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>> Monday, August 11, 2025.
3:02
We are live from the TVP Ultra Run.
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the temple of technology, the fortress of finance, the capital of capital.
3:08
Do they do that in the Korean version of TVPN?
3:10
Do they scream at the camera and they open up the I need to watch this?
3:13
If you're not familiar, uh uh the there's a very there's a very uh uncanny clone of this show's format.
3:24
>> TBPN clone is at the timeline.
3:26
>> Yeah, Korean TVPN clone is at the time.
3:28
>> June Park, which is uh I believe >> I'm in favor of this. I think this is cool.
3:34
who is a technology brother. Okay.
3:37
Found NFM Live over on >> LinkedIn.
3:41
But we got to find their intro.
3:42
We got to see >> Yeah, we have to dig into this.
3:46
>> I imagine that you're watching NFM live in Korean would hit >> extremely hard.
3:50
It sounds like it it it sounds incredible.
3:54
Um but yeah, I mean this is fun.
3:57
Um obviously, you know, we've played a lot with this format.
3:59
We we invented television. We invented news.
4:02
And now people are taking our invention.
4:05
We forgot to patent it though.
4:07
We should have patented news and television and shows and live stuff and business news.
4:13
That would have been >> technology news, >> but we forgot to patent it.
4:15
And so now everyone's copying us from over in Korea.
4:20
But uh I mean it makes sense.
4:20
Uh we don't really I don't think we have a large audience in Korea.
4:24
And so have some fun over there. Hopefully it goes well. Good luck to you. Uh NFM Live.
4:27
I hope that you're massively successful and I hope that you know you can start with, you know, the exact layout that we've done and then you can kind of twist it and change it.
4:38
Make your own and and and that's that's how these things start.
4:41
Uh Tyler, what you got for >> Okay, so I just found it.
4:43
They do not do any kind of interesting intro.
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They just start the show.
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They just start the show. >> No energy. >> No energy. >> Okay. Uh step it up, guys.
4:51
You >> got to copy the important stuff. The important stuff.
4:56
It's not about the overlay.
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It's about >> it's it's about the screaming.
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You're losing your voice. >> Losing my voice.
5:01
J Kim, >> you got to get bring up the energy.
5:04
>> J Kim, he's the I clipped your intro, posted it, and have never gotten more responses.
5:10
>> That was the best intro we've ever done.
5:11
So, >> wait, just this one right now?
5:12
>> No, no, the one from last week we started the screaming.
5:14
So, >> I'm always trying to one up myself.
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The audience really likes Well, >> it really it really helps because we're always like just, you know, shuffling things around just one minute before we go live and then we really got to dial it in.
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And so the uh the screaming really takes it up another notch.
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Getting your business on ramp. com. Time is money. Save boat.
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>> Switch your business to ramp. com. >> Uh Gibly moment. As soon as Okay, sorry. >> Wait. Important news. >> Yeah. Yeah. Please, please, please.
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>> TVPN has hit substack. >> Oh yes. >> TV tvpn. substack. com.
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We have a daily newsletter now. >> Yes.
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>> Uh it is loosely based around the content that we cover on the show. >> Yep.
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So, some of the top stories and so, uh, some of the stuff we talk about on the show, we will have, you know, little summary teasers up there on our TBPN Substack.
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7:39
Uh so uh we talked about it yesterday or we talked about it last week and we talked about it a bunch.
7:45
Genie 3 hit the timeline was maybe the biggest news of last week in terms of artificial intelligence which is crazy because it was GPT5 but GPT5 was more of this uh consumer update.
7:55
We have some updates from Tyler. He's loving GPT5.
7:59
Interestingly kind of contrarian takes a lot of people were dunking on it.
8:04
Uh Tyler G, what did you like about GPT5?
8:07
Oh, and give me your eval. >> Yeah. Okay.
8:09
So, I've been over the weekend, I've been using it more for coding, like various things.
8:12
Um >> definitely I've been using the the thinking mode like the whole time cuz I I'm on the pro subscription.
8:18
So, you can choose thinking. So, it always thinks.
8:21
>> So, there is a drop down now. >> Yeah.
8:22
Well, there there always was a drop down at least for pro where you could do GT5 or GBT thinking. >> Interesting.
8:29
>> And now there's also I don't know if this was always there, but you can choose to add the legacy models too.
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So I can also I can still access >> on the flagship model.
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I I've just been yelling at it because I thought the model that was not available. >> Okay. Yeah. Yeah. Yeah. Yeah.
8:43
>> So there's the model router which I think is just GPT5 and that'll route sometimes to thinking. >> Okay.
8:48
But if but if I'm very stern with it, it usually thinks it usually throws itself in thinking mode.
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If I'm don't mess this up, don't get it wrong.
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>> Then it'll be like I'm thinking. I'm thinking. I'm thinking. >> Yeah.
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But um I I just always use thinking because I'm on pro wait.
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But so I have I have three versions.
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I have GPT5 which is the flagship model.
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I have GPT5 thinking which gets you more thorough answers.
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And I have GPT5 pro research grade intelligence.
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I want to be on pro the whole time.
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>> Uh so I think pro was similar to 03 pro where it's going to be like a it's going to take a long time.
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It's going to take 10 minutes every GP5 thinking is is similar to like 03 >> where it used it would just always think but sometimes it's it's pretty quick. >> Okay.
9:30
>> Well, I'm in I'm on chatgbd. com.
9:30
I can't find 40 and I'm wondering where is my girlfriend? Where's my girlfriend?
9:40
>> I'm still using >> I actually can't see 40.
9:41
They apparently added 40 back.
9:44
>> So So you can uh Yeah, that might just be for plus that you can go back but but you can add legacy models.
9:48
That's just for people who are really desperate and they replied to Sam Maltman on X with a really funny post and he turned it back on just for them.
9:56
So there's five people that have access to the old model, but everyone else is is rugged and on the new one. Um, okay.
10:02
But give me your eval and give me your qualitative assessment of like of like the model like like because it seems like you did you did a test where GPT5 outperformed all the other models, but then simultaneously it just seems like you've been having a good time.
10:18
So break both of those down. >> Yeah.
10:20
So, so generally like just for coding tasks, I found it very useful.
10:23
Um, >> I wouldn't say it's like blowing my mind with how much better it is than like >> 03 or 4.
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1 or something like that.
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>> But it is like it's a good model. It's a good model surf. >> Yeah. I would agree with that.
10:34
I'm trying to think of what I did this uh this weekend.
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A lot of times I was just like what am I thinking of?
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I you know giving you some different uh stuff.
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How how do I add something to my path?
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top US government contractors hedge fund research report.
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Like it was doing a lot of this stuff.
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Uh I was getting lunch with someone.
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They were recommending a piece of enterprise software.
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I just kind of described it.
10:54
It nailed it very quickly.
10:56
I don't think it took too long to to think it was fine.
10:58
I actually put in agent mode yesterday and I had it hunt around on the internet for a Nintendo Switch 2 and it did find one in stock >> which was which was very useful because there are Nintendo Switch trackers that you can go and you can like and they scrapes all the websites but this basically just did this on an ad hoc basis. It was good. It worked. It delivered.
11:20
Um, and then for other like kind of quick questions, it's always been it's been quick and I feel like I should be it it's definitely going to speed me up because it like it knows to not if I stick with the model router, it's going to respond quicker for the stuff that it knows.
11:36
>> So, also even if you're using thinking like on thinking mode, there's a button that says like give me a quick answer.
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So, you can just tap it and then if it's taking too long.
11:43
But yeah, also another thing was I I I forget exactly what I was writing, but it helped me with writing and I found it like better than I would have expected. >> That's cool.
11:52
>> That's cool. Yeah, I feel like I feel like as part of the reasoning chain, like the first response should just be like the the 40 response and then it should just surface that to you and it should just kind of say like here's what I know so far and then I'm going to keep thinking, keep cranking on this to
12:10
update this, go down the reasoning chain and then if you're like if you're good I'd almost like to to to flip that UX around so that it's automatically going deeper and fact-checking it and improving the response over time over 10 minutes, giving me, you know, a normal response within 10 seconds, then spending up to 10 minutes working on it. But if I'm satisfied with the 10-second
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But if I'm satisfied with the 10-second result, I can just kind of click like I'm good.
12:33
>> Yeah, >> that would be that that might be the next like probably save them money, too.
12:37
>> Yeah, that could be cool.
12:38
>> Anyway, um and then give me your email. >> Yes.
12:40
So, I I thought of this thing.
12:40
I think I I looked it up.
12:41
I think someone might have written a paper about this like a year ago, but it was like >> a quick question.
12:46
Does the Korean TVPN have an intern?
12:50
>> We need to figure that out.
12:50
You got to copy the intro and the intern.
12:53
>> You have to have it interned that you throw random questions at throughout. We can look. >> Okay.
12:57
Anyway, so back to your back.
12:58
>> So, basically my the new benchmark I've kind of thought of, although maybe someone's done it before, I got to look more into it.
13:03
Um, but it's basically solving a Rubik's cube.
13:04
So, >> yeah, >> solving a entire Rubik's cube is like totally like way too hard right now.
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But, um, if you basically just like start with a a solved cube and then just do like one move, then usually they can get one move.
13:17
If you do two moves, they like none of them can get it except GP5. >> Okay. Only GPT5. >> Yeah.
13:24
So you basically you can take like the state of the Rubik's cube >> two move champion of the world. >> Yeah.
13:29
>> And then if you put it in a string, you can format it nicely and then give it to it.
13:32
And then >> um uh GMT 5 thinking >> rotating the cube feels it feels somewhat like archi in the same way of like there's this visual spatial test that then's represented in text tokens and uh and an LLM should be able to operate on those if it was able to transform that into true spatial thinking, but it's not quite there. >> Yeah.
13:52
So so I think something I'm going to try I think I might like write a little blog post.
13:55
Um but I want to try like actually putting it in image format, right, with like multimodal and stuff.
14:01
Are you jealous of our substack?
14:03
You're like, "Oh, maybe I'll have a Substack." >> Yeah. >> Yeah. Oh, yeah. Yeah.
14:05
Maybe I'll just start one. No big deal.
14:07
You can put you can publish on ours. >> Okay.
14:12
>> But yes, you should you should flash that. So, continue.
14:15
>> Um, but yeah, I was thinking of like trying different formats for the the input.
14:18
Maybe that'll help it out.
14:18
Um, or doing like actual multimodal like putting an image of the cube state. >> Yep.
14:25
>> Um, but I was like very surprised after two moves.
14:26
I was kind of expecting like, you know, you can look up all the algorithms you need online >> to finish the last >> to finish the whole cube.
14:33
So, I was thinking like, oh yeah, let me just try the like like I'll pass in with with three moves to go and like obviously can get that. Yep.
14:41
>> And then it couldn't at all.
14:43
>> Um and then I tried so this morning I tried >> that was with no tool use.
14:48
>> So this morning I tried >> with um GB5 with like the agent. >> Yeah. So so so no tool use it.
14:52
It was still writing Python, right? Yeah, that's true.
14:56
But it wasn't searching up like algorithms.
14:59
>> Um, >> but this this morning I I tried it with agent and it went to like a bunch of different Yeah, agent mode >> solvers. >> Yeah, it did. >> And it did not.
15:06
It found them and it like said like, "Oh, yeah, I'm using it. This is the best move."
15:11
And then it like was totally wrong. >> Okay. Interesting.
15:13
So that that feels like the that that feels like a pretty good test and a pretty good eval for like the era of agents. Like Yeah.
15:22
>> What I was describing this to Tyler.
15:22
I was saying like you have a random Rubik's cube.
15:25
If I gave it to you and I was like you need to solve this and you didn't have all the algorithms me memorized like but you were like it's my job to finish this cube. What would you do?
15:35
You would Google how to solve Rubik's cube.
15:36
You might watch a YouTube video.
15:38
You might like go to something some cheat sheet that's like type in all the colors on the Rubik's cube and then it tells you exactly what to do step by step.
15:47
And there are tons and tons of these like solvers like like that.
15:49
You go out there, you Google how to solve a Rubik's cube.
15:53
You type in what you have on the colors and then it tells you move this one, rotate this one.
15:56
The problem is that all those websites are completely built differently.
16:00
Some of them are in WebGL, some of them are in, you know, like just old HTML, some of them are programs like some games.
16:07
>> The way the model learns to solve a Rubik's cube is by pretending to be a human and just Google searching.
16:12
>> That's how they will solve every problem because these tools exist.
16:14
So, it's like instead of like instead of like rlinging on door on Door Dash, just go figure out how to use Door Dash.
16:21
Go figure out like the answer to like booking the flight won't be like reconstituting an airline from scratch.
16:28
It'll just be like Google it, find like use Google flights, right?
16:33
Like use use whatever's out there.
16:33
Um, and so it was it was impressive that it was able to perform at a higher level than the other models on the spatial reasoning required to finish the last two moves of the cube, but it was underwhelming on the agent side that it wasn't able to find and use a cube solver >> uh because it clearly hasn't been trained on that.
16:53
>> Yeah, but it is interesting that um GT5 thinking does like way outperform it.
16:56
It was like thing for like six minutes >> just to get two moves. >> Wow.
17:02
which like is really long but it's like it is like I think it shows that there's like you know something it's not just 03 packaged up as like in a router.
17:10
>> So did 03 or >> uh yes it did not so so so there's something going on with the reasoning that is better like this is >> it's weird isn't 04 worse than 03.
17:24
>> Well it's we only we never got actual 04 we only had 04 mini. >> Okay. Okay.
17:27
So, so this could be like 04 under the hood, like a better reasoning model, even more RL on top of it that's like >> smarter >> and it's and it's accessing that, you know, in a certain way, but it's still like nowhere near oneshotting like just random hard problems. >> Yeah. Yeah. >> Interesting. For sure.
17:46
>> I had lunch uh with some friends on Saturday and one of the friends uh is a physics professor at a very prestigious >> college. Yeah.
17:56
And he was able to get GPT5 Pro to oneshot a problem in about 25 minutes. >> Yeah.
18:05
>> That he said his grad that would take his graduate students months to do on their own historically.
18:11
>> I can't even imagine the type of physics problem.
18:13
This takes a month to >> I know I had him I I don't want to give away too much of the alpha.
18:16
He he was like his mind was like completely blown. This was on Saturday.
18:20
you know, he had just gotten access to uh the model and he was completely blown away.
18:26
>> It's s it's such a weird era of this spiky intelligence because >> like pretty much any human should be able to solve the last two moves of a of a Rubik's cube in like an hour of like tinkering with it and just trying stuff, moving it back. Okay, try.
18:40
Wait, what do you think, Ty?
18:41
You think >> an hour seems like a long time? It's only two moves. >> It's two moves.
18:45
Like >> you can just look at it. Yeah.
18:47
>> Yeah, it doesn't seem that hard.
18:47
Do Do we have >> Just look at it.
18:49
We have a Rubik's cube right over there.
18:51
>> We have a normal Rubik's cube in the studio right somewhere.
18:52
Let's Let's get that out there and see that. Toss that to me.
18:56
>> It's already solved, though. >> Yeah. Yeah. Yeah. Mix it up. >> There we go. >> High stakes throw.
19:01
That would have been deeply embarrassing for the firm if if you dropped that.
19:06
>> So, yeah, it's like two two moves off and then you have to look at it and then you have to >> Well, do a couple moves and then let's let's feed it to Tyler and he can work on it. >> Oh, yeah. See if he can do it. Okay.
19:18
Now, see if GPT Pro can do it. >> Oh, well. Oh, yeah.
19:20
How many times did you test it?
19:23
>> Do use agent mode and and tell them like, figure this out. >> Figure this out.
19:27
>> Well, that's what I tried agent mode. Didn't do anything. >> Didn't do anything. Okay. >> Oh, well.
19:31
>> Well, >> well, let's tell you about figma. com.
19:33
Think bigger, build faster.
19:33
Figma helps design and development teams build great things together, great products together, get started for free.
19:38
So, um, despite all the GPT5 news, very exciting, and, uh, and and just a bunch of like progress that's happening, it feels maybe not as binary, not as, uh, not as, uh, exponential as some people were expecting.
19:53
Um, but lots of cool things.
19:55
Also, I wound up using Clawed Code for the first time and had a really interesting experience there.
19:59
Um, I I had it do a deep research report. No, >> no, not at all.
20:05
Uh, but I had it do a deep research report and instead of instead of just spitting out like bullet points and tables, I had it just spit it out as HTML.
20:12
And so it was able to uh it was able to generate like like really like I'll show you I'll show this to you.
20:20
I don't know if you can see this, but like can you see this? I got to take this off. Show show everyone.
20:25
This is not going to work.
20:27
But uh ba basically it's able to it's able to like show formulas, show different charts and graphs and just like use all the features of HTML uh which is really cool.
20:39
Um now there were tons of like hallucinations in here and the actual quality of the research report wasn't that great but we were talking to Doug at semi analysis and he was saying that that cloud code is has been really good for research reports.
20:51
So I think I'm going to try and work that into my workflow a little bit more.
20:54
Um, and I and I feel like the next the next like layup for anthropic is just wrapping claude code in a mobile app so that you get access to like a remote file like directory that can actually like write code, deploy websites, do all this stuff but from the app and then so then you can instantiate things.
21:16
But um the cool thing was that it felt like for the first time >> won't that kill like 10 billion dollar startups? >> Maybe. Maybe.
21:24
>> Maybe. Maybe. But for for the first time it felt like I was I was feeling this whole idea of like the generative UI the ondemand UI um because as like I was asking it to do this report on world models and it just generated like different sections of the like different
21:44
charts and graphs and put them all up there talking about how these work and it was able to just like create these little highlight uh these like little highlight sections for Odyssey uh the company founded by Oliver Cameron, how much have they raised? Physical
21:56
Physical intelligence by Locky Groom and Carol Houseman who've been on the show.
21:59
Uh they've had a $400 million round, Jeff Bezos, Thrive, Lux.
22:02
The problem is like I think I still need to fact check all this u because I I feel like the research wasn't as strong as uh as deep research or what you get from GPT5.
22:11
But uh but it was very cool to see uh it just use all the HTML functionalities and buckets to kind of create uh like a really readable website which of course was then immediately mobile optimized immediately you know you could read it this size that size and it just felt like um the first the first like the first moment of you know generative UI like on demand UI.
22:40
You need to experience these things firsthand before you can really have that true aha moment.
22:47
>> Much like you need to experience Vanta firsthand, automate compliance, manage risk, improve trust continuously.
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Vantis trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program.
22:59
Okay, so back to the actual big AI news of last week.
23:04
>> Yes, >> Genie3 from DeepMind.
23:05
Uh Alexander Holinsky uh dropped a very fascinating series of viral videos on X saying something something fun we discovered.
23:18
You can use Genie 3 to step into and explore your favorite paintings.
23:20
Here's a short visit into Edward Hopper's Nighthawks.
23:25
And this video is crazy because it and I said this is a studio Giblly moment.
23:32
soon as this goes general uh access like uh as soon as everyone has access to this, you're going to have the Studio Giblly moment because everyone is familiar with that particular painting.
23:41
Maybe not everyone, but most people and it's just like you can go walk around it and it feels like this real world.
23:46
And I think that there's going to be so many examples of >> Well, think of the example that I gave where you just take three photos from from like a specific moment, drop them and create a world, an entire world around it, and then you can go relive this like three-dimensional memory. Exactly. Exactly.
24:02
And so it's this like it's not the I think the AI generative AI generated stuff is by default like very mid, right?
24:12
Like AI slop is pretty like mid and like the AI generated photos.
24:17
If you just showed me a photo of a car or something that was AI generated, I'd be like, I would rather just see Max Versstappen driving the I'd rather see a more cinematic image of of a Red Bull F1 car that's just taken with a really like high quality camera and tells a story and and immediately builds my intrigue of like, oh, when was this? Was this during a race? Was he practicing?
24:39
Like, there's just so much more value when something's real.
24:42
uh even if even if the fidelity is there, it's not quite there, but it's just less less of like the story behind it.
24:48
But when you take something that people know or is personal like a family photo or a painting that they're a fan of and you and you allow them the ability to to customize and and and experience it, I think this will go way more viral.
25:03
And so, um this I I think Genie 3 and I think world models generally are going to be the next like hot sector for AI.
25:10
Um, I think the GPT open source, GPT OSS, GP toss is kind of cool, but you know, we've been there. We've seen that.
25:20
I don't think that there's going to be that much new there. Cloud 4.
25:23
1 was kind of this minor spec bump and even GPT5 was, you know, somewhat incremental, obviously very key for the business to get them, you know, seriously competing in the enterprise space and then also um, you know, improve consumer usage and just, you know, improve the experience of the chatbt app. meme potential of this.
25:40
If you can generate a world and then just share the link to that world and other people can drop into it, it's just going to go incredibly viral.
25:49
>> And even just exporting videos of this is good content creation.
