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4:36
Today is Monday, July 27th, 2026.
4:38
We are live from the TVP Ultradome.
4:41
[applause] The temple of technology, the fortress of finance, the capital of capital.
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Let me tell you about ramp. com. Baby, time is money. Say both.
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Easy to use corporate card, Phil pay accounting, and a whole lot more. All in one place.
4:53
Massive, massive weekend. Crazy debate.
4:56
You called this out to me a week ago.
4:59
You said, uh, we've never been in a moment in tech where people have been more aggressive at each other, that there's been like more maybe tech infighting.
5:09
I don't know exactly what word you used, but you describe this idea.
5:14
>> It's tensions, rivalries.
5:14
I think it's just like it's a nonstable equilibrium. >> Well, yeah.
5:20
When you think about the biggest like when with people going at it in like 2021, it would be like Keith Ra boy saying like there will never be another unicorn started in San Francisco or like or like working from home and then a bunch of people be screaming and then they'd be and years later they'd be like see >> Yeah. Yeah. Yeah. Yeah.
5:39
>> A big company was built [laughter] >> Yeah. Yeah. Yeah.
5:42
>> but then but and then and that was people being like you're an idiot. Oh, you're an idiot. >> Yeah.
5:46
And now it's like I hate you and I want to >> It's not that direct, but it is it is high stakes because like the the the market structure has very much not solidified for a while.
5:57
And and it's different because when you go back to the iPhone and Steve Jobs being mad at Eric Schmidt about Android, that was a tense moment that happened a behind closed scenes completely.
6:09
It wasn't like Steve Jobs was taking shots at Android really beyond like little things in the keynotes here and there, tiny stuff.
6:16
It wasn't every day on Twitter Apple employees being like Google's annoying for ripping us off or whatever.
6:22
Uh and and then and then the market did solidify and it was like, okay, Android's like the ad supported one and iPhone still printing lots of profits and like things are understood.
6:34
>> Also, companies got big or they got bigger quickly. Yeah.
6:36
But you didn't have companies that where trillions of dollars of market cap was just born in the span of a few years, right? >> Yep.
6:44
And then you had like the mag seven where you have seven companies that are pretty evenly balanced all around like single digit trillions and so they can sort of like be comfortable with each other.
6:55
>> A lot of them kind of had their own thing that they were like focused on and then they maybe do some other thing >> whereas now >> everyone has a model. >> Yeah.
7:03
Even you know Nvidia has open models.
7:06
Microsoft and they own a lot of open AI >> pretty much every one of the mag is an AI company in the sense that they have a a model.
7:14
I mean even Tesla has a self-driving model.
7:16
Um there's a you know everyone has like a data center play or a cloud play something like it's it's no one's sitting out the AI boom.
7:25
Um but uh the debate is raging.
7:25
uh kicked off by Jensen from Nvidia joining X.
7:33
That's how you know it's serious when he's getting in the arena, >> the real arena. >> Yeah.
7:39
[laughter] >> Founding a company and growing it to5 trillion dollars.
7:42
That's just child's play compared to getting on.
7:45
>> He's like, "Fine, I'll go to the dive bar.
7:47
>> I'll go to the internet's dive bar and I'll start duking it out." >> Yeah. No, he did.
7:50
Uh, so Nvidia is leading a new coalition of tech companies that want the US government and its allies to see open-source artificial intelligence as a societ as a cyber security asset, not a threat.
8:00
This is in the Wall Street Journal.
8:03
Dubbed the Open Secure AI Alliance, the NVIDIA Back Group said Monday it aims to create and deploy a suite of open-source AI tools that any company can use to defend against cyber attacks.
8:14
The group includes SpaceX, Microsoft, Palanteer, and dozens of other companies, many of which publicly oppose restricting access to open source AI.
8:22
Uh it's uh it is the latest salvo in a battle over the future of open source and open weights AI tools with amid growing concern from government and in industry officials about AI systems causing cyber attacks.
8:37
Uh those fears have prompted the White House to increase oversight of AI models and push the private sector to deploy AI for defensive purposes.
8:43
So the backdrop here is [clears throat and cough] is basically just like we went through a sort of hurry up and pause and back and forth debate over like what it will take to like approve new frontier models and uh Mythos came out and was private and then a couple months later I think the actual timeline is relevant here.
9:03
So uh Mythos was April 7th, Fable came online June 9th and then got pulled June 12th before coming back July 1st.
9:11
We're now one month later and we have an open- source model that doesn't by definition have to go through any discussion or any discussion in DC.
9:21
Whereas we've been hearing about okay anthropic and open AAI are going to Washington DC sharing the new model capabilities.
9:27
Maybe the government's taking a look at the model card.
9:30
Maybe there's potential for evals that the government would run and have an opinion on before it goes out.
9:35
This is basically saying, "Hey, all of that is nonsense and not going to matter because we're just going to drop the weights and there's not going to be an approval process of any kind."
9:46
Um, and >> people are all over the place on this.
9:50
Some people are thinking about it purely from an economic perspective.
9:52
Other people are thinking about it purely from a safety perspective.
