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into this world to shape our future.
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It takes us 20 minutes to get through it. Whatever. Just make it. You're watching TBPN.
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Today is Monday, June 30th, 2025.
5:00
We are live from the TBPN Ultra Dome, the temple of technology, the fortress of finance, the capital of capital.
5:08
We got a great show for you today, folks. It's summer.
5:10
Every venture capitalist is on is vacation.
5:15
They're celebrating the fourth in France. We're not. Yes.
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When literally everyone is abroad.
5:18
Uh but we're here in Hollywood, California, the future center of media and entertainment if we play our cards right.
5:26
We're going to take you through the five most important stories in technology and business from our perspective.
5:32
Kicking it off with a dramat Yeah.
5:36
Get that gasp ready because there's a dramatic story in Wired.
5:38
Open AI leadership responds to Meta's offers.
5:44
Someone has broken into our home.
5:44
That's the title of the article.
5:46
You could hear it was written, but you could hear the pain in Mark Chen's friend of the show.
5:54
I would call him a personal friend. He's a great guy.
5:56
We've had people try to poach our team members. Yes.
5:58
With I wouldn't say similarly sized off offers, but uh meaningful offers. Meaningful offers.
6:07
Um, but yeah, I mean certainly certainly a high stakes uh situation.
6:12
People think of OpenAI as a $350 billion juggernaut, 90% market share in consumer AI. They're doing great.
6:17
They they are the steamroller. Yep.
6:20
But you forget that Zuck's built different.
6:24
He has a hundred billion dollars in free cash flow every year to play with.
6:27
in the vibe shift from two weeks ago where everyone was like, "Oh, okay, Zuck acquired Scale and then, oh, he's got Nat and oh, he's got DG and and then Sam's like, well, they're they don't have any of our they're not recruiting any of they're not able to get any of our best people to it feels like somebody has broken into our house and stolen uh something is very significant."
6:52
So, Bill Gurley has the post that defined the story.
6:54
He says, "The company that was already planning to lose $7 billion this year, that's OpenAI, is re-evaluating comp to be more aggressive.
7:03
Put that in perspective."
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And he's got the yee-haw cowboy hat emoji on. I love it.
7:08
I love I love post, you know, retirement, Bill.
7:11
He's just like before he would be much more concerned about this.
7:16
Now he's got the the cowboy hat on.
7:18
He's just he's just watching riding into the sunset.
7:21
Just podcasting, riding in the sunset, talking about the drama.
7:25
We're gonna have him on soon. Yeah.
7:26
Um I saw there there was someone else posted that uh and I thought this was accurate.
7:31
People forget that Zuck yeeted like 20 billion dollars.
7:36
You know, he's willing to lose tens of billions of dollars and he can on this on this the MetaQuest 3S Xbox edition.
7:43
I don't think I don't think he yeated 20 billion on this.
7:48
I think it was worth every penny.
7:50
We're going to be putting this to the test on the show today. Stay tuned.
7:54
Tyler Cosg Gro, our intern, is going to be trying to beat the first level of Halo in virtual reality. Yeah.
8:01
But, uh, OpenAI has incredible access to capital, but they are losing a obscene amount of money.
8:06
Meta has incredible access to capital and can deploy it and still generate tens of billions of dollars of net income. Yes.
8:13
And uniquely, Zuck has incredible control over the board and shareholders and and and so he controls enough of the vote that he can't that he can't be he's also just so big, but he can't be the subject of activist shareholder attacks saying, "Hey, we want earnings per share to go up by a little bit more.
8:33
We'd like our dividends to be a little bit bigger."
8:36
He's in that early Bezos era where he has the full faith of the shareholders and also the legal control to actually go and spend, you know, tens of billions of dollars on a project that might prevent disruption, which is absolutely in the long-term best interest of He's not thinking quarter by quarter. Exactly.
8:55
He's he's fulfilling his fiduciary duty, just on a different timeline.
8:57
And so the only reason that an investor would be upset if they're like, "Yeah, well, I just want the stock to pop this quarter."
9:03
But he can tell those people that I'm not I'm not building with you in mind.
9:07
Uh so yeah, it's uh it's it's it's getting spicy.
9:10
It's some mark on Mark violence.
9:11
Mark Chad Mark Zuckerberg today. Pull it up.
9:16
Um I'm sure I'm sure half a point. The market loves it. The market. Uh no. Uh clearly what is that? Five billion. Yeah, it's five billion. Something like that.
9:26
Uh I mean five billion that'll pay for what? 50 researchers.
9:30
That's exactly how many you need, right? Yeah.
9:31
the the the who who who is telling us the price. Perfectly priced in. Yeah. Yeah. Perfectly priced in.
9:37
Um Nikita Beer, we got a trade deal, baby. Trade deal.
9:40
Nikita Beer has joined X as the head of order inbound.
9:43
You probably know him from his viral social apps.
9:48
Uh he's he's he's been he sold one to Discord.
9:51
He sold one to Facebook back in the day.
9:54
Now he didn't even have to sell one.
9:56
He's just going directly to He's goingirect.
9:58
He's joining as the head of product.
10:00
He's cutting out the middleman which were his startups basically.
10:03
Uh he says X is the most important social network in the world. Fully agree. Fantastic app. I'm I'm obsessed.
10:10
It's where we built this company.
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Uh it's where internet culture originates and where the world's most influential people convene.
10:15
Finding my community and building an audience on X has impacted my life more than any single thing.
10:20
It's unlocked friendships, professional opportunities, and it's even where I met my girlfriend.
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Well, I already spend every waking hour on this app.
10:28
I'll now be spending that time helping others unlock the same value and will certainly be leveraging the power of Grock to create hyper relevant timelines and help people understand everything that's happening.
10:37
Thanks Elon Musk and the X team for inviting me to work on the product that I live product but also poster and residence. Right. They lost Yepsine. Yes, they did. Or uh fired him.
10:47
Uh but they're bringing back a new poster and resident who residence who's going to be absolutely, you know, dominating the timeline. Yeah.
10:53
And I think I don't know it's interesting like Nikita's had success iterating very quickly on product and and and developing viral apps.
11:02
He's also spent enough time in large tech companies like Meta and Discord to like probably be able to play, you know, there's probably some overhead that still exists even in the leaner X.
11:16
So I wouldn't be surprised that he's actually kind of the perfect person there.
11:20
And then obviously the fact that he's so dominant on the platform and obsessed with it and really he's a power user.
11:25
That's probably exactly what you want in a head of product. So I'm bullish.
11:28
Are you bringing the gong?
11:29
You know why I have this out?
11:30
Why do you have that out?
11:31
Because the rumor is that X backed up the Brinks truck. No way. This one.
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So I'm going to hit the gong for Nikita. Hit Hit the gong.
11:38
Congratulations to Nikita Beer.
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He's been on a generational run and it continues as X is head of product.
11:46
I'm going to start texting him now when there's bugs. Yeah. Head of product.
11:49
That means I actually don't experienced that many bugs.
11:54
I've I I everyone says that there's a ton of bugs.
11:57
I haven't had that many bugs.
11:58
I think it's a skill issue.
12:00
I've been having great, but there are a bunch of things that could, you know, be improved with the product and so I'm sure he'll come up with some interesting ideas and it'll be a lot of fun to follow.
12:07
Uh anyway, in other news, you got to also ring the gong for Apple.
12:12
Our boy Tim Cook, he pulled in.
12:12
He paid for half of his annual salary uh just by selling a sponsorship in Apple's F1 movie for a fictional team APXGP.
12:24
Expensify paid an 8 figure sum to become the title sponsor.
12:27
They also uh sold sponsorships to Shark Ninja, IWC, the watch brand.
12:32
They really built it out and it makes it look better.
12:34
I think it makes it look better instead of legit.
12:39
No, it looks super legit.
12:39
Yeah, this was interesting.
12:41
I I I knew that um I don't have a lot of insight into how entertainment companies sell sponsorships in shows.
12:48
I know it's super prevalent, right?
12:51
You'll see like, okay, why is this character driving a Hyundai? Yep.
12:55
It doesn't actually make sense in the context of their life, but like clearly it's Hyundai. It's all over the place.
13:00
So sometimes like uh when I was running Soilent there were uh people who would come to us and just like they would just be like we had it on the set that day and we wanted to throw it in the fridge and so we did.
13:09
So you got a spot in this.
13:11
Uh we were in a Super Bowl ad once because they needed to the cars in the Fast and Furious movie were were driving through Time Square and they needed a uh they needed like some billboard in the background so they just put up an ad for our product, a virtual billboard.
13:26
billboard. So sometimes it's like we need some we need a product that we can clear like you know Andrew Huberman is going to be fine with us with us promoting you know matina yerba mate on here but if we were at a really really Hollywood level like we would have if we were going to drink like monster or red
13:42
we're at a Hollywood level but yes we are in Hollywood but there is a level above where where where like you would have to get clearance to use the thing in the actual uh in the actual film and so a lot of times it's Can we just get quick approval and not have to pay or not have to do any legal stuff? Other
13:59
Other times it's more complicated where they're actually going out and selling it.
14:03
It sounds like they sold this for this.
14:04
But anyway, and Poly Market of the Day, they didn't just make money on the sponsorships.
14:07
Yeah, the box was it 140 million. They crushed it. 140 blew it out.
14:13
Poly market had it uh if you were looking they clocked it last week. Yep.
14:19
Um it was uh the market was uh hasn't I guess it's the predictions were I mean the the the the core predictions were around like 55 million I guess was kind of the middle band here.
14:30
50 million and blew that out.
14:33
I mean F1's popular and it's it's so Have you seen the other F1 movies? Of course not. Why am I even asking? Ford versus Ferrari. You haven't seen that. Drive.
14:41
You haven't seen that right? No. No.
14:43
But big news I saw my first UFC event. So, I'm catching up.
14:49
Jord's gonna see his first movie.
14:49
I'm gonna see my first UFC event. It'll be great.
14:53
John Yeah, we had a good crew. It was a lot of fun.
14:56
UFC with with Senra, Rob Moore. It was great.
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And uh we had a great time.
15:01
John John asked, "Who's playing tonight on Saturday?"
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I said, "Well, John, I don't think they're going to be playing.
15:07
They're going to be fighting punching each other in the face."
15:09
And uh the knockout on Saturday was Yeah. spectacular.
15:13
My wife was like, "Oh, you know how like when guys go watch the football game, they like toss around the football beforehand?
15:20
Like, are you guys going to be like punching each other before you watch the punching?"
15:24
And I was wondering if you guys are going to be like, "Yeah, let's just go like spar a little bit before we sit down and watch UFC. Let's roll." Maybe we should do that. Uh, next time.
15:33
Anyway, um, this is actually massive news.
15:36
Toby Licki has it summed it up well, but so Tesla has the first the world's first autonomous delivery of a car.
15:43
So th uh this Tesla, I believe it's a Model Y, uh drove itself from the Gigafactory in Texas to its new owner's home 30 minutes away, crossing parking lots, highways, and the city to reach its new owner.
15:55
And Toby Loki says, "Put it on the front page of all the newspapers." Well, we printed it.
15:58
It's in the front page of TBPN.
16:00
What else do you need, Toby? Come on the show. No, this is significant.
16:04
It's It's uh costly to get a car delivered.
16:07
Obviously, if you're getting a car delivered from hundreds of miles away, the gas fees are going to be high, but uh it costs money.
16:14
The other thing, you just got a car recently and the shipper damaged the car while it was being shipped itself.
16:20
Now, needs to be repaired. So, yes.
16:23
And so, I'm I'm I'm very interested in what this actually means for like structurally for the business of Tesla.
16:30
will have to dig into this, but I wouldn't be surprised if like that like so Tesla's famously like cut out the middleman of like dealerships and I think that's really improved their margins.
16:39
And I imagine that that delivery is not an insignificant line item for Tesla right now.
16:45
Like you you order them, they have to put them on trucks, they have to deliver them.
16:48
There's all this extra all this extra step.
16:49
And I I feel like delivery fees are around a thousand bucks.
16:54
Maybe it depends on how far you're going, but like you have to have multiple people securing the car traveling with it.
16:59
It's not just every time I've bought a car hundreds of dollars outside of you know a few hundred miles away it ends up somewhere a thousanducks and so and so yeah you assume that there's like a 50% margin tacked on that and it's like a it's a high margin.
17:13
The other thing here is it's effectively passing on the delivery cost to the consumer because it's really just mileage, right? Yeah.
17:20
Mileage and and energy and then you get you get a half charged car and you're like you're like, "Okay, I got to charge it up."
17:25
But who cares about that?
17:27
Nobody car Nobody cares about that.
17:28
And so I I wonder I mean this this should be you know somewhat material.
17:33
I just wonder how material it might be like okay it drops their cogs by 0.
17:36
001% but it certainly is exciting and you could imagine we're one step closer to like push a button and buy a car and it just arrives which is very very cool.
17:46
Um, yeah, finger hovering over the button with that one.
17:49
I want to get one just um but I'll be waiting for the uh for the naturally aspirated V8 or V12. Yeah.
17:58
Version as soon as they roll out. Yeah. It' be fantastic.
18:00
Um anyway, in other news, uh your your naturally aspirated V12 Tesla is getting delivered. Yes.
18:08
And it's just getting noise complaints along the way because the AI is just joy riding it pulling over to do burnouts.
18:15
I mean, have you heard Doug's riff on electric cars?
18:17
He says that they're technically naturally aspirated.
18:21
They don't have turbochargers.
18:22
They don't have superchargers.
18:24
How are the batteries cooled?
18:26
Naturally, all the air flows through the car naturally.
18:29
There's no turbochargers.
18:30
Therefore, it is a natural car. Yeah.
18:32
Xiaomi Xiaomi is not far, right?
18:34
I I posted a picture today.
18:36
Their new car is just almost a one to one copy for Sway.
18:39
Yeah, the news is apparently it's selling very well.
18:44
They've they've got two over 200,000 or non-refundable orders.
18:47
Not just over 200,000 for the This is the electric SUV, the new Xiaomi. Uh 289,000.
18:56
And that's not just so far, that's in the first hour. Okay, that's a lot. Solid.
19:01
uh potential to show that we respect business.
19:05
I'm gonna hit the size gong.
19:07
Congratulations to the folks over at Xiaomi for ripping off the Puro songway success so successfully. Uh that's on B3.
19:14
Anyway, um the last top story we have today is from Luke Metro.
19:21
He says, "I know a 409 evaluator hates to see this coming because Robin Hood has tokenized stocks and everything else."
19:28
And so now there are private company stock tokens and they're shouting out OpenAI and SpaceX, but Luke Metro works at Anderol obviously has some stock options and uh he's getting ready to uh to trade them on Robin potentially who knows in the in the pipeline.
19:44
Yeah, in the pipeline I would imagine.
19:45
Yeah, this this is interesting.
19:47
I mean, we had uh Ken from Republic on last week also building his He must have known that this was coming or something.
19:53
Or maybe there's some underlying market structure bill, but this feels like it's a wave that's everyone's doing it all at once, right?
19:58
Part of it is that this administration has been extremely crypto friendly. Yep.
20:04
Seems like everything, not everything, but most things are fair game now.
20:08
And so I think a lot of companies saw this coming and have just been racing to deliver new product experiences.
20:14
It is funny to think about I I guess these uh the the SpaceX and OpenAI uh tokens are going to be available to European uh Robin Hood users only and so it is funny to think about when is European day trading open AI and SpaceX shares I mean um could be the best place for them to apparently rolling out on the on the Robin Hood chain so they're launching their own L2 interesting with arbitrum and uh I'm interested to see.
20:44
I saw they cleared Yeah, they cleared a an exchange of OpenAI tokens today or OpenAI stock like like the first transaction.
20:52
Yeah, the first the first transactions gone through.
20:55
Uh Luke Metro had another funny post that was like I just hope that my andal stock is valued at uh like the Robin Hood DJ retail trader valuation and not the price that Founders pays. This is very funny. That's good.
21:08
Anyway, oh sorry, are we blocking the camera?
21:10
Uh anyway, let's go through some uh some of the deep dives.
21:15
I want to I want to dig into that Wired article that was burning up the timeline over the weekend and then we'll we'll read through some of the Wall Street Journal coverage of the list uh AI's secret file of geniuses.
21:28
But first, we have our first intern challenge of the day.
21:30
We the first Yeah, there might be even when you finish this, Tyler, you're not you're not safe.
21:37
Uh we we we were we we purchased and and received a MetaQuest 3S Xbox edition. Very nice foil. Look at that foil. This is a nice product.
21:46
So this is the latest and greatest out of Meta for their virtual reality headsets.
21:50
And the challenge is to uh beat the first level of Halo uh complete edition, Halo CE. This is Halo 1.
21:59
Uh Tyler, you've never played Halo at all? I've never played Halo. Okay.
22:03
But you've played first-person shooters. Yeah. Okay.
22:05
So, you should be able to do it, you think? Yeah.
22:09
So, I asked Chad GPTatch, uh, the the the speedrun world record for Pillar of Autumn, which is the first level in the first Halo game, is like 3 minutes, but you have to like cheat and go through the walls and stuff.
22:20
Uh, an experienced player can do it in like 15 minutes.
22:25
Uh, first time person ever playing should be able to do it in between 20 and 30 minutes.
22:29
So for this, let's give you let's give you an hour.
22:35
If you can do I was thinking like 12 minutes.
22:39
Okay, let's give you let's give you 45 minutes.
22:42
If you can do it in under 45 minutes, you will get to keep this. Let's go. Okay. Okay.
22:46
So, uh can we get a timer? Yeah, start timer. So, it is it is 11:20.
22:55
Let's give you 40 minutes.
22:55
So, if you can do it before noon, so go get it and start. Okay, time to start now. He's hustling.
23:05
He's hustling for good reason.
23:05
All right, have fun, Tyler.
23:06
So, so the problem is that the level takes like five minutes, but unboxing and setting that thing up, I think, is going to take like 40 minutes.
23:13
Um, so that's the real challenge. God speed, Tyler.
23:15
But, uh, Tyler will be working on that during the, uh, during the show. And good luck to him.
23:21
Anyways, back to the timeline.
23:21
A poster by the name of Toucan says nerds is quoting on the left is Ronaldo.
23:30
Another post Real Madrid spent 80 million to sign him from Man United.
23:32
On the right is Ja Hu which I struggling to pronounce.
23:39
Meta paid 100 million to sign him from OpenAI.
23:41
And Toucan says nerds have been complaining that athletes are overpaid for decades.
23:45
Finally, the nine figure nerd trading market has emerged.
23:50
Take that LeBron Jameson.
23:53
Jameson doesn't even know his name. It's fantastic.
23:57
Um well, you know, if you're uh if you're on a hiring spur, you got to get everyone in your organization corporate cards. Head over ramp. com. Time is money. Save both.
24:06
Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
24:10
Um anyway, let's dig into this opening leadership. Uh the opening.
24:16
So, this was article was all this news was kind of coming out over the weekend.
24:22
Uh there's no there's no decency anymore.
24:24
You can't even take a summer weekend.
24:26
You can't even send an email to a 30,000 person organization without it leaking to Wired.
24:30
Um Mark Chen, the chief research officer at OpenAI, sent a forceful memo to staff on Saturday, promising to go head-to-head with social giant in the war for top research talent.
24:41
This memo, which was sent to OpenAI employees in Slack and obtained by Wired, came days after Meta CEO Mark Zuckerberg, successfully recruited four senior researchers from the company to join Meta's super intelligence lab.
24:53
Uh, I have a visceral feeling right now as if someone has broken into our home and stolen something.
25:00
Chen wrote, "Please trust that we haven't been sitting idly by."
25:04
I mean, this makes sense.
25:04
Like, you need to you need to tell the troops that like, you know, we're prepared to go on the counterattack.
25:08
like we got attacked but we're ready to go back.
25:10
What's interesting is like is like I don't think that I don't think that Meta is necessarily going to try and go eat chat GPT's lunch.
25:18
Like I was revisiting that conversation that we had with Jeff Huber and he was saying like you know he was kind of reiterating like never bet against Zuck.
25:26
like he's working on a open- source model, but a lot of it is is more of this like uh B2B applied AI necessarily than trying to go and and and disrupt chat GBT because Google's already running that playbook.
25:40
Like Mark can see that and see that like what happens when you're a trillion dollar company and you roll out a basically a direct clone of the chat GPT app.
25:48
It's like, yeah, you can get a decent amount of users in a num in a notional terms.
25:55
Like, I'm pretty sure the Gemini app has like a hundred thousand user or 100 million users and like lots of five-star reviews, but it just doesn't have anywhere near the penetration of chat GPT.
26:05
And so, when you pull someone off the street and you say, "What do you use for AI?" They say chat.
26:07
They don't even say chat GBT anymore because it's so dominant.
26:10
And so I think Mark knows that he shouldn't necessarily try and go after that, but he should be going after the next thing and the next next thing and have a model that he can pipe into all sorts of different u uh features within the meta ecosystem.
26:24
But yeah, the crazy thing is there there's not it doesn't seem like there's clear precedent for a raid of a talent raid of this magnitude, right?
26:35
We covered uh Ken Griffin rating Enron, but it was post the collapse, right?
26:39
Um Apple heavily recruited out of Xerox Park in in 1979 in the early 80s, but like kind of a downswing, right? Yeah.
26:49
It wasn't it wasn't Yeah.
26:51
It wasn't anything of this magnitude, nor was it, hey, we're going to come in and just give you these like nine figure off, you know, packages and things like that. Yeah.
27:00
And it's very common for a startup to to be able to pull people from the big legacy company that's kind of sclerotic.
27:07
And you know, we've seen a lot of people that were at Apple or Goo or or Microsoft or Xerox and then they went to Google and then they went to Meta and then they went to OpenAI.
27:19
I mean, Brett Taylor, who's the who's the chairman of the board at OpenAI, was the CTO of Meta, right?
27:22
And it's like, okay, he clearly just wants to be in like the hot thing and he's he's like a startup guy almost.
27:29
Um, and I I believe he was at Google before because he worked he Yeah. Yeah. He redid Google Maps.
27:35
And so like the like the story of Brett Taylor is really like the default I think for most like startup people.
27:40
It's like he's at he's he's early at Google.
27:42
He works with Paul Bukite on Gmail. He works on Google Maps.
27:47
Then he goes over to Meta CTO there.
27:50
Then he goes to OpenAI's chairman of the board there.
27:52
And it's like he is a he's a startup guy and so he's always riding like the new wave.