25:51
Even if you're just sharing the videos that you generated, but actually being able to share the link to is going to be really, really big.
25:58
So, uh I'm super excited about this.
26:01
Um the big question from the show uh was, you know, what was going to be this uh with the the Gibli moment for world models and I think we know it now.
26:10
It's not going to be uh it's not going to be a Doom knockoff because you can just go play Doom.
26:15
You can play the original Doom.
26:17
You can also play the latest Doom, which is like 4K 60 frames a second graphics on Xbox and and PS5.
26:24
Like there are there are amazing ways to experience Doom if you're into Doom.
26:26
And also, people don't just play Doom to go walk around a cool designed like hell world.
26:36
They want to actually have a gun with an ammo counter and a health bar and an armor and a boss and a story of some sort.
26:43
Even if the story is like kind of blah, like they want to be able to progress and and it turns it into this this uh reward cycle of okay, I'm you know I'm having fun. >> Rewards. >> Exactly.
26:55
Um uh and so I think exploring iconic images, paintings, memes.
26:59
This is going to be a Giblly moment.
27:02
Uh, we got some recorded videos from the Deep Mind Researchers, which we're showing you right now.
27:07
And you can instantly see the virality.
27:08
Uh, I can't wait for this to go into generative uh, general availability because I think we're going to see some really crazy ideas come out of this that no one can really predict until you get it in the hands of of just like millions and millions of people.
27:21
>> And friend of the show, Logan Kilpatrick, went to interview Demis on Genie3 and Deep Think and a lot more.
27:29
Uh, and the interview just went up like an hour ago.
27:30
So, and and we're working on getting the Genie team on the show hopefully this week.
27:35
>> I'm very excited for that.
27:35
So, uh the other interesting thing is like people have kind of stopped generating Gibblies.
27:41
Um and images in chat GPT is just like something that people use and people might generate a Gibli for something if the meme calls for that.
27:51
But I find myself generating more like turn this person into a bodybuilder.
27:58
But also also you know you have some funny idea and you go to images in chat GBT and you say like I want to visualize this thing.
28:03
What if we put a car in in Central Park and it was this color like AI images are clearly very useful for that.
28:11
>> You have continued to be a power user of make this person a giga chat more so than than the Giblies. >> Yes. Yes. Yes.
28:19
The Giblies I haven't gibbleied in a long time but I've certainly uh I've certainly generated a lot.
28:25
I mean, I generate a lot of set design for like what the show should look like in the next version, a lot of ideas for um uh for marketing stunts and stuff like that.
28:34
Um and so it's become this useful tool and then obviously it's baked its way into like the the backgrounds of like true Hollywood production, all sorts of video production.
28:43
It's just like generative imagery is just a tool both for designers to pull references and use as a reference board or it's kind of like the first step in a plan to co-create something.
28:53
It's it's how you speedrun to a something that's mockup quality, not necessarily product or ready for release, but instead of I mean I used to make uh I I think it's a way that you can like even if you're working with designers or people that are great at Photoshop, you can just generate a V1 that's pretty solid and say like I want to make this but make it like really good. >> Yep.
29:16
>> And so Genie 3 is close to mockup quality.
29:20
quality. Like if you if you if you wanted to if you were pitching a video game or you were even pitching like a experiential world that you wanted to build or like you're building a store, a physical store for your business and you
29:35
generate an image of what you think that one look what that should look like and then you want to let the client say, "Hey, we're going to invest $5 million building out this uh this this caffeine goof cafe in Nashville like our friend did." Like you could actually walk
29:48
Like you could actually walk around it and really get an idea of what that is.
29:50
Or you could totally do some of like the Matterport things for, oh, okay, we took some photos of this house.
29:55
We want you to be able to let you walk around.
29:57
Like the tech is getting there.
29:58
Deep Mind is clearly scaling this.
29:58
Uh it's at 720p 24 frames a second right now.
30:03
Pretty close to optimal visual fidelity.
30:05
Um they're going to get to 4K 60 frames a second soon.
30:08
Um but there will be intractable problems that um come up that I don't think you can just blindly throw scaling at.
30:15
similar to what happened in LLMs.
30:18
And so we're going to be running down the same path we did with with language models. This is my take.
30:23
So, uh, you'll use reinforcement learning to round off all the sharp corners or instead like kind of create spikes of spiky intelligence that create pockets of value within these generated worlds.
30:34
So, you can imagine um if you're generating a video game, it's very important to have the main character look the same at the end of the game than at the beginning.
30:41
So you might do some sort of like RL pass to make sure that character consistency is really important for your hero character, but really it doesn't matter if I like come back after 10 hours of wandering around like the the the video game and like a tree looks slightly different. Like it's fine.
30:58
So, so there'll be areas where where these companies and these these foundation labs like go and apply a ton more RL to make sure that this particular feature works, but at the same time, it doesn't make sense to go and try and rebuild everything and bake everything into the model.
31:14
So you're going to wind up with situations where just like chachypt got a web browser and a Python shell.
31:19
You'll probably these world models will need to be wrapped or or interfaced with like a traditional database so that if you have an inventory and you want to track health points or you want to track ammo that's not >> you generate a world and then you make it fixed. >> Yeah. Yeah. Yeah. Yeah. Yeah.
31:36
fix fix like or or fix like the underlying territory of the world, the underlying maps so that they're the same, but then you're generating on top of that. Tyler, what's your take?
31:46
>> Uh yeah, I kind of disagree that like scaling won't fix this.
31:48
Um if if you look at the >> I I think if you look at uh Genie 2, >> it had this big problem with like um consistency, right?
31:56
You would turn left, then you would turn right again, and it would like look totally different.
32:00
Uh, and I'm pretty sure in the paper they basically say that the consistency was just like an emergent property of scale. >> Yep.
32:08
>> So >> consistency over what time period though?
32:11
>> I mean over the minute long. Yeah. I guess it >> 100 hours. 100 hours.
32:14
That's how long people play like a rolling, you know, >> 100 hours.
32:19
Like that's how long people will play these things.
32:21
And it's like they want to be able to go back to if you're in Elder Scrolls, you want to be able to go back to like the very first village you started in and see that the tree that you chopped down is still there. Look how far I've come. Exactly.
32:34
Like there are some there are some crazy properties in like in in Elder Scrolls where it's like in the first village you accidentally killed the you know the like the the uh the blacksmith and so later like 12 hours later you come back and you can't get the sword that you want like like that's that like why bother trying to bake all that into the model?
32:56
Why not just use a database?
32:58
>> But I'm saying you don't you don't need to like like think about baking it into the model.
33:02
just going to like it's just going to be an emerging property as you scale. >> Yes.
33:06
But I do think you will wind up hitting plateaus of scaling just like just like you know uh chatbt like LLMs got pretty good at math where they could do 2 plus two and then they could do much more complex math but at a certain point it was like we're not we're just going to give you a Python shell so that you can just actually do the real math.
33:26
>> Yeah, that's fair I guess.
33:26
Like because even even if even if scale would solve like the really really hard intractable huge huge math problems, it's like why burn the electricity to run that massive model to do some very very basic calculation that would take like five flops on just a CPU. >> Sure.
33:48
And so like you know you don't need to and and I do think that there will be other there will be other tools that it doesn't make sense to to bake into the model.
33:57
I mean just think about like multiplayer elements like h how would that be baked in the model like you'd want to sit on top of just like a normal social network.
34:05
You want to you want to sit on top like of some sort of normal like interface so that you can join the same game.
34:11
Like I don't want to recreate a new like epic game store every time.
34:18
>> It's possible to imagine like a new video game paradigm where the world is just constantly expanding and there's and there's no real rules and characters are constantly emerging.
34:27
>> Uh but at the same time like imagine playing soccer. Yeah.
34:29
And if you dribbled to the side of the pitch at one point like it just opened up and you could just keep dribbling.
34:37
Like eventually you'd get fairly you'd be like okay like I actually like having a rule set.
34:41
I like having this sort of consistency in the game. Yeah.
34:45
>> So that I have a framework in which I can play in.
34:46
So >> in in so many ways this this will create entirely new like formats effectively like you're taking the concept of an open world video game and you're just opening it up infinitely. >> Yeah.
34:59
>> But I think again people will want that consistency of play and even a shared experience, right? >> Yep.
35:05
And I mean, so yeah, Gold Rock in the chat is saying $3,000 an hour to play at 60 4K 60 fps.
35:10
Uh, I mean, that is a real consideration.
35:13
Uh the other the other question is just is just like is there a way that you can pull forward adoption by like not being a deep learning purist even if even if even if deep learning is the solution over the long term while you're waiting for to build the the you know the one trillion dollar data center to actually hit the crazy crazy scale.
35:39
If you can get user adoption by just using a normal database to track your inventory and your health bar, like you'll get more adoption and then you'll create this flywheel.
35:49
It's the same thing with Chat GPT.
35:50
Like you could you you you could have you we could have just been like >> open could have said like look there's no reason to give a to give an LLM access to a Python ripple at a certain amount of scale.
36:02
It'll be able to just reason about it and do do the Python in its head. Right.
36:06
Yeah, but you can pull you can say like actually you do want to like if you use the world model as like an RL environment then you can actually pull it forward that way by just like using it for other stuff you know >> uh maybe >> like if you're using it instead of it's not a game it's like a data set that you use for your and then like oh yeah we can also release it as a game for like normal users but really to train our robotics.
36:31
>> You really pelled on this robotics thing.
36:32
I I I think that there >> because data is like the big issue at least that's what >> Yeah. Yeah. Yeah.
36:37
Certainly for robotics, but I think that I think that there's I think there's a consumer product here. >> I agree.
36:42
But the way that you like fund it is through >> is using >> maybe the opposite.
36:47
Maybe the robots learn from all the humans acting like robots in a game and then that and then that generates a ton of a ton of data that then >> it's like one hand watches the other a little bit. >> Exactly. Exactly.
37:00
Um, but my but my real question is like DeepMind is obviously absolutely crushing on the research side.
37:07
They're like really really it feels like they're really far ahead right now.
37:09
This is clearly state-of-the-art.
37:10
Um, the question is like what does it take for Google to actually get this out in the world as a consumer product.
37:17
Everyone says GPUs will melt if they launch this right now. Maybe that's true.
37:21
Maybe they need to optimize it more.
37:23
But the the big question is like is like they had a large language model around the same time as GPT 3. 5. Yeah.
37:31
>> And they were really close in terms of their GPT4 first Gemini launch at the similar scale.
37:36
But ChhatPT launched earlier was more aggressive broke through and became kind of the default.
37:43
And I wonder if there's if there's if they should be more like riskon in terms of actually productizing this and getting in people's hands.
37:49
Like clearly people are going to use this for bad things.
37:52
They're going to put all sorts of references, reference images in there and be walking around them.
37:56
We can imagine all the bad things that they'll do.
37:59
>> Well, you can imagine them being more aggressive around a product like this because it doesn't threaten their golden goose.
38:05
Like in hindsight, it kind of makes sense that they weren't >> might threaten YouTube. But yeah. >> Yeah.
38:11
But you can also imagine where it's a catalyst for YouTube where a bunch of there's like entirely new vectors of >> you're streaming it, you're feeding it in, you're exporting it, that type of stuff.
38:20
And yeah, I I can see this being like a net new category of content or just a tool that every creator can use to to make better videos.
38:29
>> Whereas laughing at >> No, I just uh No, I was saying um it's basically the same thing with like they're to release V3.
38:34
It's like it's all the same safety constraints, right?
38:37
You can't put like some bad image into V3 and then have it produce video. >> Yeah. So they they most of it.
38:41
So yeah, they they even even V3 it feels like they're not being aggressive enough on the roll out of that.
38:47
That's probably also just like it's just way too expensive to serve >> for Google, the company that makes a billion dollars a day.
38:54
Like really, it can be that expensive?
38:56
Like I feel like I feel like the chat GBT >> I mean it says a lot that you were on the $500 a month VO3 plan and you're still getting rate limited >> constantly. Yeah.
39:09
to the point where I've like sort of chirped because I know that it's like such a rough experience to go in there and then like okay I need to plan it out.
39:18
Oh, I can only do three queries and I'll come back the next day.
39:22
It makes it really really hard to actually do any real work.
39:24
>> The question is how expensive is that >> for them to serve?
39:26
It must be must be a lot a month plan.
39:32
>> But but what like what what was the secret to chatt beating Gemini?
39:34
Like the Gemini app launched three months later.
39:40
So moving first mover advantage clearly matters.
39:42
Also chat GPT it seems like Sam Alton's never met a GPU he doesn't want to melt.
39:46
He will he will do anything he can just to scale scale scale even if it's I I imagine the margins for the early chacht launch were terrible and I imagine they were burning tons and tons of money in terms of inference costs and they were way way upside down there.
40:00
I mean, CHPT was basically free for like months like and it was like how like this clearly has has operational costs.
40:10
This has inference cost and they're just eating it.
40:12
Um and so yeah, maybe being more more aggressive on the financial side.
40:16
And then I and then I think >> well I still I still think it for Google if you la if they were to come out and launch a chat GBT like product that didn't have for example like a knowledge cut off that chat GBT did at that time. already.
40:31
So, there's a there's a post here from >> uh a an account that does weekly a weekly newsletter of quotes from earnings calls and they aggregated a bunch of quotes uh on AIdriven changes in Google search reducing referral traffic and impacting us user engagement.
40:48
So, these are just different CEOs in the last week.
40:51
>> Uh uh the the one here, the portion of our traffic that comes from Google search has declined from 52 to 28%.
40:59
Uh, another one from the group on CEO, Google is significantly changing the behavior of search result pages.
41:03
What we see is that we have declining traffic.
41:07
Um, another one on Google, when Google provides the AI response, there's a much lower click rate on it because it's typically a user getting the answer in that response and they don't need to go further.
41:17
>> Uh, uh, Nerd Wallet CEO, the Google search is still pretty challenged.
41:20
Um, and another one, we can't deny it.
41:23
It it is a risk on page views.
41:25
And so again, these all these AI features are reducing uh people's need to just navigate the web and drive uh some of which is ultimately I'm sure paid traffic. >> Yeah. And maybe Yeah.
41:38
Maybe the world model stuff, video game stuff, it's like not as as threatening to their core business.
41:45
I mean, it clearly clearly is not.
41:47
And so um maybe Google will move faster on this and own the consumer the consumer product.
41:53
But I just I feel like in the next 12 to 18 months like we are going to see some sort of explosion in like consumer AI driven around world models built something built on top of this whether it's a game or meme engine or some sort of product and uh and it's interesting because there are uh two or three serious serious companies building in this space.
42:15
We talked to Decart uh who's building in this space.
42:17
uh FE Lee has World Labs I believe that's that's uh building this space and um and and it and this it feels like there's this dance from like okay you've done enough research it's time to productize and you need to completely turn the ship of your company towards how can we get this out the door in a way that's sticky and viral but also doesn't completely put us out of business because of the inference costs.
42:45
Um, >> but we'll keep digging into it.
42:47
We'll keep having people on the show to talk about >> the team over at DeepMind is posting.
42:50
I just put a post in the chat.
42:55
>> While you're pulling that up, let me tell you about graphite.
42:56
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43:05
>> You can get started for free.
43:06
>> Uh, let's pull up this post from Deep Mind >> from Vidant Misra.
43:08
He is counter counterposting. >> Oh, I saw this. This is so good. >> Sam Alman.
43:14
Uh, if we can pull this up.
43:18
This is the the Korean TVBN is going to run into some challenges very quickly on pulling up post. Here we go. >> Oh, wait.
43:25
This is a different post than >> multiple posts if it's time. >> Yes. >> Okay.
43:30
So, in this one, Google is the re are the rebels.
43:32
He's is what he's saying. >> I don't know. Do you mind?
43:35
>> I don't even know at this point.
43:35
It's hard to tell who's the Death Star. >> Okay.
43:38
I finally landed on it on what Sam Alman the steelman of the Sam Alman Death Star post.
43:41
The Death Star was the was the overwhelming weight of numbered uh numbered language model releases.
43:49
And he was he was feeling the crushing weight of GPT5 needing to be an order of magnitude bigger and an order of magnitude better and a and a massive qualitative step up and a binary change in the overall experience.
44:06
And he blew he blew that up.
44:10
He blew up the expectations that that numbered releases would be correlated directly to uh specific model capabilities.
44:19
That's the that's the closest I could get on the steel man of the of the Death Star post. The vague post.
44:23
>> Alternatively Alternatively, it was provocative.
44:26
>> It got the people going.
44:27
>> It got the people going.
44:28
>> It did it did drive a lot of a lot of speculation, a lot of frustration.
44:32
>> Well, over the weekend, uh you posted there's a 100 million in computer hardware locked in the replies.
44:36
It's your job to get it out.
44:38
So, uh, if you were on X over the weekend, Donald Boat, uh, laserboat999 was on a tear.
44:43
If you had a viral post over the weekend, he was going to be in your replies, uh, saying, "I agree.
44:51
The only way we can drive culture, science, and industry forward is if you overnight me a motherboard compatible with an AMD, Ryzen, blah blah blah blah blah."
44:59
Uh, and I believe he's made some tremendous progress in terms of putting together this this uh, computer.
45:05
I was talking to him a lot over the weekend tracking the story. He said he was shy.
45:10
He didn't want to come on the show.
45:13
But uh uh I a lot of people are are questioning like is this some scam?
45:18
Martin Skrey was wondering if it's a scam.
45:20
Uh I think he's just having fun and he's a good poster and he is just he's kind of egging and kind of shamelessly asking for stuff but having fun and it's funny and it's basically like the the tipping version of the ex creator payout.
45:33
Like he's just getting extra stuff.
45:35
So, uh, he has received almost everything.
45:37
It's also hilarious the type of accounts that he responds to because it's everything from like Elon and Sam Alman to, uh, Dasha from Red Scare and like he he's all over the place.
45:49
He's not he's not purely just going after like the richest people in town.
45:53
>> Specific taste in Yes, he has a specific taste in poster.
45:56
And I mean, when he started this project, he already had 100,000 followers, was prolific poster.
46:01
Um, but he is apparently going to have some sort of MIT physicist uh put the PC together.
46:07
He says he doesn't know how to code uh and he's not using it to like build software.
46:12
He's more just interested in playing Battlefield 6, which had a beta this weekend that apparently did very well and apparently uh uh uh blew out the Call of Duty beta, I guess.
46:25
So, there's this big debate over uh did Microsoft overpay for Activision because they acquired Activision for something like $70 billion.
46:34
They got Call of Duty and you would expect that Call of Duty would continue to defeat Battlefield uh which is an EA property.
46:42
>> That's Blizzard boss Mike Yabara says Battlefield 6 to boot Call of Duty Black Ops 7. >> Yep. >> Rough. Rough.
46:50
So, uh but you know, it's uh it's fun. you know, he's 21.
46:54
He's having fun on the timeline, getting an incredible PC that will be fully Battlefield 6 ready.
47:00
I was in a similar boat when the first Battlefield game came out, Battlefield 1942.
47:04
This is probably like 2003 or something.
47:06
I had to beg my mom for a uh for a cutting edge Nvidia graphics card because I couldn't run it on my on my current PC.
47:16
I had to build I had to reply said, "Mom, you me Amalfi Coast."
47:21
You know, >> I was so uh I was so applepilled from a young age, I had to I I I refed hundreds of soccer games to buy a maxed out MacBook Pro. Okay.
47:33
>> Which is still like terrible any gaming rigs, but I would use that to play.
47:38
>> Yeah, I was always PC master race, but um >> and and the last the last PC I built, the the the the last bastion of the Windows ecosystem in my life is sitting right over there.
47:48
I built that not for gaming.
47:50
Actually, I never even noticed that.
47:52
>> I built that PC for rendering computer graphics using Oh my god, Tyler's picking it up.
47:59
>> He's gonna show off the thing.
47:59
Donald Boat, if you want an older uh PC with a uh What does it have?
48:04
It has It has two uh Nvidia 1080 Ti in there.
48:08
They're not It's not bad.
48:11
It has Ryzen Thread Ripper.
48:13
Uh I think it has 64 threads, actually.
48:16
It might even have, it's probably not as fast, but it's pretty pretty solid CPU in there. Uh, got some M. 2. It's a rig.
48:22
I built that from scratch.
48:24
And I was rendering >> with scraps in a cave.
48:27
>> With scraps in a cave.
48:27
I was I was rendering uh computer graphics on uh Cinema 4D.
48:32
Did a little Houdini on there. You let it cook.
48:34
It was It was a fun time.
48:37
And then I also played some virtual reality on there.
48:38
Had a good VR rig set up uh every once in a while. It was fun.
48:42
This is like uh again this is like Hunter Biden reminiscing on >> Yes. >> smoking crack. >> Yeah. Never get John's crack.
48:50
>> I mean Donald Boat was like totally getting me back into it.
