing content to motivational content and then got really into running and the idea for the app started where a lot of you are familiar with Strava probably >> yep >> noticed that so I have a big Instagram account have 1.
3:10:30
3 million followers >> hit the gong for 1.
3:10:32
3 million followers on congratulations Zack >> and towards the end of last year I just, you know, I kind of accidentally became an influencer and just hated it.
3:10:43
Hated doing other people's stuff and I was just I scrapped everything I was doing.
3:10:50
It was all my partnerships.
3:10:50
I just want to build my own thing and and I just noticed all these people, every single runner I followed was posting screenshots of their Strava or their run or their workout on social media.
3:11:01
I'm sure you guys see people who do that on Instagram all the time. >> Of course.
3:11:07
>> And then I just started thinking more.
3:11:08
I'm like, screenshotting itself is just like this unbelievably massive user behavior.
3:11:14
If you go look at screenshots on your phone, I would bet you have like 20,000 screenshots. >> Yep. It's an insane.
3:11:20
>> There's even a separate folder for them now. It's really convenient. I love it. >> Yeah.
3:11:23
But so essentially, you have this user behavior of finish your run, finish your workout, post it to social media. Yeah.
3:11:30
>> Hundreds of millions of people are doing that very specific thing every single day.
3:11:34
And yet these apps like Strava, you have to take a screenshot and then go to Cap Cut or Canva and remove transparency and do no, let's just build an app obsessively dominating that one user behavior. >> Cool.
3:11:46
And >> so that's what I started working on in February where essentially the app is a tool to share your runs and workouts.
3:11:52
It's like a creative tool for fitness and running.
3:11:54
Starting focused on running and we're expanding quickly to all the big stuff.
3:11:58
Cycling like you'd expect.
3:12:00
And >> cycling like testosterone or what are you talking about cycling?
3:12:02
We can we uh >> I'm kidding. I'm kidding.
3:12:06
Of course, we're talking about bicycling.
3:12:09
>> John's gonna start uh bicycling.
3:12:11
>> John's going to do a cycle and just every day just live on the air that's posted on >> or what was your strategy for actually getting uh feedback?
3:12:17
It sounds like you were dog fooding the app yourself, but then did you have a small community of beta testers, friends, family, like who do you trust?
3:12:27
Who is actually going to give you good signal?
3:12:29
Because if they're too close, they'll say they'll glaze you.
3:12:32
If you ask chat GPT probably tell you you're, you know, the next Mark Zuckerberg, but uh >> yeah, you got to dial it in, right?
3:12:38
You got to get the right the right feedback from the right people.
3:12:41
So, how how do you iterate?
3:12:43
>> Yeah, I mean it's like you have so many yesmen and you have to just ignore all of them. We've had a beta. So, we've had a beta.
3:12:48
Shout out to two developers of Ara, Kale Stewart, John O'Kim. Um >> for them.
3:12:54
>> I love the developers. Thank you.
3:12:56
>> Developers developers developers. Developers. Developers. Developers. Developers. Developers.
3:13:02
I haven't watched the show that I've seen the clips, but I'm not just not used to all the things.
3:13:07
>> We're really ramping it up.
3:13:08
>> You're too You're too locked in. You're too locked in.
3:13:11
>> I've been watching every day. But okay.
3:13:13
Anyway, um we've had a beta since March.
3:13:15
And yeah, I mean, I've had nothing else in my life besides this app.
3:13:17
Luckily, I'm I'm the type to just burn everything down and just focus on one thing.
3:13:22
>> And so, we've had a beta and you know, the product we had in the beginning of March is drastically different than we have have now.
3:13:27
And >> and yeah, I mean, look, I'm lucky.
3:13:29
I have been creating content so long.
3:13:31
I have people who um >> who were just hungry for something from me.
3:13:36
And this app, it's so core to the DNA of everything I talk about that um I think I was able to get really good feedback.
3:13:42
Like there are some like there's a group chat, shout out to them, called the pit >> and it's it's like a group of like my my most real they're not just about me, but like a lot of like true obsessed savage and I've been following me for a long time. Shout out the pit. The pit. >> The pit is aligned. you back.
3:14:02
>> I was here for the pet.
3:14:03
>> Yeah, created it since March and just been iterating rapidly on the product.