27:56
You usually can't poach them back into the older company. That's rare. Yeah.
28:00
Uh one one other some other precedent here in 201 in 2010 and 2011 uh Zach and Facebook went super aggressive poaching from Google. Yeah.
28:11
So Facebook had crossed half a billion users.
28:15
They were trans in that period of transitioning from a super scrappy startup.
28:19
Y um and they went heavy into Google.
28:22
So they went and got high performers from ads, search, mobile on the Android side and and some of the social product people from Google+ and Zach did something similar, not to the same scale, but just went and with these sort of heavy heavy heavy uh comp packages and was very successful.
28:41
Google had to respond and increase comp in in a number of different ways.
28:43
Do they poach any designers?
28:45
Any people that use figma. com?
28:46
Any people that think bigger, build faster?
28:48
anyone that you know because Figma helps design and development teams build great products together.
28:53
It would be a different place but but fortunately you can go to figma.
28:56
com and you can get started for free.
28:58
Um anyway, what do you think of the the the buzzword super intelligence?
29:04
This whole like they vote they've really rebranded it.
29:06
Is it a goalpost shifting? I think it's smart.
29:08
I think he he poached the the the word super intelligence. It's mine. It's mine now.
29:15
Yes, my doubt because uh and he's not saying and he's not saying the safe super intelligence team.
29:19
He's just saying super implies reckless intelligence implies reckless implies reckless super intelligence. I like that.
29:28
that. Um but it's funny because uh you know uh everyone was focused on like AI as a buzzword then it was uh AGI then it was now it's super intelligence but like you know within our group like we all think like super intelligence is kind of the old thing like everyone like me and you like we we know the secrets to this
29:46
stuff like like it's kind of it's kind of already priced in the real killers they're focused on the next thing you know what I'm talking about right giga intelligence that's the one that people are getting like really like the real killers are like, "Yeah, well, like a AGI is basically here. Super
30:00
Super intelligence is basically here, but giga intelligence, that's the one we're working on because we're going to need a new buzzword because we're burning through buzzwords and increasing rate."
30:09
And so we're just uh we we we just steamrolled the touring test completely blasted through uh AGI.
30:14
No one talks about AGI anymore. AGI is here. Yeah.
30:19
But you got, you know, super intelligence.
30:21
We're going to solve this buzzword.
30:22
We're going to churn through this in a year or two.
30:23
We got to start working on giga intelligence now. Yeah. this is the way.
30:27
Anyway, start adopting it.
30:29
Uh Chen promised that he was working with Sam Alman, the CEO of OpenAI, and other leaders at the company around the clock to talk to those with offers, adding, "We've been more proactive than ever before.
30:39
We're recalibrating comp, and we're scooping out and we're scoping out creative ways to recognize and reward top talent.
30:44
Still, even as OpenAI even even as OpenAI leadership appears desperate to retain its staff, Chen said that he has high personal standards of fairness and wants to retain top talent with that in mind.
30:57
While I'll fight for to keep every one of you, I won't do it at the price of fairness to others," he wrote.
31:03
Um, it's such a brutal dynamic if you're Mark Chen, if you're Sam, because not everybody at OpenAI is getting poached, but presumably Zuck is working with all the people he's poached already to identify who are the best people at OpenAI. Who do we really want? Yep.
31:21
And then going to them and making the maxed out offers.
31:22
Meanwhile, it it it you can't like the the team dynamic.
31:29
If you have a few researchers on a team and somebody gets you know, somebody's potentially getting poached by Meta and you say to retain them, you're like, "Okay, we're going to give you this sort of massive incremental grant."
31:40
And the other people on their team are going to be like, "Wait, well, is that my market value?
31:43
I didn't go talk to Facebook or I I didn't I I turned down I never took the meeting or whatever.
31:50
So, you should pay me the same thing, too." Yeah. Right. I'm loyal.
31:53
Shouldn't Don't you want to pay? I'm a missionary. Yeah. I'm a missionary.
31:55
Why are you paying the mercenaries more?
31:56
You should pay You should pay the the missionaries the same price just because they're missionaries. rough for sure.
32:03
Anyway, let me talk about and no, the the other the other thing is is it creates this like really nasty incentive to basically be like, oh yeah, you know, you maybe got hit up by a meta recruiter like many months ago and you can be like, yeah, I mean, they reached out to me and suddenly they're like hovering around you like being like, all right, what's it going to take?
32:26
You know, we really don't want to lose you.
32:29
Yeah, it is a Yeah, I mean it's crazy game theory.
32:32
Like every single conversation in a company is like this constant game theory and then timing that um timing that with Yeah.
32:42
with this like summer break that I guess opening eye was saying like hey everybody should take the week uh of the fourth off or not the week of the fourth but anyways you wanted to say something more important.
32:53
Well, I mean, you know, if you want to see who your high performers are, just look in the linear, right?
32:58
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33:00
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33:04
If Zuck were able to gain access to OpenAI's linear, it would be it would be illegal, but um yeah, it would also tell them tell them a lot.
33:13
Yeah, you don't want to do anything illegal, Zach.
33:14
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33:27
Uh so the news comes as competition for a for top AI researchers heating up in Silicon Valley.
33:34
Zuckerberg has been particularly aggressive in his approach offering $100 million signing bonuses to some open AI staffers according to comments Alman made on a podcast with his brother Jack Alman.
33:44
So, this this $100 million signing bonus.
33:50
This just got baked into the lexicon, but I was listening to Dylan Patel on uh Jordan Schneider's Chinat Talk podcast.
33:56
It's actually Transistor Radio, but it goes out on China Talk anyway.
33:58
Uh and Dylan Patel was saying that that might be that might be a kind of a game of telephone a little bit in the sense that it's possible that you could maybe be making a hund00 million over a number of years in stock based on appreciation.
34:18
But he was very skeptical that anyone was getting a hundred million on day one without any sort of strings attached for like a true signing bonus.
34:26
So, I don't know how real that was. Yeah.
34:28
And remember that the Zurich Zurich team came out and said uh the Zurich team explicitly said we didn't get it.
34:34
But I know I know the way that he phrased it.
34:38
Clearly, we're getting No, no, no. No.
34:38
I I I I do think that that the the round numbers are obsess are easy to latch on to.
34:46
Like why is mom Donnie talking about billionaires specifically?
34:49
He doesn't have a problem with 999 millionaires because like that that's like not easy to grasp.
34:55
like people latch on to round numbers. 100 million is so much.
34:57
A billionaire is so much.
35:00
And it's easy to it's easy to quantify.
35:02
And so the hundred million, if it was 80 million, it wouldn't be going nearly as viral as 100 million.
35:08
Um and so so I I I don't know.
35:11
I don't know how real that is.
35:12
Maybe that was thrown out as a total package and then it got kind of telephoned into well, you know, they it's basically a signing bonus because they they got the deal on the on the as soon as they signed, but they do have some sort of earnout or the shares are locked up in some way.
35:26
But there's a bunch of creative accounting that can go into basically delivering someone what feels like a hundred million dollars of value, which is not far off from, okay, what what would it take?
35:36
you know, Johnny IV got, you know, a huge offer to go to OpenAI and it was structured in an interesting way with like an acquisition and, you know, but he got what got a few points.
35:48
Yeah, we it was a few it was a few percentage points and when you think about the scale of OpenAI and the scale of Johnny Ives legacy like yeah like what would it take to get someone like that to join your he's a founding designer basically so it's a couple couple percentage points.
36:01
Um, so multiple sources at OpenAI with direct knowledge of the offers confirmed the number to wired.
36:08
So I don't know because it kind of benefits like both sides to to have that number out there.
36:14
It's kind of unclear who would who would really want to confirm that and then what the nature of.
36:20
nature of. The other thing that's interesting though, the other thing that's interesting is if you're working at OpenAI and let's say their top researchers have on average $100 million in OpenAI shares that they're like the truly top people and then you get an offer that's like a $20
36:40
million signing bonus, but it's, you know, it's kind of paid out over time and that or or they can claw it back if you don't stay past a certain and you're kind of looking at it and be like, "Okay, I'm already a centi that I don't know if I'm going to like and it's unclear." Like the vision is
36:58
Like the vision is not quite as clear at meta, right?
37:01
I'm joining the super intelligence team.
37:06
It's going to be an incredible group of people with a ton of resources. That's exciting.
37:10
But it is a big switch if you're already happily vesting out tens of millions of dollars.
37:15
So it would make sense that these $20 million, you know, if it's $20 million, Yeah. I can see that.
37:23
If it's hund00 million for the for the top top top people, it makes total sense. Yeah.
37:28
I mean, like what was the uh I mean the the deal to bring on Alex Wang was probably like way over $und00 million to him personally based on his ownership in that company which was acquired.
37:40
And so like that number doesn't feel impossible.
37:45
Uh I would just be surprised if there's not some structure around it.
37:50
Um based on based on what Dylan was was talking about, there's just enough precedent here that again going back to uh Zuck rating Google in in 2010 2011.
38:02
He was offering tens of millions of dollars in stock packages to mid-level engineers just because he was like, I need a really good ad product.
38:07
I want to make my ad product great. Yeah.
38:08
I mean, have you seen the why am I even asking this?
38:12
Have you seen the Blackberry movie? Of course not.
38:13
But the but in the Blackberry movie, there's this whole story about uh they go and and they try and poach someone and then it was controversial because they like backdated some stock options for someone to basically give them more uh like cash but without having like the the the initial impact of that cash.
38:30
It's kind of interesting.
38:32
Um but yeah, I mean to poach top talent, it's expensive.
38:34
Um it kind of benefits both maybe.
38:36
I mean, I don't know, like on on the meta side, do they want does Zuck want the idea that he's willing to pay up to hund00 million out there?
38:46
Like, maybe because that that certainly leads to more people taking the phone call of like, oh wow, Mark is really taking this seriously.
38:53
I should I should talk to Meta's recruiting team.
38:55
I should actually hear them out.
38:58
And then if they wind up coming back to me with a $50 million offer or a $10 million offer, like, you know, we can discuss that and I can see and they can evaluate how much I'm worth. They can make an offer.
39:10
But, um, at least it got the conversation started. But, I don't know.
39:16
There was also the theory that Sam Alman put that $und00 million number out in order to kind of like poison the well because if if Mark comes to you and says, "Hey, you're a top a AI researcher. Come over here."
39:27
And then the top a the AI researcher says like, "Yeah, great.
39:31
I hear I hear $100 million is the going rate."
39:33
And Mark's like, "No, no, no.
39:34
That's like fake news that that Sam was spreading like we're actually paying 15."
39:38
Then you're like, "Well, no."
39:40
Like I was I was hoping for 100 mlian people and Yeah. Yeah.
39:44
You see it could be like 40 chess on both sides. I don't know. Yeah.
39:49
don't know. Yeah. Um, over the past month, Meta has been aggressively building out their new AI effort and has repeatedly and most unsuccessfully tried to recruit some of our strongest talent with com with with uh comp focused packages, Chen wrote on Slack, a source
40:03
close to the efforts at Meta confirmed the company has been significantly ramping up its research recruiting with a particular eye toward talent from OpenAI Google uh OpenAI and Google Anthropic, while also a top rival is thought to be less of a culture fit at Meta, one source tells Wired. They
40:17
They haven't necessarily expanded the band, but for top talent, the sky's is the limit.
40:22
Which is funny because yeah, of course, like anthropic is like so missionary driven.
40:25
Like it's going to be very hard to to to go to anthropic uh research scientists and be like ads, better ads.
40:34
They're like, we're building God here. Yeah.
40:36
Anyway, $100 million is $100 million.
40:40
Not for not for anthropic guys.
40:42
Anthropic guys are true believers.
40:44
They don't care what's $100 million in a post scarcity world. doesn't matter.
40:47
You want to be on the you want to be on this on the on the post scarcity train.
40:51
Uh Chen's note including it is so it is so telling though like how how you like sort of like try to you know pinpoint like Zuck's views on AI.
41:04
He's like I'm not even going to bother with those people. Not a culture pitulture. Two AGI pill. Yeah, that's great. Senator, we sell ads.
41:14
Anyway, if you're looking for sales tax super intelligence, go to numeralhq. com.
41:19
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41:32
Uh, Chen's note included messages from seven other research leaders at the company where they wrote notes to staffers in an apparent effort to encourage them to stay.
41:40
One leader on the research team encouraged staff to reach out if they received an offer for Meta.
41:43
If they pressure you or make ridiculous exploding offers, just tell them to back off.
41:48
It's not nice to pressure people in potentially the most important decision.
41:52
Wired is not naming the leader as they are not a seuite executive. Um, this is weird.
41:58
Where's the where's the end of this quote? That's odd.
42:00
I'd like to be able to talk you through it and I know all about their offers.
42:05
Uh, the remarks come as OpenAI staff grapple with an intense workload that has many staffers grinding 80 hours a week.
42:11
OpenAI is largely shutting down next week as the company tries to give employees time to recharge.
42:17
Let's give it up for OpenAI's grind set. It's really fantastic.
42:19
Also extremely American to give a full week off right around July 4th.
42:24
Like I'm normally pretty anti- taking time off, but if you're going to go really hard on a particular holiday, make it July 4th, you know?
42:34
Yeah, give a week off around July 4th. I love it.
42:36
Um, I was I I I was posting, you know, the over I need a poly market on uh whether or not we get a Zuck American flag video on July 4th.
42:46
Do you think it'll happen?
42:46
I actually think there 100% should be a poly market on that, right?
42:51
It's kind of 50-50, right?
42:52
Like he's definitely locked in, very busy, probably not a lot of time off.
42:57
He sees that he knows from this that OpenAI is down this week.
42:58
So that's probably like really encouraging to be like, I want to go harder this week. They're off. Yeah.
43:04
My my uh at the same time my advice for founders one of the greatest pieces of content he puts out is think about how hard Zach is going right now the week of July 4th and just don't get outworked by him. Yes.
43:18
Just don't get outworked by Zach this week. It's going to be tough. He's in year 20.
43:22
What excuses do you have?
43:24
You're you're three months into your startup. Yeah. Come on. Go harder. Go harder. I love it. Uh yeah.
43:31
Meta knows we're taking this week to recharge and we'll take advantage of it to try and pressure you to make decisions fast and in isolation.
43:37
Another leader at the company wrote, "If you're feeling that pressure, don't be afraid to reach out.
43:43
I and Mark are around and want to support you."
43:46
So, while OpenAI's leadership is taking Meta's efforts seriously, Chen also said that the company is getting too caught up in the cadence of regular product launches and in short-term comparison with the competition.
43:56
The sentiment is backed by a former OpenAI staffer who worked closely with Altman and the and said the CEO wanted to see buzzy announcements announcements every few months.
44:03
This was a really this was key to their strategy was like always have a buzzy announcement ready if the competition does anything.
44:11
Just drop a Oh, Google IO is happening.
44:14
Wouldn't it be crazy if we acquired a company called IO the day before or something like that?
44:18
Like or like oh there Google's announcing the new Gemini.
44:22
Let's just steamroll them in the timeline the 24 hours before.
44:23
Yeah, I'd love to introduce you deep research.
44:28
Deep research like I mean it's it's masterful and like but that's the game you got to play.
44:31
That's the game on the field.
44:33
Like I I I I think he really aggressive but he's not doing anything wrong.
44:37
He he um is up there with Elon in terms of creating and riding hype and constantly delivering enough real product value. Yes.
44:49
To justify the hype that that was being sold, you know, 6 months ago basically.
44:54
So like staying on the bleeding edge.
44:56
And this is why the anti people hate hate him and Elon so much because they're like they're like it's overhyped. Uh it's not useful.
45:02
And then like a year later it's like there's Tesla cars everywhere.
45:06
The rockets are landing and like 90% of people are eating chak every day. Okay.
45:14
So it was real but also he was overpromising but he delivered at a at a higher level than anyone in human history and that's just like it's it those two things are in in in conflict.
45:25
So, someone said this like Elon is both Thomas Edison and Barnaman Bailey or whatever.
45:30
PT Barnum like he's a circusman who can put on a show and put a robot in a a human in a suit acting like a robot, but then he can actually go and deliver the thing.
45:38
Um, which is just it just breaks people's brains.
45:41
Um, anyway, we need to remain focused on the real prize of finding ways to to compute.
45:48
A lot more supercomputers are coming on later this year into intelligence.
45:52
Um, uh, Chen wrote, "This is the main quest, and it's important to remember that skirmishes with Meta are the side quest.
45:58
Last but not least, I'll be around this week, recharged and ready to go pound-forpound. DM me anytime. I love it. He's ready to go. Fired up. Get him."
46:06
I love talking with Mark.
46:08
Yeah, that was a that was a fun conversation.
46:10
Also, I mean, guy's in shape.
46:13
Let's get him in the Let's get him in the octagon with Zuck. Mark on Mark violence. Let's see it.
46:16
I mean, and if if there was a pound-for-pound list for the top AI researcher, in the world.
46:22
He's in the conversation.
46:24
He's in the conversation. It's amazing.
46:27
It's really been amazing to watch Mark's leadership and integrity through this process, especially when he has had to make tough decisions.
46:32
Alman wrote in on Slack in response to Chen's message.
46:35
Very grateful to we have him as our leader.
46:37
I mean, these it can't be overstated making these decisions, right? Yeah.
46:43
One of your best people comes comes to you and says, "It's hard. Hey, yep.
46:47
I'm really happy here at OpenAI. Yeah.
46:53
I have $80 million of stock. Yeah.
46:56
And I was just offered $150 over the next year and it's highly lick or over the next few years.
47:01
It's highly liquid, meaning that I can market sell it quarterly forever. Yeah.
47:06
And meanwhile, you're going through this for-profit conversion.
47:12
Do you think the liquidity thing is real at all?
47:13
I mean, obviously, what are you I mean, like, if you want to, let's say you want to buy a $50 million house and you have a hund00 million in like illquid open AI, like, is that going to be hard at all?
47:25
I feel like Goldman Sachs and Morgan Stanley, private wealth management are going to be beating down your doors to give you a loan that's backed by the shares.
47:32
You're only going to have to put down 10%. Sure.
47:35
But, but meanwhile, the company's failing to go through a for-profit conversion. Yeah.
47:40
But I mean, so that Satcha's taking 20% off the top. I mean, that applies.
47:46
No, I'm just I'm just saying that applies like a a small haircut.
47:49
I I would say I'm just saying there there is always Yeah, there's always going to be a tension of somebody having massive wealth but not having green backs.
47:58
Yeah, there's always going to be that tension. Yeah.
48:02
And people seeing that that Meta is one of the most liquid stocks in the world. Yeah.
48:11
can constantly trade in and out of it and it's ultimately just it's stable, right?
48:15
So, I mean, if you're interested in liquid stocks, go to public. com.
48:19
Investing for those who take it seriously.
48:21
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48:24
And who knows, maybe they'll have open AI soon.
48:29
Anything's apparently anything's possible.
48:31
You Yeah, we should we should, you know, Robin Hood has uh you know, uh the the tokens around private companies.
48:39
Maybe we should tokenize nonprofits.
48:39
I want to be able to trade, you know, uh uh PETA, you know, let me let me let me go long PETA.
48:49
Let me get some let me get some leverage on that.
48:50
I want some uh levered options on PETA. Look at Tyler right now. Tyler cam.
48:57
How are we doing on I think I'm I think I'm in the right mission. Oh, you did it. No way. 15 minutes left. Let's see it. Okay. Okay.
49:04
I can't believe you got it set up so fast. That's amazing.
49:10
Okay, you honestly he's sitting at he's sitting at 26 minutes so far.
49:13
All right, well have fun in there, Tyler.
49:16
I just look over and I just I didn't realize he was on VR. That's amazing.
49:20
I think he's actually playing it.
49:23
This is crazy because my number one complaint with uh with the Quest was that it just takes a long time to set up.
49:28
And I think that it you intentionally did this challenge and made it seem like, oh, I'm going to happily give away my my new my VR Xbox thinking that it there's no way he could finish it in 40 minutes.
49:41
But now now he's I think he's going to speedunn.
49:46
Pillar of Autumn, it's happening.
49:46
Um anyway, uh Swix has the story. He's breaking it down.
49:52
Some good highlights here.
49:53
The Mark Mark the Mark war has resulted in going from oh the good people don't leave to someone has broken into our home and stolen something.
50:01
One week company shut down question mark question mark.
50:07
I mean I I was going back and forth here.
50:10
I wouldn't be surprised if the shutdown was somewhat strategic. Yeah.
50:15
In that hey people already need a break.
50:17
We shouldn't have them walking around the office the way they were writing it.
50:20
It felt like this had been on the table for months because the company has been working really hard launching a ton of stuff.
50:27
Uh, and it seems like if it just seems like an odd an odd choice to if you're in the middle of this Mark vark war that that would be what you tr choose to do would be a oneweek company shutdown.
50:39
But I don't know, maybe um I I I I just I'm not 100% that like the the AI talent war has resulted in the shutdown.
50:47
It's more just like the shutdown is happening at a weird time.
50:51
Uh anyway, uh this third point is very interesting.
50:53
Pivoting product launch calendar to AGI race, especially when Stargate comes online.
50:57
Uh Dylan Patel says December is when Stargate's coming online and that should be uh a big like the biggest the biggest cluster ever and unlock even even more maybe pre-training scale, but there's a question about how important that is and maybe you can do more reinforcement learning in a more distributed way. So I don't know.
51:17
distributed way. So I don't know. also like it's not exactly like Zuck is GPU poor so I don't know I don't know how big of a deal it is the Stargate thing we'll see but number four uh for some reason Meta is ignoring anthropic don't care about safety if this is true of
51:35
course uh the anthropic point was very funny uh anyway uh there's other posts in here that we should cover uh Satwick Singh says what Sam never understood was that Zuckerberg torched 20 billion over VR headsets with Nintendo Wii graphics and didn't even flinch didn't flinch. You know what's so funny? Like those the
51:50
You know what's so funny?
51:50
Like those the the Nintendo Wii graphics thing that was like that was like three months and then after that it was he was doing that that Lex interview in the metaverse.
51:58
Did you ever see that where it's like it is like photoreal immediately?
52:05
We got a wild demo at Meta HQ of all the new products and we were blown away.
52:10
I'm not even sure I don't think we can say much.
52:13
talk about it in like the abstract.
52:14
But um but yeah, I mean none of that was like Nintendo Wii level graphics.
52:18
But um but but I mean that that was that one picture was like iconic and kind of like it felt like oh this is kind of a step back in terms of well many more people saw that picture than actually used the product. Yeah.