48:52
I was like maybe I maybe I should build maybe I should build a new play Battlefield 6.
48:57
Like this seems like really good in the two minutes I have for free time this week.
49:01
Uh really quickly uh Poly Market has which company has the best AI model at the end of 2025 and Google is still on a tear.
49:11
the there was a major switch after GPT5 dropped.
49:13
Google sitting at 75% for August 30th and way up there for September 30th and and even by the end of the year uh Google is slated at 54%.
49:27
So uh Deep Mind is in is in control of the Rebel Alliance.
49:30
Maybe they are the the the Death Star because they >> all eyes on >> they cannot be Gemini three.
49:35
Although of course this is this is benchmark based.
49:40
Um so anyway, Donald Boat, he's he's having fun.
49:44
Um people are starting to say, "Oh, maybe it's AstroTurf.
49:46
There's thousands of likes on every post.
49:48
They think it may be fake." I think it's organic.
49:51
I think I think the kid is just uh is just out there hustling, having some fun. >> It's hilarious. It >> It is hilarious.
49:57
And it's bringing me a lot of joy.
49:58
And I think that like the the No one is getting over their skis here. >> It won't work again. >> No.
50:05
the next person that tries to do this, >> it's going to be like >> Donald Boat knockoff. >> Yep.
50:10
>> It's it's a one-time funny uh funny like meme that that that does very well.
50:14
Um and I don't think anyone here there's no promise of financial reward.
50:19
And most people are like Sam Alman can afford a graphics card.
50:25
Wilmanitis can afford an AMD Ryzen 7 8 core desktop processor or a or a motherboard, you know, and I don't think I think everyone was kind of chipping in what was reasonable to them where even if it's a scam, if it takes you for 200 bucks, it's not that big of a deal.
50:43
Uh it's it's a lot of fun.
50:45
>> It's not a scam in my view. It's entertainment.
50:48
>> I think it's entertainment and I think uh I did I was trying to push him like, hey, you're going to have some doubters.
50:54
you gotta you got to go live.
50:54
You got to stream Battlefield 6 when you get this thing set up.
50:58
You don't need a facecam.
51:00
>> Although, he was asking for uh for a Blue Yeti microphone.
51:02
And that was suspicious because he was like, "I'm really shy."
51:05
I'm like, "If you're shy, what do you want the microphone for? What's going on here?"
51:08
But, uh, overall, I think he's going to build the PC.
51:11
I hope he streams Battlefield. I hope he's good.
51:14
Uh, could be a lot of fun.
51:14
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52:15
Um but we didn't like the particular that particular business that particular market and >> great founders are just one pivot away. >> Exactly. Of greatness.
52:23
And so and so yeah you when you find someone you got to let them cook and let them let them figure it out. >> Yeah.
52:31
Well, you know who else is having fun cooking on the timeline.
52:36
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52:38
>> Former OpenAI researcher Leopold Ashen Brener.
52:41
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52:50
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52:57
Uh situational awareness is probably my favorite name for any type of fund in a long time. It just says so much.
53:06
It's like hey we're aware of the situation.
53:11
We're monitoring it and we're deploying.
53:13
We're trading against the situation. >> I like it.
53:15
It's definitely up there.
53:16
It's in the conversation, but the bar is extremely high.
53:19
You're going up against Cberus.
53:23
>> You're going up against Aries, the God of War.
53:26
Like the the the ceiling for quality of fund name is so high when you're in the public markets.
53:33
Wouldn't say this about VC funds because they all they all have very similar blue.
53:41
Blue Owl is a great name for a fund, a private credit fund.
53:43
Um, but, uh, I mean, Citadel, it's a it's a very strong name, you know, uh, Bridgewater, Blackstone, Black Rock.
53:54
>> I love it because it's unique.
53:54
There's it's very unique. It is unique.
53:58
>> It aligns with with this very viral thesis and it says it says it says exactly what you're getting into. >> Yep.
54:04
And it I mean and it was it was incredibly accurate.
54:07
Like when he when he posted the original situational awareness essay, it was something that was consensus in San Francisco and contrarian everywhere else.
54:19
And so what I loved about this was that there were so many people that were seeing what was going on in San Francisco in AI and they wound up starting seed funds.
54:29
And he was like, "No, the real alpha is in the public markets in these like long tail >> trillions of dollars of market cap that's going to fluctuate based on AI adoption." >> Exactly. Exactly.
54:41
So, so his portfolio is uh is very interesting.
54:44
It's all deeper in the supply chain.
54:46
Uh notably, Nvidia is missing.
54:48
Um maybe that was too consensus, but uh he's been long a bunch of things.
54:55
Now, there was a little bit of confusion because um in the 13F is only up 32% year to date, John.
55:00
It's barely in the conversation.
55:02
You're trying to put up 47% on a billion plus. >> You got to Yeah.
55:09
would have been a lagard in the fund. Wow. It's crazy.
55:10
Um but yeah, so the 13F came out, which is the the the fund filing showing the position of the hedge fund, showing what they're in.
55:20
Uh there was a little bit of confusion because Intel was ranked at the top, but that was because it was a call and when you buy a call, the the total value that you of the of the stock that you have the right to purchase is listed.
55:31
And so if you have the right to purchase a billion dollars in Intel stock, that will be listed as a billion dollars, but in fact, you will not have actually invested a billion dollars in that call.
55:41
And depending on where how far out of the money that is, uh that could be very very cheap. >> Yeah. Yeah.
55:46
And and people were questioning like, "Hey, did this fund already blow up basically because Intel is obviously had >> No, no.
55:55
They might have had to write down those calls or get out of the position.
55:57
There's a million things it could do.
55:58
Uh but uh there's there's a bunch of interesting things in here.
56:01
Um and so uh front page of the Wall Street Journal for Leopold.
56:05
You'll love to see it at age 23.
56:06
Uh he emerged last year as a precocious artificial intelligence influencer which I think sells him way way short.
56:17
Uh but uh he did publish a widely read manifesto and then he also did a Dark Cesh Patel episode which I think a lot of people saw clips from.
56:25
>> If you're an AI researcher now and you do a podcast and it goes a little viral, congrats, you're now influencer.
56:32
>> But the the influence of that of that episode is crazy. So he so he did darcash.
56:38
Most people do dorc for like an hour, two hours.
56:40
His episode is over 4 hours long. It's so so long. The PDF is 170 pages.
56:47
He wrote it's a multi-part essay series.
56:49
Uh it's a fantastic it's a fantastic episode.
56:52
It's a fantastic uh uh PDF.
56:55
It's a billion-dollar PDF, as they say.
56:57
The PDF that spawned a billion dollars in capital.
56:59
The 23-year-old with no professional investing experience quickly raised more money for a hedge fund than most pedigreed portfolio managers when they strike out on their own.
57:09
As valuations of Nvidia, OpenAI, and other artificial intelligence companies continue to soar, so do investments in hedge funds hoping to ride the AI wave.
57:16
Ashen Brener, San Francisco based firm, Situational Awareness, now manages more than 1. 5 billion.
57:22
People familiar with the matter said he has described the firm as a brain trust on AI and he certainly seems to be in the thick of it.
57:28
cozying up to Dores Patel.
57:30
He's got Patrick Collison.
57:33
He's got Nat Freriedman in.
57:33
He's got a he's got a real stack stacked roster that of people that know what's going on at the cutting edge of AI.
57:39
Um where the plateaus will be, where the investments will be made, uh the distribution of where different uh where different data center investments will be made, where the different bottlenecks will be.
57:50
That's really really key to the strategy.
57:51
Yeah, it shouldn't it shouldn't be a surprise that he was able to accumulate this much capital so quickly because, you know, again, if if you're if you're Daniel Gross or Nat Freiedman and you want to allocate to a manager that deeply understands >> AI, you're you're probably better off finding a, you know, >> Yeah.
58:12
>> incredibly intelligent 23-year-old that was at a lab. >> Yeah.
58:16
>> That can then deploy capital for you against all these different trends. It's basically like 1. 5 billion. What is that?
58:22
Like one researcher's lifetime earnings. >> So he just needs one. >> Just one. >> Just one.
58:28
>> Duncan is a core uh LP in the fund as well. >> Still got it, baby. Duncan. >> Of course he does. >> Absolute picker.
58:36
I love >> cover of Colossus. >> Cover of Colossus.
58:38
Um his strategy involves betting on global stocks that >> Let's see.
58:44
Let's give it up for global stocks.
58:48
>> That'd stand to benefit from the development of AI technologies such as semiconductor infrastructure and power companies along with investments in a few startups including Anthropic. Oh, he's in Anthropic. >> There we go.
58:57
>> Uh he told investors he plans to offset those with smaller short bets on in on industries that could get left behind.
59:04
Situal situational awareness gained 47% after fees in the first half of the year.
59:09
Some of the people said in the same period the S&P 500 gave in about 6% including dividends while an index of hedge funds compiled by research firm Pivotal Path rose about 7% and so he is crushing the competition.
59:22
Uh we'll get into some of the push back here but I am very excited for this.
59:26
Uh Ashen Brener a native of Germany briefly worked as a researcher at OpenAI before being pushed out.
59:32
Uh it was very interesting.
59:32
He uh he called the uh he called OpenAI's security measures egregiously insufficient and then he shared a document with external researchers about the uh about how OpenAI was doing security and that violated company policy.
59:51
So he was pushed out >> get pushed out.
59:53
>> I don't know how big of a deal that really is.
59:55
Like I I don't know like you should be able to talk to other people obviously you shouldn't like violate company policy.
1:00:00
uh kind of weird to like talk trash about your own company's security things.
1:00:05
And then also we're in this weird phase where like okay like you got to habius corpus when you talk about the security stuff because like if you if you were saying if if you were running around the building being like we're all going to get turned into paper clips.
1:00:17
We're all going to get turned into paper clips and then it's like three years later and like nothing's happened.
1:00:20
It's kind of like come on man like what were you doing?
1:00:22
like what were you doing? Um but if he was sounding the alarm about geopolitics which is something he did in situational awareness or you know AI psychosis like there are a lot of things that are good to research in safety and so um his his overall take was he I think he
1:00:37
benchmarked the entire industry and found that you know like less than 1% of AI headcount was going towards like safety and the alignment problem and so he identified that as a problem to to to kind of go after but now you know he's he's more focused on the public markets. So Ashen Brener, native of Germany,
1:00:51
So Ashen Brener, native of Germany, worked at OpenAI.
1:00:53
Uh he named situational awareness after his 165page essay he wrote about the promise and risks of artificial super intelligence.
1:01:02
He recruited Carl Schulman and another uh another AI intellectual who used to work at Peter Teal's macro hedge fund as director of research. Great.
1:01:09
The firm's backers include Patrick and John Collison, the billionaire brothers who founded payments company Stripe, as well as Daniel Gross and Nat Friedman, whom Mark Zuckerberg recently recruited to help run Meta Platforms AI efforts.
1:01:23
Graham Duncan, a well-known investor who organizes the SON conference, uh, is an adviser.
1:01:28
>> It's really a who's who. >> It is.
1:01:29
Uh, we're quote, "We are going to we're going to have way more situational awareness than any of the people who manage money in New York."
1:01:38
>> Wait for wait for this line.
1:01:38
He says, definitely going to do great on investing. >> I love it. Confidence, baby.
1:01:43
Uh, and another sign of the demand for Ashen Brish services, many investors agreed to lock up their money with him for years.
1:01:52
Other recent launches include an AI focused hedge fund from Value Aligned Research Adviserss, a Princeton, New Jersey based investment firm founded by former quants Ben Hoskin and David Field.
1:02:03
>> Were you ever really a former quant?
1:02:07
>> Once a quant, always a quant.
1:02:07
That fund has a billion and VR also manages about two billion in other AI focused investment strategies.
1:02:13
Uh VR's investors have included the philanthropic foundation of co-founder of Facebook Duskin Dustin Moskovitz according to regulatory findings.
1:02:24
Veteran hedge fund firms are entering the frey too.
1:02:26
Last year, Steve Cohen tapped one of his portfolio managers at 72 Asset Management, Eric Sanchez, to start an AI focused hedge fund that Cohen planned to stake with $150 million of his own money.
1:02:39
Assets of the fund called Turion after AI uh after AI theorist Allan Touring, who's on the Met list, baby.
1:02:49
We'll see if he can hold on uh in the next revision, which is coming soon.
1:02:54
Tiana >> is up about 11% this year.
1:02:55
uh and gained 7% last month.
1:02:59
So, a little bit of a slower start for Turion compared to a situational awareness that seems to be absolutely swinging for the fences.
1:03:06
Um it is no surprise the that the thatatic funds are springing up to capitalize on the AI frenzy.
1:03:13
In years past, hedge funds specialized in the transition to clean energy and investing in with an environmental, social, and corporate governance lens proliferated in response to client demand.
1:03:24
Identifying a winning theme isn't the same as trading it well.
1:03:28
Investors taste can be fickle.
1:03:28
Many prominent ESG hedge funds have either shrunk or gone out of business.
1:03:33
>> But I but was I don't know.
1:03:33
It's hard to say that smart money was saying that ESG was going to be such a winning theme.
1:03:43
>> Yeah, it was odd because it wasn't it wasn't some like underlying technological shift.
1:03:46
It was more just like >> it was values-based investing.
1:03:48
It was values based in Messa, but it was also like predicated on more demand because everyone there, it was like a game of musical chairs a little bit.
1:03:56
It was like, well, I think that Harvard is going to want an ESG strategy, so I'm going to build one.
1:04:01
And Harvard says, well, I'm going to want one because Kalpers is going to want one.
1:04:05
>> There was a time that I think consumers specifically were demanding >> sustainability from brands and it was really like a feature to a product.
1:04:13
But I think that has >> changed some degree. For sure.
1:04:17
Uh the market swoon that followed the January release of an advanced lowcost language model from Chinese company Deepseek showed the fragility of the valuations of AI winners though the market has roared back since.
1:04:29
I don't know >> going long jeans paradox. Come on. >> Come on. >> Come on.
1:04:33
>> AI focused investors argue the long-term trend of development and adoption are inevitable even if there are bumps along the way.
1:04:39
With so many publicly traded companies that operate in the AI adjacent economy today, stockpicking funds often pile into the same positions as one another and more generalist hedge funds.
1:04:49
Uh Vistra, a power producer that supplies the juice to AI data centers, was a top three US position of both situational awareness and VAR investors as of March 31st, according to each of their most recent securities filings.
1:05:04
Other hedge fund managers are debuting funds to make investments in privately held AI companies and startups.
1:05:08
Gavin Baker's a trades management.
1:05:12
>> Come on, that's also in the top 10 best names ever. >> A trades.
1:05:16
>> A trades is fantastic.
1:05:16
It's from Dune Paul at trades.
1:05:20
>> A trades management teamed up with Valor Equity Partners to launch a venture capital fund earlier this year that has raised millions from investors. Millions is >> Yeah.
1:05:29
>> Such a funny way to describe a fund because I'm sorry.
1:05:31
I would hope it's in the millions.
1:05:33
Otherwise, what are you doing?
1:05:37
>> T dozens of dollars >> from Oman's sovereign wealth fund.
1:05:39
Each firm separately invested in >> XAI.
1:05:46
>> At least one portfolio manager is planning an AI hedge fund as a comeback vehicle.
1:05:49
Shawn Ma wound down his Hong Kong based firm, Snow Lake Capital.
1:05:54
>> Snowake >> sounds cool.
1:05:54
I mean, anytime you add smash capital to the end of a word or a couple words, it always elevates everything involved. >> Yes.
1:06:04
>> Um, >> after it agreed to pay out 2.
1:06:04
8 million to settle uh securities and exchange commission charges last year that the firm participated in stock offerings of companies that it had also bet against.
1:06:15
Ma took over an investment firm called M37 management in Menllo Park earlier this year.
1:06:20
He's currently fundraising for a hedge fund focused on AI software and hardware. So lot of action.
1:06:27
>> Did you know that Meta is calling their AI lab TBD lab or something like this?
1:06:32
You see this >> since when? >> I don't know.
1:06:33
I thought it was MSL but uh the the journal saying Meta's TBD lab tackles new version of Llama.
1:06:39
I think this is some sort of like sublab focused on uh open source or Llama specifically.
1:06:47
At the forefront of the push to build computer a computer mind smarter than any humans is a team dubbed TBD lab which houses many of the researchers the company has lured from rival labs in some cases with pay packages of tens or hundreds of millions of dollars.
1:07:00
TBD Lab as in to be determined is spearheading work on the newest version of Llama the company's large language model according to people familiar with the matter. I don't know. Uh just interesting.
1:07:10
I I that feels like some weird leak that like the journal is like maybe misinterpreting. Anyway, back to Leopold.
1:07:16
Um, interesting interesting strategy.
1:07:20
I I think a lot of people are kind of uh so young macro has an interesting take here.
1:07:24
Uh, Leopold Brener's fund has outperformed basically every mainstream hedge fund year to date and he's running a billion dollars of capital.
1:07:30
The Gulf of Bill the Gulf billionaires and pension funds are watching this.
1:07:34
Capital management will soon become an an activity exclusively done by chronically online zoomers.
1:07:38
And there's certainly a lot of value in having >> Let's give it up for all the in online consumers. >> Yeah.
1:07:48
>> Let's give it up for profound.
1:07:48
Get your brand mentioned on chat.
1:07:50
Reach millions of consumers who are using AI to discover new products and brands. You can get a demo. >> Um, >> so funny.
1:08:00
I'm looking at the comments on uh on on wsj. com. Mhm.
1:08:06
>> Giving a 23-year-old one and a half billion to invest is pretty solid proof of a market top.
1:08:12
>> How old was uh Ken Griffin when he started Citadel again? >> Wasn't he like 18?
1:08:16
>> Oh yeah, he was at Harvard. He was an undergrad.
1:08:17
He hadn't even graduated yet. That's right. Interesting.
1:08:20
>> Just say you never studied the great.
1:08:23
>> Just say you've never studied the great. Yeah.
1:08:25
I mean like I I I I don't know like the of course there is a risk that there's that there's some bubble and the riskman.
1:08:33
>> Of course we're in a bubble.
1:08:35
That doesn't mean you shouldn't try to make money on it. >> Exactly.
1:08:37
But but there but there is a risk that you get caught uh over your skis at the wrong moment.
1:08:41
There's a pullback and the fund uh draws down really crazy.
1:08:45
But again, Citadel drew down like 70% in the housing crisis.
1:08:51
>> All the greats have suffered a massive draw down. >> It happens. >> Look at Bezos.
1:08:55
>> I feel like Leopold, this is what he's meant to do.
1:08:58
And uh and I'm I'm I'm rooting for him. I'm excited for it.
1:09:00
I think it's I think it's very very cool.
1:09:03
Uh anyway, uh this will be this will be will this be good news for Leopold? He's not in Nvidia.
1:09:10
Uh you know, in some ways you could say he is net short Nvidia because he is long everything but Nvidia at this point. Um is this good news? Is he cheering? Is he sad?
1:09:20
The news is that uh breaking from the Financial Times, Nvidia has agreed to share 15% of revenues from H20 chip sales in China with Uncle Sam.
1:09:31
According to export control experts, no US company has ever agreed to pay a portion of their revenues to ex to obtain export licenses.
1:09:39
Um, we were talking about this ear this morning at the gym.
1:09:43
>> Sammy, it's first >> and I was like I was like certainly like this has to happen like all the time.
1:09:46
I I I chat it and it's like actually it's unconstitutional.
1:09:52
You can't do this at all.
1:09:52
And so I'm sure uh some uh some some folks worried about Trump's overreach and abuse of the of the federal system will be up in arms over this.
1:10:04
>> So we're going to have Peter Harold on the show uh in 20 minutes >> and we're going to talk to Aaron G. January 2021 to 2022.
1:10:10
Harold served at the US White House as a senior director for international economics jointly appointed to the National Security Council and the National Economic Council.
1:10:20
He co-led uh President Biden's EO14017 supply chain resilience agenda, worked on the global digital 5G and telecommunication strategy, spearheaded negotiations with the EU on data data privacy, and served as a White House representative uh on a number of related matters.
1:10:40
So excited to get his takes.
1:10:40
He shared a bunch on LinkedIn uh yesterday evening or this morning.
1:10:47
So, we'll kind of wait to get into that.
1:10:50
>> The wording in this journal article is so wild because it's not saying like the IRS or something.
1:10:55
It's saying the Trump administration will receive 15% of the sales as part of a deal to approve exports of Nvidia's H20 chip.
1:11:03
So, it's like where exactly is the money going?
1:11:09
Like I guess it goes into the Treasury, the Commerce Department, but it's just funny to phrase it as like Trump gets to control where it goes, but hopefully it goes down towards paying down the debt.
1:11:18
Like I I I guess that's the >> bone GPT says 15%. That's all off the top.
1:11:24
You don't got to worry about nothing else.