3:14:06
And the one thing I've learned, which I'm sure you guys know, is just you have you have no idea what's going to work until you ship it.
3:14:09
And uh it's been it's been fun to be on that journey.
3:14:13
>> Uh we have a question for the chat.
3:14:13
Do you think Sam Schoffer is shadowbanned from Share Aura for not running with a beard or for running too slowly or for not running enough or any other reason I can make up trying to roast him? That's from John Xley.
3:14:27
from John Xley. He's only he's running under three miles a day and I put out a tweet that if you're a man running under three miles is very feminine and >> oh my god >> Instagram didn't like that one but uh >> yeah you're going to get deplatform for that >> roasted for that anyway
3:14:42
>> what uh uh you're building you know it's an app but you're building a business >> are are you going to roll out are you monetizing already do you plan to what's the plan there >> no monetization yet um I I we do plan to however my thing is our app is essentially a a distribution product on drugs, right? Where the only purpose of
3:14:59
Where the only purpose of you go on Aura, the share Aura, the only purpose is to create content to share to social media.
3:15:06
And so essentially the reason I am obviously bullish on my app and I'm essentially playing with three cheat codes.
3:15:12
That is the only purpose of the app is to post content on your Instagram story and social media.
3:15:16
Number two, I have two million followers.
3:15:20
I post a little I post a graphic for the app that we might make on my Instagram story. It gets 100,000 views.
3:15:27
I I'm a pretty good designer.
3:15:27
I design a lot of it myself and or we have good designers who help. >> Yeah.
3:15:33
>> And then Donna ships it, makes it, we ship it next week.
3:15:36
>> So, okay, my audience is number two.
3:15:36
And then my friend I have a lot of friends who are the biggest running creators in the space. >> Yeah.
3:15:43
>> I don't I don't pay I don't there's no payments.
3:15:45
And we can get to that if you saw my marketing post. We can talk about it.
3:15:48
But I'm not paying a single influencer to use my app.
3:15:51
They are literally asking me right now. I just put out a tweet.
3:15:54
I don't know if you saw it. I might delete it.
3:15:57
>> The pit is here in the chat.
3:15:57
Greg Duncan says, "Shout out the pit there."
3:16:00
Colin Cornwell is in the chat. Cole Ryan.
3:16:02
I feel like a lot of these guys came from your crew.
3:16:06
I don't know if you know them by name, but >> I was just saying like there are big in Instagram influencers with millions of followers asking to use my app. >> Totally. Yeah.
3:16:16
>> And like I don't you know what I mean?
3:16:18
And so for monetization, I just think if I was to charge money right now, we have essentially a creative tool, right?
3:16:22
We could charge money for creative assets and special templates and all this stuff. >> Yeah, that.
3:16:27
Let's just build the most ridiculous growth machine possible.
3:16:31
>> Get a fuckload of users and then I already have specific ideas.
3:16:34
Like for example, let's say we have 500,000 users sharing with Aura sharing con.
3:16:38
So, not just users on the app.
3:16:40
You're kind of valuing the potential impressions on their content per day. >> Mhm.
3:16:45
>> That I think is worth something to a brand to have their assets in the app to serve as creative tools to spread their brand more. That's just one way.
3:16:50
But the reality is guys, I will be super transparent.
3:16:54
There is no ceiling, zero ceiling to my ambition with this app.
3:16:57
I think consumer health, consumer fitness is a very massive category.
3:17:00
Even if you just look at running apps, you go back 10 years to when the app store launched.
3:17:06
Runtastic, rune, map my Run.
3:17:06
Y >> when the store launched, all these apps were built, they got 50 to 100 million plus users and they were all acquired by AS6, Adidas, um there's more of them that were like five of them were acquired for 50 to like 300 million.
3:17:19
And truthfully, I'm starting this the first act of aura share aura is sharing.
3:17:28
>> But I since the beginning since March, the reason I've been taking this so seriously is I am that is just the start.
3:17:34
And I think there is a lot >> you told me you've told me off air some of your your moon more moonshot ideas and and they're very exciting.
3:17:39
I won't I won't uh >> says 1 million users is the goal.
3:17:42
Um I feel like you'll have strong opinions about AI, social networks, bots.