52:31
And so yeah because there were plenty of there were plenty of VR games that didn't have Nintendo Wii graphics.
52:34
like the hero game for the for the Quest when it came out was Robo Recall, which looked super sci-fi and just looked awesome and it was it was it was great.
52:44
And there were a bunch of other games.
52:45
But yes, I mean the point is is that like uh Mark is totally ready to spend $20 billion on a big project if he thinks it's valuable and here he clearly does and so he's going after it.
52:54
Um anyway, uh similar founder company that's building amazing AI stuff.
53:00
Finn, the number one AI agent for customer service.
53:05
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53:08
He's been on number one in performance benchmarks, number one in bankoffs, number one on ranking on G2. Let's go.
53:15
So, if you're looking to do customer service, head over to Finn.
53:17
I'm saying this, they're not saying this, but I'm going to say this is the official the official uh uh uh AI CX tool of a both AI safety and being AGI built because Anthropic uses Oh, really? No way. There we go. Okay, awesome.
53:36
So, um yeah, I'm sure anthropic love that they're like, we said we could put our logo on your website.
53:43
We didn't say these the technologies daily podcasters go way over their skis on this endorsement.
53:50
It's the official CX agent.
53:50
Anyway, Rune had an interesting uh take here uh diving into the the why the these trade deals are so they're not really trade deals, but these poachings can be so can be so damaging.
54:04
And he's trying to put it in broader consumer terms.
54:05
We're going to debate whether or not his point is well taken.
54:09
Uh he of course works at OpenAI and has for a number of years.
54:12
Uh Run says intellectual property by default is a market failure.
54:16
Single well-informed talented defectors can walk away from organizations with billions of dollars of tacet value of knowing what works and what doesn't.
54:26
The athlete me metaphor is somewhat wrong.
54:30
In industries where patents and such aren't viable, market participate aren't viable, market participants will drastically underinvest in R&D efforts due to IP seepage.
54:39
Just like the I drink your milkshake milkshake effect of oil seepage and land rights, there is a compelling proconsumer case for non-competes. Interesting.
54:51
Very rare that you hear a tech person argue in favor of non-competes. Uh interesting.
54:56
I mean the the the immediate impact of non-competes in this context would be dramatically lower wages for AI researchers like Rune. Uh which is interesting.
55:07
Um the other question is and it's interesting you'd have to move AI out of California.
55:15
Oh people would then m maybe or they or they I'm saying I'm saying if you really want to use non-competes go where they can be enforced, right? Yes. as historically. Yeah.
55:27
But then as a as an AI researcher, you'd say, I definitely don't want to leave California because I'm going to get a much better deal here school here. Yeah.
55:34
My my question is like I've always been interested in like why can you know like the consumer packaged goods industry like patent like a tab on a can for 25 years and like Walt Disney can own like the shape of mouse ears for like 80 years but like Google can't own the transformer for like even a minute.
55:54
Like I get that it's like some sort of fundamental discovery, but I've always been interested in how little IP works in technology.
56:00
So that's I think it just is isn't is a byproduct of hacker culture sort of like positive sum culture of Silicon Valley. Yeah.
56:12
But you think that would change if there were millions of dollars on the table, right? Yeah.
56:18
I mean there's a culture of you know.
56:20
So I agree with and I'll give you an example.
56:22
So, so, uh, pull to refresh on the iPhone was created by a Twitter employee, like a Twitter UX UI developer, built that, built that user interaction.
56:36
And then Twitter had a patent on it, Lauren Bricter. Yes.
56:41
American soft software developer best known for creating refresh the poll to refresh interaction.
56:46
So, he created that that design pattern and then he had a patent on it.
56:50
Twitter owned the patent and Jack Dorsey and the Twitter crew were libertarian and said, you know, we're not going to enforce this.
56:57
And then it got baked into Instagram and it's it's now natively in iOS and it's in in all of, you know, it's basically like one button to like if you're if you're tr if you're truly terminally online, you're using it hundreds of times a day. True. Like a little slot.
57:14
Now we've actually moved past that.
57:15
We moved into endless scroll.
57:18
uh where you actually don't need like if you're on Tik Tok, you're never pulling to refresh.
57:21
You're just keep you just keep scrolling to the bottom.
57:23
So So we're actually post pull to refresh and now we're in the endless scroll, but endless scroll I believe was developed by Pinterest and they had a patent on it for a while.
57:32
I think it might be wrong here, but but endless scroll was also something that was not able to be owned.
57:38
Uh which is just odd to me.
57:38
Um, and then and then there's the other question of like Coca-Cola's been able to keep the the the you know the formula as a trade secret for like a hundred years or something.
57:48
And it's just odd that that tech companies can't seem to do either.
57:52
They can't keep the secrets.
57:52
You can have trade secrets, right?
57:54
It's not like an OpenAI researcher can go over and say, "Here's here's bunch of code.
57:59
Let's roll let's roll it out." Right. Yep.
58:02
it it's basically their the in the the sort of way of doing things that they've internalized from being at a company. Yeah.
58:11
For a certain amount of time tacet value of knowing what works and what doesn't.
58:14
And so the my my like naive read on this is that if you had had a top tier open AAI researcher at meta during the llama 4 buildout, that researcher would have said, "Hey, don't focus on pre-training scale as much.
58:29
We need to get a reasoning model out and we need to focus on RL and post- training much more. Yeah. Much more.
58:35
And and when you talked to Dylan Patel, I was asking him about deepseek and how deepseek was was was doing all these innovations and like moving to floating point 8 like smaller uh smaller basically smaller numbers storing the weights.
58:47
And he was like, "Oh yeah, but OpenAI was doing that like two years ago.
58:51
Deepseek just open sourced it."
58:52
And so it's like the world found out if you found out the best practices from deepseek because they open sourced it.
59:00
Like you were not on the cutting edge and you should have been poaching AI researchers from the top labs earlier.
59:05
So two things could be could be happening here.
59:07
one, Zuck is right to just go and overpay and and try to recreate some of the magic and and get a, you know, leading a leading model or or set of models out of it that he can use in a bunch of different ways that we've discussed or none of this matters and run is is baiting baiting Zach into just overpaying.
59:32
This is like the 40 chess is like, "Oh yeah, this is they're getting everything.
59:36
They're taking everything." Yeah. Yeah. Yeah. No. No.
59:38
I I I don't I I don't necessarily believe that because I I did talk to Run like years ago and I was like, but like is this going to commoditize?
59:46
Like is the foundation model layer going to going to commoditize?
59:49
commoditize? And he was like there like there are like the secret to open AI in many ways is like the tie secrets like they understand things at a lower level that other that other people just don't and so that will compound and stay advantage and he hadn't even predicted
1:00:03
the uh the the the dominance of the consumer and like the aggregation theory that happens when you're the front end to consumer AI that's incredibly valuable but just on the research side just on the research side like they can stay ahead just by understanding like the secrets of what works and what doesn't. Um, but it's interesting.
1:00:18
Um, but it's interesting.
1:00:20
Anyway, uh, let's tell you about Adio.
1:00:22
Customer relationship magic.
1:00:22
Adio is the new is the AI native CRM that builds, scales, and grows your company to the next level. Next level. Next level.
1:00:29
Uh, it well, I mean, we, you know, we we we have a light guest booking today.
1:00:36
Um, but, uh, you know, we're spending an hour talking about one story because it's fun stuff. Uh, we can continue.
1:00:42
We can we can do go over to the Wall Street Journal uh because in the exchange section there is a a fantastic article related to this says it's known as the list and it's a secret file of geniuses. And I'm looking at this.
1:00:57
It says uh Mishka Baleno Yu Jang uh Mark Zuckerberg's been reviewing this list.
1:01:03
Lucas Buyers on this the new guy says Jordy Hayes, John Kugan, Tyler Cosgrove, Ben Kohler, a couple other folks, but you know just the usual people that we know.
1:01:12
Uh anyway, it's known as the list and it's a secret file of geniuses.
1:01:18
Only select AI researchers have the skills for the hottest area in tech.
1:01:22
Mark Zuckerberg and his rivals want to hire them even if it costs ungodly sums. We love ungodly sums.
1:01:26
We should be ringing the gong more to this this this episode.
1:01:30
All over Silicon Valley, the brightest minds in AI are buzzing about the list.
1:01:35
a compa a compilation of the most talented researchers and engineers in artificial intelligence that Mark Zuckerberg has spent months putting together.
1:01:43
Lucas Byer works in multimodal vision research which Kyler broke down for us.
1:01:48
Can can you imagine if if if Zuck spun up like basically like a hot or not style tool that's just like pins pin p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p pins two researchers together and like he makes other researchers like just do the test and then just puts out a list of like these are the this is the the top 50 people. Yep. This is so good.
1:02:07
Um uh so uh Lucas Byer describes himself as a scientist dedicated to the creation creation of awesomeness.
1:02:19
Ejang very Reddit coded but he's a poster on X as well.
1:02:22
E Jang specializes in automatic speech recognition and barely has an online presence besides his influential papers.
1:02:33
Misha Baleno is an expert in large-scale machine learning who also enjoys hiking and hill clim uh hiking and skiing or as he puts it on his website applying hill climbing search and gradient descent algorithms to real world domains. That's very cute.
1:02:47
Uh the recruits on the list typically have PhDs from elite schools like Berkeley and Carnegie Melon.
1:02:52
They also have experience at places like OpenAI in San Francisco or Google DeepMind in London.
1:02:57
They're usually in their 20s and 30s and they all know each other.
1:03:01
They spend their days staring at screens to solve the kinds of inscrutable problems that require spectacular amounts of computing power and their previously obscure talents have never been so highly valued.
1:03:10
The chief executives of Tech Goliaths and heavyweight venture capitalists are cozying up with a few dozen nerdy researchers because their specialized knowledge is the key to cashing in on the artificial. It is funny. It is funny.
1:03:23
Some of the, you know, some of the losers out of this talent war are just VCs because how do you compete?
1:03:27
How do you compete when you know historically you could have gone to some of these and really overpaid to invest?
1:03:37
You could have come to them with a ridiculous what what would be very ridiculous for a VC which is I will spin up a new company. Not ridiculous.
1:03:42
It happens but it is kind of ridiculous in some ways. Spin up a new company.
1:03:46
I'll give you 200 on a billion and you can take 10 million personally in secondary immediately. Yeah.
1:03:55
And that is no longer even that compelling of an offer if the odds of actually winning are low and you just want the most access to compute and be traded.
1:04:11
Uh, absolute absolute banger whipping.
1:04:14
This was this was Tyler's handywork. Oh, Tyler, how we doing?
1:04:16
I I have I'm in like some kind of maze right now. Oh, no. You lost. No, I lost already. I think you lost. It's past noon. It's past noon.
1:04:28
Wait, Ben, what you got on the timer?
1:04:30
I've got four minutes still on the tape. Four minutes still.
1:04:33
Okay, let's give him another four minutes. You better finish this.
1:04:35
I'm surprised, but I bet you I bet you if we roll the tape, it took him 30 minutes to set up.
1:04:43
And he's and he's actually on track.
1:04:43
I bet he's going to I bet he's going to finish the pillar of bottom the level in normal time, like 20 to 30 minutes.
1:04:48
But the setup was cuz I only gave him 10 minutes for the setup. Moged.
1:04:52
Anyway, uh This is this is the reality of of pledging pledging to be a technology brother.
1:05:02
I guess uh nobody is in this escalating arms race is chasing the prize recruits quite like Zuckerberg who has tried to raid Silicon Valley's top research labs dangling hundred million dollar pay packages.
1:05:14
We're hearing it again to a select few superstars in hopes of poaching them.
1:05:17
Uh the billionaire CEO of Meta wants them to join his new company's new lab focused on super intelligence.
1:05:22
Uh, one recruit has who has spoken with Zuckerberg, who is personally courting his dream team of potential hires, describes the company's goal as nothing less than a transfusion from the country's top AI labs. It's all it is. It's a transfusion. Blood transfusion.
1:05:37
It's a blood transfusion. Uh, it is it is wild. Yeah. Uh, yeah.
1:05:39
I I we we got to talk to some more VCs about how they're coping.
1:05:44
We got We got to get some coping VCs on here to hear them cope about Yeah. Yeah.
1:05:48
It's actually a fine time to invest in AI.
1:05:51
Hey, what do we got here? Tyler, I'm done. I'm done. You're done? No way. What's the clock? What's the clock?
1:05:55
2 minutes 45 seconds left. No way. He did it. Oh, that's amazing. Wow. Congratulations, Tyler.
1:06:05
Did you even get to play your new? He He had to unbox it. I did.
1:06:10
I wanted the unboxing to be part of the experience. Wow.
1:06:13
He just ate your lunch, Sean. He did. Congratulations, Tyler. Very good. That's amazing. Oh, okay. So, break it down.
1:06:21
How long did it actually take you to get set up and get the game running? Uh, yeah. Well, okay.
1:06:24
For the first like 5 minutes, there was just like a software update.
1:06:27
And then, that's what I was worried about. Yeah.
1:06:29
And then I had to connect to my phone.
1:06:30
There's like the Meta Horizon app. Yep.
1:06:31
And then it was probably like another couple minutes, I had to create a new Microsoft account and then get Xbox Game Pass.
1:06:37
And then I I wasn't sure which Halo it was, so it took me like a minute or two there. Yeah.
1:06:43
And then the first like probably five or six minutes of playing the game was just cut scenes. It wouldn't let me skip.
1:06:49
I'm like, it's like the tutorial of how to play the game and then finally and then I just crush through it. Okay. Crush through it.
1:06:56
So, uh, how long do you think it actually took you to go from like I gave you the box to you were playing the game?
1:07:03
Uh, I actually have no idea.
1:07:03
I mean, I was pretty locked in.
1:07:06
I don't know how long I was playing. Okay.
1:07:07
We should have had splits because um because my my my big push back on VR right now is that if you get an N64 or you get an like the old if you if you got an Xbox for Christmas with Halo the DVD like you would put that thing in, plug it into the to the TV and you would be playing in two minutes.
1:07:26
Like it was so fast to get up and running.
1:07:29
And I've always been upset with how many things you have to you have to link it to your phone, take it off, log in, create a password, like all of that.
1:07:36
that I've always been really annoyed with.
1:07:37
I think that they should make you do the account creation after the fact, after they let you get hooked on playing and be like, "This is fun. Okay, cool.
1:07:44
Yeah, now I want to create a social profile because I'm I'm having fun."
1:07:47
Anyway, yeah, I mean, the app seems very unnecessary.
1:07:49
I don't know what the app is for. Odd.
1:07:52
Because it wasn't like to sign in.
1:07:52
I I still to sign in on the using the joysticks.
1:07:56
I mean, at one point I had I had four I I I counted I had like six different passwords that were relevant to play Oculus games because I had I had a PIN code that was like you draw it.
1:08:06
I had a qu uh an Oculus password, but then Oculus got rolled into Meta and so I had a Meta password, but then I also had a Facebook password that was different.
1:08:18
And then I had like a PIN for paying with things.
1:08:20
And it was just like so many different things.
1:08:22
And and it it's not that hard when you're on your phone and you get one password and you just kind of like autofill passwords all day long and two factor codes, but when you're in VR, it's super hard to type everything out. So, wow.
1:08:33
I'm very, very impressed that you pulled that off.
1:08:35
I thought that that was going to be a a failure. So, congratulations. Enjoy it. Oh, wait.
1:08:41
So, so so break down the experience of actually playing.
1:08:43
Were you playing on a big big 2D screen and you were sitting there in like a theater basically? Yeah. Yeah.
1:08:48
So, the screen was probably like six feet in front of me.
1:08:51
It was like in front of this light.
1:08:53
Um it was like great experience. Yeah.
1:08:53
I didn't find it to be like uh like the refresh rate was like totally fine.
1:08:57
I I'm not motion sick at all.
1:08:59
No screen door effect or anything? No, it was totally fine.
1:09:02
And then and then also break down.
1:09:04
Um, so you were you technically streaming the game over Wi-Fi, I believe.
1:09:09
So I I I'll look, but I think it was like cloud gaming, I think. Yeah.
1:09:14
So I think I think the the actual Xbox uh like like frame rendering is happening in the cloud and they're and they're streaming that to you and then rendering it in VR and then the headsets just pinning that to the world, which is really really cool.
1:09:28
So, I have this thesis and and and you'll have to play with the headset more and and let me know if it plays out that I think that uh you know, Palmer Lucky has that take that's like uh soldiers will be wearing VR headsets on a daily basis before consumers are because the the military can underwrite like a $5,000 VR headset.
1:09:48
And so, he's he's betting on augmented reality glasses for the war fighter being the first real use case.
1:09:56
Um, I have this thesis that, you know, before before people were using the iPhone for dedicated iPhone apps like Tik Tok and Uber, um, people were using to make phone calls.
1:10:06
Like, it was a phone first.
1:10:07
And I think that that will be basically a TV first and people will be playing traditional video games and watching traditional movies before we get VR GTA 6.
1:10:16
People will just be playing GTA 5.
1:10:19
And so I think all the VR companies should focus on making the the movie watching experience and the traditional video game experience like super super smooth so that you just get in, you can actually chill in that thing for two hours actually beat Halo.
1:10:32
May maybe maybe you know the whole game only takes three hours to to beat.
1:10:36
Maybe you got Okay, gamers.
1:10:38
Anyway, let's get back to the news.
1:10:41
This is Let's get back to the sleep scores.
1:10:42
How did you sleep last night?
1:10:44
Before we was absolutely mogged. No. What happened?
1:10:51
I'm going to get a pod five. Get a pod five. 69. Rough. I got a 92, baby. Let's go. Generational run.
1:10:57
Hit me with the Ashen Hall. You know the rule.
1:11:02
If I beat you, I get that sound effect. Ashton Hall 92. Get Go toleep. com/tvpn.
1:11:13
I'm worried to think about what how I would have slept if I didn't have an eight sleep.
1:11:16
And you know, the only thing that I got penalized on was I went to bed too early, 9:30.
1:11:19
And they're like, "You don't usually go to bed at 9:30." And so I pulled it off.
1:11:23
I was penalized by screaming children in the middle of the night. Brutal.
1:11:30
Uh, inside the secretive world.
1:11:33
No, we have some breaking news.
1:11:34
I'm going to dive into this.
1:11:34
So, uh, this morning, Zuckerberg, uh, announced his super intelligence.
1:11:39
4,000 likes on this traded post. No way, Tyler.
1:11:41
Oh, and here on a generational runational run today. Okay. Wow. 4K likes. Okay. It's awesome.
1:11:53
Back to the breaking news. Yeah. Yeah. Please, please.
1:11:56
Uh, so, uh, Zuckerberg sent a message this morning in a memo introducing the new super intelligence team.
1:12:05
So, we were just covering his list.
1:12:07
Y, he got a seemingly a lot of people uh, from his list.
1:12:11
So, Uh Zuckerberg introduced Wang who will be the company's chief AI officer and leader of MSL as well as found uh former GitHub CEO Natt Freriedman.
1:12:21
Freed Freriedman will co-lead the new lab with Wang with a focus on AI products and applied research.
1:12:27
Here's the list of all the new hires as seen in Zuckerberg's memo.
1:12:32
It notably doesn't include the employees who joined from OpenAI Zurich office.
1:12:36
So this is Kylie Robinson's uh reporting over at Wired.
1:12:39
So, Trapit Bonsil pioneered RL on chain of thought and co-creator of Oser models at OpenAI. Corrected.
1:12:47
Uh, Shu Chow B, co-creator of GPT4 voice mode in '04 Mini.
1:12:50
Previously led multimodal post training at OpenAI.
1:12:56
Huawen Chang, co-creator of GPT4O's image generation and previously invented Maset and Muse text to image architectures at Google research.
1:13:03
G Lin helped build 034 mini, GPD 40, GPD41, GPD 4.
1:13:10
5, GPD40, image genen, and operator reasoning stack.
1:13:15
Joel Pobar, inference at Enthropic, previously at Meta for 11 years at HHVM, Hackflow, Redex, performance tooling, and machine learning.
1:13:23
Uh, Jack Ray, pre-training tech lead for Gemini and reasoning for Gemini 2.
1:13:27
5, led Gopher and Chinchilla, early LLM efforts at DeepMind.
1:13:32
Hong Yu Ren, co-creator of GPT40.
1:13:37
Uh, and th this just goes on and on and on, but uh, the big takeaway here is that, uh, these seem to be some important, uh, people and not, uh, not what Sam had originally messaged as as none of our best people.
1:13:54
Wow, that is a big, but obviously things have changed since uh, since that.
1:14:01
Maybe we need some more trade deal posters except it's not much of a trade deal. Just full poaching.
1:14:08
It's pretty pretty crazy.
1:14:08
No, this there will whenever whoever writes the book on this era AI, Ashley Vance obviously will have at least a chapter dedicated to this talent raid. Yep.
1:14:22
This is pretty unprecedented.
1:14:24
But yeah, I think the difference the difference when when Facebook was raiding Google Yeah. in 2010.
1:14:31
It was just spread out over a much longer period of time and it wasn't it wasn't I mean this is unique because in that situation Zuck was poaching from Google.
1:14:44
Zuck poaching from a company that still is like many people view as a startup, right?
1:14:49
Even though it's worth hundreds of billions.
1:14:50
So yeah, this is pretty remarkable.
1:14:54
Turner Novak said, "Is it true they poach Matthew McConna from Salesforce?" I like that one.
1:15:00
Uh anyways, so we could go back to this list, but uh clearly he made a list.
1:15:03
He checked it twice and he got a very meaningful.
1:15:12
It's time for Zuck to head over to Bezel and get him something.
1:15:14
Get himself something to remember this moment by because his bezel concierge is available to source him any watch on the planet. Seriously, any watch.
1:15:23
He could get a new Rishard Mill.
1:15:26
He could get a new Vashron or a new PC. He has a Cubidus.
1:15:31
Maybe he needs to fill out the fill out the the stable a little bit after this. Uh, pretty remarkable. Yeah.
1:15:38
The other thing that's that's interesting here, Daniel Gross is not anywhere in this memo. Oh, interesting. Who was rumored?
1:15:46
Is the full memo listed or is it just like they just didn't include this because uh it's just wired reporting and they don't realize how big of a deal DG is.
1:15:56
I I I think I think they they would have they would have included it. Yeah.
1:16:01
Maybe maybe like the negotiation is still like ongoing like it is it is a more complex situation because it's like a CEO leaving an active company and so uh it's not it's not like a full like free agent or acquisition or you know going from W2 to W2.