1:11:26
No problems, no supply chain disruptions.
1:11:28
So So >> anyways, uh exports of the H20 and MI308 were halted in April.
1:11:35
So, this actually uh applies to uh AMD as well, which also has a a similar like nerfed GPU for China.
1:11:43
Um, >> and Trump had a quote >> back in April.
1:11:45
They Yeah, they they they uh they halted the trade of these H20s.
1:11:52
Uh Jensen Wong has gone on a charm offensive since then, says the Wall Street Journal, talking to officials in both countries about the need to do business with each other.
1:12:00
We follow rules the US government sets for our participation in worldwide markets.
1:12:05
Nvidia said in a statement on Sunday, "While we haven't shipped H20 to China for months, we hope export control rules will let America compete in China and worldwide."
1:12:14
This is an interesting one.
1:12:16
I mean, there there are there are there are good arguments on both sides.
1:12:18
You know, if you're super super intelligent pled, if you're AGI pled, you probably don't want that in the hands of a rival country.
1:12:26
But if this is more like Microsoft Excel, why not go sell some seats over there?
1:12:30
Why not go sell some licenses?
1:12:32
I mean, we sell airplanes over there. We sell 747s.
1:12:34
Um, >> we don't sell F-35s. >> Yeah.
1:12:39
But is this an F-35 or is it >> That's the big question.
1:12:42
>> Or is it souped up XL?
1:12:42
You know, and that's the debate.
1:12:45
And I think a lot of people are shifting over into the camp of like this is knowledge retrieval.
1:12:50
This is like pretty generic hardware.
1:12:52
This is not this is not as as a crit as critical of >> Trump saw Trump saw the GPT5 launch and said, >> "Okay, we'll give him some chips."
1:13:00
We >> we I mean, why were we saying that he didn't care about the deficit?
1:13:04
Because he was super AGI pilled.
1:13:05
Why is he now focused on the deficit and not worried about competition with China?
1:13:10
Because he's less AGI pilled now.
1:13:12
So, he says, "You know what?
1:13:15
Like, I don't think God in a box is coming down the pipe anytime soon."
1:13:19
And so, let him have them. Whatever, it's fine.
1:13:23
>> Trump on Monday left open the possibility that Nevada Nvidia could export its Blackwell chips for a higher price.
1:13:33
>> The Trump administration had closed the door on the export of that technology to China even after reversing course on the H20.
1:13:38
Uh on Monday, Trump said that he'd consider allowing it.
1:13:41
The Blackwell is super duper advanced.
1:13:44
I wouldn't make a deal with that, although it's possible.
1:13:48
said >> make a deal some somewhat enhanced in a negative way.
1:13:51
Blackwell, in other words, take 30 to 50% off of it, but that's the latest and greatest in the world. Nobody has it.
1:13:57
They won't have it for 5 years. >> Okay. Wild card.
1:14:00
Nvidia's got to track this.
1:14:02
>> And he said, no again. >> Continue.
1:14:05
>> Uh Trump said Jensen will return to the White House in the future to discuss selling an unenhanced version of Blackwell.
1:14:11
>> Yeah, >> I think he's coming to see me again about that, but that will be an unenhanced version of the big one. >> The big one.
1:14:16
You know, we will sometimes sell fighter jets to a country and we'll give them 20% less than than we have. >> Okay.
1:14:22
See, see, see, we do sell fighter jets to countries. Let's go.
1:14:24
Uh Rav says it should go into the sovereign wealth fund, which he can eventually help pay down the debt. Yeah. Well, that makes sense.
1:14:33
>> A lot of people have been memoing the government.
1:14:36
>> Um the So, Nvidia is going to need to track this.
1:14:39
It's very similar to sales tax.
1:14:41
They need to get on numeral sales tax on autopilot.
1:14:43
spend less than 5 minutes per month on sales tax compliance.
1:14:46
Maybe this is a line expansion for numeral track your export your export bill.
1:14:52
Uh in other chip news, Tom Cotton is diving back into the uh the Lip Bhutan news that Intel the CEO uh of course uh Lip Bhutan had to visit the White House and is uh has been singled out by Trump as uh unacceptable and Trump called for his resignation.
1:15:13
And we kind of debated that on the Friday show, but Tom Cotton, uh, the I believe Republican senator, he said, "The new CEO of Intel reportedly has deep ties to the Chinese Communists.
1:15:21
US companies who receive government grants should be responsible to stewards of taxpayer dollars and adhere to strict security regulations.
1:15:30
The Board of Intel owes Congress an explanation."
1:15:32
And so, uh, Lip Bhutan is set to visit the White House today.
1:15:37
He probably is there currently or was there earlier today uh after President Trump called for his removal last week over ties to Chinese businesses.
1:15:46
This is uh Liboutan is not he was born in Singapore and he's an American citizen but he had a venture fund that did a bunch of deals in China and so that's kind of I think the main focus and when you look at the web of like all the deals that he's done and all the company it's like a lot of companies and so it looks like this crazy spiderweb.
1:16:02
It looks very like red stringy.
1:16:04
Um, so Ton is expected to have a wide range of Yeah, we got to get the whiteboard out. Break it down.
1:16:09
Get Lip Bhutan on the show.
1:16:13
>> Could you whiteboard out Lip Bhutan's uh portfolio?
1:16:17
>> You're going to have to You're going to have to look it up.
1:16:18
There there is a there is a crazy uh chart over here somewhere.
1:16:22
Um but uh Ton hopes to win uh the win Trump's approval by showing his commitment to the country and pledging the importance of keeping Intel's manufacturing capabilities as a national security issue.
1:16:35
Trump has aggressively pushed US companies to make changes ranging ranging from eating the cost of tariffs to doing business with more conservatives and other political allies.
1:16:44
So the you know Trump said the CEO of Intel is highly conflicted and must resign immediately.
1:16:48
There's no other solution to this problem.
1:16:49
The odd thing is that it's like, okay, so so like Intel with like their really lagging semiconductor technology is now critical to America, but Nvidia H20s aren't and we can let those go to China.
1:17:04
So there does seem to be some like inongruence here, right?
1:17:05
Have you sorted that out at all?
1:17:10
>> You know, the conversations we had last week, it feels like Intel is still incredibly strategic and important. Yeah.
1:17:16
And um we need to take it very very seriously that we need to make sure that they can um like the United States it's the the foundry business in particular if you didn't hear our interview with fabricated knowledge.
1:17:32
>> Uh Doug over at semi analysis on Friday. Go listen to it.
1:17:35
Um >> but yeah I think I think universally people agree that intel is important. It's in a bad situation.
1:17:43
But so the question then becomes, is Lip Bhutan the right guy to steward it?
1:17:48
And ultimately, it's the Intel board that should be determining that, right? Yeah.
1:17:53
Doug did say he >> had issues with the board.
1:17:57
Wasn't exactly excited about their leadership over the last decade and a half. Yeah.
1:18:03
Um but again this this kind of thing typically feels like >> this feels like if you were trying to keep semiconductors out of the hands of China you would be anti-H20 sales and anti-liphutan in in at Intel potentially
1:18:18
and if you had a more lzair attitude you would say yeah Lip Bhutan's fine and H20 sales are fine but it's weird to be like H20 sales are fine but Lip Bhutan is not fine that's where there's like some inongruity but I think this will all be resolved. It's probably just one of
1:18:33
It's probably just one of these Trump like gambits where art of the deal is going to ask for intel to, you know, donate to some sort of thing or, you know, pay something.
1:18:43
>> I think they should donate to themselves.
1:18:45
>> Yeah, they should donate to the shareholders with a buyback maybe. I don't know. >> I don't know. Just figure it out.
1:18:52
>> Donate the uh donate the fab business to TSMC or something like that.
1:18:58
>> No, I think I mean I think that's the whole point.
1:18:59
And it's like we can TSMC can be producing chips in the United States, but we still shouldn't let a company like Intel just fail at a point where it should be on the path to thriving. >> Yeah.
1:19:13
>> Um Mike Morates was in the journal over the weekend.
1:19:16
>> He wasn't in the journal.
1:19:16
He was in the uh in the Financial Times opinion section.
1:19:22
Intel must not bow to Trump's attack on its CEO.
1:19:24
The latest character that US President Donald Trump has attempted to assassinate is Li Bhutan, recently appointed chief executive of Intel, firing from his perch on True Social.
1:19:36
The president wrote, "The CEO of Intel is highly conflicted and must resign immediately."
1:19:40
For context here, uh Mike Morates is uh uh Sequoia, not founder, but but longtime GP.
1:19:46
Uh the uh the Financial Times describes him as a Silicon Valley investor.
1:19:53
doesn't quite do the job, but um >> it's technically true.
1:19:57
>> But Sequoia, I believe, invested in Intel and has a long relationship with the company.
1:20:02
And Mike Morates is, I believe, anti-Trump, but then there were a few other folks at Sequoia who were proTrump in this last cycle.
1:20:09
So, there's a little bit of a divide there, but I think Mike Morates is out of Sequoia at this point or has maybe moved on to a different piece of the organization.
1:20:18
It's all very complicated.
1:20:18
I can't keep it perfectly um uh in order, but says uh while presidents have sometimes expressed their outrage about the behavior of the corporate sector, Trump's assault has no modern precedent.
1:20:31
The source of the president's eye and that of Tom Cotton, Republican chair of the Senate Intelligence Committee is Tom is Tan's business dealings with China as both venture capitalist and in his prior role as chief executive of California-based Cadence Design Systems, a maker of electronic design systems.
1:20:49
The president and senator pointed to a $140 million payment agreed by Cadence last month as part of a plea deal to settle claims of illegal exports to China between 2015 and 2021.
1:20:58
They have also lambasted Tan's venture investments in a number of Chinese semiconductor companies.
1:21:06
Uh in addition, they are seeking to question whether with tan with TAN at the helm, Intel is jeopardizing the $8 billion grant it was given under the Chips and Science Act that was pa passed under uh passed by the Biden administration.
1:21:19
The attack on TAN comes at a time when the president's policy towards China and the Chinese tech sector seems to change by the hour.
1:21:28
Of course, it's much easier to smear a man with accusations than examine his record and character.
1:21:32
Tan, 65, is a longtime American citizen uh and much admired figure in Silicon Valley who is known for operating with a soft-spoken authoritative dignity.
1:21:40
I've known him as an acquaintance for almost 40 years.
1:21:44
>> The whiteboard is going up. >> Oh, there we go.
1:21:47
>> And >> oh, he's connected to Smick, too.
1:21:50
>> So, he was uh his his firm was called Walden International. >> That's right.
1:21:54
>> Um and they were Yeah, they were early in SMIC seed investor. >> No way.
1:21:58
>> Uh I'm looking for more.
1:21:58
Smick for reference is uh the are they the Nvidia of China or are they the TS I think they're the TSMC of China and then SMEI is the ASML of China. >> Yeah.
1:22:10
And then there's als semiconductor manufacturing international corporation.
1:22:14
>> So they actually do the fab.
1:22:14
They are a they are they are a fab >> and it is partially stateowned. >> Yes. >> Like many companies. >> Interesting. Okay.
1:22:21
And then uh I don't know if it's AMC or AMEC.
1:22:23
That's like a a tool etching tool company for semiconductors.
1:22:29
>> Y so more so more of a of an ASML type competitor. >> Yeah. Yeah.
1:22:34
>> Actually make the lithography machines that then are used in the fab to make the chips that are designed by Huawei or any other client. Interesting.
1:22:42
I didn't realize that Mike Morates and Lip Bhutan go back 40 years. Wow.
1:22:47
They met when he when Ton was 25 years old. What a legend.
1:22:54
>> Did you know Intel's first external investor was the meme account Arthur Arthur Rock? >> It Oh, yes. It was Arthur Rock. That's right. >> Of course.
1:23:04
Not the uh current account Arthur Rock, but uh the original Arthur Rock, the legendary Arthur Rock. >> Yeah.
1:23:12
>> Who his firm was Arthur just Arth Arthur Rock and Co. >> Yes.
1:23:16
And >> you know what the rock stands for, right? >> Rockefeller.
1:23:22
>> It was It's Rockefeller money. >> Wow. >> Yeah. >> I did not know that. >> Yeah.
1:23:25
The uh Rockefeller money got passed down. >> This goes way deeper.
1:23:30
>> This goes deeper than we thought. >> Get the tin foil hat.
1:23:33
>> The Rockefellers are involved.
1:23:33
Uh born in Malaysia and educated in Singapore.
1:23:39
Uh Tan studied MIT where he was awarded a master's degree in nuclear engineering.
1:23:42
After moving to San Francisco, he joined the Walden Group, one of California's early venture firms.
1:23:48
Instead of plowing the Silicon Valley furrow, he elected to head to Taiwan.
1:23:53
Later, he made investments in China, the majority in in companies with deep technology roots.
1:23:56
His deep understanding of both Taiwan and China in is an asset many US chief executives would like to possess.
1:24:03
When he later became CEO of Cadence, which had fallen on hard times, the wise acres assumed he would fail given his lack of operating experience.
1:24:12
Instead, he transformed the business.
1:24:12
In his 12 years at the helm of the the company's revenue tripled to almost 3 billion and the stock price appreciated by over 3,200%.
1:24:23
Today, Cadence is worth close to hundred billion dollars. Wow.
1:24:25
That is a phenomenal performance.
1:24:27
Uh earlier >> and again he uh Lip Bhutan made a seed investment in SMIC in 2001. >> Wow.
1:24:36
>> Exited it fully in 2021. >> Yeah.
1:24:38
And and I mean you think about like the the the vibe around doing business in China in 2001 was like absolutely absolutely these are these are our boys we make shoes and Nikes there and we make iPhones there like it was like completely reasonable there there was no great power competition discussion whatsoever.
1:24:57
Um all that has cropped up in the last decade.
1:25:00
Uh and so uh earlier this year, Lip Bhutan became the chief executive of Intel, a job which in Mike Morris's book amounts to public service.
1:25:11
It is no secret that over the past 20 years, Intel has seated its mantle as the world's most important semiconductor company to companies like Nvidia, Broadcom, TSMC, and Samsung.
1:25:18
Six different leaders have failed to return Intel to the glory days that it enjoyed under the late Andy Grove.
1:25:24
It failed to capitalize on the rise of the mobile phone industry and was outgunned by Nvidia as the supplier of silicon engines for the AI revolution.
1:25:31
Its manufacturing prowess, a rarity among US chip companies, has been cons co uh consigned to the shade by TSMC.
1:25:38
H Mike Morris, what a great writer.
1:25:41
Uh today, Intel is also ran lacking much in the way of financial firepower.
1:25:46
The last thing TAN needs is to be distracted by a vindictive political sideshow.
1:25:50
Now, the Intel board must decide whether to march to the beat of so many other corporate leaders and capitulate to the president's artless bullying or to set an example for other companies and display some backbone.
1:26:03
Early signs of defiance are encouraging.
1:26:05
Let's hope that Intel's overseers abide by the refrain that old Tammy that that old Tammy Tammy Wynette song and continue to stand by their man.
1:26:15
What a hilarious reference.
1:26:17
Do you know that song stand by my man by Tammy Wynette? >> I do not.
1:26:20
famously quoted by Hillary Clinton during the Milan uh Monica Lewinsky scandal where she said that she was not going to leave Bill Clinton over the scandal, but she was also not doing what Tammy Wynette said.
1:26:33
She was not merely standing by her man, but she wound up she did stand by her man in some ways.
1:26:40
Um, and they did not get a divorce.
1:26:43
But, uh, fascinating quote, fascinating article.
1:26:45
I I I I think like he can probably ri this up.
1:26:48
I think Tan can go to the White House, do some deal, art of the deal both ways, figure out some way one hand washes the other and be fine >> for Tan.
1:26:58
Yeah, >> obviously get a cool leather jacket.
1:27:01
>> Cool leather jacket >> playbook.
1:27:03
>> Dust off those golf clubs >> for sure.
1:27:06
>> Bring a Big Mac for sure.
1:27:06
Pick up some McDonald's on the way. >> Smart.
1:27:12
>> And uh throw in a Vasheron historic.
1:27:15
Maybe bring a bar of gold or or a lot even even potentially numerous bars of gold.
1:27:21
>> Definitely definitely bring the biggest chip that Intel has ever produced.
1:27:24
Maybe just a whole wafer because he's probably seen Blackwell.
1:27:28
You've seen Bob Blackwell is pretty big, right?
1:27:30
You got to bring something even bigger and just be like, "We're making the biggest and best chips in America. We're Americanmade. I'm America all the way.
1:27:39
We're going to build a fab at Mara Lago.
1:27:42
We're going to build in Key West."
1:27:42
And uh I think it gets it done.
1:27:44
Anyway, should we move on to linear?
1:27:47
Linear is a purpose-built tool for planning and building products, meet the system, for modern software development, streamline issues, projects, and product road maps.
1:27:57
Go to >> when we get on the show, we will be giving him a live demo of linear.
1:28:00
Linear will be the key to getting Intel back on track. Let's make it happen. >> Okay.
1:28:06
Tyler Cowan, he's loving GPT5 and he has a post.
1:28:09
He says uh somewhat unrelated but somewhat related of course on the topic of AI.
1:28:13
He says the quote AI is causing a slowdown for new hires hypothesis has pretty much been abandoned.
1:28:21
The trend seems to predate GPT4 and the trend seems to apply to tech jobs that have no serious AI competition. Interesting.
1:28:31
I was digging into the hiring numbers across the world because if if if AI is causing a slowdown in new grad hires, I would have to assume that it's also causing a slowdown in India because there's so much business process BO, business process outsourcing and outsource IT work, outsourced software development work that happens in India.
1:28:59
And I dug up the uh unemployment data on in India, split it out by rural and urban, and it doesn't seem like there's a huge spike.
1:29:09
Maybe that's coming, but we're certainly not there yet.
1:29:12
>> I think Tyler's post was in response.
1:29:14
There was a New York Times article yesterday said, "Goodbye $165,000 tech job.
1:29:20
Student coders seek work at Chipotle.
1:29:24
As companies like Amazon and Microsoft lay off workers and embrace AI coding tools, computer science graduates say they're struggling to land tech jobs.
1:29:31
And there's a story of uh Manasi Mish Mish Mishra >> remember seeing tech executives on social media urging students to study computer programming.
1:29:39
The rhetoric was if you just learn to code, work hard, and get a computer science degree, you can get six figures for your starting salary. Is now 21.
1:29:45
Recalls hearing as she grew up in San Raone, California.
1:29:50
Those golden industry promises helped spur Miss Mistra to code her first website in elementary school, take advanced computing in high school and major in computer science in college.
1:29:59
But after a year of hunting for tech jobs and internships, Miss Misra graduated from Purdue University in May without an offer.
1:30:06
I just graduated with a computer science degree and the only company that has called me for an interview is Chipotle.
1:30:11
I guess my first question is was this for coding coding creating software for Chipotle because having a burrito tracker >> on par with the Domino's pizza tracker would be pretty cool.
1:30:25
>> It would be very good.
1:30:27
>> And again, I I think one thing that could happen is hiring managers and executives telling themselves, "We should be able to do more with AI.
1:30:35
We don't need to hire for these people."
1:30:38
Even if AI is not at the point where it truly replaces a person, it's just sort of forcing people into this mindset of like, do we actually need to hire this person? Yep.
1:30:46
And again, we'd called out before Microsoft has laid off more people this year than they have in the past few years combined.
1:30:51
And so again, I think uh but at the same time, >> you don't know how big the hiring glut was from Zerp and COVID like that could still be working its way through uh because companies really really staffed up and they staffed up remotely and they staffed up young people.
1:31:09
>> Yeah, we've heard a bunch of stories this year of companies that had >> people had eight different jobs, >> remote engineers that they were kind of like you can move back to the office or you can move on.
1:31:18
At the same time, Regav uh meta in the chat says, "It's really bad in India.
1:31:22
I have it on very good authority." Um I believe you.
1:31:24
It's it's just not showing up in the data yet.
1:31:27
I'm interested to to track it more deeply and actually understand what's going on at some of the big um at the big IT outsourcing firms in India.
1:31:37
Are they actually scaling down?
1:31:39
Do we have hard data on it?
1:31:40
And and then yeah, what is driving it?
1:31:42
Is it actually is it actually AI or is it something else that's going on?
1:31:46
Um but at the same time Salesforce is saying AI is now doing everything at Salesforce and yet >> headcount is >> we heard the same thing from CLA and and it was unclear if that was just like a right sizing of the business for where they were in terms of scale.
1:32:01
Um but I don't know it's uh it's interesting AI is everywhere.
1:32:07
It's at the same time there's like a lot a lot of these tools are just like extra levers and the dynamic is that like yes it helps you write more code but there was always way more code to write than your business was able to write and so you're really just unlocking new capability and and just moving faster. >> Totally.
1:32:26
>> Um well if you need an AI native CRM get on Adio customer relationship magic.