3:17:46
We just heard from an investor who said that maybe there will be a new social network that's heavy on bots.
3:17:54
We talked to Pico Labs yesterday.
3:17:57
They want to build an app that's like a social media app that's entirely AI generated.
3:18:01
Share aura the vlogs you've been putting out.
3:18:04
They feel uniquely human.
3:18:06
Uh talk to me about the trade-offs between uh like AI content being allowed or promoted or demoted.
3:18:14
And >> Sher is shar great because you guys can use generative AI to give people these creative tools, but they still have to go out in the real world if they want to actually really use the product, right?
3:18:25
It's it's doesn't matter if they can >> Tesla Optimus, go run 17 miles and then come back and post for me under four minute miles, please.
3:18:34
>> But yeah, what's your take on like AI on social media like its correct place? Yeah.
3:18:39
I mean on social media like it's it can't be the heart of things.
3:18:45
Like I my writing gets tens of millions of views a month.
3:18:50
I've never written with AI once.
3:18:52
>> I've never made a vlog with AI once.
3:18:55
However, my whole app like I just pulled it up like so for our app we have like stock backgrounds, right?
3:18:59
Because it's like >> you've heard of stock images, right?
3:19:02
And like so we make I'll just pull it up.
3:19:05
Like they look like that. Like they're super sick.
3:19:06
It's a crazy percentage of our app use them. Like 40% plus use them. >> Um, which is wild.
3:19:11
And and >> like, yeah, I think it should be used to expand a creative vision.
3:19:15
Like my creative universe, yeah, I'm going to use AI.
3:19:19
I think AI videos, I'm so bullish on it.
3:19:21
And like the we're doing for Aura, for the AI backgrounds I just showed you, I have a person named Nat who's cracked on it.
3:19:27
It is going to break the internet. It is so good. >> It is so good.
3:19:32
And and but the heart of everything is me taking >> Yeah.
3:19:38
>> filming this whole thing.
3:19:38
By the way, what's up, guys? >> Nice.
3:19:41
>> Hey, great to see you.
3:19:42
>> Taking this 19 2000 1999 year old camcorder and taking it on a vlog and filming my entire life.
3:19:47
So, the heart of it, >> I don't think you build a personal brand with AI.
3:19:50
It can't be the heart of it, but it should be you should use it to expand your creative universe.
3:19:55
>> We're going to use AI to bleep out your mouth. >> I cursed. I didn't notice. >> I love it. quarter vlogs.
3:20:02
Are they working on YouTube?
3:20:04
Are they working on Instagram? Are they working on X?
3:20:06
Who what audience likes that more than the other?
3:20:12
>> I They're definitely working.
3:20:12
I'm not a YouTuber, so like I just don't know if they're working yet on that platform. It's too early. Yeah.
3:20:18
>> My Instagram, it's funny. I have 1. 3 million followers.
3:20:20
I don't think I posted a real for a year. >> Yeah.
3:20:23
>> Because I'm just a I was a writer. I was doing other stuff. >> Yeah. Yeah.
3:20:26
>> They're already working on reels and I just started them.
3:20:27
And on X, they're 100% working.
3:20:29
And the big thing is like look, the the thing I obsess over more than anything is just like how to get attention on social media, right?
3:20:34
And it's just like I've gone ridiculously viral in the past for some certain innovative things.
3:20:39
And um the camcorder is the same thing.
3:20:42
You're giving someone something new on their screen. That's number one.
3:20:47
>> And then number two is you're tapping into just nostalgia, which brands know is an unbelievable weapon.
3:20:55
>> An unbelievable weapon for attention. Totally.
3:20:57
And and when you combine that with someone actually doing something like I'm actually building my app, it's it's it's interesting.
3:21:01
And so I think they're 100% working on X.
3:21:03
Like look at the the vlogs I've done on X have gotten hundreds of thousands of views already.
3:21:08
And the little launch video mini one I did got has 144,000 views. It's pretty good. >> Yeah. Yeah.
3:21:15
I mean we felt that early on with like we were printing out tweets and reacting to them and wearing suits and there was a little bit of nostalgia.
3:21:23
Tastefully the thing is brand you can't just use Apple Garam with three letter people to care. No one cares.