1:16:16
It's it's a little bit more complicated than that. So fascinating.
1:16:20
Well, the AI talent wars are the current thing and we have been enjoying following them.
1:16:24
It's a great time to be an AI researcher.
1:16:27
Even better time to be a podcast. Yeah.
1:16:29
Incredible overnight success success for all these researchers.
1:16:33
It's not like they spent, you know, 10 to getting PhDs, 15 to 20 years, you know, also in a field where people were like, "Oh, that will never happen."
1:16:43
Like that like like this is crazy sci-fi.
1:16:45
This is not like going to ever be real.
1:16:47
Like you're just you're doing like complex math. Cute chatbot. Yeah. Cute picture. No way. Yeah.
1:16:54
Cute picture that makes a morphed hand. Yeah. Oh my god.
1:16:58
Look at that hand with six fingers.
1:17:00
That'll never be commercial. You bozo.
1:17:06
Oh, you're working on image gen. Yeah.
1:17:08
Why does that person have Oh, DeepDream.
1:17:10
The thing that puts dogs in every picture. Oh, yeah. That'll work. Yeah, right. Yeah. Cat detector. Hot hot. What is it? A hot dog. Hot dog. Not hot dog. Yeah.
1:17:21
Now it's the most valuable technology in the world. Yeah.
1:17:27
I I'm I'm super I'm super interested in seeing like what they build.
1:17:29
Obviously, like it's going to be like a good model.
1:17:35
Like we know that they're going to try and build like a a a big good model.
1:17:39
It's going to be open source. Maybe it might not be. Maybe not.
1:17:41
There's like like Mark Mark has guarantee that he'll be open source.
1:17:45
The model is really good now.
1:17:47
We're going to we're going to charge for it.
1:17:48
No, but he could he could I mean like open source. Yeah.
1:17:50
I mean it could be it could be closed source.
1:17:54
It could be open source variations.
1:17:55
It could be you know a a chat driven product that directly competes with chatbt.
1:18:01
It could be something that just lives behind the scenes. It's gonna Yeah. It could be a tab. It could be a new tab. You know what?
1:18:06
I actually like I would like to own a piece of search too. I got a bunch of DAUs.
1:18:11
They're searching stuff all the time.
1:18:14
I kind of like that market.
1:18:15
I think people might want to discover products that way.
1:18:17
I think you could build a pretty good ad product on top of that.
1:18:23
It is interesting though.
1:18:23
I mean that the the it feels like LLMs right now are so single player and meta products are so social and communication and entertainment oriented.
1:18:34
Y launching a consumer and the social thing is like it's right around the corner.
1:18:40
It's right around the corner already.
1:18:41
I will I will I've done this with you where I will go and generate an 03 pro response, let it cook for 10 minutes, have have 40 generate some charts or graphs or images off of it and I will just share the chat with you and then you can trace through the whole thing as you like. Yeah.
1:18:58
And that workflow back and forth is amazing.
1:19:02
Ben Thompson wrote about it, how he has a research assistant who isn't at the level of him in terms of analysis, but can ask a bunch of questions and then he can go back and see, okay, he asked this question slightly the wrong way, so he got slightly the wrong answer.
1:19:14
Let me just continue chatting with the same interaction in GPT4 or 40 um and and actually improve and get the answer that he wants. So, it's fantastic.
1:19:24
Are you about to hit the gong for something?
1:19:26
or you're I mean there's like 20 researchers that just signed a beta and um I'm just going to do it. Why did you throw it?
1:19:35
We're just experimenting here. Um yeah, it's funny.
1:19:42
Uh Dan Rackcliffe in the chat says uh every researcher hire I see I think of Jord's tweet on companies doing NBA style trade deals, open AI trading researchers with anthropic throwing in a couple 2026 Waterlue grads.
1:19:52
The only thing here is it's very one way.
1:19:55
So, I called it, but I kind of didn't call it.
1:20:00
And that uh Zach's just just absorbing, you know, he's not saying he's not.
1:20:06
Turns out in tech, everyone's in free agency. Yeah. At all times. At all times. Yes.
1:20:10
There are no binding contracts that can keep someone at a comp at a company for five years. It would be Yeah.
1:20:17
It would be very interesting if sports shifted to that model where there was no long-term contracts and you could just midseason be like, "Oh, I guess Tom Brady's going to the Eagles."
1:20:29
Like Saquon Barkley is being traded Midame like at halftime and we switches teams because there's there's a team that paid more like that would be possible I guess like and that's and that's what we're going through here. Um I don't know.
1:20:43
We'll have to we'll have to get Tyler to give us a breakdown of these folks on tomorrow's show.
1:20:50
Maybe we could go through these folks and and talk about some of their history, what they've actually done.
1:20:55
Uh who's who's the most legit?
1:20:57
I wonder how important the uh oh, what's that called?
1:21:00
The Dunar, is it Dunar's number? No, I forget.
1:21:02
There there's a there's a there's a quantitative quantitative way to assess how powerful how uh why can't I uh jigster Dixster's number I forget Bench press yes Bench press um no basically you look at the papers that they that they authored and then you look at how many citations that paper has and so if if really great researchers are citing your research then you are a great research researcher that type of thing.
1:21:32
Uh, it's kind of like a six degrees of separation like the B Kevin Bacon thing.
1:21:36
Anyway, should we go to Apple F1?
1:21:40
You know that it's also on the in the Wall Street Journal.
1:21:42
Yeah, let's cover this cover this journey uh journal piece.
1:21:46
Uh, can Brad Pitt's F1 movie finally deliver Apple a big screen hit? It did. It did. This is old news.
1:21:51
Also, uh, it's funny because the paper version says Apple is now trying to make people make movies people actually watch.
1:22:01
Did you see how brutal the the the the written the written headline is compared to the online one?
1:22:06
So the online one is can Brad Pitt's F1 movie finally deliver Apple a big screen hit.
1:22:12
Like okay that's like kind of shade at Apple like they haven't really had a big screen hit but then this one is just like oh yeah they haven't even been trying before and now they're trying to make movies people actually watch. Brutal.
1:22:23
Well, uh, you probably if you if you're familiar with F1, you're probably familiar with it some from some billboard ads you saw.
1:22:31
So, if you're trying to run billboard ads, go to adquick. com.
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1:22:43
It's crazy how so the the um I was off earlier.
1:22:47
The this is Apple's first box office hit. It's a $55. 6 6 million debut.
1:22:54
Y and the poly market had it there was uh under 43 million, 43 to 47, 47 to 51, 51 to 55, and then over 55 million.
1:23:05
So um it had it at uh 80 71% uh just about a week ago and uh that ended up being true by half a million. So close but accurate. Oh, interesting.
1:23:20
I thought it was like 140 million. What was that number? That that's different.
1:23:23
I think I Okay, so they actually clocked it pretty well with the with the Okay.
1:23:27
Anyway, we'll get the details here.
1:23:27
So, uh in the Wall Street Journal it was so so it was domest um Oh, the domestic box office versus international.
1:23:35
Yeah, those are the numbers. Okay.
1:23:37
Well, uh Ben Fritz and Joe Flint over at the Wall Street Journal have the story.
1:23:41
They say when the team behind this weekend's Brad Pitt movie F1 first pitched their idea around Hollywood, nearly every major entertainment company wanted in and a bidding war quickly erupted. We like that.
1:23:55
Uh then Apple Bigfooted them all.
1:23:59
Tech companies, they love Bigfooting.
1:23:59
Uh the tech giant agreed to spend nearly $250 million, more than two AI researchers uh than more than any other studio thought the drama about an aging driver's last shot at glory was worth, said people with knowledge of the matter.
1:24:18
Pit was paid more than 20 million standard uh more than the $20 million standard for A-list movie stars and will get a cut of the film's revenue if it's a hit.
1:24:27
F1 is one of Apple's biggest entertainment bets since it le since it leapt into Hollywood in 2019 and embodies the unusually lavish and meticulous approach to the business which has brought little commercial success.
1:24:41
People who have worked at or with the company say Apple executives crave hits but only want to produce content they believe reflects the high-end aspirational qualities of the iPhone and MacBook.
1:24:53
There's little chance, in other words, that Apple would make a critically re reviled blockbuster like a Minecraft movie. Yeah.
1:25:00
I talked to um a a very successful Hollywood producer about this dynamic with Apple that so much of being a movie studio is it's a hits driven business.
1:25:13
You got to slop it up sometimes.
1:25:15
You got to do the kids movie like Shrek.
1:25:17
You got to hallucinate a little bit. Yeah.
1:25:19
Shrek is not is not an Oscar-winning film, but it's a hugely valuable franchise. franchise. Yeah.
1:25:26
And so he was basically saying that Apple had one hand tied behind its back because of the brand standard and that it would only want to do things that had a polish and a prestige and that expensive expensive.
1:25:41
And if you're if you're only doing like half of the surface area of what a movie studio can do, you you're just going to get eaten by Netflix that's going to say like, "Yeah, let's put the reality show on this show. Let's do this. Let's try this.
1:25:52
Let's drive some prestige. Let's try some stuff." Yeah. Yeah. Let's do Love Island. Whatever.
1:25:56
Uh and Apple just wouldn't do that because it's not the brand.
1:25:59
Uh but it seems like they're figuring it out and F1's a good example of that.
1:26:02
So with sleek production values and strong reviews, F1 is exactly the kind of movie Apple wants.
1:26:08
It was made by Top Gun Maverick director Joe Joseph Kosinski and producer Jerry Brookheimimer.
1:26:15
And Apple executives have privately said they hope it will be the landbased version of the Airborne Blockbuster, which grossed 1. 5 billion in 2022. Wow.
1:26:25
You think it could get up there? That would be fantastic.
1:26:27
Uh, but pre-release surveys indicate F1 is struggling to generate interest among audiences beyond older men.
1:26:33
Its success or failure will be a referendum on Apple's ability to meld carefully curated and I got to go to B4.
1:26:42
Um, carefully curated content with broad appeal after six years in which it hasn't released a single box office hit to date.
1:26:53
Worldwide box office of Apple Apple original films.
1:26:56
Killers of the Flower Moon. I did not see that one. 2023 160 million. Napoleon. That was an Apple movie. Oh, 221 million. I saw that. Did you see that? People didn't like it.
1:27:08
I I I thought it was pretty good.
1:27:09
It was long, but it was fun. Uh, Argyle, 96 million.
1:27:11
That one didn't do too well.
1:27:14
Fly Me to the Moon 2024 did 42 million.
1:27:17
You have not seen any of those, correct? Nope. Fantastic. F1 will be available. It's okay. I haven't seen UFC 724. Who cares? To each their own.
1:27:27
F1 will be available on Apple TV, the company's streaming service after its run on the big screen.
1:27:35
Apple's TV Plus to, you know, I knew this I knew this movie would be somewhat significant. Yep.
1:27:42
I felt inclined to watch it. Yes.
1:27:45
And so knowing that it was releasing or I thought it was releasing, I was like, "Okay, great. I'll watch it on Sunday. There's no HBO.
1:27:52
I'll watch it on Sunday." Okay. And what happened?
1:27:54
And it wasn't on Apple TV. It was Yeah.
1:27:58
It was at the movie theaters. Yep.
1:28:01
And I didn't want to go to those movies.
1:28:04
You're allergic to movie theaters.
1:28:06
When was the last time you were in a movie theater physically?
1:28:08
When we Oh, when we saw saw Dune 2 with an absolute squad. Yeah, we did.
1:28:14
This is the movie to take the boys to. We got to do it.
1:28:16
Uh it's hard to say, but we got to do it.
1:28:18
This is a call to action for all the fans.
1:28:21
Many podcasters are descending on Malibu for the month of July. this is a thing.
1:28:25
So maybe we'll maybe we'll get it done together.
1:28:29
So uh yeah and and Ben Thompson's been uh beating the drum on this this idea of like Taylor Swift understands windowing better than like Netflix executives.
1:28:37
Have you seen this thing?
1:28:39
So basically like windowing is the concept that um when you have a valuable media property, you should monetize it at in at at increasing rates of cost based on time.
1:28:50
And so when Taylor Swift comes out with a new tour, you can first go and see it live in person at Sofi Stadium and tickets are like a $100, maybe more, like couple hundred bucks.
1:29:04
It's expensive to go see it.
1:29:06
Then months later, you can see the movie version of her tour in movie theaters, but it's not on streaming.
1:29:14
And so then you're paying $20 instead of $200.
1:29:18
Then after a couple months of it being exclusively in theaters, then you can stream it for free if you're subscribed.
1:29:26
So it's like, let's call it like an average cost of like $2.
1:29:27
So you went from like 200 bucks to see it live in person, 20 bucks to see it in the theaters, $2 equivalent to like stream it on Netflix for like, you know, 10% of your Netflix spend that month or whatever.
1:29:39
Um, and then eventually it'll be like free on TV or whatever.
1:29:41
Free it'll be even free or maybe she'll put it on YouTube.
1:29:44
And so it's this very it's this very good way to price discriminate and get the maximum amount of value out of a piece of content.
1:29:50
And Hollywood had been very good at this for a very long time.
1:29:53
Like it would come out in the movie theaters.
1:29:55
Then there would be a big gap for like 3 months.
1:29:56
You just couldn't see the movie at all no matter what.
1:30:00
It was like you got to go see it in the theater because if you don't see it now, everyone you won't be able to see it for six months.
1:30:05
And then and then the DVD comes out or the Blu-ray comes out and it's like exclusive just and you have to buy it and then and then after that it goes to Blockbuster.
1:30:13
can rent it and then it goes on TV or HBO later and like it might not be it it might be a year or two until you can actually go and see uh the movie for free.
1:30:22
And so Hollywood was really good at that and they were printing money and then then you know the streamers came and disrupted all this and like the binge era started and you can just watch everything for free constantly.
1:30:34
Um, but Ben Thompson's point is that they kind of went too far and they started giving away things that people would actually go see in theaters for free on streaming.
1:30:45
And so even this the I I think there's going to be a lot of people who are like, "Okay, it's an Apple TV Plus exclusive."
1:30:50
Like, how long do I have to wait to just watch it at home? Oh, like two weeks.
1:30:53
Like, okay, I'm not going to go see it in theaters.
1:30:57
Um, but if they window it hardcore and they say, "Look, yeah, it'll be on Apple TV Plus uh in seven months, then people will be like, well, it's worth it for me to go see it now."
1:31:06
Anyway, uh, well, we have some notes in the chat.
1:31:08
One, Michael Ginsburg says, "Community note, Shrek won two Oscars." Owned. Owned. Owned. Shrek. Apologies. Apologies.
1:31:19
Is not only a cult classic, but it's an awardwinning. It won. It won.
1:31:22
Wait, did it win best animated? No way.
1:31:25
Cuz that's actually hard one.
1:31:27
CGI or best music or something.
1:31:27
And then Blake Blake Dryer says, "Just got back from F1 IMAX. Incredible.
1:31:32
As a fan of the sport, very well done."
1:31:34
I I think you got to see it.
1:31:36
I I think it's also the type of movie that you want to see.
1:31:38
Turner says, "It wasn't a bad film." Cool.
1:31:40
Nick Kotov says it was just too long. So F1 too long. How long is it? Two. Over two hours. Gota be 90 minutes. Get me in. Get me out. Two hours 36 minutes. That's so long.
1:31:53
Anyone that would put out content Yes.
1:31:56
more than two hours a day is just completely out of line and unhinged.
1:31:58
We would never put out 3 to four hours.
1:32:04
This is a pot call in the kettle black situation, but we're doing it. Yes.
1:32:05
So Shrek uh according to Michael says best animated feature and best adapted screen. Okay. Okay. I stand corrected.
1:32:14
Let's give it up for Shrek.
1:32:14
Do we really think Shrek meets the brand standard of Apple? Like no way. Right. My my point holds.
1:32:21
I don't think Apple Tim Cook would kill to to be able to put out a film of that caliber. You think so?
1:32:28
Well, the Wall Street Journal disagrees with you.
1:32:30
They say that they wouldn't put out the Minecraft movie.
1:32:31
Uh anyway, uh Apple TV Plus has earned a reputation for content that excites critics more than audiences, including the Leonardo DiCaprio, Robert Diro, content that excites critics. Yeah, Apple TV.
1:32:45
There's a lot of examples of that in media.
1:32:51
There's the there's a lot of tech media that's just for the insider for me for the media folks.
1:32:54
It's Jouro on Jouro content.
1:32:56
Um, Killers of the Flower Moon, Oscars, best picture winner, Kota, literary adaptation, Pachenko, and the spy drama Slow Horses.
1:33:04
Yeah, I tried to watch Slow Horses. It was pretty good.
1:33:08
Um, it's its few mainstream successes include sports comedy Ted Lasso, sci-fi workplace drama Severance, and straight to streaming film The Gorge or the Gorge.
1:33:16
Uh, we're into entertainment to tell great stories and we want it to be a great business as well, says Tim Cook.
1:33:24
He told Variety, an Apple TV Plus spokeswoman declined to comment.
1:33:28
Analysts have questioned why Apple spends billions annually on a business so far field from its core consumer electronics operation, even if it's barely a blip for the company worth more than three trillion.
1:33:36
The strategic value it brings is sufficiently mysterious for people not to talk about it very much.
1:33:43
Says Craig Moffett at Moffett Na Nathansson, good buddy at Ben Thompson's.
1:33:47
Uh, Apple TV Plus cost $10 a month.
1:33:49
And yeah, so a lot of people think that the Apple TV Plus like production team is to like take take pressure off of the like the 30% Apple tax discussion.
1:33:57
Anyway, we have our first guest of the show. Will is in the studio. Welcome back to TVPN. How are you doing? How's it going?
1:34:05
Congratulations on the trade deal.
1:34:07
Thanks for having me back. Yeah.
1:34:07
What superc car did you buy?
1:34:10
Did you go Bugatti Chiron or you go F80?
1:34:12
I mean we we hear that the the numbers are huge right now for folks like you.
1:34:18
I mean I'm taking a plane more so like that was a lot of luck. Yeah. Yeah. Yeah. Yeah. Yeah.
1:34:26
People say you know fly you know we wanted flying cars.
1:34:27
We got the fact that you would imply that Will drives himself is offensive. Offensive.
1:34:35
Um I mean Yeah, lot of Whimo.
1:34:35
Whimo for the first time recently.
1:34:39
I' like I'd been to like SF, but like I hadn't been around SF proper that much since the the Whimo craze took off.
1:34:46
And so like that's been like the the car experience really. Just like Sure. self-driving cars. Damn. Yeah.
1:34:53
So, are you in SF full-time now?
1:34:56
Uh, still back and forth New York.
1:34:56
I'm like kind of slowly starting to spend more time in SF. It's on brand. You're decentralized.
1:35:03
You're decentralizing AI.
1:35:06
It's it's it's a perfect fit. Perfect fit.
1:35:08
Uh anyway, did you touch grass at all this weekend or were you locked into the timeline?
1:35:14
It's a lot of stuff was happening on the timeline.
1:35:16
I did I mean I'm in New York right now.
1:35:18
I did some New York stuff uh on Saturday, but yeah, I mean it's been it's been good.
1:35:23
Lots of uh drama intrigue as usual. Lots of drama. Um the trade deals.
1:35:28
I know I've been tuning in to earlier.
1:35:30
I know you guys have gone over all the the major roster updates.
1:35:35
Um but yeah, it's uh exciting times.
1:35:39
Open AI, open model soon hopefully, but not this week.
1:35:42
Um yeah, so yeah, I mean the first place I want to start with is um the actual trade deals.
1:35:51
Did do any of these people jump out to you as particularly interesting?
1:35:55
Have they been on your radar?
1:35:56
Have you met any of these folks?
1:35:58
Can you give us more context on uh how how academic are they?
1:36:02
How product oriented are they?
1:36:05
It does it's it feels like this is purely research you know uh beefing up of the research team and meta kind of has products solved.
1:36:14
Is that the right model to think about this?
1:36:16
What how can you characterize like the shape of the team that talks about even um there's thousands of really great software engineers that work in AI. Sure.
1:36:28
And but what you know even kind of getting a sense of like how many people was was Zuck really going after? Was it 250? Was it a hundred?
1:36:39
The list that came out today is you know somewhere somewhere I don't know there's like 20 people on it something like that. Right. Yeah. Yeah.
1:36:47
I mean it's a great list.
1:36:47
It's a lot of like very senior senior researchers who know who have like been through some like real product cycles who like I think the goal is people who can bridge the gap from research to product.
1:36:58
Um because like like one thing Meta has a strength of but I think doesn't translate in like this era is they have a lot of really good like academic researchers like Yan Mcun's whole org has a lot of very talented very capable researchers who write important papers but it's the kind of stuff that doesn't really turn into exciting products.
1:37:16
It's like more betting five or 10 years out, how do we want to do things eventually versus like going through a pre-training cycle for a Gemini or a Claude or an OpenAI model like that has a different set of considerations.
1:37:31
And so this to me looks like they want like 10 15 great people who have been through those research to product cycles in terms of the model being the product.
1:37:44
Um, and it seems like they probably like they got uh Alex um and then supposedly Nat and or Daniel uh to kind of handle a little more of the not the business side but producty business stuff. Yeah. It's a management role. Yeah. Yeah. Yeah.
1:38:03
What what is your take on Yan Lun right now?
1:38:10
How should we think about his position in the AI world?
1:38:12
There's uh I I you know I see these memes of like he's a non-believer.
1:38:19
He doesn't believe in like super intelligence and like AI god.
1:38:22
He's a little more practical.
1:38:24
It seems like he's been he's been right about some things in the sense that like we haven't had we we're not feeling a fast takeoff right now.
1:38:33
So I think you got to give him some credit for that.
1:38:35
At the same time, like there's Ben Thompson's been criticizing on Lacun a little bit for not driving the the product side of the business.
1:38:44
business. It's like it's one thing to say that hey we're not going to go straight shot to AGI god but then the the the downstream implication of that is that if you believe that we're going to be living in like B2B SAS world of AI implementation and productiz
1:39:01
productization then like go do that and like make sure that the models work really well for business and so uh I don't know what is your take how would you how would you describe Yan Lun in his history and kind of where he sits in the organization to like a layman Sure. Yeah. So, I think people overindex on Yeah.
1:39:16
So, I think people overindex on thinking of Yan as the meta guy like too much. Sure.
1:39:20
Um I think it's a shame that they didn't necessarily have someone in the llama or who was as visible as him because he was not involved with llama at all.