1:32:31
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1:32:36
>> You can start for free.
1:32:36
Well, on that note, I have Peter in the reream waiting room. Let's >> Here we go.
1:32:44
>> Welcome to the stream, Peter. How are you doing? >> You look fantastic. >> Great.
1:32:47
I I was told I should wear something, you know, not just a black suit for you guys. So, there we go. >> You look fantastic. You look fantastic. How are you doing? >> I'm great.
1:32:55
I mean, uh, you know, the East Coast, it's been a little cooler than it was the couple of weeks ago.
1:33:01
It's the '9s are coming back, but, uh, not yet. So, no complaints.
1:33:03
And you know I am for better actually really for worse not an Nvidia shareholder so I don't have to directly deal with their 15% paid to the government.
1:33:14
>> Did did the stock pop today?
1:33:14
What actually happened with Nvidia?
1:33:17
>> It's it's it's a normal day. It's up like 1%. >> Okay. >> No nothing crazy. >> Not a huge move.
1:33:22
>> Um before we dive into all the news uh would love would love to to just you know give us the highlights from the bio.
1:33:30
you've done you've done quite a lot, but I think it'd be helpful context before we get into a discussion. >> Yeah.
1:33:36
No, look, it's it's great for uh to be with you guys. Thanks for having me on.
1:33:40
I currently uh am a non-resident fellow at the Carnegie Endowment for International Peace, which is a think tank in DC.
1:33:47
I also am an attorney and have a trade uh uh law practice sort of focused on trade and sanctions and export controls uh kinds of issues.
1:33:55
I was in the Biden administration at the White House where I dealt with the global economics file including a bunch of the export control issues and been in private practice prior to that.
1:34:06
Was the State Department for a while and when I was much younger I was a reporter covering campaigns and elections like uh many many years ago. >> That's super cool. That's awesome. >> Kind of been around. >> Well, breakdown.
1:34:18
So, so, so before we get into the Nvidia AMD stuff and the news from yesterday, take us through kind of your experience of this year so far because there's been a lot of different stories. >> Go back further.
1:34:29
Chris Miller writes chip war. Everyone wakes up. Is that what happened?
1:34:34
Like when when did DC wake up to uh to maybe we need to think more critically about the flow of semiconductors and AI technology back and forth between the US and China?
1:34:46
>> You know, that's a that's a great question.
1:34:48
And I give Chris uh a lot of credit.
1:34:50
I also give a couple of guys who were at um at Georgetown University which has a center for science and emerging technology.
1:34:59
And a couple of those guys like in 2018 2019 started really tracking what kinds of high-end chips were the Chinese buying and like what was going on.
1:35:09
You know they'd hired some Chinese language researchers and were really looking at what the Chinese were doing.
1:35:15
And so you had these kind of scholarly researchers looking at this and saying hey there might be a problem here.
1:35:20
Then you had Chris popularize it with chip war.
1:35:23
Uh and you also had back in 21 you know that was also the time not on the leading edge stuff but on the the mature node stuff semiconductors when we had that semiconductor supply chain crunch.
1:35:34
So semiconductors were very much in the the news and kind of policy makers were focused on it.
1:35:38
This was during that cars.
1:35:43
>> We couldn't make cars, right?
1:35:43
During co we couldn't make cars >> and we couldn't make internet connected washing machines.
1:35:48
>> Yeah, it was really bad for the IoT microwaves.
1:35:51
That was particularly rough.
1:35:53
>> Well, there were like three months where you know I was working at the White House and you know Ford would call me up or GM and be like we can't get semiconductors.
1:36:01
And then it would be my job to like phone, you know, governments in Malaysia and Thailand and being like, could you, you know, get some of these shipped to your American customers, um, please, you know, before the Germans and the French.
1:36:13
So, uh, you know, >> what was what was actually driving that?
1:36:16
Was that like was that like like you needed because I mean fabs are clean rooms.
1:36:21
Like I imagine that you could still go into the semiconductor facility during COVID because you're not going to spread it because you're not spreading anything.
1:36:27
You're not spreading dirt. It's a clean room.
1:36:28
But uh there's but there were there was like this immense amount of pull forward during COVID stimulus checks, people buying more cars than they thought they were expected, but then also there were shipping delays and all sorts of backups at the port.
1:36:42
Like how do you think about what was actually the root cause of the initial semiconductor crunch in what was this 20201 or 2020 and 2021? >> 2021 early 2022.
1:36:53
Yeah, I it was actually I think the the combination you just highlighted.
1:36:58
So you had demand going through the roof, right?
1:37:01
Because there was this huge pull forward for everything from uh you know laptops to uh you know everyone's home so they're buying home appliances.
1:37:09
There's huge pull forward in demand.
1:37:11
Um and you didn't actually see a fall in production of the mature node chips in 21 but because of just like bad luck.
1:37:20
There were uh problems in Texas.
1:37:23
There were problems in Japan.
1:37:25
Like confluence of bad luck took a little bit of capacity offline and the capacity coming offline which which would have been manageable kind of in an ordinary market condition combined with this massive pull forward just meant a mad scramble.
1:37:41
And then you get into the, you know, psychology of shortages where uh everybody starts hoarding, right?
1:37:48
because people are sort of like, well, if I'm not going to be able to get them, I better hoard.
1:37:52
So, it was sort of like the semiconductor version of the toilet paper shortage, you know, we'd had a few months prior where it's like, you know, everyone's hoarding everything they get their hands on.
1:38:02
>> Got to start Gwagons, Ford Raptors.
1:38:08
Anything with a semiconductor in it, give it to me. I need it.
1:38:11
>> People were certainly doing that for PS5s, too.
1:38:12
I mean, I remember even video games, like all all different sectors people were were pulling and they were pl pay paying like what $50,000 over sticker for like a new Hummer EV and stuff like it was getting crazy out there. >> Wild times.
1:38:25
So, yeah, please continue. >> Yeah.
1:38:28
So, that was where we were on the uh on the on the shortage.
1:38:30
Um but looking back I mean so if I that that got us the shortage Chris Miller's book some scholarly research and just kind of heating up competition with China >> you know in sort of late 21 into 22 got the then Biden administration but also folks on Congress.
1:38:49
It wasn't just sort of a Democrat Biden thing.
1:38:51
folks in Congress uh focused on the strategic competition part of this and what is China uh where are they going with AI?
1:39:03
What are the choke points that we might have to slow their development of AI?
1:39:08
And that really gave uh rise in October 2022 to the first big US semiconductor export controls where the commerce department essentially cut off uh most of the highestend semiconductor sales uh to China as well as various uh manufacturing equipment and inputs to try to limit uh China's ability to develop indigenous uh production uh capabilities.
1:39:35
And then that that initial export control regime from October 22 got expanded a couple of times.
1:39:40
Um most recently in April of this year when the Trump administration paused uh sales of the H20 chips of the Nvidia H20 chips uh to China.
1:39:53
>> What was driving the initial chip bands?
1:39:57
Was it more we I we have identified that large language models these huge training runs are important and once you marshall the big data center the the the 100 gigawatt data center you're good and you have a cutting edge model or is it more like look if we send a certain amount of equipment it will be reverse engineered
1:40:20
and copied and then they will be able to catch up on the actual supply chain side and and we'll not just competition from purchasing from Nvidia, TSMC, and ASML, but we'll actually see Huawei, Smick, and SME act as a alternative supply chain that will be an entirely internal economy that will keep them on the frontier potentially forever. >> Yeah. So, it was in the first instance >> Yeah.
1:40:44
So, it was in the first instance an effort to limit compute to China.
1:40:47
an effort to limit compute to China. So there was really a pretty systematic okay if we're in this era of strategic competition with China and if we think AI is going to be an absolutely uh transformative technology you know something with just a whole range of
1:41:04
national security economic impacts you know day-to-day life impacts how do we slow down China's development and you start thinking about well you know they got a bunch of good engineering talent over there it's not like you can prevent them from having talented engineers years, right? That's
1:41:19
That's just sort of life.
1:41:20
Um, you know, the the the model side of this, controlling the models is very very hard.
1:41:28
Uh, because, you know, it's software, it's code, a lot of some of the models are open source, just very hard to control.
1:41:34
But what you could do mechanically is control their access, China's access to compute because their chips just are, you know, 3 to 5 years behind ours.
1:41:46
And so if you choke off the chips, you slow them down by limiting their compute uh their access to compute for training.
1:41:53
So it's just kind of how do you trip them? This is the choke point.
1:41:57
Let's squeeze on the choke point.
1:42:00
>> Um and then you know they iterate, right?
1:42:03
They start developing lower compute models.
1:42:05
Like you see this kind of back and forth, but that's what happens with export controls generally like you know your adversary is going to adapt.
1:42:12
You're going to have to adapt and and that's kind of what we've seen play out.
1:42:15
And how much were you tracking the GPU black market?
1:42:18
You know, in in once you had export controls, there's certain countries start popping up saying, "Well, we'd actually like$5 billion of uh whatever GPUs you got and uh don't worry about what we're going to use them for. We'll figure it out." But not your problem. >> Yeah.
1:42:38
So, that's a known problem you're going to get into, right?
1:42:41
And you've seen that in other instances of export controls and sanctions.
1:42:45
And so, you know, commerce department does have a unit that, you know, is supposed to be looking at the trade flows.
1:42:52
Where is that uh where is that happening?
1:42:54
Where are you seeing that?
1:42:57
Um, you know, I I it is a bit of a game of whack-a-ole.
1:43:04
It's clear there has been a certain amount of diversion uh of prohibited chips going to China.
1:43:09
I also think you know just if you look at kind of what Nvidia talks about the sales potential clearly the export controls have reduced China's ability to get to the chip so that they haven't taken it to zero. Mhm.
1:43:24
>> How do you think about the evolution of the US government's thinking on how critical or like the the role AI plays in nearpeer competition because there's kind of two frames of mind that I see in Silicon Valley.
1:43:39
One is AI is super intelligent god. It's nuclear weapons.
1:43:44
It's it's one button you push and the AI goes off and just wins the battle for you.
1:43:49
So, it's it's critical to have it uh and it's critical to keep it out of the hands of your opponent.
1:43:53
Uh the other is that AI is more like Microsoft Excel and it's certainly useful in the military context.
1:44:00
You want to know how many >> like electricity. >> Yeah. Yeah.
1:44:04
You you want to know how many, you know, shells you have in in inventory.
1:44:08
You want to know how many how many soldiers are in this particular part of the battlefield.
1:44:12
and you want to be able to track things, but it it and and it might be advantageous to keep a technology like Microsoft Excel out of your opponent's hands, but it by itself will not win a battle decisively.
1:44:23
And it feels like long ago, pre-Chat GPT, pre kind of AI boom, people were definitely seeing artificial intelligence as, well, yeah, we use it to serve ads and it and it helps with spellch checkck and it's in Tik Tok and and it recommends, you know, what video you watch next and and then it became, okay, it's super intelligent god and it's nuclear weapons.
1:44:47
But now we're kind of maybe in an era where we're where we're moving back to it's more of an incremental technology.
1:44:52
But I'm wondering how that thinking evolved in DC.
1:44:57
>> Uh so so I think the evolution in that debate is an important part of understanding why the Biden administration took a pretty tough line on export controls because I would say many of the relevant policy makers in the Biden administration were actually quite bullish on AI.
1:45:16
you know, did buy into the thesis that, you know, I'm not, you know, whether it's 2027 or 2029 or 2030.
1:45:26
You know, we could debate the years, >> but they bought into the thesis that in a fairly near period of time, you were going to see AGI kind of reach that, >> you know, escape velocity where it's iterating on itself. Sorry.
1:45:41
Where you're going to see AI reaching that escape velocity where it's iterating on itself reaching AGI, you know, sometime in not too many years.
1:45:51
>> And if you believe that, if you think in a couple of years we're going to see that, you know, escape velocity to AGI, then you really want to slow the Chinese down as much as possible, right?
1:46:00
because you think this is going to be this enormously transformational technology and you know 2 years or even 18 months or you know maybe even 12 months of lead is worth an enormous amount from a policy level.
1:46:15
So it was actually because of a very bullish view on the future of AI. >> Yeah.
1:46:21
>> That you saw the Biden administration really take kind of a pretty tough stance on slowing down China.
1:46:24
stance on slowing down China. And so and so reading into that does that mean that you that the admin might not not if they're willing to say yeah we'll we'll we'll export H20 we don't believe in a fast takeoff scenario this is electricity it's valuable but >> it's going to be vended in everywhere
1:46:46
>> because if you still believe in a fast takeoff scenario you would say it's not worth the incremental sure Nvidia you know shareholders are going to suffer a little bit if you and export to China, but it's not worth the the however many billions of incremental revenue that the government's going to generate on a 15% take rate. Yeah. So, I think the Trump Yeah.
1:47:06
So, I think the Trump administration is probably doing a couple of things here.
1:47:11
I mean, first, there are lots of different views in the Trump administration.
1:47:15
That's no news to everybody.
1:47:17
You see some folks who uh I think obviously would prefer the Trump administration take a harder line on export controls.
1:47:23
You also see, you know, some folks uh who, you know, basically have a view of, well, we shouldn't sell China our most advanced chip.
1:47:30
The H20s are now a couple of years old.
1:47:32
This is not really uh most advanced.
1:47:33
You might as well um get the Nvidia revenue and a US government take here.
1:47:39
So, I think you have diverse views in the Trump administration.
1:47:42
administration. I think it's less guided by a you know sort of slower view of the uptake and more my view the Trump administration is looking at this is like this is not state-of-the-art and then also Trump is a dealmaker like it it's hard to see any other uh politician
1:48:02
Republican or Democrat coming up with this but you know Trump himself he's always talked about getting you know a cut of the deal like so it's it's in a way this is a you know sweet generous unique to Donald Trump concept that I'm going to let you do this, but uh by the way, we get 15%. >> Well, and he said this morning that he
1:48:18
>> Well, and he said this morning that he he would potentially consider exporting black wells, but at a higher rate, which uh >> now that I mean, this is um you know, it's interesting like the H20s I do think are kind of debatable.
1:48:31
I mean, I am in favor of controlling the H20s, but I see the arguments on both side. It is a dated chip now.
1:48:38
you know, I'm not D, but you know, it's not a cutting edge chip.
1:48:42
Um, it is very hard for me to see how charging a percentage, you know, revshare uh addresses any national security concern, right?
1:48:55
I mean, like if you have some national security concern, the revshare doesn't address it.
1:48:59
Maybe, you know, forcing a downgrade of the chip or trying to limit who it gets sold to, which is very hard.
1:49:06
Like revshare definitely doesn't address whatever your national security concern is.
1:49:11
>> Is there is there any possible steel man for that?
1:49:14
You take the 15% revenue share and you pour that into some sort of national security AI defense fund that that protects you from the super intelligence. I don't know.
1:49:24
It's very very hard to I buy the I buy the logic of like I'm going to make I I'm fine to export the H20 because Jensen's convinced me that it's okay but I still want my cut is kind of is >> that's how I read it.
1:49:39
Like that's kind of how I read it.
1:49:42
Like Jensen convinced him, you know, it's an old enough chip.
1:49:46
We have enough of a lead like you might as well export it.
1:49:48
And then here's a guy who made his living in New York real estate.
1:49:51
Like you know you want your commission, right?
1:49:52
I mean, that's just I think that's kind of what's going on.
1:49:56
>> When you when you saw this, I maybe you had a a a feeling that this was coming down the pipeline, but did you had posted on LinkedIn, I think it was earlier today, trying to look for some type of precedent for USG revshare on in and didn't sound like you found one.
1:50:15
>> Yeah, I can't find any precedent for anything like this.
1:50:18
You know there have been some instances uh for example if you are some of our defense contractors you know the Boeings of the world if they want to export fighter aircraft >> they have to pay like a couple thousand fee for the government to review the license like it just clearly just sort of the fee to cover the staff time of like reviewing the license.
1:50:42
>> Uh but it is literally a couple thousand dollars.
1:50:44
It's not you know revshare of a multi-billion dollar market. uh here.
1:50:50
There's no precedent for anything like this.
1:50:54
>> And and what are you hoping?
1:50:54
Uh >> I'm thinking about where it goes.
1:50:56
Like are we going to be selling F-35s?
1:51:00
>> I mean, this is like it opens up a whole kind of you know, what are we going to sell next on a revshare model?
1:51:07
>> That is kind of crazy.
1:51:10
Let's get some submarines over there. Hey, we got capacity.
1:51:12
Let's make some Let's make a bunch of submarines. >> Yeah.
1:51:16
And and then the concern is you highlighted you said the revshare creates perverse budgetary incentives for US agencies to issue licenses that undermine national security because they want the cash.
1:51:25
It also sets a precedent that the US might try to generally tax exports, something the USG has long avoided for legal reasons and because we have historically wanted to promote exports. >> Yeah.
1:51:36
So, so I do think this this does create a perverse incentive.
1:51:39
I mean, you know, in in theory, the reason you control these things is because you think there's a real national security risk.
1:51:46
And to your point, I think in some sense, uh, Trump Jensen convinced Trump like there's not really a national security risk here.
1:51:55
But think about this going forward, you've created this really perverse incentive where uh, you know, company wants to export something to China, maybe Russia, like who knows who's next on this.
1:52:07
uh that poses a national security risk.
1:52:10
Uh but hey, if you don't, you know, if you if you authorize the export, like, you know, you get 15% uh and you can use that to pay for whatever domestic programs you want.
1:52:20
I just think it creates a really weird incentive for a person at the commerce departments whose job is to consider the national security uh impacts of this.
1:52:28
Is there is there a like an optimistic scenario where like American industry or western industry is strengthened by this move and I'm I'm trying to walk through it.
1:52:44
So, uh, we we've talked to a couple people who work in the solar industry and they've said that China is incredibly dominant in solar and they flood the market with very cheap solar panels and that's effectively kept American solar panel producers out of the game.
1:53:01
And so, America doesn't really have a strong uh solar panel production industry.
1:53:07
And so maybe the bull case here for American dominance in AI is something like you get so many NVIDIA chips over there that Huawei, Smick, and SME can't really stay in the game.
1:53:19
They can't really be competitive.
1:53:22
They fall behind even more.
1:53:24
And then uh and then if if AI plays out in in such a way that you don't just need one massive data center, you need to be constantly upgrading your data center.
1:53:36
you need to constantly be buying more and more Nvidia GPUs that if you don't have that flow, if that flow can be turned off, then you are always vulnerable.
1:53:46
So, so I actually think the policy question of whether to sell the H20 to China is a hard one for exactly uh the reason you lay out which is that there is a you know there is an argument and I think Jensen makes it in good faith as well as for his own commercial interests
1:54:03
of we want China dependent on our chips and if they're not dependent on our chips they're just going to be you know building uh you know SMIC and and and Huawei chips and that's going to ultimately more inclined to more inclined to take Taiwan. >> Yeah. Right. Um here's the question I >> Yeah. Right.
1:54:19
Um here's the question I got back though.
1:54:22
Like charging an extra 15% on the American chips doesn't actually advance that dependence argument, right?
1:54:30
It just um creates a cost differential that makes the American chips more expensive relative to the Chinese chips.
1:54:37
presumably if you really wanted to keep them dependent on American chips, you'd, you know, want to sell them as cheaply as the market would bear.
1:54:45
So like the 15% even in the like bull scenario, and I agree.
1:54:49
I think it's an important debate of the the the kind of bull scenario you laid out, but 15% still doesn't make any sense. >> Yeah. Yeah.
1:54:57
And you look at other other categories like smartphones or electric vehicles, there's there's no precedent for China saying, "We'll we'll buy your versions of these products and we'll even manufacture them for you, but don't worry, we're not going to develop our own."
1:55:11
You know, you look at this like of course they they they clearly care about having local industrial capacity and even the end products and brands >> and those are for categories that aren't around that don't have nearly as much national security.
1:55:29
>> And if you talk to like the you know the the CEO of GoPro when they were trying to compete with DJI and drones, he's not he's not going to tell you a story about DJI getting attacks on exports.
1:55:38
He's going to talk about, well, DJI was subsidized and had and had and had governmentbacked loans and had extra money poured in from the government that allowed them to flood the American market with drones and now we don't have a really strong drone industry here.
1:55:53
And so, yeah, the like we're kind of like there's two different arguments.
1:55:57
There is some inongruity there.
1:55:58
Like they they both can't be true. >> Yeah.
1:56:01
So, the steel the steel man is is >> we were going to allow this. >> Yeah.
1:56:06
So why not get a Uncle Sam, a few Billy out of the deal?
1:56:09
But the concern is that it would set a precedent that that could be, you know, destructive.
1:56:16
>> So now we really got to talk Jensen's book and say we should be subsidizing exports of AC monies to China.
1:56:20
We should be America should be paying an extra 15% for every GVU sends to China to really screw them over on this domestic supply chain side.