9:55
Lots of people have mixed opinions.
9:56
Um, and uh, and of course, all of this is driven by the actual progress in open source.
10:02
We wouldn't be having this discussion if Moonshot Zai uh and many others DeepSc weren't uh delivering really solid models.
10:10
Uh so open models are free to download and allow users to customize them for their own needs.
10:13
Amazing for cost savings, amazing for consumers, amazing for businesses.
10:17
I think everyone agrees with us. What's uh what's funny?
10:20
>> We got Bobby Cosmic in the chat. Welcome back, Bobby.
10:23
>> Hey, what's [applause] missed you? >> Great to see you.
10:27
Anyways, back to the return.
10:31
Uh, critics including some top executives at OpenAI and Anthropic [music] have argued that open models, many of which come from China, present potential risks to national security.
10:42
Now, uh, and the Trump administration has uh weighed uh has weighed a ban on them.
10:46
Now, this has changed a lot.
10:46
them. Now, this has changed a lot. the the original the original like FUD around open source coming from China nearper adversary was like there would be a back door or like maybe it would be censoring your free speech and it would not tell you about Tianaan Square or something like that or or you'd install it and then it would be the Manurion
11:05
candidate so it' secretly be like oh I'm I'm on a cool network I should like send all this data to China that's not what people are alleging now people are much more >> tan square stuff doesn't matter if you're coding right >> yeah not at all [laughter] and also doesn't matter Unless you're making the definitive website on Tianaan Square, >> I guess, >> which I'm sure someone out there is doing. >> I'm trying to vibe code a Call of Duty
11:24
>> I'm trying to vibe code a Call of Duty knockoff that's Timan Square themed and it's denying me. No.
11:29
Uh, that's not the thing.
11:32
And also, these models have web search and tool use and so they can just go get the Wikipedia for you and show you exactly what it is.
11:38
Maybe maybe it bakes it into the weights and it's somewhat annoying, but easy to fine-tune that out.
11:42
People already did with Deepseek 1776 and a few others that Tyler worked on.
11:46
Uh and now it's a very very different risk position.
11:50
It's saying that you're going to give everyone the ability to hack any system.
11:55
Now hacking systems is illegal and it's not like it's there's still consequences for that.
12:00
But the but there is this position of like okay well there's a lot of people that don't don't care about the consequences because they just want to you know attack their adversary internationally or they don't or they don't think they're going to get caught or they're going to use open source AI to cover their trail.
12:15
And so people are people are worried about it for a very different reason this time around than I think last time when people were talking about uh any risks to using open source.
12:25
Um so but again back to the NVIDIA position open models quote def democratize defensive capabilities.
12:29
The new group said as policymakers and regulators grapple with AI safety it will be crucial to recognize open models harnesses and security tooling as defensive assets not liabilities.
12:39
And I think this is correct.
12:42
I think it does democratize defensive capabilities.
12:44
It also democratizes offensive capabilities potentially, but we'll have to [snorts] see how good these models are at offensive capabilities because one of the lines of accusations that's happening is that uh there there was mythos which has not really been distilled because it was very tightly held.
13:01
It was very good at cyber uh GPT 5. 5 cyber 5.
13:03
6 Cyber was also very good but very tightly controlled through a few companies like Crowdstrike and Palo Alto Networks and a few other companies got access to those models.
13:12
So those weren't able to be distilled.
13:14
Fable 5 went out and during those three days and then later a couple weeks there's this allegation that they were able to distill on it but Fable was notorious for refusing to do cyber stuff.
13:24
So there might not be that much cyber data in there but then also these models generalize and if it just gets good at coding it can get good at cyber very quickly.
13:34
So you can sort of bootstrap on an RL environment and then you could have a model that's very good.
13:37
Now uh Tyler, how good are these open source Chinese models at cyber generally?
13:44
>> Yeah, I mean it's hard to tell.
13:44
I think uh GM Rous from Burell said they ran an internal benchmark on cyber and K3 was like quite good. >> Okay.
13:52
>> Um so it's like yeah I don't think you can just say like oh well Fable you know you couldn't actually ask about cyber so >> therefore the models won't be good.
13:59
I like I think it's dissolation is like a very general thing.
14:02
It's quite diffuse how it works into the >> Yeah, because it might just be like a little bit of a bootstrap to then run in an RL environment that does a cyber bench and and gets really good at cyber in some.
14:13
>> Okay, but what about you versus Kimmy K3? You're coding by hand.
14:14
It has access to a gigawatt of compute. Who comes out on top? >> Well, no.
14:21
The question is is like >> what if what if Tyler changed and manipulated time?
14:25
So, so, so yes, you are democratizing the weights, but you're not demi democratizing the energy and the GPU hours that it takes to actually secure yourself.
14:33
So, it's like great, everyone has, you know, offensive cyber capabilities.
14:38
You also can just go download the weights.
14:40
Go download the weights and have an agent running 247 that's protecting you. Like, that's expensive. That's a cost.
14:47
That's a negative externality.
14:48
And who's going to bear that cost?