1:39:29
Like fair fundamentally research is like a whole other group that they mostly write papers and do very academic work.
1:39:36
Yan lun's work is very academic.
1:39:39
Um, and it's really like it's I think he's like I think on one hand he like is right in the sense of like we don't have the full picture yet.
1:39:47
Like we don't have full-on AGI that can like do a human's job forever.
1:39:52
And I think that's kind of the drum he's beating is like there's more work to do.
1:39:56
There's more science to do.
1:39:57
It's not just productize the current set of techniques um in terms of like the end of AI forever.
1:40:03
Um, but his goal is not to do the productization.
1:40:06
Like he like the org he's in at Meta is really isolated from product.
1:40:13
Um, he's there to kind of boost the uh reputation of the org academically.
1:40:20
Um, as well as to be able to potentially advise on other stuff that's more productive.
1:40:25
But his job is not to like go train a business model to train a model that is going to be used by businesses.
1:40:30
be used by businesses. And like I think people like that or fair the friends I have who are there like are there because they essentially wanted to be a professor but they want tech company resources and not to not have to teach
1:40:45
and that is essentially what that or is yeah does that lead to better recruiting on campus essentially like you can go get researchers because Yan Lun can come do a really powerful lecture Maybe, but I think of it more as like the same way that Zuck did Metaverse stuff. Zuck is very willing to make
1:41:05
Zuck is very willing to make 10-year bets. Yeah.
1:41:06
Um and so that org for Meta is not about what product are releasing next quarter.
1:41:13
It's what are our 10-year bets? Yeah. Um okay. Uh I want Sorry. Yeah, you can.
1:41:17
So Meta shares just hit an all-time high. Really?
1:41:22
So the stocks the stock's uh performing.
1:41:25
I'm I'm curious um from your time at Morgan St.
1:41:30
Thank you for that, John. That is incredible.
1:41:33
But but generally up 5% over the last week.
1:41:36
Um what h what how did Wall Street generally sort of like process the like meta AI story?
1:41:46
Because now obviously at least the market seems generally excited.
1:41:51
Uh, it may get to the point where we did with VR where people are like, "Hey, whoa, whoa, whoa.
1:41:54
Cool it on the metaverse, you know."
1:41:56
Well, it's funny because like like like you add all you add all this up, even if the hundred million dollar offer number is real, it's like, okay, so now we're at like $1 billion in spend.
1:42:06
It's 5% of the metaverse hole that was burning.
1:42:08
And it's like, you know, from a Wall Street perspective, you're like, I don't care about I don't care about $1 billion.
1:42:15
I care about $20 billion because that was what was weighing on the stock during the metaverse buildout.
1:42:21
But this is like AI is so much more productizable.
1:42:23
You can make so much more money from it upfront.
1:42:27
And it seems like even though it's a big number, $100 million offer, it feels like the spend is maybe less, but I don't know. What do you think, Will? Right. Yeah.
1:42:34
I mean, I think the I don't know the context fully of the hundred million.
1:42:39
I know people have all these theories, but like the the scale AI numbers we do know. Yeah.
1:42:42
And like that that's a big chunk of their like I don't know they don't do those every day. Yeah.
1:42:50
Um but they've done a handful in the past at that scale like WhatsApp was 20 billion or something like that.
1:42:57
Um, and I mean it's hard to read into like the the charts like I Yeah, I think people are generally like expecting that Meta will take AI seriously and are kind of happy to see change.
1:43:11
Um, whether that is like justified or not, I mean, we'll see.
1:43:17
Um, yeah, it was interesting.
1:43:21
The product side is going to be interesting because like they're not a B2B SAS company. Yeah.
1:43:26
Well, so content, they're an entertainment company.
1:43:31
And I think that that I I don't I don't think that people are are fully understand the potential of Gen AI around entertainment.
1:43:40
Like it gets talked a lot around, oh, you're going to be able to generate, you know, an entire movie or generate video games or things like that.
1:43:48
like that. And I and I think that we haven't seen we've seen some fantastic examples so far, but nothing nothing that that is I I think like George Hotz was on our show and he was talking about how like basically AI is going to be like having five CIA agents follow you
1:44:07
around all the time convincing you to buy products and like that is like one kind of dark bull case for dark bull case dark bullc case for meta in the context of AI because it's It's possible that that Facebook is already the best ad advertising product in human history. Like period, hands
1:44:22
Like period, hands down, there's nothing better and then could you make it like two, three times better? It's very possible. Crazy. Yeah.
1:44:33
I want to push back on the B2B thing because yes, yes, they don't sell B2B software, but I was thinking it in this terms like if you if you were running a company where your entire you only had one client and that client was Meta and you sold them CRM and infrastructure and uh LLMs to improve the back office and do uh you know censorship and and uh you know and reality checking and and uh looking for bad words and looking for
1:45:05
improper posts and recommendation algorithms like how much would that company be worth and how much revenue would they be making just from that one client and I think it's in the billions because it's just such a large organization that it's potent it's potentially like just the B2B applications of AI inside of Meta are like it's a multi-billion dollar like cost center or revenue driver or something like that. I don't know. I I don't know.
1:45:27
I think a company at Metascale has already rewritten all that stuff themselves for the most.
1:45:31
Like they probably have some services. Yeah.
1:45:33
That they're using, but like they like they could they rebuild their own cloud like because they use AWS for a lot of Yeah. Yeah.
1:45:40
Um can they're not a compute company though and in terms of like platform stuff? Yeah.
1:45:45
I feel like those companies once you hit a certain size and you just like have so many engineers that you want everything like Google rewrites all their own stuff. Yeah.
1:45:55
Um, Microsoft rewrites all their own stuff.
1:45:57
Um, and can they is there another like a tale of end of that that has not been done yet that they can squeeze some more money out of? Sure.
1:46:05
Um, entertainment will be interesting.
1:46:08
So, one thing that just I was just reminded of um, have you seen the Italian brain rot videos? Oh, yeah. Love them. Yeah. Yeah.
1:46:13
So to like I know people it's like silly it's stupid but it there is something there in terms of this like communal narrative storytelling with a level of vibrancy that we haven't seen so far. It's like Looney Tunes.
1:46:26
Um but people just like come up with these where you could imagine Meta kind of eating a good chunk of the like videog market.
1:46:34
Um if they have an answer to like V3 um where that becomes part of the platform.
1:46:41
It ties into the whole metaverse thing of like creating stories and sharing these stories with your friends.
1:46:46
Um, but instead of like Instagram stories, it's like, okay, what's what's the evolution of stories? Yeah.
1:46:52
Have you have you seen Higsfield? No. Higfield AI.
1:46:55
I think it's an ex Snapchat team. Yeah.
1:46:57
Their new image model is basically already at a point where it's creating images that are photo realistic, but in the photo realistic it looks like some not fulltime influencer generated it after spending hours trying to create it and you can't tell that it's not real.
1:47:19
And so it it feels like um it feels like meta integrating that kind of thing where it's like y it'll be interesting to see how this actually plays out because everybody will be able to be a super tasteful creator or like generate these sort of unique styles and I'm sure at that point it'll switch.
1:47:37
Everybody will be like, "Well, I only follow organic farmtotable influencers." Who knows? Yeah. Yeah.
1:47:46
I feel like they their uh AI integrations so far have all been kind of weird.
1:47:51
Like there's these like Instagram accounts you can chat with and then there was the whole uh meta AI homepage disaster where old people were like leaking personal info without realizing it.
1:48:03
But yeah, I guess Facebook's always had that.
1:48:04
Facebook's always had that. Um, yeah, I think it'll they'll have to thread the needle on product in a way that we'll have they'll have to get creative because they haven't like it's been a while since they had a product innovation that was homegrown that
1:48:20
really stuck like Yeah, it's it is interesting that they haven't tried to create a Studio Giblly moment by you're like going I was saying this they should just pre-render everyone's profile picture as a Giblly And just when you open the Instagram app, it's just like here, we did this for you. It would be incredibly
1:48:40
It would be incredibly expensive from an inference cost, but then it's just like you could share it and it's just more virality around it. But I don't know.
1:48:47
And and like even baking that down into a filter.
1:48:49
No, be so like OpenAI branded now. They have to go.
1:48:54
Yeah, I'm saying like an entire something like that. But yeah. Yeah.
1:48:56
B basically like the the the filters in the Instagram app should be like style transfer or like fully generative instead of just like color grades.
1:49:07
That's clearly the next thing and they should just and they should just do that.
1:49:10
Um but what what do you think of uh Sam Alman's ability to get through this?
1:49:15
this? like he's had a series of exoduses and seemed to continue to march on the anthropic departures then SSI and thinking machines like XAI like this is not the first time his first rodeo it's not his first rodeo and so there's this
1:49:32
whole narrative like never bet against Zach he's been down on the metaverse came back he's been down on mobile with the HTML 5 thing and he came back from that went native and super dominant and bought Instagram WhatsApp super dominant in mobile. Uh, and so never bet against
1:49:45
Uh, and so never bet against Zuck, but then also maybe never get bet get bet against Sam and maybe they both win and maybe like the real loser is like I don't know some some other company or something. I don't know.
1:49:57
I think as long as OpenAI doesn't totally drop the ball on product or research like they have the center of gravity for the AI world like in the same way that no matter what Android ships people are not going to switch from their iPhones like something would have to go very wrong for people to not see OpenAI as the winner I think or as the kind of the default. Um, yeah.
1:50:18
I mean, the other thing is, uh, the average ChatgBT user is not waking up today being like, "Oh, I can't believe OpenAI lost a handful of its top researchers." Right?
1:50:33
They're right, they're just still using ChateBT as a Google replacement or they're talking with it as a companion.
1:50:39
So yeah, I think the lead is still very very real and um and I just and again it's going to create opportunities for people to say hey I want to go work on this product that hundreds of millions and soon billions of people use every single day. Right.
1:51:00
And I do think it'll get to a point, especially with like 2025 into 26 where there's a lot of product stuff that people seem like I think we're early on products and we'll keep getting better versions of the same things in a way that's like kind of predictable.
1:51:17
Like the image models will keep getting better, the agents will mess up less, but like we can already use those things and we can start building proof of concepts around them.
1:51:26
And the question is like okay, what are the winning apps?
1:51:29
Um like I I imagine that like the real time clearly kind of thing some OpenAI is going to do their version of that at some point.
1:51:38
Um other people probably will too.
1:51:40
Like does that become a modality that people really want like live overview uh on their screen on their phone?
1:51:47
Like what's the what's the way that people are going to be interacting with AI generally?
1:51:50
Um because a lot of those use cases like it's they're already smart enough.
1:51:55
It's not about making the models like way smarter at whatever.
1:52:00
It's like how do you have the model be useful or fun, engaging?
1:52:08
There's a bunch of paths here going back to the Cluly thing where one Roy is like right about the UX and like wins the market and the other option is like he's right about the UX but like doesn't win the market and then there's like you know it's just not the right form factor or whatever.
1:52:26
But any of at least the first two outcomes are hilarious in that in that Roy Lee ushers in the new the new paradigm of uh for for engaging with with language models.
1:52:38
I'm curious any um is all the stuff around every B2B SAS player descending on the sort of like single interface like a a chat interface that generates software was that predictable to you?
1:52:53
Do you think that's do you think that that's like part of a multi-year trend or is that just FOMO?
1:53:01
I mean like Copilot was early.
1:53:01
It was like 2020 21 like the first GPT3 copilot came out and like that was already one of the early like LLM applications that people were interested in at all and then it took until cursor for it to really like I think cursor plus like 35 sonnet was when it became a thing that was good enough that people were excited about it.
1:53:22
Um, and it really ushered in the trend because people were starting to find it more useful than a toy and like a thing that actually want to use day-to-day.
1:53:30
Um, and so I think like that's one path is like and then the more background agent kind of things are like starting to take off now, which I imagine like those will get reliable enough that they're like useful for cranking stuff out.
1:53:44
Um, they already are kind of depending on what you're doing. Yeah.
1:53:48
Like I think yeah, we're about halfway through the year.
1:53:56
What What are What are kind of like the big moments that you're kind of tracking the the OpenAI open source model could be one?
1:54:02
Whatever meta launches next, right?
1:54:05
I'm assuming they're going to be dark until this new team can can really cook and and bring something great.
1:54:12
May maybe they don't do anything this year, but I would assume they they come with with something.
1:54:16
What else are you are you tracking?
1:54:22
Yeah, I mean for me the 03 release in chat GPT was like a pretty like game changer kind of thing where it was like we saw with like deep research that like okay they kind of figured out how to make agents work but it was also just like this one version of an agent and 03 you can kind of get it to be a pretty general agent where it can like do some pretty complex stuff that was kind of new to see like the geogesser thing was crazy.
1:54:45
Um, and having that as a like vision of like what AGI starts to look like, I think is pretty cool.
1:54:54
Of course, from the like research open source world, there was the Deep Seek as like the RL craze taking off.
1:54:59
But like I mean, I'm I work on RL, so I like obsess over it and like think about it a lot, but I do think we're really starting to see these recipes at least in the broad strokes of like, okay, here's how the LM thing can go.
1:55:12
We figure out what we want it to do.
1:55:14
we give it some tools, we set up these environments, we figure out how to how to evaluate it, and then we can just kind of like let it go and these things get better at doing those things via trial and error.
1:55:24
Um, and so like I like I think that is one way to kind of forecast where things are going is just like what are the plausible use cases that people want to use LMS for?
1:55:33
They want an agent to do XYZ.
1:55:36
Um, and then how do you make this a thing that you can help climb?
1:55:40
And I think like you see a lot like there's been a lot of news about OpenAI trying to like sell their RF service.
1:55:46
There's these startups popping up.
1:55:48
There was a RF service uh reinforcement packing. Okay. Yeah.
1:55:51
Um and so like they're pushing this pretty hard.
1:55:55
This if you're spending over $10 million like Palunteer uh OpenAI will also customize a model for you.
1:56:00
So they have like a uh serious heavy like a heavy paying customer one, but they also have like a more like in the thousands of dollars service. Sure.
1:56:11
Where you are getting to essentially do fine-tuning on 04 mini. Yep.
1:56:16
Um and that is a little more self-s serve.
1:56:19
Um but they're also like doing consulting around that the forward deployed thing around that.
1:56:24
Is that an important strategy for open AI to c to to kind of stay in the game against open-source models like llama? Yeah.
1:56:36
But I think also against other like thinking machines.
1:56:38
There was some report that this is a version of the strategy they're taking is like go to enterprises y talk to them about their problems.
1:56:48
uh turn these problems into things where you can create really good customized agent models. Mh.
1:56:52
agent models. Mh. And if the like that's one potential roadmap towards like having more like AI everywhere is just like having services that were whose job is to like come in whether or not it's fine tuning or not just like make them into agent-shaped tasks um
1:57:13
where you can then optimize the model and have someone craft the model experience like for you because like I think a lot of enterprises are still like in a spot where they don't really like there's there's not as you see by the like the talent war there's just not that many
1:57:29
people in the world or in the market who really understand this stuff at a level where they can go make it happen and so like the open source thing on one hand it's cool that you in theory can go do it but it's also like there's not that many hands who can who are equipped to like go make the thing happen actually
1:57:48
fine-tune llama 4 or whatever yeah we actually talked to a startup that's doing basically that like small models for specific business use cases like okay you just have a ton of CSVs that need to be turned into JSON and we build you an LLM that just does that or whatever. Um, interesting. How how do Um, interesting.
1:58:04
How how do how do you after the the scale news and then there's a bunch of players um popping up or you know everyone from uh Merkor to Labelbox uh to Handshake a lot of different people competing for that market.
1:58:23
How do you see that market evolving over the next one to two years?
1:58:27
I think there were certain people saying scale got out at the perfect time in many ways.
1:58:33
Um but clearly there's a lot of at least gross revenue up for grabs right now in the near term. Yeah.
1:58:38
I mean I think like the t the broader sphere of like creating stuff to train models on with humans in the loop to do that curation is going to be important especially for these uh domain specific applications.
1:58:57
Um, I think it's going to be less like, oh, we just need more tokens and it's more about we need uh curation of goals and objectives.
1:59:05
Um, because like tokens, you kind of hit diminishing returns pretty quick in terms of just like more internet text or more like human written math solution examples.
1:59:21
Um, and it doesn't scale super well.
1:59:25
But the thing nice thing about the task specification is you can kind of like pour in more compute without necessarily needing more data.
1:59:32
Um it scales much better with compute.
1:59:34
Um whereas we don't really have like a great way of like spending 100x more compute per pre-shain token other than make a giant model. Yeah.
1:59:44
Do you think uh Llama will stay open source for the foreseeable future? We'll see.
1:59:51
I it wouldn't surprise me if they go kind of the Google route where like they are still they still do open source.
1:59:57
They still have the Llama brand, but it isn't like their flagship thing where they start doing whether it's for internal products or it's they really want to show that they're the winner um releasing closed models uh via API or other services where Yeah.
2:00:12
Do they do they have the infrastructure to serve a closed model?
2:00:17
I mean you mentioned that they use AWS so it'd be kind of awkward, right? Yeah.
2:00:21
I mean, I don't know that they really want to that much.
2:00:24
I I think that it'd be something that comes in a product. Sure. Yeah, that makes sense.
2:00:30
Or maybe they partner with like you could see them partnering with someone like a core reef. Yeah. Um or Nvidia directly.
2:00:36
Um Nvidia's hoping to get into the infrance serving game, it sounds like. Um yeah.
2:00:44
Do you think uh so so uh one of Swix's takeaways from the the Wired article was that um like one big development that's coming is when Stargate comes online, OpenAI will have the largest single cluster for pre-training, but it feels like we might be at the end of that game and we might be doing more compute inensive work in a distributed fashion.
2:01:10
And so maybe having it all in one place is a little bit less relevant to just, you know, oh, Trump card, Stargate, boom, I win.
2:01:18
I have the best model by far.
2:01:21
Um, how how do you think about the impact of Stargate on like the AGI race?
2:01:29
I mean, I think the biggest experiment that they're definitely going to do is take a pretty big model.
2:01:33
I don't know if it'll be like quite as big as like a 4.
2:01:35
5, but like a big model and do way more RL on it than anyone's done.
2:01:39
like what does like an '05 level of RL look like?
2:01:44
Okay, see how good that is.
2:01:44
See what what new that unlock.
2:01:46
Do you do that though or could you do that just across a bunch of data centers?
2:01:50
Because I've heard like a lot of RL is like you're generating you're doing verifiable rewards.
2:01:55
You're generating in a bunch of different data centers.
2:01:57
You could do it completely distributed and you don't necessarily need a Stargate to do that.
2:02:01
You can do it distributed like it is very inference heavy.
2:02:03
There is still like a lot of weight updating.
2:02:05
You have to sync the model across.
2:02:07
you have to keep sending the training model to your inference workers. Okay.
2:02:10
Um and so having it colloccated certainly makes it easier.
2:02:15
You it is easier to do it in a distributed way if you want to versus pre-training.
2:02:19
Um but it's not like trivial.
2:02:22
Um but I think like a lot of this is just data people are building the data centers without necessarily knowing exactly what experiments they're going to run.
2:02:32
They just know more stuff is coming.
2:02:34
But also, a lot of this is going to be inference where like they want to be able to do like Meta has a ton of GPUs they just use for Instagram ads. Yeah. Um recommendations.
2:02:42
Um a lot of Stargate will probably be serving Gibli.
2:02:48
Like I mean that makes a ton of sense.
2:02:50
Like I'm I'm running into rate limits on literally everything like like Google.
2:02:56
It's like how how do they run out of TPUs?
2:02:58
They spend 60 billion on capex every year at least. Um and 03 Pro too.
2:03:03
I I mean I I get timeouts on this stuff. Last question.
2:03:06
Uh I'm guessing you weren't surprised to see OpenAI leveraging the TPU for for inference or reporting to be starting to use it.
2:03:14
Was Was that kind of I mean it makes sense that they are considering all options given the friction with Microsoft.
2:03:22
Um like they don't have a a core cloud that they're super close with.
2:03:27
they're not like there's they need to both try to lower their cost for infrance um as well like that maybe was a factor behind the because the 03 had a big price drop that might have been TPU related I don't know um pure speculation but like Google has TPUs and they can serve Gemini really cheap and really well really fast um if openi wants to compete at that level they kind of have to consider all options Yep. Makes sense.
2:03:56
Well, great day to have you pop on.
2:04:01
Yeah, thanks so much for hopping.
2:04:03
Knowing knowing how knowing how things are unfolding, we'll probably we'll probably ping you to jump on again later this week. So, stay ready. Great to have you. Hot topic. Cheers. Yeah. Bye. I'll be right back.
2:04:14
And we got another Will coming in the studio. It's Will day on TVPN.
2:04:16
We got Will from Ulisses coming in.
2:04:20
Not talking about AI, talking about the ocean, talking about boats, talking about the Gundo, military.
2:04:27
Who knows what we'll talk about, but we will talk about the origin of his company. How you doing, Will? I'm good, John. How are you getting on? I'm great.
2:04:34
Good to have you on the show, finally.
2:04:36
Uh would you mind kicking us off with just an introduction on yourself and your company? Yeah, absolutely.
2:04:42
Um uh my name is, uh Willow O'Brien, um one of the founders of Ulyses.
2:04:47
We are building um autonomous vehicles to solve the most critical tasks in the oceans.
2:04:52
Um so in practicality of what that looks like um we build an autonomous surface vehicle.
2:04:59
It's a 30foot uh vessel that launches and recovers swarms of uh autonomous underwater vehicles.
2:05:04
Um these underwater vehicles can read as well as write. They can sense. They can take maps.
2:05:09
They can take images and collect data.
2:05:11
But they can also do uh physical manipulation as well and robotics.
2:05:16
they can they can do kind of whatever you want, whatever you want to task them to.
2:05:20
And uh we make both these vehicles probably about 10 times cheaper than anyone else in the world.
2:05:25
So while some people are building maybe humanoid robots is a general purpose robotics platform for land, we're building um the maritime equivalent of that.
2:05:32
Humans obviously are not evolved for for land um so or for the ocean.
2:05:36
So we need we need something for that.
2:05:37
So um that's a bit about us.
2:05:39
We're based in San Francisco as you can tell. I'm not um an American. I'm Irish.
2:05:43
Um, and some of our founders founding team are Irish and Scottish.
2:05:46
And um, yeah, that's uh, it's a bit about us.
2:05:50
How did you settle like Yeah. Yeah.