3:21:27
You have to find You guys have the synth wave intro. It's great. >> Yeah. Yeah. You Yeah.
3:21:33
You have to pull different things from different elements.
3:21:36
We We're showing the >> We're using a camcorder ourselves. >> Yeah.
3:21:40
We have one in the studio, too. It's fun.
3:21:43
It's fun. I I I I think these are just creative tools like the generative AI, like the gener I like the fact that you're saying generative AI backgrounds because I feel like the magic happens when there's when there's it it's like
3:21:56
if you go to any any like Photoshop or like MS Paint like you'd always have like the template for like I want to just stamp a tree down and that's just one of the tools and it feels like these generated AI backgrounds it like they're not going to go viral by themselves. the
3:22:08
the virality, the human element is going to be injected and it's going to be like a collaging effect on top of some of some base that's really going to be the thing that pops >> totally >> stands out.
3:22:20
>> Anyway, >> well, I'm excited for more people in the world to get the app.
3:22:22
Congrats on the launch and uh come back on anytime.
3:22:27
>> Everyone's demanding codes.
3:22:29
>> Is this this isn't the first time, right? You've been on before. >> First time, I think. First time. This is crazy.
3:22:34
>> When we do another big update, I'll come back on. >> Yeah. Yeah, come back on.
3:22:36
The the honestly Verdusco says, "Zack looking yolked.
3:22:41
Glad you went with the black tank," says. >> There we go.
3:22:46
>> Greg Duncan says, "Nostalgia is emotion track.
3:22:49
You >> look good either way.
3:22:50
You look good authentically."
3:22:52
>> Colin says he's cooking and making us feel.
3:22:55
>> Next time you go on a on a long run, just just FaceTime us.
3:22:58
We'll we'll drop you into the show. >> Yeah. Yeah.
3:23:01
You can call in for a run.
3:23:03
>> We'll be your running We'll be your running coach. >> Yeah, I'm sure. I'm sure. >> Anyway, great chat.
3:23:07
We will talk to you soon. >> Cheers.
3:23:12
>> And you know what he should do to promote this?
3:23:13
He should run from one wander to another.
3:23:17
>> He should find his happy place.
3:23:17
He should book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service because it's a vacation home.
3:23:25
>> We should do a campaign with Zach and just have him run, >> you know, 100 wanders in a 100 days all on foot. >> That'd be great. That'd be great.
3:23:32
Uh, let's go to the timeline.
3:23:34
The billionaire Porsche family prepares for war with new defense fund.
3:23:37
German dynasty expands into weapons amid Europe's rearmorament drive.
3:23:43
Uh so shank Josie says enter the 911 the 911 technical.
3:23:49
Um this is just funny that like more and more people are p are pouring into uh defense tech.
3:23:53
We were kind of discussing this.
3:23:56
>> It's not the first time that Porsche war.
3:24:00
>> It's not the first time.
3:24:00
Uh, oh, I you put this in the you put this in the feed and I didn't realize it was from John Summit, but John Summit said, "Uh, >> no, no, no.
3:24:07
Let me give some context." Yeah. Yeah. Yeah. Yeah. Take take this.
3:24:10
John Summit had >> he said, "Every great bender leads to an epic lockin."
3:24:16
>> And then, and then people, someone quoted this and said, "You're 31, big bro." And went viral.
3:24:20
Uh, obviously dunking on him.
3:24:24
>> John fires back and says, "Do you do people think you just stop having fun in your 30s? Such a loser mentality."
3:24:28
and then says David Ghetto is 57, Tiestto is 56, Carl Cox is 63, and they all still rip till 6 a. m.
3:24:36
in Aiza while all these finance burner burners cry themselves to sleep at night.
3:24:45
>> An East Village guy just says banger.
3:24:47
John Summit, I didn't realize he was just declared war on declared war on the timeline and put Lover Boy in the in the truth zone.
3:24:53
Um, anyway, fun fun fun to have people back and forth.
3:24:58
>> Show up at get backstage at at a Johnsummit show.
3:25:00
You guys should make up and uh and send it.
3:25:04
>> And John Summit, head over to getbasel. com.
3:25:06
Your bezel concier is available now to source you any watch on the planet. Seriously, any watch.
3:25:09
Nick Carter, >> he says, "I'm increasingly convinced that a substantial percentage of kids brought up in the age of AI will be post literate.