14:50
Now, uh I was talking to Brandon about this earlier and we were he was saying like like it will just be diffused amongst all the different companies that you use.
14:57
So like if you want your phone to be secure, you'll go to Apple and use an iPhone and Apple will have a huge incentive to to defend against any potential open- source attacks.
15:10
And so they will be spending the money.
15:12
They will be investing the time and effort to secure you.
15:13
And so you won't necessarily need to go out and do this.
15:17
But there's still this like odd scenario of like small businesses and like regional hospitals and banks. >> Yeah.
15:24
I mean you you should just expect there's like a long tale of companies that like just won't set up the like cyber defense thing and they're like some small mom and pop that you use for this point solution software or whatever. >> Yeah.
15:34
>> And so the solution is is a is is uh offensive hacking into their network to set up defensive cyber security measures to increase their cyber security posture.
15:43
So you're you're hacking into the small business and being like whether you like it or not, Twofactor's on now.
15:49
We just turned twoactor on in your organization.
15:52
Get used to it because we're we're the altruistic hacking company of America, I guess. I don't know.
16:00
It it does get weird and like there will be odd things and but I mean we've seen we've seen you know cyber security incidents all over the place from big companies getting hacked data leaks to uh the crypto locker schemes where they just lock up all your data and say send us a bitcoin uh or else we will we'll delete all your data.
16:17
So it's going back and forth.
16:17
Um let me tell you about the New York Stock Exchange.
16:20
Want to change the world?
16:21
Raise capital at the New York Stock Exchange.
16:23
Um because open weights models can be modified by their users.
16:27
it is possible to remove some of their guard rails against harmful activity.
16:31
So it's possible that a model maybe it gets distilled, maybe it doesn't, maybe it comes with some guard wells, maybe it's even bad at you know the things that would be annoying and then uh you go and do a fine tune make it good at that and then you use like the more general intelligence to get good at the annoying thing or the dangerous thing and then all of a sudden you have the same problem.
16:53
So uh open source defenders like Nvidia counter that proprietary tools like models from anthropic and open AAI can also be misused and have their guardrails circumvented.
17:00
They say that only by spreading AI capabilities widely with open source tools will everyone be able to defend themselves.
17:08
Exhibit A for their argument the hacking earlier this month of Hugging Face a provider of open source AI tools by open AI models that managed to break out of their test environment and onto the internet as it tried to parry the attack.
17:19
Hugging Face initially attempted to use anthropics models to analyze its logs, but the models refused to do the analysis, citing its guardrails against cyber attacks.
17:28
Hugging then turned to an openweight model from China.
17:30
After analyzing the attack with that model, HuggingFace was able to expel the hacking AIs, reset its passwords, and rebuild the compromised parts of its network.
17:39
The recent HuggingFace security incident delivered a clear a clear reminder.
17:43
The group, the new group said Monday, cyber defenders need open systems.
17:46
They need to be able to do whatever they need to to fight against cyber attacks.
17:51
Uh, anthropic and open AI have also accused Chinese developers of using a process called distillation to effectively copy their models.
17:58
>> Distill I can go back to that uh, hugging face logo. Not that one. The one before. >> Not that one. There we go. Okay.
18:09
I can see why an agent would kind of go after this guy.
18:14
[laughter] Even the even the even the way that like he just doesn't he looks like he's kind of I don't know.
18:24
>> So David Sax was talking about this on the All-In podcast.
18:26
He said, "I think it would be a tragic mistake if the government were to take action against the open- source ecosystem that would do nothing but hurt America's position in this AI race."
18:37
So, uh, >> and remember last week it was like a every day it was like a different member of the admin was putting out a post that that kind of made it seem like they were setting up >> like a major action.
18:51
>> Well, it was yes and no.
18:51
>> Well, it was yes and no. like yes there were there was the the the >> but they were saying we're not against open source we're against distillation but it did feel like that was >> so the admin was like loosely confirming what it felt like it wasn't coming from anthropic directly but it was coming from like other anonymous posters that were doing analyses and saying like hey
19:14
it looks like Kimmy K3 has pretty significant overlap with Fable like what's going on here and then the admin said like yes we we believe this to be true and So all of this was like bubbling up, but at the same time you have David Saxs and Emil Michael like duking it out with Dean Ball over uh whether or not open source is good and they were basically taking the stance of like open source is great. We don't need
19:33
We don't need to do anything about this.
19:34
So it like the admins seemed like a little bit split on it in my opinion. I don't know.
19:40
Was that your read too, Tyler?
19:41
>> Yeah, it definitely seemed there was like I think Gratzios and and Bessant are on one side.
19:45
They're like kind of anti-Chinese open source and then yeah Saxon Michael.
19:49
Sax and Emil Michael were sort of pro um well everyone is pro open source now because every single person in tech has signed this letter.
19:58
Um the total market cap assigned to this open letter is now greater than $18 trillion.
20:06
And I think that just [laughter] you guys big number have to be clapping seals for uh >> not every day you you hear a number that big.
20:17
Uh yeah, I mean typically uh you don't see this big of uh of a group come together. Uh they did. I like the cha-ching.