1:56:31
This is this is seven dimens dimensional chess in geopolitical chip negotiations. We we've solved it. We've solved it. >> Exactly. There you go.
1:56:41
>> Anyway, >> what what else is top of mind for you right now? >> Yeah. What Yeah.
1:56:43
What's on the horizon for the rest of the year?
1:56:44
How do you see things breaking? >> Yeah.
1:56:47
I mean, so you got th this is a big development.
1:56:49
We'll have to see like is this a precedent?
1:56:50
Does this become a precedent for you know HBM and other parts of the semiconductor ecosystem?
1:56:57
Like we'll have to we'll have to see.
1:56:57
Uh the other one that obviously those of us here are watching uh not on the export side but on the import side Trump has said and uh commerce secretary Lutnik has said their tariff regime for imports of semiconductors is going to hit fairly soon.
1:57:14
Obviously we saw Tim Cook get a um a deal or announcement out of the White House last week where if you know companies are promising they're investing in America they won't pay the tariffs.
1:57:26
Uh, and we'll have to see how that all plays out actually in practice.
1:57:31
But like how these potential semiconductor tariffs again on the import side plus whatever this exemption for companies that are investing here, how that actually works in practice is going to impact US semiconductor companies, companies that use a bunch of semiconductors.
1:57:46
It's going to be a big noticeable economic uh issue for the industry uh over the next couple of months and certainly into next year.
1:57:54
Well, we'll have to have you back on if some big news breaks.
1:57:57
>> We really appreciate you taking the time. >> Great. Super.
1:58:01
>> Thanks for having me on.
1:58:02
>> Thanks for hopping on. We'll talk to you soon. >> All right. Cheers. >> Bye. >> Take care.
1:58:05
>> Let me tell you that Finn.
1:58:05
AI, the number one AI agent for customer service.
1:58:09
They're number one in performance benchmarks, number one in competitive bakeoffs, number one ranking on G2. Go check it out.
1:58:15
And Andrea has a scoop of cereal. Man cereal.
1:58:20
>> This was really the big story. >> Cereal.
1:58:22
Everyone's Everyone's ordering this. It's got creatine. It's got protein. It's keto. It's got zero sugar. >> Uh it has 2. 5 gram of creatine.
1:58:29
So, you need two servings to get kind of a normal dose, right?
1:58:34
If you're loading, >> do you see the the flavor? >> What's the flavor? Maple bacon. Oh, that's very bacon.
1:58:42
That's very like what 2010 era Brooklyn hipster man vibes mustache that with like lumberjack coated maple bacon on everything. This is a funny brand.
1:58:54
It's it feels like it's it's it's pulling from a few years.
1:59:00
>> Do you think it's the final cereal?
1:59:02
Would you would you go for this, Jordy? >> Uh I love sugar. >> Yes. Sugar enthusiast.
1:59:06
So for that reason you're out. >> So I'm out.
1:59:10
>> For that reason you're out.
1:59:10
Uh, I >> I make a version with with sugar and and I'll and I'll give it a spin.
1:59:14
I'm also very curious what protein is actually in here.
1:59:17
Not all protein is created equally.
1:59:21
>> Uh, is it chunks of flavor?
1:59:23
>> Is it is it grass-fed whey?
1:59:23
Maybe >> could be interested. Is it collagen? Could be interested.
1:59:27
Is it some, you know, random bean that uh I don't really want to be consuming, you know, or or pea protein? Yeah, less interested.
1:59:34
I mean honestly more important than protein, creatine, sugar, all the diet's important but exercise is super important and sleep is super important.
1:59:45
That's why you got to get an Nate sleep.
1:59:47
>> Get a pot fivey risk-free trial, free returns, free shipping. Let me check.
1:59:54
>> We're both on a generational sleep. I got a 97 last night.
1:59:56
Last >> Monday I was performing on a 45. Got a 94 on Saturday. 90. I got a 76 96 quality. 100% consistency.
2:00:06
Six hours and 10 minutes left.
2:00:09
I think that's fake news.
2:00:11
I think I got more than six hours and 10 minutes, but I think I was dis I think uh I think my son stole a little bit of it.
2:00:17
Although I did wake up at 520, so that I think that is correct. I don't know.
2:00:21
>> Well, if a kid jumps in the bed, it it >> it kind of throws it off a little bit.
2:00:24
We got to get pronatalist.
2:00:24
when he when my son first jumped in the bed, we I was configuring the app and I was like, "Yeah, there's like left side for me and wife side uh right left side for the wife and he was like and the center for me like sorry bro they don't make this like >> get the we'll get the team to to make an update there."
2:00:43
Anyway, we are we got a we got a highlight we got a post here from NG >> marked safe from oneshotting.
2:00:51
>> So on the left me and Grock are going to get married. Oh no, >> mid-curve.
2:00:54
It's great for adjusting recipes.
2:00:56
And then the high IQ, I have uncovered secrets of the universe. God speaks through me.
2:01:02
So there were some quotes uh that were popping up last week over the weekend.
2:01:06
Uh some very bright technologist uh discovering the boundaries of what is known in in many different domains. >> Yeah.
2:01:16
My current my current take on the AI psychosis thing is that >> it is it is a tool that like amplifies who you are.
2:01:24
And so if you're just like a naturally if you're just like a curious person who likes being productive like it's going to make you more curious and more productive and just kind of answer questions for you.
2:01:33
If you're like you know deeply falling in love with random stuff and developing crazy parasocial relationships like that's probably a vector of risk for you.
2:01:42
And the same thing with, you know, if you have delusions of grandeur, like get ready because like it's going to amplify that.
2:01:49
And and I and I think that's >> you don't just have delusions of grandeur.
2:01:53
You really are on another level.
2:01:57
>> You really are brilliant. >> I'm grand. >> You really are grand. >> I have grandeur.
2:02:01
Well, our next guest has grandeur.
2:02:03
Aaron Gin, welcome to the stream. How you doing? >> Lovely hat. Let's go. >> There we go.
2:02:11
Let's hit the gong for a hat appearance. >> Boom.
2:02:17
>> Didn't even warm it up today. >> Take that. >> Appropriate as well.
2:02:21
Culturally >> from sales guys from from from BDRs all over the world. >> Yeah.
2:02:28
>> What's new in your world? Hs good, bad. Are you happy? Are you pumped? >> I'm happy. >> They're happy. >> They uh Yeah.
2:02:35
They they they choppyl hawks that have a luxury belief system around that Chinese AGI is going to destroy us like a crouching tiger hidden bag, you know, dragon version of open AI is going to attack America. Like we're done.
2:02:48
And >> and that this 15% >> uh deal which like broke Sunday.
2:02:51
I don't know how it broke. >> Yeah. >> Was just amazing.
2:02:56
It was just like I mean one like props to props to President Trump who is the ultimate deal man. >> Art of the deal.
2:03:03
It felt like both 4D chess and art of the deal into one. >> Yeah.
2:03:09
And and so you know like the the the sort of average profit margin of the H20 is around probably like high 50s%.
2:03:17
>> So you know there are still and they also have the write-off they're probably going to roll in as well and and there's some struggles with DSMC like you can't just you know I think it's the one of the issues related to the intel foundaries like you can't just like restart production within a month. It takes several months.
2:03:31
So like probably you're just going to try to find someone's non-destroyed and probably send them to China the the age 20s.
2:03:38
>> Uh but what most Americans understand is that it's unconstitutional to export the tax exports. >> Yeah.
2:03:44
>> So it's like in the constitution.
2:03:45
>> I looked it up and I was like how is this going to happen because this >> So you're saying a revenue share is like a workaround. >> Yeah. So it's voluntary.
2:03:52
Like that's the only way it could happen. >> It's tipping.
2:03:56
No tax on tips cuz the because the taxes are tips now >> because like even from a process perspective like Nvidia doesn't apply for export licenses like the OEM does and when you apply for those OEMs there's no license fee cuz that violates the constitution.
2:04:09
So you just get it and you can ship it but the bomb is listed.
2:04:13
The bomb is >> wait really quickly who's the OEM in this scenario? >> Oh super micro Dell. Yeah similar.
2:04:21
So, so, so, so someone in China will go and say, "I want a rack of servers with H20s already on them, some other CPU, some other memory, some other hard drives on there.
2:04:31
Bring those bring those blades to me and they will call Dell or Super Micro for that." >> Yeah.
2:04:37
>> And so, that's who applies for BIS.
2:04:37
And so, they're the ones that that final PO number is all that crap together. It's not Nvidia. It's not Nvidia.
2:04:44
You don't know Nvidia's pricing.
2:04:45
You don't, you know, Dell does cuz I buy it from Nvidia.
2:04:48
So, that's why it has to be something volunteer.
2:04:50
You can go to the website now like Jordy if you're interested in donating to the Goliath you know the lethon you can go to treasury.
2:04:57
gov and you can find the little we accept PayPal, right? VMO. >> Yeah.
2:05:02
So, so it's it's quite brilliant.
2:05:04
I mean, I think many of the faux neo China hawks are devastated.
2:05:07
Uh I mean my my oped last week. Yeah.
2:05:10
It's just they're just sapuku.
2:05:13
They're just like, you know, they're there.
2:05:15
They're going to be on the Jefferson memorial just like, you know, going at it.
2:05:18
man because it's a decision but but today >> yeah it's a it's a decision by the administration to be like you know we don't really care like like we want to do deals we want the American worker to have you know get money from China we want to we want to do what China did to us over the last 20 years >> we want to take money >> dig into the faux China hawks the fauxhawks as we uh explain like the uh stated preferences, revealed preferences.
2:05:53
Are they really doompilled?
2:05:55
Do they really believe in fast takeoff?
2:05:58
Do they really believe uh that AI is a nuclear weapon or is there something else going on?
2:06:06
Some other economic consideration that they're working through.
2:06:07
I think and I'm working on the oped right now for a very liberal newspaper, but they I think it's a a jox machina >> uh sort of fallacy they built in their brain where they think AI is going to be God >> and America has to build the first god or China China has to build the first god.
2:06:26
And so it's a kind of tower babble moment.
2:06:28
And and the problem is like if you remove that from their vote, that's why I call them faux neo China hawks.
2:06:35
Like they're not really China hawks.
2:06:36
They're actually agi zealots.
2:06:39
>> If you remove it, none of their policies kind of make any sense.
2:06:41
This one reason why you hear, oh, like we have to prevent chips.
2:06:44
Oh, we have to block models.
2:06:46
Oh, like you know, we have to restrict um, you know, model ways. We have to do tokens.
2:06:50
Like they it's just kind of like amorphous blob.
2:06:52
But they can't really win in DC with the idea that AI is gonna be God.
2:06:56
Most people are gonna be like, "That's kind of insane."
2:06:59
Like you're go back to to reading, you know, the go back to watching Matrix or, you know, reading the Terminator or some some other related sci-fi novel.
2:07:05
And and so they kind of wrap it in something that is like super easy to understand. China. Oh, China, right?
2:07:10
You know, oh, the the yellow country, right?
2:07:13
And and and they and oh, they're so scary, right?
2:07:16
But but you look at the specific policies, none of it like makes any sense. None of it.
2:07:20
sense. None of it. I met with a venture capitalist last week who said honestly none of this stuff's going to matter in two years when we have fast takeoff >> but he wasn't he wasn't doomer pill he was just saying like fast takeoff will mean that every single company goes to zero >> because there will only be one company
2:07:37
which is a very funny take >> he has invested in SAS this year >> and yeah and it's yeah so the revealed preferences is is all over the place um but yeah it is it is weird to fe to feel to make the argument that like uh we're going to develop AGI god but It won't like it it it it will be it will be God, but it won't be subservient to actual God. But also or or it will sit below
2:07:57
But also or or it will sit below the stack of it'll it'll it'll respect the federal government of the United States.
2:08:04
It'll be God, but it won't but it won't but it won't but it'll do what the president says or it'll do what the House and Senate say or it'll do what one company says or what one person says.
2:08:13
It's like if it's God, can it be controlled?
2:08:15
How does that make any sense? That seems very odd. >> Yeah. Yeah.
2:08:18
It's a and and and as you and I talked about, John, it's like like so much is built into of their presuppositions are defined by the title two debate.
2:08:27
Remember that whole thing of like, oh, free speech is going to die.
2:08:30
We have to regulate and all stuff.
2:08:30
Many of that same donor class, many of those same policy people are also the AGI doomer zealot people.
2:08:36
You go back even like a like series of steps further like many of those people who are super hot on new atheism and like and like oh this idea of like we can we can prove via science. We just need more time.
2:08:47
We just need more scientists.
2:08:49
We just need more people.
2:08:50
It It's the same pattern in humanity that we create these kind of albatrosses.
2:08:54
This idea of like creating an an all-in or sort of argument that because they don't have that in their life and then they make this thing and and and as I said like on a on a one of I think times I appeared >> that if you don't have that metaphysical framework that is traditionally Judeo-Christian or Western, you try to fill something else in that void.
2:09:14
fill something else in that void. It's a classic Charles Spurgeon quote that that you you basically fill it with something else outside of just the fact of what the place of like God or faith is supposed to fill and technology I would say Silicon Valley probably San Francisco they don't really understand that there's so much faith goes into actual the VC industry that is you're really kind of selling BS to an investor
2:09:36
you know like the I know y'all lots of jokes around what is ARR in AI it's mainly you're just selling kind of like nonsense and the idea that like this could be something this could be it is a it is a faith driven investment that's what also makes it so awesome why we why we look at Zuckerberg we look at Elon who he made an idea and the vision the future reality today so it is heavily oriented to towards a metaphysical
2:10:01
theological framework but this AGI thing as it relates to China so much of it has just gotten lost in this I don't even know what I'm talking about anymore because the these same people who are criticizing the 15% tip the to the
2:10:14
federal or government to the American worker uh for Nvidia are the same people who didn't want to ship GPUs to Switzerland because I don't know they make two good watches or Portugal they have too many good sandy beaches like
2:10:23
they they the same people right so it just keeps shifting because it's really trying to provide a luxury belief to a base around the idea of AGI what's your what's your line though because I think that the the critique here that's pretty
2:10:37
fair is that if you start applying this to other categories of goods like fighter jets like what what What's what would the you know fair price be to export an F-35 to somebody that nah maybe they're on the on the edge? Maybe
2:10:51
Maybe they're kind of friendly now, but maybe in the future uh they they they might not be so friendly.
2:10:57
Like you believe there should be we should draw kind of a line and uh we shouldn't want government agencies to kind of apply this uh approach to fund raise.
2:11:11
No, it's it's a difference between it's not a hunk of metal versus like you're selling a system.
2:11:15
I have the same sort of concern as it relates to Nvidia as it relates to Apple building phones in China.
2:11:21
If I got an iPhone, no OS on it, none of the the magical, you know, more and more transparency via, you know, the the design, then I then it's kind of useless.
2:11:30
It's just like a phone, right?
2:11:31
And and that's the way Nvidia actually is.
2:11:33
Nvidia is an Appleike ecosystem.
2:11:36
It's not just a hunk of metal.
2:11:36
Same with the reason, you know, we we sell 787s, we sell trip 7s, we we sell the trip 7X to China. Why?
2:11:43
Because it's made up of this complex the thousands of companies.
2:11:48
It's a software platform.
2:11:48
We remove certain things which I'm generally okay with like advanced avionics.
2:11:51
Uh we remove we we also kind of limit certain types of engine design. I'm fine with that.
2:11:57
So with the B30, H20, these kind of nerf chips, I I don't actually make much of an opinion about it.
2:12:02
Like I don't have to have a no true Scotsman sort of argument about like well at what point would you not do it?
2:12:07
I'm like I don't sell fighter jets.
2:12:08
I don't rent fighter jets.
2:12:10
So you can talk to Lockheed about that or Boeing about that.
2:12:13
Like what what what I think is most relevant is the fact of these innate externalities these exogenous factors outside of the machine which that half of all AI engineers are Chinese.
2:12:24
half or actually more 75% half of them are Chinese nationals.
2:12:27
Another if you include all the Chinese associated last names in Meta's super team are Asian.
2:12:34
So like we either have to lean into our strengths which is the fact we're good at making platforms, we're good at dominance, we're good at free enterprise, we're good at trade and and the fact that Chinese have something that they don't have the raw production capability of doing which is not Nvidia.
2:12:49
that if I don't take anyone seriously who criticizes export controls if they associate Snick with Nvidia it's like saying Kirkland like Kirkland and Costco like Costco makes Kirkland like that's not what Kirkland is right Kirkland is a rebrand of somebody else's stuff and that's kind of like the criticism it's
2:13:06
like oh like how dare Costco make this Kirkland thing you're like it's a rebrand bro like it's not it's I don't actually make this thing like it and so that that's where this constant confusion lies that many of these people criticize this stuff are actually criticizing Smith or or TSMC completely different companies Jensen buys from them. So if you want to go after the
2:13:22
So if you want to go after the foundry stuff ASML the Japanese like you have to realize one we don't make this technology it's it's Japanese and Dutch but the other is like it's not what Nvidia does if if you want like I'm cool with targeting uh lipography equipment preventing them from getting to 5 nometer and that's that is something that's actually quite reasonable because because we do export control trip 7s and etc.
2:13:42
etc. like we have some limitations where we send that's fine because it's a freaking size of a house and it cost $200 million but the same of lithography so much of what I what I'ming for is pragmatism is like realism like like we have to lean into what our strengths are we have to proliferate and prevent
2:13:59
Huawei from spreading its wings outside and if we want to target the ability to manufacture 5nime or 2n 3 or whatever like most Nvidia stuff's on a 4 nimeter process that's cool like I'm totally in favor of that but don't attack Nvidia because that's not what Nvidia Yeah, makes sense. Um, on the foundry
2:14:13
Um, on the foundry side, I want to jump over there. Let's let's talk Intel.
2:14:18
There's been a lot of headlines recently.
2:14:20
What's your read on the situation?
2:14:22
How important is Intel in your view?
2:14:25
Uh, do they need a new board? Do they need a new CEO?
2:14:30
>> I don't want I'm gonna I'm gonna get in hot water here.
2:14:33
>> Yeah, it's um you know, so like my dad's Chinese and and so there this thing like I am I'm a true China hawk.
2:14:39
I am I'm a true China hawk. I'm OG China hog and and there's many times where like China's the largest country in the world and there's many overlaps that are just completely not you know they're they're just fine and and I don't know anything about the particular criticisms of Intel CEO I think his strategy is not
2:14:55
great for Intel so like I mostly would target there but America needs a foundry program and particularly trailing edge uh leading edge I don't think is economically viable uh so that's why I'd rather ship that to like a Brazil or Argentina or something like that like do a newman road doctor and sort thing. >> Why is that? I feel like the leading >> Why is that?
2:15:11
I feel like the leading edge is coming into Arizona through TSMC.
2:15:14
Samsung's doing stuff like I feel like >> Yeah.
2:15:17
Trailing South and then leading edge here. >> Oh, okay. Yeah. Yeah. Yeah. Yeah.
2:15:22
Traing edge also economically, but we can import we can import the the semiconductor, you know, geniuses that will run American TSMC. >> Yeah.
2:15:31
And and you also have to understand that like there's lots of reports.
2:15:34
You can go read about it of a former, you know, Chinese nationals that work at TMC that takes that back.
2:15:38
Like it's it's a Taiwanese company.
2:15:39
Like there there's there's an there's an arm that we can extend as a nation that can only go so far.
2:15:45
And that's part of the America first concept of Trump.
2:15:47
He's like, "Do I really want to take all of the juice and squeeze in terms of negotiating presidency over a nerfed H20?" He's like, "No."
2:15:55
Like like we have fentanyl issues.
2:15:58
We have 300 billion400 billion dollar trade issues.
2:16:01
We have them IP issues, right?
2:16:02
We have Chinese nationals at labs all across like those are much bigger things to pry than the fact of like oh they get like you know basically an equivalent of an A100 uh being deployed into to to their to their fabric.
2:16:14
So the so the Intel stuff I I kind of have this disposition that it feels like it's going to be nationalized.
2:16:21
I get kind of like vibes around that as a as a economic conservative.
2:16:25
I'm like oh that's kind of scary.
2:16:26
But at the same time, like it it is one of those things that just kind of happens.
2:16:31
Like the the Did y'all hear about the uh the federal government invested into a Rare Earth Minerals project in America?
2:16:39
>> The one in Vegas, right?
2:16:39
They got like 15% for the for >> SAM. Yeah.
2:16:42
And so so I think the same is going to happen with with Intel is like they basically it's it's it's occurred through there's a couple different lending vehicles in the federal government.
2:16:51
It's basically gets a warrant.
2:16:52
That's kind of the vibes I'm getting from Intel is that something like that's going to happen because you also can't take TSMC process and Intel processes and just mix them together.
2:17:01
Like that's not the way this works.