3:25:18
like they won't really know how to write and I'm going to say or think and and will rely on AI to autocomplete their thoughts.
3:25:26
>> I mean we have a friend who is illiterate and he's very successful.
3:25:28
He doesn't know how to read. It's fine.
3:25:31
Maybe maybe >> but because he doesn't know how to read it clarifies his thinking.
3:25:36
He has no one else is able to influence >> his thought with the written word. >> Yeah. Yeah. Yeah. You can't oneshot him. >> No.
3:25:46
I've been pushing people on this.
3:25:46
I think I think if somebody is struggling with how to communicate an idea and they think I should go to Chad GPT and and work this out. >> Yeah.
3:25:58
>> I think that the more you do that, the more you're going to atrophy your brain and you got to be a little careful there.
3:26:04
>> It's so crazy because if you can write a good prompt, job's finished.
3:26:07
You can just send that as an email.
3:26:09
like very rarely does the result because I have GPT5 running in my brain in terms of like rewriting emails.
3:26:19
You can just send me the bullet points.
3:26:20
You don't need to send me the hey chat GPT turn these bullet points into uh a bunch of paragraphs.
3:26:25
You can just send me the bullet points and I will expand it in my brain.
3:26:28
Uh, and so, um, I I I find that the, uh, I find that I find that the chat GPT for for email writing, uh, does not actually improve communication or save all that much time.
3:26:40
Again, knowledge retrieval, knowledge retrieval, knowledge retrieval.
3:26:43
If you're thinking of something, it's on the tip of your tongue, type it into Chatt.
3:26:46
It'll give you what you're thinking of.
3:26:48
If you need five examples of something and you can think of two, it's going to nail the next five.
3:26:53
Uh, speaking of which, I had an interesting thing that I pulled up.
3:26:56
We didn't get a chance to talk about this, but um are you familiar with the story of John Hinckley Jr.? >> No.
3:27:02
>> So, we were talking about AI psychosis, AI making people crazy, maybe social media had a similar effect.
3:27:09
>> Well, what about movies?
3:27:09
So, in 1967, has anyone in this studio seen Taxi Driver? >> Yes. >> Thank you.
3:27:17
I know you haven't, but Taxi Driver is a Robert Dairo film uh where um Travis Bickl the character becomes obsessed with a young woman played by Jodie Foster and attempts to assassinate a presidential candidate. So uh John Hinckley Jr. was 25 years old.
3:27:33
He was a drifter from Texas and he had developed an intense fixation on the actress Jodie Foster after seeing him in that 1976 film Taxi Driver.
3:27:44
So in 1980, Foster was a student at Yale University.
3:27:48
Hinckley moved to New Haven, where Yale is for a time, writing her letters and calling her, even though she never reciprocated or encouraged contact.
3:27:57
Hinckley believed that committing a spectacular act such as killing a US president would gain Jodie Foster's attention and impress her.
3:28:06
So he trailed he first was going after Jimmy Carter.
3:28:09
He trailed President Jimmy Carter during the 1980 campaign, but was arrested on a weapons charge in Nashville.
3:28:15
But when Ronald Reagan got elected, Hankley shifted focus to Reagan.
3:28:20
And so on March 30th of 1981 at the Washington Hilton Hotel in Washington DC, Reagan had just finished speaking and was leaving the venue when Hinckley fired six shots with a 22 caliber revolver.
3:28:33
He hit Ronald Reagan with a ricochet bullet in the chest. Reagan survived.
3:28:38
He hit uh the press secretary, James Brady, in the head and left him personally uh permanently disabled.
3:28:44
And he also shot uh a Secret Service agent in the abdomen and a DC police officer in the neck.
3:28:49
And so later, John Hinckley claimed he did it to impress Jodie Foster.
3:28:54
He uh his defense argued not guilty by reason of insanity.
3:28:59
He pleaded insane uh citing severe mental illness.
3:29:02
and he was eventually acquitted on those grounds in 1982, but was committed to a psychiatric hospital for over three decades.
3:29:09
So, one shoted by technology, one shoted by new video, new imagery, a v a film, something that's not real, but told a story that convinced him.
3:29:22
And he had delusions of grandeur and he went on this run.