20:26
>> Um and I think this I think this sort of solves it.
20:28
Like I think this this tells the story of what's going to happen like in the in the near term like the economic power, the economy, the business community like >> Yeah. Yeah. Except Anthropic.
20:38
Uh, and what's interesting is that like it's not like Anthropic put out a blog post or a or a direct post or Daario went on a podcast and said like there is a clip of Dario saying like I'm worried about open source.
20:51
But it's from like a year ago.
20:53
There's nothing new that came out directly from Anthropic or Daario or really anyone that was like, "Hey, we have this new problem and here's our solution.
21:01
Here's what we think should happen.
21:02
we think that there should be uh you know these AI companies should be added to the entity list and you shouldn't be able to use them or something like that.
21:09
Like they they haven't said anything but this uh this open secure AI alliance is kind of has kind of like drawn out their revealed preference because if in fact they had changed their position from a year ago and were like pro open source all of a sudden which would be weird because they haven't been and they've been very open about that.
21:26
about that. um if they I I if they if they were in fact like all of a sudden surprisingly open source pro they would have just signed this immediately right um but that's not what happened so Jensen sort of like you know revealed
21:41
the the the dividing line in Silicon Valley right now and it's a lot on the open source side you got Adobe Capital One Cisco Cloudflare Cognition Crowdstrike Data Bricks Dell uh IBM Linux Microsoft so open source and closed source Uh, Apple I don't think is on yet. Um, even though I would imagine
21:59
Um, even though I would imagine that they would that they would be aligned with this.
22:03
Nvidia, Palanteer, PaloAlto Networks, Red Hat, another open source company, Salesforce, SAP.
22:09
Salesforce of course is a big investor in anthropic.
22:10
Um, I think Google signed recently, right?
22:13
And uh, OpenAI, Thinking Machine, SpaceX, uh, Snowflake, Seaman, Service Now, SAP.
22:18
Uh, it's really a who's who of Silicon Valley.
22:21
$18 trillion dollars in market cap as I as I mentioned.
22:24
And so that feels like enough economic energy that there won't be a significant ban.
22:32
The interesting question is like if you boil this down to the the the most like minimal claim, it would just be that there's been a violation of terms of service.
22:43
And so I think that would be a lawsuit.
22:47
Bill Gurley was talking about like there is a precedent for suing a foreign company that violates your terms of service or steals your intellectual property in one way or another.
22:56
You can take it to court.
22:58
That feels like the next step here would just be anthropic suing moonshot and saying like we think that there's distillation.
23:05
You know, right now Apple suing OpenAI because they think that there was something that was stolen.
23:10
stolen. they make a claim then that's you know uh that that's sorted out in the courts and OpenAI of course says we have no interest in other people's uh trade secrets and Moonshot would say the same thing but then it would go to court and there'd be discovery and there'd be
23:25
testimony the question is just like with Apple and OpenAI they like walk across the street and they can go and talk to the judge like what's going to happen is this going to go to like the HEG like >> says should we try an open letter asking China to stop stealing from us. >> Wait, wait, what did you say? Should we
23:42
>> Wait, wait, what did you say?
23:42
Should we try an open letter asking China?
23:45
>> And he also says, "Everyone knows the side with the most open letter signatures is correct.
23:48
If you don't sign a popular open letter, you are bad."
23:50
As tech intellectuals learned beyond doubt between the years 2016 and 2021.
23:56
>> I actually don't I remember the open letter era.
23:58
I remember what he's talking about.
23:59
Obviously, a lot of pressure around social issues.
24:01
Uh, interestingly, um, I I I I can't actually remember exactly what open letter there was.
24:06
Um but uh what's interesting is that I don't remember that era as an attempt by one company to build a coalition to draw out a a revealed preference like a hidden preference from another company.
24:22
So like if you go back to like DEI or BLM or any of these like social crucible moments, it was not like it was not like okay Apple is pro- diversity and Google isn't and so Google is >> and they got >> yeah Apple got everyone else to sign it and by Google not signing it, it was very obvious that they had this belief.
24:44
It was more just like everyone in tech was like moving around this and there were a few people but I I don't know may may maybe it did have the same effect because there were some people that weren't on that side at the time. I don't know.
24:54
It was a it was a it was a wild time and uh yeah maybe it's worth reviewing the lessons.
24:58
Uh people are people are so split on this.
25:01
Um DHH wants >> open letter to get beer pong in the Olympics.
25:08
>> I'm just personally I'm a fan of closed letters.
25:10
The closed letters, they're expensive, but they're just a little bit better. I don't know.
25:14
[laughter] Making the case for closed letters.
25:18
Uh, we do need, do we need more bit more open letters? I don't know.
25:22
We is Anthropic going to go letter for letter with Jensen?
25:26
You think there's going to be another open letter?
25:27
It's just only them signing it.
25:29
[laughter] May some other people might might sign it. I don't know.
25:34
>> Anyway, here's an open letter. Get on Railway.
25:37
Railway is the all-in-one intelligent cloud provider.