2:05:50
What was the inciting uh, like problem set like how how did you land on this industry to work on?
2:05:58
Like what what what got you in the industry? Yeah, good question.
2:06:02
Uh so about two years ago, one of my co-founders, um a crazy Scottish man called Jamie Weatherburn was on a search trip and uh he got talking to a biologist working on this plant called seagrass.
2:06:14
He'd never heard about seaggrass before.
2:06:16
I had never heard about seaggrass really before despite growing up by the seaside.
2:06:20
And uh he became captivated by it.
2:06:22
And then he like uh you know like uh any good uh autistic engineer does.
2:06:27
He goes down a rabbit hole learning about it and telling all his friends about it and telling us about it.
2:06:32
Um seagrass is this wonder plant in the oceans that supports 20% of the world's fish stocks.
2:06:35
Um it um holds about 20% of the the carbon in the ocean as well.
2:06:41
Underneath it it's 35 times better than rainforest or removing carbon.
2:06:44
But it wasn't in Finding Nemo, so nobody knows about it really.
2:06:46
Um so we kind of discovered this and he you know in learning about it he realized like it's dying off all around the world and um it's basically very time intensive and expensive to uh bring it back to restore it and uh basically the methods people are doing to restore it um are manual.
2:07:02
They're divers going down with their hands and they're manually planting seeds and um takes a lot of time takes a lot of money and it's it's not really working.
2:07:09
and he kind of had, you know, we kind of had this insight then that like while we've mechanized, you know, nearly every kind of form of large scale outdoor work on on land, that really hasn't happened in the oceans yet.
2:07:20
Um like nobody's built the tractor equivalent for the oceans.
2:07:22
Um and that really like a lot of the kind of tasks in the ocean um whether it be in this you know narrow uh weird wonderful domain of seaggrass restoration or um in the the world of defense or in the commercial industry if you're building infrastructure we're still sending down tons of divers um to do like manual tasks that really just like make absolutely no sense. They're dangerous. They're expensive.
2:07:45
Um, so we kind of started in this like world of crass.
2:07:48
Got very obsessed with that and and had a very successful kind of first year just doing autonomous seagrass restoration services for for different governments around the world, working with governments in Australia and the US.
2:07:59
We did a million dollars in revenue last year and we're on track for for over two this year. Congratulations.
2:08:05
Yeah, when I met when I met when I met Will and I heard this like initial wedge, I was like this is so fascinating, interesting, like find like the most weird obscure market that no one would ever think of and just absolutely dominate it and then use that to earn the right to do many other things.
2:08:19
And I think I introduced Will to like 10 seed funds in like 30 minutes at one point um without getting the opt-in from Will.
2:08:27
I was just like people need to meet you and then within a few days I people were committing. So that's awesome.
2:08:33
awesome. Yeah, I learned to scuba dive off the coast of Catalina Island and when I was I was like 15 when I was doing it and it was um had all this amazing tall California kelp and I went back like a couple years ago and you you've heard the story there was like an
2:08:50
invasive kelp species that came over from Japan I believe on like a shipping container shipping shipping tanker and it completely wiped it out and it looks completely different and I I don't know if it's particularly important to restore the original California kelp. I
2:09:02
I imagine it probably is in some abstract sense, but uh it was just a bummer as a as a scuba diver to be like, it's not what I remember, which was like swimming through this beautiful forest.
2:09:11
It's just kind of these tumble weeds now.
2:09:12
Yeah, it's man, it's those purple urchins. Um it's it's that's it.
2:09:16
What happens a big a big way of uh like that invasive species are transmitted in the mo ocean is like a a t like a a ship will like um you know be in in the in the in Tokyo um in the port and then it'll fill up its it's like its ballast.
2:09:33
So it'll pull in water and when it's pulling in water it'll take in fish or urchins in this instance and fill up and then it'll go out to sea and then it'll land in San Diego or San Francisco in the port and then it'll release them all.
2:09:45
So, this happened as well with lion fish um in the Caribbean um in Miami.
2:09:49
And uh uh yeah, those lionfish are gnarly.
2:09:52
They're just like chewing up the coral everywhere.
2:09:53
Um I I went I went clawing them once.
2:09:56
You get I was in in the in the Cayman Islands uh working there one summer and we were getting paid like spear fish these lion fish. Yeah.
2:10:06
I mean, they taste great. They taste great.
2:10:08
That is the good side of the lion fish is that you can just hunt them relentlessly because no one cares about them because they're so invasive and they're like pretty fun to shoot and you shoot them with and you can make leather wallets with them as well making line fish leather wallets and you're like I'm actually I'm hunting but I'm saving the world. Yeah. Yeah. But you Yeah. It's like pigs in Texas.
2:10:28
I mean it's actually a problem and and it needs to be like really dealt with.
2:10:31
But as a as a consumer of hunting it's fantastic. Oh, it's great.
2:10:36
But yeah, these are these are good examples of tasks again that are just like still today it's like Irish dudes with spears going down just like yeah real realistically there aren't that many people that want to go spear fishing line fishing all day every day forever because like the like yeah a couple tourists doing it once a weekend is not going to do the job.
2:10:54
So yeah, you need automation 100%. Yeah. And like we Yeah.
2:11:00
So that's the kind of these are the types of this is like you know the same platform that we built for Seagrass. It's a service vehicle.
2:11:06
underwater vehicle with a different robotic payload and a different model on board fine-tuned on finding urchins or finding uh line fish.
2:11:12
You could, you know, we could have like a service that just like solve this problem for someone.
2:11:17
Uh what's the origin of the name?
2:11:19
Uh yeah, it was uh there was there was kind of a few things.
2:11:23
I mean, as most great ideas, it was uh conceived uh in the midst of drinking a rake points.
2:11:30
Um and uh but we were we were me and my co-founders were out.
2:11:33
We were like thinking about different names for the business.
2:11:36
And then we were thinking about that um 1997 animated movie the uh called Treasure Treasure Planet um where uh these like people that go on these this quest in the submarine um to to kind of save the world and uh they uh they we looked it up and it was called the submarine in that movie was called Ulyses.
2:11:52
And then interestingly when we got our first office, we got our first office in Dublin just after we raised the the preede in um October uh 24 uh or 23.
2:12:03
Um and uh we got our first office and to to the left of us was the house that James Joyce grew up in.
2:12:08
I sorry the Ulyses have the Irish connection as well which is you know another reason we chose it but to the left of us there was a house that house that James Joyce grew up in.
2:12:16
up in. to the right of us was the house or the museum of literature Ireland where the first uh copy of Ulyses is kept and uh in the in the park opposite our street just there's a big huge statue of James Joyce with a quote from
2:12:29
Ulyses there um and uh that also like about a week later my mom found a photo of me at home next to like a picture an extra like a James Joyce quote and there's like a quote underneath it all all this kind of happened in the same
2:12:42
week so it's kind of like okay we're keeping it now yeah because the nominative determinism here is that I mean the story of Ulisses Adysius is like a 10-year grind and it's like absolutely miserable like facing the
2:12:54
Cyclops and the getting enchanted by Cersei and the sirens and like I imagine that if things if nominative determinism holds the sirens for you are you won't be getting a quick buck in an aqua hire at meta anytime soon. You're going to be
2:13:08
You're going to be at this for a very long time.
2:13:10
I'm rooting for you and I think I think you will ultimately ultimately be successful, but uh buckle up.
2:13:15
You're going to go on an entrepreneurial journey if the name holds.
2:13:20
What uh who are your who are your biggest uh Irish Irish tech uh heroes?
2:13:27
What makes the Irish so so so infatuated with technology?
2:13:30
Um I mean what makes Irish people so infatuated?
2:13:34
I mean, you guys are well aware of the Hibernian conspiracy, of course.
2:13:37
As uh as two uh I I don't know what you guys have to say about your uh the the accusations that you know that Mr. Kugan and Mr.
2:13:44
Hayes are at the core of this uh cabal of Irish people in technology or Irish beating allegations.
2:13:52
Never beating the allegations.
2:13:54
What about Pachy McCormack? What about Molly O'Shea?
2:13:56
What about all these people with Irish surnames? What are they doing?
2:14:01
Why do they Why do they all suddenly have media programs all follow each other.
2:14:05
Why does Apple doicile all of their cash there? It's a good question. Yeah.
2:14:09
You think you think it's the Rothschilds, you know, running the money supply actually. Exactly. Sashi Satoshi Nakamoto.
2:14:17
Nakamoto is actually an Irish name.
2:14:19
The old father on on Nakamoto.
2:14:21
So there's Oh, interesting. It goes It goes deeper. It goes deeper.
2:14:26
And mine my my favorite Irish technologist would probably be George B, the inventor of Boolean algebra. Oh, there you go.
2:14:32
Foundation for modern computing. Yeah.
2:14:33
I didn't realize he was on deep cut.
2:14:35
Uh yeah, and then modern modern ones on Mab's a good friend as well.
2:14:41
Big fan of everything they're doing.
2:14:42
It's very very inspiring um to see to see someone like that and obviously the Collisons as well.
2:14:47
Um but I feel I feel the CO's everyone appreciates the Cson.
2:14:51
I don't think I know people appreciate the the great business that the guys at Intercom are building and I know you had him on the show recently and we just partnered with him.
2:15:00
Yeah, he's a sponsor now. Ring the bell. Ring the bell. Yeah. Yeah.
2:15:05
You can have in your tinfoil hat uh conspiracy.
2:15:07
There's definitely a line between us and own and then us and intercom and own appeared on the show.
2:15:14
He just happens to pay us through Stripe, you know. Yeah.
2:15:15
So, um uh I I had a random question for you um that I'm sure you have strong opinions on.
2:15:24
Uh, every now and then I'll see a video that's off the like coast of Chile and there's just like just fleets of fishing vehicles as far as Yeah, I can see what's going on down there.
2:15:35
Um, is there any solution to it?
2:15:39
I'm sure you've gotten asked that.
2:15:41
Is is your guys' tech something that could help address that? It is.
2:15:45
Yeah, we're speaking to some partners about about kind of supporting on this problem right now.
2:15:51
I think there's like two aspects to this problem.
2:15:53
So yeah, like characterizing the problem um the Chinese are um you know destroying um many oceans around the world, particularly in countries where they basically just don't have the money to monitor um their their seas and enforce marine protected areas and these sorts of things.
2:16:08
So up and down the coastlines of South America, this is like the single biggest thing that like South American navies are spending time on right now.
2:16:16
West Africa as well um is just being um completely like the fisheries there are being completely decimated in and around the Antarctic as well.
2:16:24
There's massive krill populations and krill populations are they're this kind of foundational species for a lot of other um marine life in the ocean.
2:16:32
You take away the krill which is the kind of bottom of the food chain.
2:16:33
You know it knocks all the way up to the to the whales and then you lose the whales as well and nobody wants to lose the whales.
2:16:39
Um so that's kind of like characterizing the problem.
2:16:42
Okay, the reason the problem exists is okay two reasons.
2:16:44
natives that basically just can't cover enough area um and get maritime domain awareness.
2:16:49
They just can't they don't have enough assets.
2:16:51
Um you know that's part of the problem and there's like a governance aspect of the problem as well, right?
2:16:56
So okay, how does China get away with it?
2:16:58
Well, so you know the the people responsible for kind of looking after um you know law on the high seas quite often is what you'd call the flag state.
2:17:07
So where the boat is registered, all these boats are registered.
2:17:11
Chinese Chinese kind of like knows this is their kind of they use this as what you know you'd call like gray warfare.
2:17:16
Um it's kind of similar with the critical undersea infrastructure.
2:17:19
You know, it's not really officially the Chinese state, but it may as well be because they're not like prosecuting on it.
2:17:25
like prosecuting on it. Um so uh on the on the technical side I suppose like the the problem here is like the again the paradigm of of um maritime operations is kind of you know is is stuck and it's it's broken right it's you know you could probably characterize it we call
2:17:42
it this the heavy tech bottleneck right so basically any mission you want to do in the ocean kind of has like a few um features around it like it it generally uh you know relies on these expensive manned assets so these could be airplanes like P3 3 Orions or they could be um you know expensive uh national security cutters. These big coast guard
2:18:00
These big coast guard cutters, these 100 foot 200 foot long vehicles and uh these cost like tens of millions um to you know in capex and then the running cost for them on a day is like tens of thousands if not hundreds of thousands of dollars to run daily.
2:18:14
And then you use these things as like a platform on which you put sensors um uh or you you use like an unmanned system and that's kind of like what it relies on.
2:18:21
So, it's like small numbers of very expensive assets.
2:18:23
Whereas the way we're seeing autonomy going around the world, whether it be like self-driving car transport network, like self-driving cars or drones in Ukraine, is like we're moving away from these small networks of exclusive vehicles to large networks of small autonomous vehicles, right?
2:18:39
So, it's like going from buses and trains to like a network of Whimos or Tesla robo taxis.
2:18:43
Uh, you know, on the battlefield, it's moving away from fighter jets to like a bajillion Neros drones.
2:18:48
um you know it's like it's like this is like just the way we're going.
2:18:52
But that hasn't really happened yet in the ocean.
2:18:53
And the limiting factor we think is that um basically drones are still like crazy expensive in the ocean.
2:19:00
Unmanned systems are crazy expensive.
2:19:02
Even if you want to buy, you know, the the sexiest unmanned surface vehicle, you're still paying hundreds of thousands of dollars.
2:19:08
Underwater vehicles, you're spending hundreds of thousands if not millions of dollars.
2:19:10
Um but we haven't had like a DJI yet for the ocean, right?
2:19:12
We haven't had someone that really like completely collapsed costs to the degree that you can buy fleets instead of single units.
2:19:20
So again, that's kind of like what we're trying to position ourselves as is like this person who you can buy, if you're like the Argentinian Navy and your fisheries just getting obliterated, you can buy like a swarm of um surface and subc vehicles to kind of solve the problem for the fraction of a cost you purchase a MAN asset for that works 24/7 um with zero opex just controlled over scom.
2:19:42
How much is the problem that people, you know, these governments don't know something is happening or they know but it's 30 boats that have showed up somewhere and they're just going to fish, you know, and and basically decimate all life until they're maybe pushed away by a boat.
2:20:02
like what what is I I can see the technology angle of of getting just like more coverage uh and knowing more about what's happening in these different areas, but it feels like there needs to be um more will from the government as well to just say like we're not going to let this happen.
2:20:23
Yeah, I mean the the the will is like certainly there.
2:20:25
It's just they don't they don't have the budget on current assets like it like you know like some of these like if you want to buy more of these like um like boats that they would need or these planes that they need to like survey or or get like awareness on the area like these are like tens of millions if not hundreds of millions for some of these assets and the Argentinian Navy just doesn't have that kind of money.
2:20:44
Um so they know that in general there's a problem there but they just don't have enough assets out there.
2:20:46
Um I mean it's crazy that like most of the Argentinian air force's time is now spent on looking for Chinese ships over their waters.
2:20:54
It's it's um so it's like they just yeah they don't have the money.
2:20:58
So yeah, you really do need cheaper solutions for for these types of folks.
2:21:01
What other what other stories are you are you tracking or kind of problems globally that that you think you're I want to hear about like this big ship building bill.
2:21:09
Like how does the new budget fit in?
2:21:11
What are you tracking in DC?
2:21:13
I know you're still an early stage company, but I imagine that um the the long term has to be figure out a way to get to program program of record, work with the DoD, but break it down.
2:21:25
How are you actually thinking about that?
2:21:29
Because it feels like there's a lot of different applications.
2:21:30
You got to stay dual use.
2:21:31
You got to stay agile while you're building the underlying tech.
2:21:33
But what are you what are you looking at in DC?
2:21:36
Yeah, like for us on the kind of um government BD side, there's there's kind of three plates that were always spinning, right?
2:21:43
There's like the the DC plate, there's the like operator or war fighter end user state, and then there's like the acquisition st uh teams play.
2:21:53
So, we're always just like in constant dialogue and with like you know different members of these these three um these bodies.
2:21:58
So, yeah, the the the most recent um you know, appropriation for for defense is very interesting.
2:22:03
Um there's uh many many billions going to uh maritime unmanned systems particularly surface vehicles and underwater vehicles.
2:22:11
I think there's a general recognition um on the hill right now that like you know you know the Chinese are producing like hundreds of ships per per year and uh you know US is producing one ship per year and that like trying to build beat them on ship building is like probably not feasible.
2:22:30
We're not going to ramp up that production that quickly.
2:22:31
We need to just play a different game.
2:22:33
And I think they're seeing like unmanned systems as like the the way to that.
2:22:36
Um so um yeah, just this week it was announced again another um nine billion.
2:22:42
Um you know, a few months ago as well, there was another four billion allocated to this line item.
2:22:46
So um yeah, they're the things that that that we're tracking.
2:22:50
There's some some existing um programmer records that are already set up that um that we're, you know, in the kind of running to um to kind of to kind of challenge for and uh get a get a position on.
2:23:01
And uh there's also talk of some new ones being set up for these some of these newer categories of vehicles that haven't been developed yet.
2:23:08
But yeah, out of the three plates that we're spinning right now, it's you know, generally that you know, you you do want to have like um a presence in DC kind of like at this early stage. It's not the main focus.
2:23:16
The main focus is refining our product with the end user, understanding what their needs are and building building to spec.
2:23:22
Um so that's kind of like our main focus right now and spoken to speak to some some folks in Navy about that.
2:23:27
um and uh members of DHS and Department of Homeland Security and other other groups as well on this.
2:23:34
Um so they're kind of our main focus right now in that front.
2:23:39
Probability P Atlantis, what's the probability that you guys find it?
2:23:45
Uh I think I think uh very high.
2:23:45
Um I think it's probably in very high.
2:23:49
Do you think that Atlantis exists? Yes.
2:23:51
I think there's like two very good uh candidates for Atlantis.
2:23:56
Um there is one um structure in Moritania in um modern modern day Moritania called the recap structure.
2:24:05
Um so the recap structure is basically three concentric rings in um the middle of the desert with salt deposits between each of them. It looks man-made.
2:24:13
You can see it from space.
2:24:13
You can look up the recap structure or IC.
2:24:18
And uh the only des the only description we have from of of Atlantis is actually from Plato.
2:24:23
Plato describes it as being this like walled city full of gold with you know built with the kind of this city hall being at the middle of three concentric rings.
2:24:33
The ring you know the rings were each filled with um seawater and um modernday Mortania is also where um the richest uh the richest uh man that ever lived uh existed.
2:24:43
So there was this Moritanian king who had um more gold.
2:24:48
gold. he would have been the I think the you know the first trillionaire um and uh yeah that's for and uh and he uh and and and so that that's the gold part of it the reconstruction of three rings is that part of it and then there's also these all these like salt strayations
2:25:05
all the way from the coastline in West Africa to this location so it's kind of the theory that there was this um there was this uh apocalyptic event about 11,500 years ago called the related to the comet hitting the earth and uh Atlantis was there there was a great flood and uh this this city was um lost. So um that's that's one location. The
2:25:22
So um that's that's one location.
2:25:22
The other one is in the is in um the Atlantic Ocean um which then would lead to some of the first survivors potentially leaving the Atlantis and going to Ireland um to set up the the next modern day civilization. Okay. Okay.
2:25:36
We're bringing back next time we're getting to the bottom of the Bermuda Triangle.
2:25:40
Uh but thanks so much for stopping by. This is fantastic.
2:25:44
We'll talk to you soon, Will.
2:25:44
Great having you on, Will. Thanks for having us. Cheers. Bye.
2:25:46
Really quickly, let me When we find Atlantis, you know what we're doing.
2:25:50
Cure the cure for male loneliness being called lads. Lads. Yeah. Uh what are we doing? What's the first thing?
2:25:56
The first thing, set up a wander. That's right.
2:25:58
You got to find your happy place. Find your happy place.
2:26:02
Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
2:26:07
It's a vacation home better.
2:26:07
A video dropping with Wander this week. Cannot wait to release.
2:26:11
And we have a new guest dropping on the stream.
2:26:12
We are surrounded by journalists. hold your position.
2:26:16
Uh we're going to bring in Kylie.
2:26:18
Kylie did the reporting that we covered uh for Wired covering the leaked uh the leaked memo. Very cool.
2:26:27
Um so let's bring her on in. There she is. What's happening? Welcome to the stream. Hello. Hello. My first time. Thanks for having me. First of many hopefully. Uh how's the day going?
2:26:39
You've been scooping scooping up a storm. Yeah, it's been busy.
2:26:43
Um, just that this morning and tweeting non-stop and now you guys. Fantastic. Awesome.
2:26:49
Uh, so what did your what did your weekend look like?
2:26:51
What's the god what's like?
2:26:54
Break down like a a a weekend of of scoops.
2:26:57
It's pushing signal messenger to the max.
2:27:04
Um, well, it was Pride weekend here in San Francisco, so that wasn't uh fun to combine.
2:27:08
I helped a friend move and then I got the first scoop and ran to Pride in Dolores, drank a bunch of White Claws, ran home, slept for 12 hours and um my editor started scooping again.
2:27:22
Then we're scooping again Monday first thing in the morning scooping the Everything's been moving quickly.
2:27:26
What was the first scoop and and maybe like break that down. Yeah. Yeah. Yeah.
2:27:29
So I think that was Friday.
2:27:32
I reported on a research paper that's not being released at OpenAI because it talks about the definition of AGI and uh sources have said that allegedly managers were saying that the Microsoft deal and those neg negotiations were a reason for not releasing that paper and it's really really tense as the journal and Reuters have reported those negotiations.
2:27:53
Then Saturday for OpenAI researchers went to Meta's new lab.
2:27:58
Sunday, uh, Mark Chen, uh, an executive at OpenAI, sent out a memo saying they're basically Meta's basically robbing our home.
2:28:06
Uh, my editor published that one.
2:28:08
And this morning, Mark Zuckerberg sent out a list of all his new hires. It's been fun. Huge.
2:28:16
So, we got to ask, who's your source? No, I'm kidding.
2:28:19
Um, you're not going on the record as you guys. Yeah. Yeah. Yeah. Um, no, no.
2:28:23
So, um, yeah, I'm I'm curious kind of what what you expect next in this in this saga.
2:28:27
Do you expect I mean it clearly OpenAI is not seeing Zach announced his current list and being like, okay, we're safe now.
2:28:37
We don't, you know, we don't have to worry.
2:28:40
But at the same time, you know, it's very possible that the worst behind them. Yeah.