3:29:25
He was effectively, you know, he he he he had film psychosis, but it was very very he was this is like the only example of something like that happening.
3:29:35
And overall, I would say that films are fantastic and a major net good.
3:29:38
>> Did he get Jodie Foster's attention? >> I don't think so.
3:29:43
>> Hopefully, she paid a little attention.
3:29:45
>> I think she did address it at one point.
3:29:47
Um but I don't think she was interested in him. >> Yeah.
3:29:50
But interesting rough way to get attention that this this idea of of seeing some sort of media, text, imagery, something on social media, something in in chat GPT, something on the screen could drive someone who's, you know, has mental illness to do something crazy.
3:30:07
This is this is not entirely new.
3:30:09
The question is scale and the question is how can you resolve it?
3:30:15
um when the film industry you know I I think it was I think it was handled just by you know like they've made more movies like uh like Taxi Driver they've made uh Joker and people were worried about that having an effect but overall our society learned to adapt and and probably identify hey my friend saw a
3:30:35
movie and he's acting weird like let me talk to him about that like no that just because Jody Foster's in that movie doesn't mean that she's going to love you if you do the thing that happened in that movie the movie is fiction Um, and so people developed kind of a mimemetic defense to uh the the imagery in films. Uh, they'll hopefully do the same for
3:30:50
Uh, they'll hopefully do the same for social media and have in many ways.
3:30:52
I think a lot of people are are are adapting to the age of of uh social media with like screen time and understanding that, you know, there's all these different incentives.
3:31:02
>> Getting a notification.
3:31:04
>> Wow, I used Tik Tok for 60 hours. >> Yeah. Don't talk to Tyler.
3:31:09
>> I gotta get those I gotta get those numbers up. >> Yeah.
3:31:11
Um, well, we got to talk about a uh potentially the next Fed chair. What is going on here?
3:31:18
>> David Zervos, who is a currently a managing director over at Jeff. Okay.
3:31:25
>> And he has a fantastic wardrobe. Let's pull this up.
3:31:27
>> This is wild wardrobe.
3:31:29
>> QC Cap says, "This might be the Fed chair." And you're bearish.
3:31:31
And this looks like a Burning Manesque outfit.
3:31:38
Um, do you want to >> And then next up, he's got a fantastic orange suit.
3:31:42
>> The orange suit is fantastic. >> Incredibly sharp.
3:31:43
Uh, David >> put him on the McLaren F1 team.
3:31:46
Um, >> David was already an adviser to the Fed back in 2009 for a year and then has gone on quite the run.
3:31:56
>> Something about David in finance because this David has fantastic suits and fashion sense and then David Solomon is a DJ.
3:32:03
Something about being a David in in finance really puts you on the track for eccentricity.
3:32:09
>> Does he does look like in another life he would have dominated digital assets?
3:32:14
>> Oh, I thought you were going to say uh Oh. Oh, yeah. Yeah, for sure.
3:32:16
Crypto, but uh he he definitely has the crypto aesthetic down.
3:32:20
But, uh the question is that could you imagine him going headtohead, backto-back in a boiler room set with David Solomon?
3:32:25
I think he would give him a run for his money. >> Absolutely.
3:32:30
>> What else should we talk about today? It's 2:30.
3:32:32
Should we get out of here or should we continue down the timeline down the rabbit hole deeper?
3:32:38
>> You know, uh should we pull up this video?
3:32:40
Uh Dylan highlighted Dylan Abuscato highlighted uh there is >> react to a movie trailer.
3:32:47
>> Yeah, let's react to a movie trailer from A24.
3:32:49
It's called Marty Supreme.
3:32:49
It just was released this morning.
3:32:52
It features Oscar nominee Timothy Shalomé, Oscar winner Gwennneth Paltro, and of course, >> startup investor, >> Kevin, uh, Shark Tank Shark Kevin Olirri. >> Let's watch it. >> Hello.
3:33:09
>> Hey, it's Marty Mouser. I'm in the royal suite.
3:33:11
I saw you in the lobby yesterday. >> Okay.
3:33:15
>> Well, I never talked to an actual movie star.
3:33:16
You know, I'm something of a performer, too. >> Are you? >> Yeah. You don't believe me? >> I What? Do what?