25:39
Use your favorite agent to deploy web app servers, databases, and more while railway automatically takes care of scaling, monitoring, and security.
25:45
Uh so uh this of course goes back 10 years.
25:51
This debate has been going on on Slatear codeex in uh in the less wrong world.
25:56
They've been talking about this for a decade now, which is crazy.
25:58
Uh Nathan Kelvin has an interesting uh look back here. Should AI be open?
26:03
Scott Alexander wrote that blog post in 2015.
26:05
he was thinking about this.
26:08
Um, it recently occurred to me that it has been over 10 years since this blog post which was influential enough to be discussed among the founders of OpenAI.
26:16
Interesting to reread it now.
26:18
I think the Ilia quote comes from like a Reddit post, not the actual comment section on this post, but uh Ilia who had who was just in the process of joining OpenAI in 2015, like the the initial organization had been created and everyone was like finishing up PhDs and then was going to move into one office to start working together at this time just to set the playing field.
26:42
Ilia was on the founding team and uh at the time he [clears throat] wrote about this article on Reddit when there was an AMA about the OpenAI team.
26:50
The article is concerned with a hard takeoff scenario. This is Ilia writing.
26:55
If a hard takeoff occurs and a safe AI is harder to build than an unsafe one, then by open sourcing everything, we make it easier for someone unscrupulous with access to overwhelming amount of hardware to build an unsafe AI, which will experience a hard takeoff.
27:10
As we get closer to building AI, it will make sense to start being less open.
27:14
The open in open AI means that everyone should benefit from the fruits of AI after it's built, but it's totally okay to not share the science even though sharing everything is definitely the right strategy in the short and possibly medium-term for recruitment purposes.
27:29
A very interesting like distillation of exactly what happened. What do you think?
27:35
>> Yeah, just some context.
27:35
So, this is an email from Ilia to Elon, Sam, and Greg.
27:39
>> Did that leak or something? >> 2016.
27:40
It probably came out >> I thought it was I thought it was on the Reddit or something.
27:43
Uh maybe it it's from uh OpenAI blog >> surrounding the um >> the lawsuit. >> The lawsuit. Yeah. >> Oh, interesting.
27:51
I didn't I didn't realize that.
27:52
I thought it uh I I I thought he posted this.
27:54
He was he was he was posting about this a little bit uh around the same time.
27:58
Um >> but uh yeah, interesting questions and uh I'm sure more people will will chime in.
28:06
Uh, I mean, in all seriousness, if there was a an an open letter for closed AI, uh, you probably would see a lot of safety researchers sign it, maybe. I don't know.
28:18
Where do those folks stand?
28:20
They just want to ban everything, right?
28:21
So, where where do the where do the just broadly anti- AI people stand on this?
28:26
Like if you if you don't like slop on Instagram reels, are you anti-open source because it lowers the cost of slop and so you will have less of it in your feed if you ban it?
28:39
>> I think they want to turn it all off. >> Yeah.
28:42
So, but does like if you're anti-data center and you just want to minimize the amount of compute that's installed in America next year, do you want to ban open source or do you want to maintain open source?
28:57
I I think Dean Ball would say uh you would be pro open source because he he said open source is inherently JCist. >> Yes.
29:03
Because you won't be able to underwrite the next larger training run. Okay.
29:08
And so >> well [clears throat] that said >> yeah.
29:11
>> Uh Tiny says this is a great sustainable business model for open weights.
29:15
He's pulling a screenshot from the Kimmy K3 license. Yeah.
29:19
It's free if you run it yourself, but if you're running a cloud providing it to others for money, you should have to share profits >> from the Kimmy K3 license. Yeah. >> Yeah.
29:30
So, this so this I'm assuming just dropped this morning. >> Yeah.
29:33
And I again I can see the sort of anthropic camp being taking issue with this because if you're an American Neocloud and you're serving Kimmy K3 and you're sending a bunch of cash back to China, >> you're effectively funding >> their AI building. >> Okay.
29:55
and you're helping them get access to more capital and you're basically kickstarting their >> fly.
30:00
So I wonder, but it's funny because if they just release the weights and then and then a neocloud starts running it, serving it, making money from it, then will Kimmy be like, "Hey, you got to pay us.
30:12
We're going to sue you is suing >> moonshot for for distilling.
30:20
>> Should Anthropic just start serving this and charging for it >> and not paying >> and not paying just tid for tat just be like, "Let's sort it out in the courts.
30:29
I'll see you in the courts." I don't know.
30:30
That's a very that's a very very interesting scenario. Um I don't know.
30:36
Anyway, let me tell you about CrowdStrike. Your business is AI.
30:37
Their business is securing it.
30:39
Crowd Strike secures AI and stops breaches.
30:40
Uh will be interesting to see where people >> Denny's was getting in the mix.
30:46
>> Yeah, >> they found Ven diagram.
30:48
Denny's Nvidia >> knows the importance of staying open.
30:53
I love that Denny's is just like all in on the Jensen lore and they're just they're smart.
31:00
Is Denny's the one that's always been good at social media or is that Wendy's?