2:28:45
My my question I talked to Will about this was just like were you surprised that the memo didn't lean more on the fact that this has happened like three or four times at OpenAI and they've gotten through it every time?
2:28:59
Like I would be leaning on the fact that like yeah Daario left, Elon started XAI, Thinking Machines exists, SSI exists, we we still have 90% penetration in consumer AI.
2:29:10
walk down the street, ask someone what they use for AI, they're not even gonna say OpenAI or Chat GBT.
2:29:16
They're just gonna say chat.
2:29:16
And and and just leaning into that that that hey, we are this compounding dominant force in consumer AI.
2:29:24
This is the place that you want to stay and be as opposed to getting I think a little bit more in the weeds of like the nature of the deal.
2:29:31
It felt like an appeal maybe not very defensive and and came across.
2:29:37
I mean, they were clearly scared. Yeah. Yeah.
2:29:42
It it seemed very focused on like the the the the actual dynamics of like how how one of these offers comes together as opposed to just um just reiterating the strengths that like here you get to work on the consumer product in AI. Yeah.
2:29:56
Yeah, it was it was like a lot of messaging around please talk to us if you're if you're getting offers versus let's rally, let's let's all be in the like let's ride.
2:30:10
Yeah, I think it's you know a big part of it came over the weekends like these people are just these executives are scrambling to tell staff like for the love of God do not talk to anyone at Meta and sign any offers and they're going on this like weekl long break next week.
2:30:24
So, I think they were just trying to get ahead of that.
2:30:25
But I think that your guys's argument that's right.
2:30:27
I think it's just like a very emotional, high stress time.
2:30:31
They're trying to ship to very large models and Mark Zuckerberg's coming in calling employees directly and offering millions and millions and millions of dollars.
2:30:39
So, I think like their response is emotional and defensive because it's like just so high stress, but that would have been a good tactic and I don't doubt it's coming eventually.
2:30:47
How how solid do you think you are on the $und00 million offer?
2:30:52
That's been floated multiple times and yeah, and we were kind of digging through the game theory of it like in in one way it benefits Sam to get that number out because if someone if Mark tries to poach someone for 50, they might be like, "Ah, I've been hearing that everyone's getting a hundred." Like come on.
2:31:06
Thought I was one of your top guys.
2:31:08
I thought I was near the top of your list.
2:31:09
And then and then you know it in some ways it benefits Mark because at at at Meta because if you're hearing about these hundred million offers you might be more willing to take that preliminary phone call because you know that they are ready to put money where their mouth is.
2:31:25
And so it kind of benefits both sides.
2:31:28
Dylan Patel was on a podcast a couple days ago talking about how they're not really sending a hundred million dollar wire with cash on day one that the there's earnouts to these structures and they can claw it back if you don't say and so how much nuance do you think there is on on that number specifically
2:31:45
because it's certainly headline grabbing the the the Wall Street Journal I mean they they put it in the special infographic right here like because 100 million is a nice round number and it reads very well and it works in a headline, but I'm just wondering if you think if you think it's 100% real or 50/50 or there's more nuance to it. Yeah. So, my take is the Wall Street Yeah.
2:32:04
So, my take is the Wall Street Journal and the New York Times both printed that number and they have really really rigorous editorial standards to get get to print.
2:32:12
So, they must have seen something, some highle sources that proved to them that that number is real.
2:32:17
I for one have not seen that number and for me I would have to see an offer letter with that number.
2:32:21
But knowing how tech salaries work, I don't think it's just like a wire transfer.
2:32:25
it's, you know, going to be golden handcuffs.
2:32:27
It's going to be over a certain amount of time.
2:32:30
And, uh, you know, the information had a really good story breaking down, you know, researcher salaries.
2:32:35
And just imagine if you came to OpenAI a couple years ago at 80 billion, 40 billion valuation and what that is now.
2:32:42
They don't really need um, you know, all this crazy money from Meta.
2:32:46
Uh, but it is attention grabbing.
2:32:49
Attention grabbing for sure.
2:32:51
It's also just funny when you when you say hund00 million for one person, it sounds like a lot.
2:32:56
But if you were to say we're going to spend $5 billion to put together a team that is super core to our entire business and win, it doesn't feel nearly as significant for a company that is a multi-trillion dollar company.
2:33:10
So, I'm looking at the the the the WhatsApp acquisition price and number of employees.
2:33:19
I'm pretty sure they paid more than $100 million per person because it was $19 billion.
2:33:22
Uh4 billion in cash, 14 billion in Facebook shares which are probably worth like 120 billion now because this is in 2014.
2:33:29
And at the time WhatsApp was a remarkably lean team with around 50 employees. So I mean not far off.
2:33:37
I mean what if they had slightly different comp though just given that they were buying a product with Totally. Yeah. Yeah.
2:33:44
the product super valuable, but you know, the the the the researchers that can build the next model and and bring Llama to the frontier makes a lot of sense.
2:33:52
Um, what what else should we dig into here? I think that was it.
2:33:57
Any Yeah, I I don't know if you touched on this specifically, but any any any like specific predictions about what comes next or you just waiting waiting for one of your little birdies to send you a note?
2:34:09
Well, if you're watching birdies, my signal is kylie.
2:34:15
I will be impressed if they get someone of Ilia's Ilia Susver's capabilities.
2:34:17
I think that the people who want to build super intelligence are true believers and you're giving them a value proposition of we will give you so much money but you're making super intelligence for Mark Zuckerberg.
2:34:31
And I think that some of the best brains that really believe in AGI is this prosperous future or you know perhaps the end of humanity don't necessarily want to do that for Mark Zuckerberg.
2:34:42
Uh so I will be impressed if he gets one of those minds.
2:34:46
Uh he still has about 50 people he wants to hire for this team.
2:34:48
So it's just going to keep coming.
2:34:50
I think a lot of them are going to continue coming from the top labs.
2:34:53
Uh but what the vision is, what Mark's vision is, I'm waiting to see.
2:34:58
So uh what about la last question? What about Daniel Gross?
2:35:02
It had been initially reported but but he wasn't on the wasn't on the list that that you released earlier. Yeah. Yeah.
2:35:08
I noticed that neither was the um the team from Switzerland.
2:35:13
I'm going to guess this is pure speculation.
2:35:15
For Switzerland, they have EU laws that make it uh strange to employ them right away.
2:35:19
But for Daniel Gross, I'm not sure what happened.
2:35:21
I saw that was reported by the information with Nat Freiedman.
2:35:24
I tried to be in touch with anyone who could tell me if Daniel's going, but he wasn't on the list.
2:35:29
So, uh I guess we'll see. Yeah. Very cool.
2:35:33
Well, I wouldn't be surprised if uh you start getting some major offers.
2:35:38
I can see the the the AI researcher space is hinging heating up.
2:35:42
The AI journalist uh it might be the next domino to fall. So yeah. Oh god.
2:35:48
We're here we're here to help talk you through any any sort of offers that you might get from you.
2:35:52
You guys can take a percent. We'll work it out. Fantastic. Awesome.
2:35:56
Well, great great having you on and uh yeah, excited to follow the rest of your reporting this week. Thanks. Cheers. Bye.
2:36:05
Next we have Joshua from Chai Discovery with a big launch this week.
2:36:08
It's always tough to to launch when um the biggest trade deal in tech history is going down.
2:36:15
Not even a trade deal, the biggest poaching.
2:36:17
We keep calling it a trade deal.
2:36:19
It was not much on the other side of the trade.
2:36:21
It was a non-consensual trade deal.
2:36:23
It's a It's more of like a a draft and Zuck is just drafting from the entire league.
2:36:28
I take 12 of your best people. Yeah. For nothing.
2:36:32
Yeah, he's kind of just building an allar an all-star roster.
2:36:35
It's like all-star weekend over at Meta this week.
2:36:37
Anyway, uh Joshua, welcome to the stream. How you doing? I'm doing great.
2:36:41
Thanks so much for having me. Excited to be here. Of course. Great to have you. Uh kick us off.
2:36:48
Great work, you know, uh launching on on such a a wild day in in tech history.
2:36:54
Um but uh is the time run really getting like completely steamrolled by this story or I don't know. It feels like that.
2:37:00
Maybe maybe I feel like there's also people on vacation and stuff, but break it down for us. What is the big news?
2:37:04
Well, the big news is we've just announced CHI 2, which is our latest foundation model at at Chai Discovery.
2:37:11
Chi 2 is actually allowing us to now generate antibbody sequences with a success rate that's high enough for us to skip the usual high throughput lab testing.
2:37:20
This means that you can go take a target, put that into our model, go generate a set of uh potential protein sequences, and then test them in the lab, and they tend to work with extremely high hit rates.
2:37:31
Uh previous methods were like 0. 1% or so.
2:37:35
So, you'd have to screen, you know, hundreds of thousands uh to to potentially find something.
2:37:38
Uh but here, the hit rates are actually upwards of of 15%, approaching 20% uh of success. Amazing.
2:37:44
uh break down some immediate applications of that tech across maybe different types of uh categories.
2:37:50
You want to you want to ask him about making a more more potent testosterone that maybe we get to that next. Okay.
2:37:57
Um yeah, may maybe that's the right spin output.
2:38:08
I think one thing that we're uh really passionate about is going after areas that are really hard to do today.
2:38:13
So, you know, like this allows us to do things faster and cheaper potentially, but I think what's really going to be gamechanging is just opening up new kinds of biology that wasn't possible before.
2:38:22
So, we've got scientists that are like, you know, maybe working for years trying to enable a certain class of drug program.
2:38:27
uh and if we can now use machine learning to jump uh to to potential solutions uh that could really just really uh kind of push up uh the bar of of what people need to do.
2:38:37
I think it's you take a step back like look at what happened with LLMs.
2:38:42
Everyone has to be an AI company now to compete, right?
2:38:44
What's that going to look like in biotech where if you don't have access to a technology like this and then you start to have these certain areas that are closed out to you like what is that going to look like?
2:38:52
Um, so I think that that's something that we are uh really excited to figure out.
2:38:56
So if we benchmark it to the LLM market, uh, do you see yourself taking more of an anthropic path or an open AI path?
2:39:04
And what I mean by that is uh, or do you develop the drugs?
2:39:07
Do you wind up being the front end to this and kind of being full stack or do you go more like B2B and you have a bunch of pharma companies or you know traditional biotech companies that are buying a product or or service from you?
2:39:19
Yeah, it's a great question.
2:39:22
You know, I think if we take any lesson from the LLM market, it's that the winners are going to be the ones who are most agile.
2:39:27
The technology is evolving at a faster clip than we ever expected.
2:39:31
Our our company goal for this entire year was to get to a 1% success rate on this task.
2:39:35
And you know, we're halfway into the year and we're already past 15%.
2:39:39
When you have progress like that, it is really hard to predict like how the market is going to evolve.
2:39:45
And that's why I think just like being flexible, making sure that we have the best technology, making sure that we have the best way to use that technology as well.
2:39:52
You know, it's not just throwing a model over the wall and you get a drug.
2:39:55
Uh we really have to make the models work well for the specific applications where they're most important.
2:40:00
And we also have to make them much easier to use.
2:40:01
We have to get them into the right people's hands.
2:40:03
Uh there's a lot of scientists that if we can bring their creativity and ingenuity together with these new models, that that's where the magic's going to happen.
2:40:10
What's the state-of-the-art in like actual the actual impact of antibodies?
2:40:15
Like the last time I heard antibodies in the news was when Joe Rogan was taking monoconal antibodies for COVID infection and uh that was one of those weird things where it felt like a very modern totally not controversial.
2:40:28
Yeah, it felt like a very modern piece of science and the narrative around him was that he was not adopting the modern science but he was kind of on the cutting edge of that fork of the tech tree.
2:40:38
And so is are monoconal antibodies like the most like the latest and greatest or are there other applications that are uh particularly interesting or just driving value even if they're even if they're there are indeed like the traditional way. Yeah.
2:40:49
So about half of drug approvals these days are are actually biologics protein drugs.
2:40:54
So antibodies monoconal antibodies are actually just one type.
2:40:58
Uh that's closer to what you know we've been exploring in in this paper.
2:41:02
But I actually think what's going to happen is that uh people have now started to push beyond that.
2:41:08
They're basic like by specifics are all the rage right now.
2:41:10
That's basically you can think of it as two antibodies that are kind of stuck together.
2:41:13
So you can actually go after multiple targets at the same time or you can actually get like a more potent behavior for single target.
2:41:21
You know it's kind of just like two things in one.
2:41:22
So if we can make you know the fir if we can make each one of those chains like easier to design then you know bringing them together is going to be going to be even easier as well.
2:41:29
So I think it just like raises the bar for the kinds of therapies that you have to work on because it becomes easier to make those drugs.
2:41:34
So that's what monoconal antibodies are.
2:41:36
They were really important in COVID, right?
2:41:37
They can neutralize viruses.
2:41:38
Uh the way that people found them during COVID was they actually went to patients who had COVID.
2:41:44
Uh they just like, you know, you would go and just like take someone's blood, for example, and and try to find uh antibodies that are in there and then try to develop that into a therapy.
2:41:51
But now we can just make it on the computer in 24 hours and then go test it in the lab and have some results in in a few weeks.
2:41:58
So, there's a lot more work to do to make sure that these molecules will actually work in in in the clinic uh and will work well in patients.
2:42:03
We have early signs uh that that they have drug-like properties, which is really nice to see.
2:42:08
Uh but we've got a lot of work ahead of us in order to really bring that to production if if you will.
2:42:13
Uh there's still some more engineering that you might want to do on on the molecules that are coming out of the platform today. Yeah.
2:42:17
What what is your sci-fi vision for the state of drug development 50 years from now?
2:42:23
And how would the FDA have to adapt regulations to enable that?
2:42:29
Because I can imagine my vision is like you come in to some type of doctor clinic setting, you have some set of conditions and they're just sort of like autogenerating drugs on the fly specifically to your current conditions, but that obviously wouldn't work in in the current um paradigm.
2:42:50
Yeah, I mean that that would be the dream.
2:42:52
Um the north star that we have for this space is something uh that we think of as like zero shot drug candidates.
2:42:58
Right now we have these zorshock proteins, right?
2:42:59
So we specify a target, we get some protein that binds it.
2:43:03
But the fact that this is possible makes us believe that someday we'll be able to actually just like have the models think about all the other properties that we need for a drug.
2:43:12
And it's possible that the first sequences that come out of the model will actually be good enough uh to eventually move into patients.
2:43:18
And yeah, if you can do that, then you know, maybe the next stretch is like can we actually do hyperpersonalized medicine, right?
2:43:24
Maybe there's something where we take some sample from a patient, we figure out what exact target we need to go after, then we go and generate the drug.
2:43:31
I mean, there's multiple leaps that need to happen.
2:43:34
Uh, but I I can't predict what's going to happen 50 years from now.
2:43:37
Like, honestly, I failed in predicting what's going to happen in 6 months.
2:43:39
I I thought this now you're going to be at 1%.
2:43:42
Do you use AlphaFold or is it just a separate tech that is kind of complimentary but not uh in your direct supply chain? Yeah.
2:43:49
Uh, the foundation models are built in house here.
2:43:53
So we don't use alpha fold.
2:43:53
Uh we actually can't use alpha fold.
2:43:56
The latest one is isn't available at the company. So we built our own.
2:43:59
Uh we have a state-of-the-art model uh for predicting protein protein structure and its interactions with molecules.
2:44:04
We actually open sourced that.
2:44:06
So we started the company a little over a year ago and then 6 months in that was the first thing we did because you really need like an atomic level microscope uh if you're going to design drugs.
2:44:15
That was our thesis when we got started.
2:44:17
um uh but we realized that you know that kind of level of the technology we thought would would get out there anyway.
2:44:23
So so we open source that uh it's being used in in most of the major pharmaceuticals today.
2:44:27
I think the community has has gotten a lot of engagement around that.
2:44:30
Uh but now the models are becoming even more complicated.
2:44:33
So that's why we're starting to invest in not just the model layer but but how we actually make those models useful.
2:44:38
Uh they're really starting to look more like pipelines.
2:44:41
It's it's kind of like chat GPT 03.
2:44:41
It's not just a single inference.
2:44:44
there's actually, you know, a bunch of complex tricks that you need to run if you're going to get the best results.
2:44:49
Um, so, uh, that that's that's kind of how we're thinking about it right now. Very cool.
2:44:55
Well, congrats on the launch.
2:44:55
We'll have to have you back soon. This is fantastic. Yeah.
2:44:57
With a with a rate that you guys are are moving, I'm sure you'll be back on in a couple weeks. So, congrats.
2:45:03
Congrats to you and the whole team. We'll talk to you soon. Really appreciate it. Cheers. Thank you, guys.
2:45:08
Up next, we have John from Campfire coming on the show.
2:45:10
Welcome to the stream, John. How are you doing? I missed this.
2:45:19
You You haven't been hitting the soundboard enough. I love it. Boom. Welcome to the stream. How you doing, John? Can you hear us? Yes, I can.
2:45:29
Thank you so much for having me on today. Fantastic.
2:45:30
Uh, do you want to kick it off with an introduction on yourself and the company? Absolutely.
2:45:36
I'm the founder CEO at Campfire.
2:45:36
We're based in San Francisco and I was a finance exec for about 15 years and just lived the pain. Thank you. Operation unsung heroes. The unsung heroes.
2:45:47
Um never featured in the all hands but uh we're working on changing that here and uh lived in spreadsheets my whole life and just helping I don't think they're going anywhere anytime soon but helping folks take all the transactional accounting all the financial reporting and get it into software.
2:46:06
And so campfire is the modern ERP for high growth companies to just help them uh move to an AI uh powered platform. And so that's we do.
2:46:17
How young were you when you realized you wanted to build the modern ERP?
2:46:24
Uh I would say it's not something you think of growing up.
2:46:26
It's not like I'm sure kids I'm sure some ambitious kids these days think I'm going to build I'm going to build the nextG ERP. Go ahead. You'd be surprised.
2:46:37
So going into White Cominator, there's about 4,000 companies that have gone through it, but they probably hundreds of thousands apply.
2:46:44
They're like, you know, no one came to us and said, "We want to build a new ERP."
2:46:47
They're like, "You're you're like the only one excited about the category."
2:46:50
So, um, I would say I this was in 2020 2021 when I really was feeling the pain at a midsize company that I'm like, "This is the largest category in software.
2:47:01
Why is nobody disrupting it?"
2:47:03
And that's that was a that was a critical moment for me.
2:47:06
Well, it's interesting because it's it's not going to fit the pro like you need to have lived and breathed the problem to know what to build.
2:47:15
And I think that YC has like the the sort of default type of founder that does that.
2:47:22
Maybe they have a few years as an engineer at Palunteer or they were a product manager at Coinbase or something like that.
2:47:27
is very different than being like on you know being in being in the seauite actually living and breathing and and having that ability to go and figure out what to build.
2:47:38
Give us the latest on the fundraising side.
2:47:40
Yeah, we announced today Excel is leading our $35 million series adulations.
2:47:50
[Music] You like hitting the gong.
2:47:51
Uh I I want to talk you said high growth.
2:47:53
Um I remember I was running a company and uh there was a big debate over like oh like you know like thank goodness we don't need to implement Oracle we get to implement Netswuite and it was like still a lot of work. It was a big big ERP.
2:48:09
Uh and so it seems like uh the the playbook is is start with high growth startups be the first ERP and then scale into that and then eventually you'll be able to service the really really large Fortune 500 companies.
2:48:22
But it's it's fair to say that you're not ready to go into a Fortune 500 company today. Is that right?
2:48:28
And how do you think about actually growing the business long term? You said it well.
2:48:31
We're hiring on the sales team.
2:48:33
So, we would love to have you, but in all seriousness, uh we are not ready for the Fortune 500 yet.
2:48:37
We do have customers with hundreds of millions in ARR that have ripped out SAP.
2:48:41
They've ripped out Netswuite.
2:48:43
They've ripped out everything below that.
2:48:45
So, we are filling the pullup market quickly.
2:48:47
And one of the reasons for the raise is to go make us enterprise ready. Sure.
2:48:51
And our customers are saying, I don't want to be on an ERP for a few years, right?
2:48:57
I want to be on it for 10 plus.
2:48:57
I talked to the CFO at a 10,000 employee company still on Netswuite.
2:49:02
They really scaled into a hundred billion dollar plus market cap on Netswuite and they bought it at 100 employees. Yeah.
2:49:09
And so like how do we go how do we get them at 100 and scale with them to 10,000 and and that's really where we're going. Yeah.
2:49:15
I mean pretty sharp guy running the company over at Oracle.
2:49:21
it is a competitive market.
2:49:21
Um, but it does seem like there's there's lots of pockets of opportunity because uh the the I mean I I remember just like the implementation bill for Netswuite was going to be like half a million dollars in consulting or something like that.
2:49:34
It was it was pretty staggering.
2:49:36
How do you think about pricing and getting uh a growth stage company to actually match the value that you're delivering with the money that you make?
2:49:46
It's obviously great if you get a big contract up front and they're locked in for a long time and they're paying this massive implementation bill.
2:49:53
There's real costs to you if you have to implement stuff.
2:49:57
Um, how how are you thinking about uh ramping a customer into a great profit center for you long term? Yeah.
2:50:03
Um, first off, like we rethought the whole implementation process for the reasons you've stated.
2:50:10
Like you tell your accounting team, we bought an ERP.
2:50:11
Like everyone's ready to quit.
2:50:13
Nobody wants to go through a one-year implementation. Yep.
2:50:17
And so we've made it where like you give us a log into your old system, we go do all the work because everybody says, "I just don't have time.
2:50:23
Our team is way too lean to do this."
2:50:24
So a lot of the switching costs to your point, a lot of it is just like dollars, but a lot of it is just time.
2:50:31
So we've solved for both.
2:50:33
But to your point on like how do we get them into a profit center um we're just very focused on getting them in the door and making people super happy because we know like customers drive customers like referenceable and one of your sponsors ramp has done a great job at driving referenceability and customer love has really been I think the the verality within the finance and accounting community.
2:50:55
It's been a huge driver of their growth and so we're focused on the same.
2:50:58
How are you guys uh leveraging AI internally and then in the in the product itself? Never heard of it. Irrelevant. Don't need it. What it stands for? I'm not familiar. Yeah. Yeah. Don't need it. Built different. Yeah. We're doing it all.
2:51:15
Everything's if statements over here. Yeah, I know.
2:51:17
You know, I found I forgot what it was, but Excel's if statement limit.
2:51:21
I like over, you know, you That's the final boss of ERP.