3:33:22
You got the Daily Mail in front of you? >> This is you. >> Yeah, the chosen one.
3:33:26
>> It's a nice picture, right?
3:33:31
>> Are we going to get copyright for this? >> Probably.
3:33:33
>> And if you think that's some sort of blessing, it's not. >> Hopefully not.
3:33:36
>> It means I have an obligation to see a very specific thing through.
3:33:38
And with that obligation comes sacrifice.
3:33:43
>> Everything in my life falling apart. Let me figure it out. Do >> you need help? I could help you.
3:33:45
I know it's hard to believe, >> but I'm telling you this game that fills stadiums overseas, >> and it's only a matter of time before I'm staring at you from the cover of a Wedies box. >> The Wedies box.
3:34:00
[Music] >> Forever young. I want to be forever. [Music] >> All right. team movie night.
3:34:18
When this drops, we're doing it.
3:34:22
>> They uh I guess that's just Josh Say, but his brother David Safty is also a partner in most of his creative uh endeavors. >> Benny Safy. >> Yeah. Yeah.
3:34:30
Benny Benny Safty and Josh Say. That's the crew.
3:34:35
Um but they are fantastic at finding uh like undiscovered talent that would do well in film.
3:34:42
I just like Adam Sandler in Uncut Gems.
3:34:46
He's known as a comedian.
3:34:48
He'd done serious movies, but it was he was still kind of an odd choice for that.
3:34:52
They also cast Kevin Garnett as himself in Uncut Gems and that was like a fantastic performance and people kind of didn't expect uh an NBA player to just like jump straight into a prestigious Hollywood movie and do great. Uh Julian Fox as well.
3:35:04
The weekend was in uh was uh was in um that movie as well.
3:35:11
And then there's been a couple others uh where he's pulled odd folks in.
3:35:15
Benny Safty jumps in, plays.
3:35:18
So I'm extremely bullish on Kevin.
3:35:20
>> We're gonna end on this next post.
3:35:20
It's from the account financial dystopia.
3:35:24
>> Okay, we're playing this one.
3:35:25
>> But this doesn't seem dystopian to me at all. I can see why.
3:35:27
The uh caption is a remote salesman makes a call while he's driving a boat.
3:35:32
So let's >> spx maximalist.
3:35:34
Thank you for the shout out.
3:35:37
I'm glad you're tuning in daily. This is >> Maggie. How you doing, darling? Oh, we're blessed. We're blessed.
3:35:40
I'm sorry it's a bit noisy.
3:35:43
We're out on the lake right now doing some surfing for this weekend. >> Oh, yeah.
3:35:48
You ever done wake surfing before? >> I'm ready to buy.
3:35:53
>> Get your ass out here. >> This is amazing.
3:35:55
>> You scared of the water? >> Masterass. >> You can't swim?
3:35:59
>> You're telling me an AI agent is going to be able to do this?
3:36:02
>> I'd like I'd like to see an AI agent wake drive a wake surfing boat on a call.
3:36:08
We get you surfing no time. >> It's great.
3:36:14
>> Did you have a chance to talk?
3:36:15
>> Can we make an intro to Sam Bucket Ramp?
3:36:18
We need to get this guy on the ramp, too.
3:36:20
He's ready to close deals. >> Anyway, >> fantastic.
3:36:24
>> I have some breaking news, >> please.
3:36:25
>> Okay, so um XAI co-founder >> Igor Babushkin is leaving to start a venture firm >> that it supports AI safety research and back startups and AI agentic systems. Huge news.
3:36:38
>> Yeah, he he was number 24 on the menace list.
3:36:40
>> He was number 24 in the new in the in the V2.
3:36:43
>> Yeah, >> he's like super goated. >> Igor Babushkin. >> Absolute. >> Uh, wow.
3:36:48
11 minutes ago this broke and you guys got the >> Good work so quickly.
3:36:54
>> We have to get in the car and hit the road.
3:36:57
>> And Eigor, open invite. Come on the show.
3:36:59
Talk about your new fund.
3:36:59
We'd love to hear from you on this. >> Let's make it happen. >> It's fascinating. >> Great stuff. fun show today.
3:37:06
>> Leave us five stars on Apple Podcast and Spotify and we will see you tomorrow.