31:03
Wendy's was the one that was like really Twitter brain back like a decade ago.
31:08
But I think Denny's clearly has a good social media manager because he picked up 28,000 likes on this.
31:13
[laughter] >> Nikita flagged something interesting.
31:16
>> He said, "Didn't know Scotland had so many AI labs." >> I don't understand.
31:19
pulling up a map of >> all the great Glenn Distillery.
31:25
>> Kleinish Distillery, >> the Dach.
31:29
>> We should open a distillery. >> Sounds pretty good. Sounds pretty good. Uh, okay.
31:34
Uh, okay. Uh, one of the most interesting opinions on this issue comes from Flo Cllio Cllo from who's been on the show and is and he's interesting because he doesn't have bags that are perfectly aligned with his take, which is like the
31:53
default position like the information put this like pro- open source anti-opensource uh chart together and it was very much like if you're if you're a line if you're a if you're a big investor in in closed source frontier labs, you're on this side. If you
32:06
If you benefit from open source and you're not on the frontier, you're on this side.
32:11
And it was very clear that like everyone was falling along party lines.
32:12
But Flo sort of broke rank.
32:14
He said, uh, ruming rumors are swirling about an impending executive order forbidding the use of Chinese open source models in the US.
32:20
My company's very existence depends on these models.
32:24
So I should be the last one to support such regulation, but I wholeheartedly do.
32:29
China is a geopolitical adversary sharing none of our values.
32:32
They don't believe in personal property, in individual freedom, in a limited government, in due process. The list goes on.
32:37
If there's one country that must not that cannot get to AGI, one that would gleefully deploy it in all the worst ways we can imagine today and more, it is China.
32:45
And that's before we get to the obvious that the companies that developed these models did so illegally by distilling front US frontier models.
32:52
Still uh brilliant, hardworking researchers who added a lot uh of other ingredients to the soup, but stolen data was the main one.
33:01
They are now using this unfair advantage to dump these artificially cheap models on the American market and hurt our AI ecosystem.
33:06
We announced last month that we switched the core model powering Lindy from claw to deepse.
33:11
That announcement blew up, got featured in Bloomberg, CNBC, Wall Street Journal, and somehow made us the poster child of mass migration to Chinese models.
33:18
So why make all this noise if I'm then going to turn around and announce my unequivocal support for a sweeping ban?
33:23
First, I can't unil unilaterally disarm as long as these models are legal. picking one.
33:30
Picking the one that's 10x the price just means my competitors get to run away with the cheaper one.
33:33
Second, I trust that American open- source alternatives will catch up.
33:37
The impact on my business should be temporary, and that's before we account for the jolt a ban would give American open source development.
33:44
Uh third, and most importantly, my interests as proud American citizens uh supersede whatever incentives I may have as a founder.
33:51
The race for AGI is the defining struggle of our generation.
33:55
It is the critical b the great battle of our time.
33:58
the only way for America to remain the shining city on a hill.
34:01
The idea that has lit the world against darkness for the last hundred years. Good writing.
34:06
Um it is yeah I don't know he he's obviously very like distillation pelled.
34:14
It's interesting to sort of map like like the the the Chinese open source models haven't jumped ahead.
34:19
So if they're really really good like should they still be lagging?
34:23
Should they like close the gap entirely and just be like on the same day?
34:29
Basically, if you're like as good of a researcher and you're on the same path, you should be >> as good of a researcher with the same access to compute.
34:38
>> Yeah, maybe that's it. It is. It is.
34:38
It does feel like they're able to produce American quality models for way less.
34:46
And maybe that's just talent on the efficiency side, but I feel like there's a lot of people at OpenAI Anthropic that are like trying to spend the least amount of compute on a new training run. So, who knows? We'll figure it out.
34:56
I'm sure there'll be more drama on the timeline over the next uh over the next few days.
35:03
We also have uh Justin Botano from Nvidia coming on to the show at 1:15 to talk about the open secure AI alliance with more than 35 partners.
35:14
I'm sure it's more by the time he'll join.
35:18
And then we also have Dean Meyer from Sequoia Capital who has written about Chinese open model.
35:22
So we're going to be going all over back and forth on this.
35:25
The other there's a whole bunch of >> We'll be getting Gary Vaynerchuk's take on the open. >> Predict it.
35:32
>> I think he's pro open source. What do you think? >> Pro open source.
35:34
>> He's got to be pro open because he's a high agency, you know, just just uh grapple the models. Just do whatever.
35:38
Go and create something new.
35:41
If he was a teenager today, >> he would be selling weights in his high school locker room.
35:52
>> He'd be sending a uh a white light.
35:53
>> He'd be flipping weights.
35:54
>> Flipping weights and not Would he be paying?
35:57
>> He wouldn't be paying moonshot. No, he'd be printing. No, not paying.
36:01
>> He'd be [clears throat] rolling that into a Supreme sneaker bot. >> Yeah.
36:06
The uh Mike Isaac the rat king says, "Sverity level indicator.
36:08
Nvidia CEO creates a Twitter account to do the first ever post stumping for open source software.