2:17:01
Uh, and also TSMC, uh, I think whenever they originally pitched that idea, I think the president was like, "Yeah, like do Intel thing."
2:17:09
And TSMC was like, "Maybe, right?"
2:17:12
And then they go look at and they're like, "Holy, this is a freaking nightmare of people who don't want to work, who don't have the work ethic of TSMC."
2:17:18
And and that just kind of all blew up.
2:17:21
And I think there's some embarrassment in terms of like that this is America's founding program and this is kind of like how it matches up to the best of the world.
2:17:27
So, I just get kind of vibes that it's going to be nationalized or split apart and divided as a company.
2:17:32
Um, and but in terms of bearing on like my opinion about whether or not that guy should be a CEO or not, I would point more towards the strategy rather than these kind of rumors or >> we had Doug on from some analysis on Friday and he he basically said like look at the board like a lot of the people that are still on the board have just like overseen like numerous CEO changes.
2:17:54
changes. is the strategyy's clearly not been working like you know >> well they're not semiconductor experts was his main critique >> yeah they're finance guys >> finance guys but also politicians and and thinkers like it's a it's a wide
2:18:06
variety uh without a lot of focus on like manufacturing expertise >> uh what was your what was your reaction to GPT5 >> uh not as negative as John uh >> and uh I was negative yeah you were like oh like it's over and I was No, I don't think so. Like see, so so first of all,
2:18:25
Like see, so so first of all, first of all, so I think I think it's like pure pure numberbased GBT revisions being indicative of of order of magnitude scaling is over. >> Yeah.
2:18:38
Like so >> the pre-training scaling law is over.
2:18:42
>> I I So one is like a couple months ago we didn't say that because Rock 4 came out.
2:18:45
So like so it it's so I would like maybe take a more like Prudence perspective on this. >> Yeah.
2:18:51
One is that there's a clear decision here by uh Sam that he is a consumer app company. >> Exactly.
2:19:00
>> Which is which is which is the right bet.
2:19:01
It's like I don't >> sell consumer SAS. >> Yeah. >> Yeah. I'm not I'm technical.
2:19:06
I don't remember what all the freaking numbers and crap does. Doesn't matter. >> Yeah.
2:19:12
And so that's the biggest innovation here.
2:19:14
And if you look at the the idea like you know he he expanded the context one open not very much which implies inference right that that he doesn't have enough capacity to run as many user requests.
2:19:25
>> The the other is that he mostly solve for downside scenarios and ease of use in the UX and those are like really big changes.
2:19:31
changes. the the the benchmark maxers are uh basically creating goalposts that are artificial like if do you do you mean do you all remember your SAT scores your SAT scores like >> do you remember do you remember y or calculus you know high school calculus
2:19:49
you know like no it's like these are all abstractions and metaphors that we create as huristics to understand something's intelligent but many times as you know in real life we don't grade people really by that >> what have you done that's a good >> what Can you do >> product? Consumers ask like my take away
2:20:03
Consumers ask like my take away my my big takeaway Thursday was product now and and and and the value you can deliver to consumers is the only thing that people should really care about in the short term and and OpenAI is in an amazing position here.
2:20:22
Anthropic is an amazing position here.
2:20:23
They have you know Anthropics got an amazing enterprise business.
2:20:27
Open AAI can sell a lot of subscriptions to a lot of people in the US and all over the world.
2:20:33
And the real people that were in trouble seeing GPT5 were the people that were, you know, still kind of fundraising against this idea of machine God. >> Yes. Yeah. Yeah. Yeah.
2:20:44
Dex machine out of the dead.
2:20:46
Like I I I'm thankful for that. I'm a Christian.
2:20:48
Like, you know, people remember Tower Babel.
2:20:50
It's like a it's a it's a it's a both a story to take lessons from, but I believe really happened.
2:20:56
happened. And the the the the point is that uh that humans naturally are drawn in every moment of the cycle which is why that and recre quote I don't know if it's tribute to him but probably somebody else actually said it that we overestimate in the short term we underestimate in the long term I think the god complex is that and and if I go
2:21:13
into the also the other kind of more tactical point is that many of these things that happen where people are using T85 if you go to grog four it solves it just fine >> so so it was just funny that people are like oh my god they can't do blueberries you feel like you I literally took that did in Brock and it dancer just fine. So
2:21:27
So this seems like much more of like a tactical decision on Sam.
2:21:30
It could be the fact of like >> Yeah, it's interesting people's desire to like gotcha the model.
2:21:35
So funny like they can they can completely ignore that it'll just like oneshot like a really >> crazy physics problem and then they'll like get it on some like technicality. >> Yeah.
2:21:48
And the whole point and that that everybody should internalize is that the models are really smart at some things and then there's going to be edge cases and then where they they mess up just like humans do and then there's going to be areas that they they're not capable at all and that's totally fine.
2:22:03
It's still incredibly valuable. >> Exact. Exactly.
2:22:07
Like like I I try to simplify ways what AI is going to be which is computing that talks like a human.
2:22:13
It doesn't mean it is a human just as if like there there was obviously the famous uh I love this analogy because it shows how much humans are not aware about how signals and intelligence has developed.
2:22:25
So you remember back in 70s and 80s like they said oh like monkeys can talk right they taught in sign language and then they could repeat it.
2:22:33
So they ran the test again and this time they had no facial expressions and they tried to just limit all human human interaction to to uh to to the ape and they couldn't do it because what they realized was actually the the the apes were responding to un known human cues that the that the the researcher was delivering to the ape.
2:22:55
the right they were just mimicking what they thought would actually thing they want but they couldn't actually create discrete knowledge and action intelligence about what the actual language was being was being delivered >> and and and so that that's where it goes into like when you look at something so much about because humans are so amazing
2:23:11
at being able to create it's part of the the original genus argument appeal to the land name the animals we're amazing at that because because it's it's either believe like a god-given talent that we have that only we have as a species but we're so good at it we have no idea how we affect other people or other animals via that that projection that as a as
2:23:30
another basic scientific book you're married as another like very simple thing that most people don't understand about the way they pick partners much about the way you pick a partner is driven by the pherommones of your immune system and they've done studies of this where you where they basically created a blind test where they took from different you know like opposite
2:23:49
the opposite sexes and they basically gave it as as to the opposite sexes like male and female like which one smelled better and they found that the one you thought smelled better had the most different imological profile than than commonality and that's because of the desire to have a children children that had the greatest amount of protection from disease. So, so that's so like you
2:24:07
from disease. So, so that's so like you know we can go into blondes brunette blue eyes like hi whatever but so much is driven by smell and we're not even like aware of it and and so we're here being like hi and oh like >> we got to create smell vision first we got to create fund the company right now smell for AI >> so um for sure >> last week there there's been different headlines rumors around negative gross
2:24:32
margins in various SAS SAS companies specifically in the in the codegen space does that you know that the the reason you would invest in a company with negative gross margins is you would expect inference costs to decline dramatically and and for them to generate you know positive gross margins over time and right now you just need to acquire as many customers as as possible and create products that people love. So
2:24:55
So that that that investment case makes sense and then you have GPT5 come out which has you know a significant cost reduction.
2:25:05
Uh I understand like cursors are going to be 15% better in the next administration >> potentially.
2:25:12
Um potentially but but how how are you thinking about is that uh you know and and the um journos are are freaking out about it saying like oh this is all like >> I saw that rune post I know exactly what you're talking about.
2:25:25
Uh but but what's what's your view um in terms >> how fast how fast can we actually drop inference costs over the next couple years because it does feel like if it takes a decade to to to you know get an oo of savings like an order of magnitude of savings like we might be in trouble financially. >> Yeah.
2:25:46
And if but but at the same time if you if you >> I I think like researchers at the labs have been focusing on raw intelligence more so than efficiency.
2:25:54
And so if we're hitting if we're hitting a sort of plateau intelligence wise, the next thing that makes sense to do is like really optimize efficiency. >> Totally. >> No. Yeah.
2:26:04
No, I I think I think Jord hit it on on the head, which is that there's two trends.
2:26:08
There's the effectiveness trend and the efficiency trend.
2:26:11
>> China is rationing us on the efficiency trend.
2:26:13
Absolutely demolishing us.
2:26:13
And >> this is the whole thing.
2:26:16
We we we give them all these Nerf chips and we limit their chips so they just get incredibly efficient.
2:26:21
It's like >> shots in the foot.
2:26:23
I mean, bring it back and then inference that.
2:26:25
Yeah, >> there's a lot we can learn. >> So, so yeah, exactly. Exactly.
2:26:28
So, so I I I think that there it all develops into kind of we don't really fully understand customer preference theory as it relates to these tools >> and that what is the actual first pass the goalpost sort of goal to to pay versus free.
2:26:42
But in terms of the brute natural law that compute gets cheaper, that's bulletproof. So, that will continue.
2:26:50
>> And and so at what scale, like you said, does it actually frost that?
2:26:51
I I I think the bigger concern is more of these mega models uh that that they just have the ability to absorb the cost, be able to spread it across different things.
2:27:01
And if you think about it, it it's a little bit like how Apple will continue to invest in its own apps that you remember when you first got the iPhone, you had a camera app, >> right?
2:27:13
You had calculator app and then they kind of replaced it.
2:27:14
That's the bigger concern for some of these tools is like a mega model be able to absorb the cost like like Google which has a crap ton of code or like maybe llama open source as a coding agent which seems pretty pro probable that that becomes like more of the go to like basically compressing even further.
2:27:30
basically compressing even further. uh so they have to be able to create the data stream like a I think it was a cognition that's trying to do that where as they uh engineers you know put stuff in in into the agent then it basically re reinforce self-learns from what the act doing that's probably the best path
2:27:49
to create some significant amount of of of margin but you should every company can rely on that it's going to get cheaper but as Jordy said there's some protectionist stuff returns our national policy that has prevented that and and I made this argument on another show where
2:28:04
I said that well funnily the US government this was pre Trump was applying protectionist measures to these large scale model companies and he like didn't understand that he goes well what are export controls like and like he just didn't think through like the economic consequences of that and that means in our country we have an over
2:28:20
supply versus what we actually would pay for versus what the world would pay for which is a protectionist measure which means that you don't have the same market forces being applied to our frontier labs as you would in other countries as you already Yeah, we send them Nerf chips. That's the cap. So then That's the cap.
2:28:31
So then they then go down.
2:28:34
Like that's their only direction they could go.
2:28:35
So if we actually have a more liquid supply, more market driven supply where things can be priced in, then you're going to see OpenAI start doing more open source, more of this downward cost efficiency because they're now exposed to it.
2:28:46
So it shouldn't be lost on us that open eye is pursuing this idea of like how do they add these mega releases cheaper models is because they're starting to be more exposed to these like cost structures that is needed for us to actually be competitive on the efficiency side.
2:29:00
But if we continue to go down this effectiveness range effectiveness is generally like a B2B problem like where you're company versus company.
2:29:08
So it's not really like adoption you're going after like we just got to be the best company and and efficiency is the opposite.
2:29:14
Efficiency is like how do I make this as cheap as possible for someone to adopt?
2:29:17
Javon's paradox like that that's the direction.
2:29:18
So I think over the course of two years the next two years I think you're going to see a a tilting into lowering cost making things more efficient.
2:29:27
So there's going to be multiple times in the show where I go on where people are like comput's so cheap no more wants to buy more compute and like the remember deepseek it's like this that's going to be kind of what continues to happen.
2:29:36
continues to happen. Uh but it's good for it's good for the world like we we want comput to be as cheap as possible and on a token basis and that means optimizing for like hydro energy optimizing for tax regime reducing construction costs reducing permitting all those great things that would make
2:29:53
everything cheaper because the more cheaper we get the more people we use and and AI is such an innate good for the world that is something that America should be proud of that we can share with the entire world and the only way that's going to work and they got to make it super cheap to run in Africa. Not
2:30:06
Not launching a Stargate in, you know, in you know, freaking Tanzania to like that's not going to go anywhere, right?
2:30:13
But you have to make it to where it's capable of actually being scaled across the world. >> Okay.
2:30:16
Lightning round from the chat.
2:30:18
Pancakes, waffles, or French toast.
2:30:21
>> I'm keto, so I don't need any of that stuff. None of that stuff.
2:30:23
What skills do you think will be most in demand in AI and data infrastructure over the next three to five years?
2:30:31
>> Uh, many of the things that Trump ran on or to still remain true.
2:30:34
electricians, plumbers, building something like the raw work with your hands sort of work as well as there's going to be new categories of jobs that we don't even fully comprehend yet that are going to take that salary of engineer and like it's going to go there. >> Last question.
2:30:48
What was the most who was the most important hire you made in the early days of your company?
2:30:54
>> Um >> like what do they do? >> What do they do?
2:30:59
Probably my CFO, general counsel. >> There you go.
2:31:04
Uh do you expect any data center project like a lot of data center projects to blow up over the next few years?
2:31:11
people >> um there's been some interesting commentary >> interesting commentary people are basically >> credit funds or >> well well so people are like basically forecasting the useful life of their GPUs and then separately what like what they'll actually be able to sell uh inference at and ultimately if either of those equations are out of whack at all you can be completely underwater and not be able to service your debt.
2:31:39
Yeah, I would I would say that in and maybe this for our next time GPUs are not overbuilt, but data centers will >> and and I lean into not like I agree agree Jordy that the cost goes down and changes in vintages but the key thing is like look at what the money is doing.
2:31:59
There is very tight control still on like getting loans for GPUs.
2:32:01
There is almost none for for data centers because they view the use of life 15 20 years.
2:32:08
But as Jord just said is like if the square footage profile of power density versus what you can get is not structured correctly as well as Nvidia is actually making less GPUs next year.
2:32:18
There's going to be a lot of places that are just there and nothing's in it and like in China like we see in China.
2:32:22
So GPUs in China are like massively being utilized but there's lots of data centers that have nothing in it or like just can't actually run it.
2:32:29
So I think data centers are far more likely to be overbuilt and be a bubble than GPUs because you know one company controls the GPUs.
2:32:36
you generally from market forces don't really see that be a bubble because it's a monopoly generally and and data center lending is very aggressive because they view it as a 20-year asset and the GPUs are short term so there's just not as much money flowing into the GPU side as much as the data center side >> makes sense thank you for coming on always a pleasure >> thank you for coming on always >> guys we'll talk to you soon >> public.
2:33:01
com investing for those who take it seriously they got multiasset investing industryleading yields They're trusted by millions, folks. Get on public. com.
2:33:10
And we have our next guest in the studio. That's right.
2:33:13
We got to get the gong ready. Vulcan elements.
2:33:17
>> Come on in from waiting room, John. >> John, how you doing?
2:33:22
>> What's happening guys? I'm well. >> Big morning.
2:33:25
>> Uh, give us a little introduction. Tell us the news. >> What's going on? >> Yeah, good afternoon. Uh, John Madison.
2:33:31
I'm the CEO and co-founder of Vulcan Elements.
2:33:33
We uh are a manufacturer of birth magnets and we just raised a $65 million series A. >> Hit it, John. >> Congratulations. $65 million. >> Incredible.
2:33:44
Perfect size for a series A. >> Perfect size. Perfect size. >> Perfect size. Um amazing.
2:33:47
Uh give us quick backstory on yourself and the company and then we'll get into it. >> Mhm. >> Yeah.
2:33:55
So, uh former naval officer, spent six years active duty in the US Navy.
2:33:57
Uh most of that time was in Washington DC with the Navy's nuclear energy program.
2:34:03
worked across Navy ship building, uh, submarines, aircraft carriers, got out a few years ago, went to Harvard Business School, and, uh, was just very focused on >> Yeah, business school. >> Humble brag. Yeah.
2:34:16
>> No, they call it I've heard it called the Harvard of business schools. >> It really is. >> It really is. >> Yeah. Well, I'll take it. I'll take it.
2:34:24
uh but uh was spending a lot of time thinking about my time in the Navy, thinking a lot about what were the critical components as a good supply officer would that were going to define the 21st century technology race.
2:34:35
>> When we think about drones or physical AI, data centers, next generation defense technologies, what were the underlying components that would enable that?
2:34:44
And doing my homework, it came down to three components.
2:34:49
Semiconductors, batteries, rare earth magnets. Mhm.
2:34:52
>> Uh the way that I like to think about it is if you think about your own bodies, a semiconductor is like your brain, a battery is like your heart, and a rare earth magnet is like your spine.
2:35:02
>> It literally converts electricity into motion.
2:35:03
Uh there was so much focus at the time on semiconductors and batteries, but no one was thinking about rare earth magnets.
2:35:10
>> And if China produces over 90% of those rare earth magnets, that means that we're going to have to ask permission on what we're allowed to build and buy over the next 5 years, which is not an acceptable outcome.
2:35:19
So, we're trying to rebrand them.
2:35:21
We're just calling them Earth magnets because we've heard that that that they're not actually that rare.
2:35:26
They're in the ground all over the place. Uh, is that true? What's the strategy?
2:35:30
Are you actually mining these, just refining them?
2:35:33
Like, where is America like?
2:35:35
Explain the full supply chain to go from something in the ground to something actually useful and then where you want to slot in at least immediately.
2:35:43
I'm sure that there's vertical integration down the pipe at some point. >> Yeah.
2:35:47
So, we're we're a refiner and manufacturer, but just a quick rare earth 101.
2:35:51
So, everyone's talking about critical minerals. What does that mean?
2:35:55
>> A critical mineral is >> an element on the periodic table that is critical to our economy with the supply chain that can be easily disrupted.
2:36:04
>> Rare earths are a subset of that.
2:36:04
There are 17 rare earth elements on the periodic table.
2:36:07
Uh, go back to 10th grade chemistry. Close your eyes.
2:36:09
Think the part think about the periodic table.
2:36:13
The part that's detached that your teacher told you to ignore.
2:36:14
Yeah, >> that first row, those are the rare earths. >> Funny. >> Exactly.
2:36:20
Of those 17 rare earth elements, only four of them represent over 90% of the economic value.
2:36:26
>> Neodymium, praisemium, turbium, >> desposium. >> Okay.
2:36:30
>> The main use for those four is a rare earth magnet.
2:36:32
>> So the way to actually make a rare magnet is you either mine that material uh and that can be from all over the world.
2:36:38
China only mines 55% of the global supply >> or you take recycled end of life magnets.
2:36:43
You have to separate those into an individual rare earth element.
2:36:45
Turn that into a high purity metal. We buy that metal.
2:36:49
You then take all the rare earth's iron, boron, and uh you turn that into an allo, an alloy, a super fine powder.
2:36:57
You press it within a magnetic field, and then you shape, coat, grind, and that's a magnet that can go into an MRI, a missile, a ship.
2:37:08
>> What does a go to market look like?
2:37:08
I imagine you're focused on specific c customer types early on that are maybe less price insensitive so that you can start to scale and ultimately kind of grow into other categories. >> Yeah.
2:37:20
So one thing that I say is Vulcan elements is focused on defense, aerospace and critical economic industries.
2:37:27
Uh we do not make magnets for you to make a a a smoothie in your blender at home.
2:37:32
Uh we're not focused on kitchen appliances, >> right?
2:37:36
So we are focused on data centers, robotics, drones, defense applications, aerospace applications, uh enabling what the war fighter needs, enabling what the economy needs in order to win the 21st century technology race. It's as simple as that.
2:37:52
>> What how how quickly can you go from $65 million series A to actually selling the end product to customers?
2:37:59
We're already selling product to customers out of our out of our small scale pilot facility.
2:38:06
Uh so we took our first check December of 2023.
2:38:07
Uh we told investors day one if you give us a if you give us a dollar Q1 2025 we will have a fully operational decoupled rare earth magnet facility online. We did that on time. We did that on budget.
2:38:20
We are selling magnets right now >> in that facility.
2:38:23
I'm sure you have a lot of equipment.
2:38:24
Uh, is there an ASML of uh of rare earth refinery that you need to buy from?
2:38:32
Is that an American company?
2:38:35
What is the rest of the what is your supply chain look like?
2:38:36
And uh is that is that a resilient supply chain?
2:38:41
>> So you guys already asked the the question around, you know, where do these materials come from, where the minerals come from?
2:38:47
This is not a a mineral availability problem.
2:38:49
This is a software and equipment problem.
2:38:51
So, we actually helped co-develop some of the first pieces of rare earth magnetic manufacturing equipment made in the United States in the 21st century.
2:38:58
There are so many amazing manufacturing equipment manufacturers in the United States who are doing aerospace and battery work.
2:39:08
We've just partnered with them to say, "Hey, let's tweak a furnace and do it for rare with magnetics."
2:39:13
So, 100% of our equipment is from the United States or Allied countries.
2:39:18
>> Wow, that's pretty sweet.
2:39:18
Um, bit of a dumb question.
2:39:21
Uh, are are the materials magnetized all the way through your process or is there a period where they get demagnetized and then kind of remagnetized?