2:51:26
You have to build an ERP after you hit the limit on XL.
2:51:30
You just unlock a like like Sacha Nadella just comes through the computer and says, "Good, you you've broken out of the matrix.
2:51:36
Welcome to the big leagues, writes you a check."
2:51:38
Um, anyway, our very first version of Campfire was I built a three-statement model that was framed into uh like a login and it was it was me on the back end running a Google sheet a three-statement Google Sheets for customers. Wow.
2:51:53
So, you got to start somewhere.
2:51:55
Um but uh yeah, we're super excited about AI.
2:51:59
So obviously one thing about us relative to the incumbents is like we are investing and putting AI everywhere, but whether it's Meta winning the AI talent war or Open AI, like we're always going to be on the latest models and we're always going to be multi model.
2:52:15
And so we're going to be inheriting all of the amazing work of all of these amazing AI engineers.
2:52:21
And we're of course building out our own proprietary AI models.
2:52:24
Um, but the gap between us and the incumbents is growing every time a new model ships irrespective of a vendor because we're always putting in the latest models. A few examples.
2:52:35
Customers are uploading their board minutes from the last meeting and saying take all of our row every row and campfire of every financial data and come up with a story narrative for the next board meeting and it's it's reading the board minutes.
2:52:49
It's going through and it's like here's the five things you should focus on based on all of it.
2:52:53
Um on the accounting side it's automating a lot of the accounting.
2:52:57
Um but we've built like a chat GPT for your finance and accounting data.
2:53:02
It'll write to the ledger. it'll report for you.
2:53:04
Um, customers are saying like kind of feels like we got a promotion.
2:53:09
I'm not in there doing formatting my y and x- axis anymore.
2:53:11
You know, the charts are coming out uh through AI.
2:53:15
And that that's been exciting to me because I I live that pain, guys.
2:53:18
I had a diligence report.
2:53:18
I had to build the day of my wedding. Wow.
2:53:24
That's pretty because we were we were in a bad ERP. So, don't be me.
2:53:26
You know, enjoy your wedding day. Enjoy your wedding day.
2:53:32
Uh last question for me in the news.
2:53:34
Uh Zero acquired the US uh the American B2B payments company Melio for three billion.
2:53:40
I think this was announced last week. Two and a half.
2:53:41
Uh who who's who's counting at this point?
2:53:45
Um can you explain to me like what the rationale you think was behind that? Why?
2:53:49
And and Zero feels like a different tier of product, not full ERP, more accounting suite for small businesses.
2:53:58
Why would they need a payments product?
2:54:00
Are you thinking about payments as a potential uh revenue generator in the future, whether it's through Stripe or Stable Coins or maybe you're going to buy an payments firm at one point? I don't know. Yeah.
2:54:10
So, um I can go really deep on this one.
2:54:13
So, as deep as you guys want to go, but at invoice to go, we were an air company, 250,000 businesses.
2:54:18
We were powering their invoicing globally in 150 countries. We competed with Melio. We sold to Bill. com.
2:54:24
Obviously, they're a titan in AP, a billion in in AP revenue.
2:54:26
And so I I know Zero and Millia well.
2:54:29
Um I'll say Zero was really looking to be stronger in the US market.
2:54:36
They're very strong in Australia, New Zealand, very strong in Western Europe and other parts of the world.
2:54:41
QuickBooks, unsurprisingly given their headquarters is here is dominant in the US.
2:54:46
Melio brings a strong footprint.
2:54:48
QuickBooks also launched their own AP products and Zero needed a response to that. Sure.
2:54:54
And so getting into the payments game, getting into APA in that solo entrepreneur category where I came from at Invoice to go is where Zero and Melio have a lot of strength.
2:55:06
We don't compete with either at all.
2:55:06
Y so we're really like a cut above.
2:55:08
So no competitive angle for for Campfire.
2:55:10
Um but I think one that actually no one has really covered is Melio is very strong in indirect.
2:55:18
So Ferve and others and this is public.
2:55:21
um Fiser and others are are selling uh Melio through their channel.
2:55:27
So Clover and other systems are out and so this is a new go to market that's becoming really popular.
2:55:32
We saw Brex embedded bill is embedded embedded go to market is is really a way to solve for really like efficient go to markets and I think this is a new one for for zero that is a great play. That's really helpful.
2:55:47
Thank you for that context. Uh, I appreciate it.
2:55:49
I always like when breakdown of their stuff and congratulations. Yeah, congratulations. Thanks. We'll talk to you soon. Have a good one. Bye. Cheers, Sean.
2:55:56
Up next, we have Tom Lee from BitMine, the first uh new uh treasury uh crypto treasury company.
2:56:06
This time on the New York Stock Exchange, not the NASDAQ.
2:56:08
Uh we're going to talk to him about crypto.
2:56:11
Really, really iconic stock exchange, if you ask me.
2:56:16
It's the New York of stock exchanges in many ways. Totally.
2:56:18
The city that never sleeps, the big apple. Totally. Totally.
2:56:22
If it was a stock exchange, it would be the New York stock exchange.
2:56:27
Um, very excited to talk to him. Yeah.
2:56:30
So, today they announced a 250 million private placement to implement buying Ethereum for their ETH treasury. Yes.
2:56:37
The stock ETH has been one of these was up 48% in the pre-market. Yes.
2:56:40
Uh, so welcome to the stream. how you doing? Good. Good to meet you.
2:56:47
Uh would you mind kicking us off with an introduction on yourself and the company and some of the news today? Uh glad to. Uh my name is Tom Lee.
2:56:55
I'm the uh founder of Funstrat, which is a research firm and many of those might know me from that role where I'm I periodically appear on CNBC and talk about markets. Mhm.
2:57:11
I'm also the chief investment officer of Funstrat Capital, which is the asset manager, and we have an ETF called Granny Shots. That's um 1. 4 billion of assets now.
2:57:22
And Funstrat as a research firm has 300 hedge fund clients and 10,000 RAAS.
2:57:31
and Arth uh and today uh it was announced that I'm uh taking a role separately from Funstrret as chairman of Bitmine Immersion Technologies and the ticker is BMNR and that's to help the company transform its existing treasury strategy to be one that is focused on Ethereum.
2:57:54
What was the decision to go with Ethereum?
2:57:55
We've seen a lot of Bitcoin treasury stories happening over the past year, I would say.
2:58:00
I mean, even going back further with Micro Strategy, but uh Ethereum is one that we just would highlight that the that Bitine uh is up 679% today.
2:58:13
So, uh the market is excited about what you're doing.
2:58:16
But back back to John's question.
2:58:22
Um well to me one of the things that caught my eye is that stable coins uh are the chat GPT of fintech right now because it's seen rapid adoption by consumers merchants and banks and now Visa uh and credit card providers.
2:58:38
It's because it really does have a a log function benefit over traditional dollars or over, you know, the credit card system.
2:58:51
And uh it's $250 billion today.
2:58:51
Treasury Secretary Bessant estimated or said it's reasonable it could go to two trillion.
2:58:59
That's a 10x market, you know, addressable market change, which means it's an exponential opportunity.
2:59:06
Stable coins have to transact on a layer 1 blockchain and the the blockchain that is considered the biggest and the most secure and the most commonly used for stable coins is Ethereum.
2:59:15
So we saw an opportunity to say listen, let's think about more tokenization uh you know that chat GG stable coins is the chat GBT but it's opening doors to other ways to tokenize assets and so uh we thought it would make sense to do some a treasury strategy around Ethereum and it it plays a role that the bigger we become the more important we are to the Ethereum ecosystem.
2:59:43
So, I think we're actually playing a role in stabilizing Ethereum because we essentially act as a staking entity.
2:59:50
And if we sort of think forward a few years, sorry if I'm rambling. Um, it's interesting.
2:59:55
Goldman and JP Morgan as they get into the stable coin business and Walmart and Amazon, they're going to realize that they need to really secure the layer one that they're operating on.
3:00:05
So, they want it to be a big blockchain, a lot of validators.
3:00:07
Um, Ethereum is the biggest.
3:00:09
And then the opportunity is that we're kind of like the plumbing of what banks will look like in the future because they'll be staking Ethereum on their balance sheet or crypto in order to fund and operate their stable coin.
3:00:25
Can you talk about the differences between the New York Stock Exchange and the NASDAQ and what it means to be uh listed on one or the other? Uh yes.
3:00:33
Um, if you look at our press release, what we announced and we put prominently in the headlines was New York Stock Exchange listed. Mhm.
3:00:43
And uh, and we listed all of our partners.
3:00:46
The reason for that is that most people know me as a traditional Finance World person that also is trafficking in crypto.
3:00:53
We've written about Bitcoin uh, for eight years.
3:00:57
We first recommended it when I was under a thousand to our clients, but it's been a slow road.
3:01:01
This project, the Bitmine immersions treasury strategy is really a convergence between traditional finance and crypto, right?
3:01:11
That's where stable coins are intersecting.
3:01:13
And the partners we brought on, you know, Founders Fund, Panta, Kraken, um, Falcon X, Galaxy Digital, uh, are companies that are really straddling the the crossover world and we want it to be on a prestigious exchange.
3:01:30
Most of these Treasury strategies are trading on the NASDAQ CM, which is like a a a sort of the Junior League of NASDAQ.
3:01:38
We want it to be on something prestigious because we want our traditional clients to come in and say, "Look, Tom, if we're going to be um interested in this treasury and learning about why this is might be a new bank model, uh we don't want to be buying stocks that are on a bulletin board."
3:01:56
So it was really important to be on a prestigious exchange like the New York Stock Exchange.
3:02:01
So I think that that's a real you know one of the advantages of uh Bitmine immersion is that they invested the time to be uplisted and so that they are on the New York Stock Exchange.
3:02:10
are on the New York Stock Exchange. H what uh uh is is is liquidity like different on the stock exchange versus like I mean as as someone who's like younger and and more I guess internet native like the idea of needing to buy a stock on a stock exchange is a little
3:02:30
bit foreign compared to just like self-custoding crypto directly uh and then you have access to buy the major cryptocurrencies on pretty much any app in the app these days like it it feels very accessible and yet um and yet in the in in the past we've seen uh the ETF as a catalyst for price movements in the major L1's. So uh talk to me about like
3:02:51
So uh talk to me about like what's actually going on in the market and and some of and characterize some of the different buyers and market participants and why they choose one way to get exposure over another. Yes. Um Yeah.
3:03:10
And and so let's say I I'll take it in two parts.
3:03:12
You know, the first is um like in terms of a product to buy a New York Stock Exchange listed stock, which is what BMNR is, has market makers.
3:03:24
Um it's almost like you have like this invisible hand protecting price and the exchange will halt the stock.
3:03:32
uh if it's if it feels one-sided, that's really important because it protects investors and these treasury strategies need to get institutional investors to sort of back the back this and become essentially create a two-way market so people can combine and sell these um with with real little price erosion.
3:03:52
Now, uh the second part though is someone say, "Well, Tom, why don't I just buy Ethereum ETF?" Yeah. Yeah.
3:03:58
Or I'll just layer one and I think the treasury the Ethereum treasury strategy.
3:04:04
Now there's another one which is sharp link um which was led by Joe Luben and consensus and that ticker is SBET.
3:04:12
I think the treasury strategies especially for Ethereum can actually deliver better returns um for holders because let's say the metric for a treasury strategy is um Ethereum per share.
3:04:32
Um now if you buy an ETF, your Ethereum per share is going to always be fixed because it's you're just buying a unit of Ethereum.
3:04:39
So you only benefit if Ethereum price goes up.
3:04:41
Whereas a treasury strategy, let's say has a Ethereum per share value, then there's three ways that that price of that treasury stock goes up.
3:04:55
One is um that the company generates staking yield.
3:04:59
So, you're getting a little income.
3:05:01
The second way that you benefit is if the company can capitalize on volatility.
3:05:07
And Ethereum has twice the volatility of Bitcoin. Mhm.
3:05:09
um which means the stock's twice as volatile.
3:05:14
That means you're you're going to be able to fund uh transactions like convertible instruments or sell stock in the open market and people are buying it for the liquidity and then you can increase the net asset value of Ethereum per share.
3:05:29
So you're kind of like growing someone's actually if you own a share of a treasury stock, someone's working to get you more Ethereum per share for every share you hold.
3:05:38
So they're they're actually like growing it.
3:05:39
And the third, of course, is the price of Ethereum goes up.
3:05:43
And that's where I think it's really interesting because like Circle, which is a the second largest stable coin issuer.
3:05:49
And it's been a it's probably the most successful IPO in like several years, it trades at around 100 times enterprise value to Ebida.
3:06:01
So, um, so for every dollar of Ebida, it's like $100 of market cap.
3:06:03
Um, Ethereum has a network yield of four.
3:06:11
So in other words, like Ethereum's four times cheaper than Circle, even though Circle runs on Ethereum.
3:06:17
So if usually like the more you get into the infrastructure layer, the higher the multiple is, that's why software has a higher multiple than a a retailer.
3:06:25
So that means like if but if you just said Ethereum should be a 1% yield then Ethereum should be like 12,000 um per unit and it's only like you know 20 500 now.
3:06:40
So I think that there's the third way is of course Ethereum could go up a lot. Yeah.
3:06:47
What uh what do you see as kind of the important milestones in Ethereum over the next few years?
3:06:54
uh we went through kind of the NFT boom.
3:06:56
We're now in the stable coin era.
3:06:59
Uh people have been still talking about store value.
3:07:02
They're also starting to talk more about prediction markets.
3:07:06
Um what is interesting to you about uh maybe crypto broadly over the next few years? Um yeah, glad to.
3:07:15
Well, you know what the I'd say the story arcs that we see is one the regulatory landscape has become very friendly for crypto. Um, huge deal.
3:07:28
Uh, the second is that institutional fiat money traditional is getting into crypto.
3:07:34
95% of institutions don't own crypto.
3:07:37
So, that's a huge addressable market. Mhm.
3:07:38
Uh but then there's technological innovation as you're pointing out and that and there's a lot of great projects because of that.
3:07:44
So Bitcoin um it's still our favorite layer one.
3:07:49
Um and so you know but that to us is digital gold.
3:07:52
You know it's it's really the best way to measure trust and if it ever traded at the value of gold's above ground value it's it's over a million dollars.
3:08:00
So we still see a lot of upside.
3:08:02
Ethereum unique feature is the smart contract.
3:08:08
Um, and we know that the majority of real world assets, tokenized things, including tokenized dollars and tokenized real estate and sec equities, etc.
3:08:19
, um, they're actually being minted on the Ethereum or created on the Ethereum blockchain.
3:08:24
So I I think as the world starts to tokenize and experiment and remember there's a lot more equities and real world assets to tokenize onto layer ones then the other way is the traditional financial world is trying to equitize crypto right through ETFs.
3:08:38
It's there's more to move into tokenizing on layer ones.
3:08:44
Um and the third of course is things like solving some of the risks of AI.
3:08:48
You know the whole idea of a decentralized blockchain.
3:08:53
I mean, look, let's face it.
3:08:55
There is a a a non- insignificant risk that AI is going to be malevolent.
3:08:58
Like, there'll be a catastrophe because every innovation has always led to a catastrophe in the short term.
3:09:06
Like um consumer credit was a technical innovation on um uh for consumer uh access to money and nearly every country that rolled out a credit card, whether it was Asia or Latin America, has had a credit crisis.
3:09:19
And then in 2008 we had a mortgage innovation with the securization of mortgages and it boomed for a while but then we had the GFC.
3:09:28
then we had the GFC. So I think AI is obviously going to be innovative and there's a lot of opportunities but it's inevitably inevitably going to lead to a catastrophe and I think that's when decentralized blockchains are going to be one one answer to sort of managing
3:09:44
the risk around AI and so uh I mean I don't know if bit tensor is a solution but I can see something running off Ethereum and validators you know human validators um is one way too interesting yeah talked to brand about that any any reactions to there's been a couple announcements in the last week. Republic
3:10:00
Republic came out creating their mirror tokens products which are bringing uh private company stocks on chain and then Robin Hood had an announcement I believe it was this morning around bringing OpenAI SpaceX on chain.
3:10:14
Uh any any kind of predictions around uh private company uh assets coming on chain?
3:10:25
I I love all these experiments because they're trying to provide a a hybrid form of liquidity to things that are illquid, you know, and um so it it makes sense and um you know the the answer to that is it is a big deal that Republic and then Robin Hood are doing this because you're you're going to create uh the probability of a more healthy market.
3:10:52
you know, this has to become a two-way market because if someone's just tokenizing assets, but then very few people use it.
3:10:56
And the way what I mean by use it, someone may want to own it, but someone might want to hedge something.
3:11:04
So like an open AI token isn't just someone's long bet on OpenAI.
3:11:10
They might be invested in, you know, Grock or something and then they need to hedge it by shorting the token.
3:11:15
Like if you can create a two-way market, then it's definitely going to work.
3:11:20
But if the if the market is purely on like let's just tokenize it, you buy it and hodddle it, then it's going to have the same liquidity problem that it originally had and then they might even trade it at discount and then you you create other risk because now you're putting it on a blockchain.
3:11:36
So now you have the actual risk of the physical asset being missing and then the blockchain being broken.
3:11:42
So I think it'll be important for two-way markets to develop around it. Very cool. Well, congratulations.
3:11:50
Yeah, congratulations on the announcement and uh we're excited to follow along.
3:11:54
Hopefully have you on again soon. Yeah. Fantastic.
3:11:55
Well, thanks for having me. We'll talk to you soon. Cheers. Bye.
3:12:02
Well, what else is going on? All of our ads. We are out of ads.
3:12:05
We need to We need more sponsors, but more on that soon because we have a new one coming.
3:12:12
Um um there's a story on Apple weighing from Mark German weighing using anthropic or open AI to power Siri in a major reversal.
3:12:19
But let's save it for tomorrow. Save it for tomorrow.
3:12:21
We do have some other news.
3:12:23
Cursor is now available on your phone and on the web.
3:12:28
Spin-off dozens of agents and review them later in your editor.
3:12:29
Andrew says, I join Cursor to build the future of coding.
3:12:34
And yes, as of today, you can code from anywhere with a coding assistant on every web browser and phone. Very, very cool.
3:12:39
We'll have to see how we'll have to give Tyler over there in the VR headset uh a challenge coding. There he is.
3:12:47
What are you doing over there, Tyler?
3:12:50
I'm just chilling in the metaverse. Oh, yeah. Yeah.
3:12:51
But what what specifically are you doing?
3:12:54
Are you I'm not playing video games. No, you're grinding. Oh, yeah. Yeah.
3:12:58
How how is the uh now that you've had this headset for a few hours? How it's sick? Wait, it's way better.
3:13:05
So, I I have the Quest 2 at home and um I think it's just all the Quest 3s, but they have this like back strap.
3:13:11
I don't know if you can see it, but I see it.
3:13:12
It's way more comfortable.
3:13:14
Like I'm not It's like totally comfortable to wear this right now. That's awesome.
3:13:16
Are So, are you doing pass through?
3:13:18
Are you using your computer?
3:13:19
I can see you guys right now. You can see me. Wow. I fingers. No way. Got it. How many fingers? Two. Oh, wow.
3:13:28
You can see right through. It's amazing.
3:13:30
I don't I I didn't realize the password was that challenge.
3:13:32
Don't take it off for 24 hours. starts now. Go on a date with it. Use Cley with it. Yes. Yeah.
3:13:42
I mean, this is the Clue This is the Cluey device right here.
3:13:44
We need a Cle app in there ASAP. ASAP. For sure. Yeah. You show up there. Why?
3:13:51
Why don't you take off your uh your MetaQuest 3s for the interview?
3:13:56
Actually, I' I'd prefer to leave it on.
3:14:01
Anyway, uh there's some other good posts we should go through.
3:14:02
Uh, apparently Xfinity is allowing people to use Wi-Fi signals to detect motion in your home at no extra cost.
3:14:11
And uh, this 5 seconds uh, account says, "I apologize to all my local schizophrenic schizophrenics. I owe you an apology.
3:14:20
I wasn't really familiar with your game because it's You remember there was a super there was a video that came out.
3:14:26
It was probably a year ago where somebody was showing how you can use Wi-Fi signals to people. Yeah.
3:14:32
to get a very accurate map, a 3D render of what's happening in space. And this was60.
3:14:38
It was almost hard to believe.
3:14:40
And then now Xfinity for free, no extra cost. Crazy. Crazy.
3:14:47
The the the concerning thing here is is introducing this technology to more people.
3:14:52
They're going to realize, oh, I can if they have if they're in apartment building, they're like, "Oh, I can see when my neighbor's home or a thief could set up a Wi-Fi router outside of somebody's home and start mapping it.
3:15:06
See what what what what's this person's schedule?
3:15:07
When are you going to put this on a on an assault rifle and give the uh give the special forces wall hacks?" I bet they No, no.
3:15:14
Somebody was Somebody was saying the CIA and and other law enforcement groups use this already to understand when there's like an active shooter scenario, understand where they are, the positioning of everything.
3:15:24
They got a fly on the set. Yeah, this is disaster. He's going after you.
3:15:27
Um but uh anyways, in other news, uh Kristoff Thulene Futurist says, "I am developing an LLM benchmark test that I believe is truly the first of its kind.
3:15:36
Very excited to launch this soon and hopefully partner with some of the Frontier Labs on it." Uh congratulations.
3:15:42
We'd love to check it out when it goes live, Kristoff.
3:15:43
So, thanks for the hard work.
3:15:46
Uh you're you're you're going up against Arc AGI.
3:15:50
So, you know, it's a it's it's not an easy easy the benchmark battle is hot, but good luck to you.
3:15:54
And uh Delian reflects on the progress of AI.
3:15:57
He says, "Uh, imagine gathering Allan Turing of 1942, Marvin Minsky of 1992, and Nick Bostonramm of 2012, and explaining to them that we have passed the Turing test several years ago.
3:16:09
And yes, there are some changes to society, but largely day-to-day life is the same.
3:16:14
Would be a funny conversation. It is it is crazy.
3:16:19
The soft singularity is real.
3:16:21
Everyone's feeling the the soft acceleration.
3:16:25
Um anyway, any other I mean it's just like Yeah, there's just like it.
3:16:28
Yeah, we beat the touring test and now we're on to super intelligence and then eventually giga intelligence.
3:16:33
Um but that's a great place to end the show. Thanks for watching.
3:16:36
We will see you tomorrow.
3:16:38
Leave us five stars on Apple Podcast and Spotify.