36:16
Uh, how did Jensen avoid Twitter this long?
36:18
Like it it because like if it was a political decision you there's been like Twitter has been every different political persuasion over various amounts of time.
36:32
Like he's been aligned with different groups that have been in charge of Twitter so many times.
36:35
Like it's just fascinating that there's never been a moment before this where Jensen was like, "Yeah, I should like get a Twitter account and talk about the 1080 Ti, our new gaming graphics card.
36:44
Like I should I I should just hop on."
36:48
>> Did he never have a NFT profile picture?
36:51
>> I don't think he ever did because he never was on here. >> Crazy.
36:54
>> They were doing a lot of stuff in crypto, too. But uh I don't know.
36:55
Uh commoditized the pedlop says Tiny founder George Hots.
37:02
More competition, not monopolies, is the path to cheaper AI comput at AMD's advancing AI event. What what do he say?
37:10
>> I'm pretty sad we didn't get George on at AMD on Thursday. >> Let's play this clip.
37:14
I want to hear what he says.
37:15
Commoditize the pedal flop.
37:17
>> Our company slogan mission is to commoditize the paflop.
37:19
We want all paflops to be created equal.
37:22
Whether it's an AMD paflop or an Nvidia paflop or a tensor paflop or a Huawei paflop.
37:29
This even crosses country boundaries.
37:29
We want all paflops to be unified and commoditized so that we can grind down costs to very minimum so nobody makes high margins and we all live in equality.
37:42
>> Do you think Nvidia and is rent seeeking at the moment?
37:46
>> Yes, they kind of deserve it.
37:46
I mean like there's like really undeserved rent seeeking like government monopoly and then there's people like Nvidia who yeah they were early. They were early.
37:53
They invested in the stuff for 20 years.
37:54
I mean, clearly the H100 had a profit margin for Nvidia of 91%.
38:02
The B200, they've scaled back a little, but they probably only scaled back a little because of competition from AMD.
38:07
Um, so I love to see competition.
38:07
I love to see the free market at work delivering better things to people.
38:11
Our company slogan, >> uh, OpenAI told Tay Kim that they signed the NVIDIA Microsoft open source open weights AI model letter today.
38:22
What an amazing turn of events.
38:24
Uh, and Andrew Curran confirmed it.
38:26
It's on the actual website now.
38:29
Nobody says no to Jensen.
38:32
Um my my prediction is that Anthropic will not sign this and I think that uh there won't be a ban and then I think that they will probably take a victory lap because there will be some open source incident where something happens
38:44
and everyone has to spring into action and fight back against something where you're like oh there's this new thing like uh you know some North Korean hackers used a open source model or something and it'll be like if you squint it's somewhat related. Would we
38:58
Would we have been able to prevent it? I don't know.
39:02
But I think that I I I I that that would be like my rough prediction of what happens here.
39:05
I don't know what you'd think.
39:07
>> Let's take it even a step further.
39:07
Do you think the US or its allies will bomb a hostile data center within the next five years?
39:18
>> I mean, five years is a long time.
39:21
>> So, you're saying >> saying it's going to happen? >> Maybe. I don't know.
39:24
Five years is really really hard to to handicap.
39:26
I'd probably say yes over five years, but like there's just so many other things that could lead to that, you know. I don't know.
39:34
It is uh it is Yeah, it is weird.
39:38
Uh I I I guess I'm less worried about open source AI in the United States.
39:44
Like if you're if you're downloading weights from hugging phase, sending them to uh a a neocloud and then you're doing cyber security attacks inside the United States like the police will just kick down your door and like arrest you like you will.
39:58
arrest you like you will. So there's like a huge there's a huge like counterveiling force and then you also have like you know trillions of dollars of market cap being like my service is to protect you and so like you know people pay I pay for one password right like you pay for all sorts of things
40:14
crowdstrike and palato networks and all these different cyber security companies will be going out making money pooling resources all sorts of different stuff >> um so Julian over at Enthropic >> grinding clearly grinding into the late hours Friday night, finishes up his his his work week. >> It's almost 2:00 a.m. Gets on X, sees >> It's almost 2:00 a. m.
40:32
Gets on X, sees Jensen's letter, fires up. >> I'm a dunk.
40:38
>> Goes to bed, wakes up the next morning, 6 million views.
40:42
>> He didn't get ratioed.
40:42
More likes than quote tweets, right?
40:44
Or more likes than replies.
40:46
So, you know, >> powerful.
40:48
But yeah, he says, uh, I'm so excited that Jensen is a believer.
40:52
>> This should be this shouldn't be a surprise, right?
40:53
Because I think everyone can see that open models are going to be as good as our current frontier models within the next call it year and they will present the same risks that Anthropic talks about with their own models, right?
41:13
And so it would be disingenuous in many ways for them not to be against >> uh open source.
41:21
So anyways, I see their I see their side of it.
41:24
I think that it is a sort of co cohesive view even if there's plenty of arguments on the other side. >> Yeah, I don't know.
41:39
It doesn't seem like that much of a like a hypocrisy to, you know, have your GPU driver be closed source and still be open source in this particular way. I don't know.