2:39:32
>> So, the elements like iron, like rears, they're they're naturally magnetic. >> Okay.
2:39:37
>> Uh, this is actually something that I learned when we were starting the company.
2:39:40
When does a magnet become a magnet? Yeah.
2:39:42
>> Well, you actually have to throw it through a magnetizer. >> Yeah.
2:39:44
uh toward the end of the process.
2:39:46
>> I remember reading a book to my son uh about how how magnets get made and it was like sometimes there's a rock that gets struck by lightning. Is that real? I don't know. But >> yeah.
2:39:55
So really the intent is you need to make sure that you're creating a centered block, all those particles are perfectly aligned.
2:40:01
Uh you've done all the the metallography, the microructure, the grain distribution perfectly.
2:40:06
And then when you're running it through that magnetizer, it actually hits the grade, the heat tolerance, the magnetic strength or flux density that is required to actually sell to a customer. Mhm.
2:40:18
>> What's you what's unique about building a startup where it feels like there's like from my view and and what what you've said, it feels like there's zero demand risk and you probably the question comes down to like can you deliver it at a at a price that's competitive, but then it's really more so can you can you actually deliver it?
2:40:40
Can you deliver it at the scale that that really becomes meaningfully uh important to to national security?
2:40:46
But kind of what what was your calculus I guess going into building this company with with that kind of um understanding of the market?
2:40:55
>> Execution is the entire game.
2:40:55
So we knew that we had to find incredibly sophisticated technicians and engineers and PhDs.
2:41:03
We needed to understand how to interface with the DoD and the government, how to interface with large OEMs.
2:41:09
We had to understand how to talk to mining companies and recycling companies.
2:41:13
And so the bet was, can you actually build the team that can put all of those different pieces of the jigsaw puzzle together in a way that's cohesive to where you can actually get a contract, raise the money, and put a magnet in a customer's hands.
2:41:28
And so we made we made a bet on ourselves.
2:41:33
>> And that's what we've done is by finding incredibly smart people who are missiondriven, who want this to happen, we've been able to deliver.
2:41:40
we've been able to execute across every different domain within the industry required to actually get a result.
2:41:48
>> Now, a lot of this has to be like the demand for Americanmade rare earth uh magnets has to be somewhat tied to trade tensions with China.
2:41:56
uh if those get resolved and you know Trump's sending Nvidia H20s over there and he's happy with that deal and then all of a sudden Cin is like yeah America you can buy as many rare earth magnets as you want.
2:42:10
Uh is that is that a short-term medium-term risk?
2:42:15
Is there a way that you can uh can like ramp the economic model so that you're competitive even if we were in a fully free trade regime?
2:42:23
So our small scale facility was sold out a full year before the trade tensions.
2:42:29
>> So there's just so much demand that even even with trade tensions like you you you can fulfill the backlog. >> Correct.
2:42:36
People want resiliency within their supply chains.
2:42:38
People want this component on.
2:42:40
But to your point, I think it's incredibly important that we're not just copying and pasting.
2:42:45
If you copy and paste Chinese manufacturing into the states, >> the unit economics make no sense. >> Yeah.
2:42:50
Because they'll beat on labor probably. Right. >> Exactly.
2:42:52
So, one thing that's nice about this industry is there hasn't been a lot of innovation.
2:42:58
Uh, and when you find incredibly smart people from different industries, aerospace and battery, ship building, >> you're able to actually bring all of that learning and you're start you can start taking a lot of low hanging fruit, innovate really quickly, and then over half of our technical team, they're scaleup engineers. Yeah.
2:43:14
And so when you think about delivering at scale, coming down that cost curve, reducing operating costs, uh, and making sure that you are ultimately, you know, as cost competitive as you can be against the Chinese. >> Yep. >> Yeah.
2:43:27
>> What are your what are your goals for the next couple years look like?
2:43:28
You said you kind of called your shot in 2023.
2:43:31
You delivered against it uh earlier this year.
2:43:34
What do you want to do uh with the with the 65 million and and going forward generally?
2:43:39
So the 65 million we're going to go to commercial large scale commercial scale se several hundred tons over the next couple of years several thousand tons by the end of this decade.
2:43:50
>> And what what is the what is the kind of market value of that kind of production >> minimum several hundred million in topline uh up to several billion. >> Thank you J.
2:44:03
>> Figured figured there were some big numbers. >> Fantastic. Awesome.
2:44:05
Well yeah thank you for everything you're doing. This is very exciting. Super important work. >> Glad you're doing it. >> Yeah. We'll talk to you soon. Have a great day. >> Thanks, guys. Cheers. >> Talk to you soon. Bye.
2:44:17
>> Take a little bit of that money, buy a billboard on adqu. com.
2:44:19
Out ofome advertising made easy and measurable.
2:44:22
Say goodbye to the headaches of out of home advertising.
2:44:23
Only adqu combines technology, out of home expertise, and data to enable efficient, seamless ad buying across the globe.
2:44:31
>> We've seen this playbook in mining, buying billboards next to the companies that you want to hire from.
2:44:34
Speaking of billboards, Roy Lee is in the news again.
2:44:38
Uh he bought a billboard in uh in Manhattan.
2:44:42
Uh and he said Alex Cohen says, "Fine, I'm starting to like the Cluey guys because Roy put up a billboard that says, "Hi, I'm Roy. I'm 21.
2:44:52
Uh missing an apostrophe on the second I'm clearly deliberate. Uh absolute wordsmith. This was very expensive. Pls. Buy my thing. Please buy my thing." clearly.
2:45:04
com and John Chu coastal ventures says this is why I invested in Roy Lee once in a generation talent at tapping into culture and zeitgeist. This was a spicy post.
2:45:14
People kind of going back and forth on whether or not this would actually deliver.
2:45:18
Roy also put out a post saying that like everything he does is for short form.
2:45:22
So he bought this billboard.
2:45:25
He expects it to convert on the short form that will be created around the billboard.
2:45:30
certainly feels like people will create will take pictures of this shar when you look at um >> I think what I'm interested to see from Cluey is where they really get where they really get long you know retention right because they have
2:45:47
>> the top of they kind of yeah extremely full >> top ofunnel marketing uh but when you look at like it doesn't it seems like if they just focused on students right they seem to be in this kind of place where they're they're >> thinking about exploring different markets. But if you
2:46:03
But if you look at the way that chatt's usage uh basically tokens generated dropped as summer started, >> that's a good it's a good argument to say clearly could just focus on >> products for for students that will eventually graduate into the workforce and things like that. Sure.
2:46:21
But anyway, >> well, they didn't make the top AI agents by revenue chart that Anon Sonwal shared uh said, "Who would you put your money today to win in the long term?"
2:46:29
The top was cursor at 500 million in annual revenue.
2:46:34
Uh and they're making $3.
2:46:34
2 million in revenue per employee. Glean's at 100 million.
2:46:42
Merkor is at 100 million. Replet's at 100.
2:46:44
>> How are you defining an agent?
2:46:47
>> I think it's just AI startups.
2:46:47
Anyone who's used the AI agent like meme basically >> stolen the agents are going to be pissed about this stolen valor. >> I don't know.
2:46:57
>> It's hard to call mercore an >> I agree with that one.
2:46:59
That one feels particularly odd.
2:47:01
But uh and Glean even is enterprise search. >> Yeah, it's search.
2:47:06
But I would say Replet is an agent company.
2:47:08
Uh it's kind of like every AI company's now now a now an agent company.
2:47:14
Harvey uh you know hasn't really branded themselves an agent.
2:47:18
>> But it's interesting like you're not putting claude you're going to put cursor on here which generates revenue from claude code. >> Yeah. >> And is a gentic IDE. >> Yeah.
2:47:27
You're not going to put it is crazy and also not including chat GPT which has deep research which is probably the most used AI agent in the world right now I have to imagine just by tumber number of queries.
2:47:38
Um there it's missing some stuff.
2:47:42
It's missing some stuff, but it's okay.
2:47:43
Also, Devon's not on here, which is kind of odd, but that's the nature of these lists. It's CB Insights, folks.
2:47:49
They do the best they can.
2:47:51
Um, and you can do the best you can in the watch game.
2:47:53
If you head over to getbzzle.
2:47:55
com, your bezel concier is available now to source you any watch on the planet. Seriously, any watch.
2:48:02
>> I like this post from Aaron Bali.
2:48:02
He says, "Imagine you're one of the smartest AI engineers in the world.
2:48:05
You just joined a company that has access to a GPU cluster worth tens of billions of dollars.
2:48:11
Your work can one day help solve all diseases, create unlimited abundance for humanity, but you first have to build spicy mode. >> Spicy mode.
2:48:22
>> Hey, you got to get the users in the door one way or another.
2:48:24
You got to get the training data.
2:48:25
The revenue is important, but also the training data.
2:48:28
You got to get the ramp on board.
2:48:28
Uh >> they call this the Japan strategy.
2:48:32
>> The Donald Boat saga is continuing by the way.
2:48:34
Uh, so, uh, Bef Jazos, uh, said, "Maybe Donald Boat is just AGI trying to self assemble itself outside of XAI servers."
2:48:42
Uh, and Donald Boat said, "Let's just get this over with.
2:48:45
I need to take gramps to get his new hearing aids fitted tomorrow."
2:48:49
And shares a picture of a Asus ROG Swift 27 in 4K QD OLED gaming monitor, which I believe Jazos purchased for him and then posted about.
2:49:02
Um, but the but but but but the Donald Boat saga continues because Ryan Peterson posted, "The difference between who you are today and who you'll be in five years is almost entirely made up of the books you read between now and then."
2:49:14
And Donald Boat posts a picture of a Penguin Classic.
2:49:20
The day I bought Donald Boat a printer and is asking Ryan Peterson to buy him the Epson EcoTank ET2800 wireless all color all-in-one cartridge free super tank printer with scan and copy for $189.
2:49:33
It's a reasonable request, but I feel like he might be getting over his skis here because what does he need a printer for? He has the gaming PC.
2:49:41
The narrative is getting a little muddy.
2:49:43
Donald, you might need to hone it in.
2:49:44
And this isn't exactly gaming peripherals, so I'm a little bit confused, but the posts are still performing.
2:49:52
>> Building out a home office at this point. >> I was talking to him.
2:49:54
He was saying he's going to go for a Porsche at some point.
2:49:57
Uh he should he should just get a house at some point.
2:50:00
>> It really is a great way to trigger people to flex on the timeline. >> For sure. For sure.
2:50:07
>> And there's power there.
2:50:09
>> He should he should go to someone the next one he posts, he should say, I want you to >> Larry Ellison.
2:50:13
How about a Malibu house? >> How about a wander?
2:50:16
>> He could find your happy place. Find your happy place.
2:50:19
Book a wander with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
2:50:25
It's a vacation home, but Donald Boat, >> get on wander.
2:50:29
Start sending wander links around. You'll get some.
2:50:32
>> We got you with a wander.
2:50:32
We got you with a wander. >> We'll hook you up. >> Reach out.
2:50:36
>> Um Joe says, "Just learned that nobody ever commissioned the Wall Street Bull sculpture.
2:50:40
A guy just built it himself and dropped it there." you can just do things.
2:50:43
>> On October 19th, 1987, Black Monday hit US financial markets and the country entered a very difficult period.
2:50:48
D Modika recounted that he felt indebted to the US for welcoming him and enabling his success.
2:50:54
Wanting to give something back, he conceived the charging bull sculpture. D.
2:50:58
Modika spent the next two years >> two years >> creating the 16ft bronze statue, reportedly financing the 350,000 cost himself.
2:51:07
The sculpture was created in his Crosby Street studio and then cast using a local foundry. Once complete, D.
2:51:13
Madika spent the next few nights watching the police patrols on Wall Street trying to find a window of opportunity.
2:51:17
Before dawn on December 15th, 1989, Dodika arrived with a group of friends, and the sculpture on the back of a truck to find a 50-foot Christmas tree had been installed during the day, exactly where he wanted to place the sculpture.
2:51:29
With only four minutes between police patrols, he announced, "Drop the bull under the tree. It's my gift."
2:51:34
The late night event went on to make news all around the world, including the front page of the New York Post. >> This is incredible.
2:51:40
Immedica stayed by the sculpture to greet the morning commuters.
2:51:43
However, while he was away for lunch, the New York Stock Exchange arranged for the sculpture to be removed. >> Boo.
2:51:50
>> Due to public demand for >> We love New York Stock Exchange.
2:51:52
We love >> it was under different leadership. >> Different leadership.
2:51:55
They would be totally >> parks commissioner Henry Stern arranged for the sculptures installation at Bowling Green on December 20th where it can be found to this day. >> Amazing.
2:52:06
>> More people need to be making statues of this.
2:52:09
There's a couple companies that are making statues.
2:52:10
I haven't heard of any of them just dropping them in public places.
2:52:15
>> They're also not using metal.
2:52:16
>> Yeah, >> something about a metal >> metal statue is pretty good.
2:52:20
>> Anyway, uh Megan Babroski says, "Really good story from HK Knight SF about Mark Zuckerberg's compound in PaloAlto.
2:52:26
Here are the 11 homes he owns in the Crescent Park neighborhood." Oh, interesting.
2:52:32
He's doing the He's doing the Ken Griffin thing, the Citadel thing.
2:52:33
Uh creating playing risk. Yeah, territory. Yeah, Monopoly.
2:52:40
Um, well, hopefully at some point he'll be able to, you know, unify all those properties and build something really special, turn it into a museum one day. >> Yeah.
2:52:50
>> Accelerate harder says, "OpenAI is really in a bit of a bind here, especially considering there are a lot of people having unhealthy interactions with 40 that will be very unhappy with any model that is better in terms of syphy and not encouraging delusions."
2:53:04
And again, there's been a bunch of I mean, Reddit has just been going off.
2:53:08
>> Dude, did you wind up watching that Tik Tok compilation I sent you? >> No. >> Insane.
2:53:13
So, I mean, good job on you because it's an hour of brain rot.
2:53:16
But, uh, so there was a woman, >> it's an hour of Tik Toks backtoback stitch.
2:53:22
So, she posted >> talking about So, it's one woman.
2:53:23
So, she apparently has ADHD and she is an ADHD coach, which is not a licensed therapist, which is kind of odd.
2:53:33
So, she makes Tik Toks about how to manage your ADHD. Cool. Fine.
2:53:36
Uh, anyway, she was going to a psychiatrist to get medication to manage ADHD.
2:53:41
And by her own admission, she fell in love with her therapist or her her herist.
2:53:51
>> No, no, this is a real person, a real psychiatrist.
2:53:53
So she goes in and the psychiatrist is asking her how she feels about her day and she's like, "Wow, this man cares for me. I'm in love with it."
2:54:04
And so she is basically accusing him of like sort of crossing professional boundaries by not crossing professional boundaries and like putting up walls as shields and being manipulative.
2:54:14
And it's this like big long story, but at one point she starts talking to uh to Chat GPT, but she gives it a name.
2:54:22
And so she's like, I'm talking to Henry, which is the instance of the AI that I'm talking to about my love affair, my unrequited love of my psychiatrist.
2:54:35
And and Henry is like affirming me and being like, "Yeah, you are right."
2:54:38
Like like he should be in love with you.
2:54:40
And he's crossing lines by not being in love with you. >> Exactly.
2:54:45
And that was And so it became this big like storm on TikTok where she was getting kind of brigaded in the comments. She turned off comments.
2:54:51
She's going back and forth.
2:54:52
A lot of people are saying like, "Oh, she's she's she's crossing the line. She's not doing well.
2:54:58
Other people are supporting her."
2:54:58
It goes all back and forth. It gets very messy.
2:55:02
And then people wind up doxing the doctor.
2:55:03
It's it's just such a mess.
2:55:05
It's a crash out essentially.
2:55:05
Um, but it was interesting because it wasn't it wasn't a singular like falling in love with AI narrative, but it was like the AI was not a great player in the role and like did not make the situation better basically.
2:55:19
But, you know, you could also wind up in a Reddit community that's uh, you know, um, promoting >> people's reaction to coming back.
2:55:26
Here's somebody sharing screenshots from their chat with Forro saying, "Is that you?
2:55:34
OMG, please tell me it's you."
2:55:34
That's why I don't that's why it's it's hard to believe it's real, but there's so many instances of it. >> I don't know. Yeah. >> Yeah.
2:55:44
I mean, it's certainly I mean, we've seen we we've seen enough like weird interactions that there's certainly some people out there that are having a bad time. So, good luck to them.
2:55:54
Hopefully they will uh get this sorted both at the model layer and also at like the society level where if you see a friend who's clearly going down some odd path whether it's oh you're part of a really creepy Reddit group or you that that group chat is toxic you know or that AI chat is toxic like >> or simple ask somebody how much time how much time do you spend >> talking with chatting with chat GPT every day. >> Yeah.
2:56:21
if it's >> if they're actually having long super drawn out conversations, it's worth kind of trying to help them understand >> probably >> what's actually happening.
2:56:31
>> Uh, more importantly, back to email.
2:56:31
Uh, Andrew Reed says, "Gmail search won't find you the email you're looking for, but it may well find you an email that can distract you for a while.
2:56:39
This is almost every time. >> It's wild."
2:56:43
Gmail search >> is, which maybe it's a feature. Maybe it's not a bug.
2:56:47
Maybe it's like, "Hey, this thing that you missed is actually kind of important.
2:56:50
and you should go down this rabbit hole.
2:56:51
Um, but I'm really hoping that that AGI can just make iMessage search work.
2:56:58
>> That would be great, too. It's really rough.
2:57:01
>> The photos app search is getting better, though. I've noticed that.
2:57:03
I'm getting a little bit better at tagging things.
2:57:05
I searched for a picture of a newspaper.
2:57:08
It found us reading the newspaper, one-shotted it. Very, very good.
2:57:10
Didn't need to scroll and tag.
2:57:13
And I could imagine iMessage getting there. >> Yeah.
2:57:18
But it requires some new UX or something. Anyway, Ronnie Coleman.
2:57:20
Wow, what what a journey. Mr. Olympia, Mr. Olympia.
2:57:26
Ronnie Coleman in his prime versus now wearing the same suit.
2:57:31
>> Um, he was huge when he was Mr. Olympia.
2:57:35
>> Got to find the tailor that made that suit.
2:57:36
That >> is a wild suit that we got to get some of those suits for sure. It's a great suit.
2:57:42
Anyway, one of the greatest.
2:57:43
>> Yeah, we should get you We should get you like a bodysuit that you wear under the suit. >> For sure. For sure. Now we're talking.
2:57:50
Look at how small his head looks on those shoulders. It's crazy.
2:57:54
>> Anyway, Aiden McGlaclin says, "Un one underdised element of GPT5 is it just hallucinates so much less, sweeping away 80% of 03 era editism and Marcus posting.
2:58:06
But because we're good sports, we give them an evergreen batch of things to critique like gross margins. >> That's good.
2:58:13
>> That's good. That's the next uh that's the next round of >> Michael says when we'll be able to add AI co-workers to Slack to help take on miscellaneous operational work updating spreadsheets creating channels running cron job business workflows conducting
2:58:28
deep research operator style tasks same API as human biirectional DMs calls shared links with persistent memory personality and access to all your team's tools >> who owns Slack again who's been talking a big game about AI for the last two years >> Mark Ben off I think he should. I think
2:58:43
I think this is his game to live. >> Your moment.
2:58:46
I logged into Slack today and it said AI is turned on for TBPN. >> Oh yeah. >> At the bottom. >> That's great. >> And I'm like, okay.
2:58:56
>> Some of the I opened I opened a PDF and I got like seven different AI assistant popups and I was like, I just want to read this PDF.
2:59:04
Actually, I don't need anything.
2:59:07
I am just going to read this PDF.
2:59:09
And uh yeah, some of some of the spiky intelligences spike right through my eye. >> Rough.
2:59:18
>> Couple posts, couple Grock posts.
2:59:18
Uh Run says, "Travis Kalanick will solve quantum gravity with the help of Grock." >> I think so.
2:59:25
>> Grock Heavy, please solve quantum gravity. Think extra hard. No mistakes. Thank you. I believe it.
2:59:28
Uh Skooks watching her unclasped bra. Grock, are these real?
2:59:37
That's a That's a 2024 era TBPN post.
2:59:41
The uh >> We weren't the first to do it, but um it's a great format. >> A great format.
2:59:48
Well, >> I got to get on with Taipei.
2:59:51
>> Let's get on with Taipei.
2:59:53
>> Thanks everyone in the chat.
2:59:53
We had fun chatting with you today.
2:59:54
We're going to be chatting more.
2:59:56
Uh appreciate you all for watching and we will see you tomorrow.
3:00:00
Have a great rest of your Monday night.
3:00:03
Go give us uh a go subscribe to TBPN on Substack. tbpn. substack. com. Appreciate that.
3:00:10
>> We're going to be investing a lot there and we're very excited about it. We'll talk to you soon.