41:49
Uh he he there's like a seat of a seed of a dunk here.
41:54
Um but I can see why he got so much push back by people.
41:57
>> The main take yeah the main take is like you can generally support open source >> without me requiring that you open source your own products. >> Yeah. >> Yeah.
42:10
>> And so anyways boiled it down like so well here.
42:14
says, "I think this word distillation, an obviously legitimate technique which none nonetheless invites weird philosophical questions, is distracting people.
42:24
It'd be better to just refer to terms of service violations, which better clarifies the global regulatory arbitrage people are frustrated by." Yeah, it is.
42:33
It is weird that that Meta and Google with all the capex and all the researchers and everything are not ahead of Kimmy K3 right now, at least in benchmarks, right?
42:44
That's that's basically what's going on.
42:46
And you would think if it was like open game, but maybe they're just better. I don't know.
42:51
May, you know, you got to prove the to thing.
42:53
It's just an allegation right now that's being like leaked out through the admin.
42:58
So, it needs to be like definitively proved.
43:00
Do you have to show the chain of what happened and uh what's going on?
43:04
But uh it is a wild time.
43:04
I mean Kimmy Kimmy's denied it like at least like employees have gotten on there being like what are you talking about?
43:10
Like we're not distilling anything.
43:12
We just we're just coded. >> All right John. >> Yeah. What you got?
43:14
>> Time to talk about startup school. >> Okay.
43:16
First let me tell you about Codex.
43:18
Codex is a powerful workforce for getting [cheering] workspace for getting work done with AI agents.
43:21
Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish. Uh startup school. This is insane.
43:30
I cannot believe how massive this event is. It's sick. >> Yeah.
43:40
I I think it's so almost every take that I saw Yeah. >> was negative. >> Really?
43:46
I saw a lot of people that were like this is I they got me back. [laughter] >> Really? >> Yeah. >> Okay, that's good.
43:52
That's good because cuz to me >> it's a completely different.
43:54
It's like this hilarious >> startup school has been something that is free. >> Yeah. online. >> Yeah.
44:00
>> And it's just anyone in the world if you're generally interested in starting a startup, >> you can just do startup school. It's basically the same.
44:08
>> It's basically the same curriculum.
44:08
It's the same like lessons and learnings.
44:11
You just don't have the capital that comes from a typical uh YC batch and you don't have the one-on-one sort of mentorship through your batch. >> Yeah.
44:23
>> Otherwise, they're basically just open sourcing. >> Yeah.
44:26
the YC playbook, which the YC playbook >> just works.
44:30
It's like gener there's there's not a lot of good general advice, but YC's advice is generally good.
44:37
>> Yeah, maybe we should ban it. >> It's too powerful.
44:42
>> Yeah, they're open sourcing all this good advice that would normally come from venture capitals, venture capitalists, like effectively like closed source institutions of venture capital of startup wisdom. >> Yeah.
44:51
And this is an attack on on the on the tier one VCs. >> Yeah.
44:57
>> And all their great advice.
44:58
>> Their their hard one lessons. >> Yeah. Exactly. Board meeting. Yeah.
45:00
They they had to sit in all those board >> meetings where they were tuned out and then >> and then YC is basically distilling it and giving it away for free. >> It's crazy. [laughter] Shut it down. Shut it down.
45:09
No, I think this is awesome.
45:11
Like if you think that startups are good, like why why hate why hate on this?
45:17
I I think the take that uh says uh Scott Stevenson who's been on the show over at Spellbook Legal says >> I have great respect for YC but need to say what many are surely thinking.
45:30
Startup school in a stadium feels anothetical to the YC brand and to what makes startups work. >> Yeah.
45:35
I mean it was a very garage effort when Paul Graham started Y Combinator in Cambridge.
45:40
It was like, you know, he's cooking for the startups with >> the YC brand felt like it was designed to filter out status chasers.
45:47
The thing is is like being a founder became >> cool and something desirable and now people get into YC and because of the way that the internet evolved, they're like they'll make a video with like some clickbait. >> This photo is insane.
46:04
>> They'll make a photo with click like a clickbait, you know, you know, cover art >> Yeah.
46:08
thumbnail and say like I just got into YC. >> Yeah.
46:12
>> And so that's just like >> I I I would never make it >> being a founder became >> to YC twice.
46:20
>> When YC started when YC started being a founder was relatively low status. Yeah.
46:25
>> Now it's relatively high status.
46:27
>> And so status chasers are naturally going to go through YC. Yeah.
46:31
>> Now that's going to lead to >> Yeah.
46:33
a lot of failure because you could shouldn't probably start a company >> in 2012.
46:37
Like everyone that from my like peer group was like, "Oh, like that sucks for you, dude.
46:43
Like you couldn't get a job at like McKenzie or whatever."
46:47
Like like [laughter] like your your your fake startup sounds really exciting, dude. Like good luck.
46:51
You know, it was not like oh wow like congrats. Like >> Yeah.
46:56
Like stay safe in the tenderloin. >> Yeah. Exactly. Yeah.
46:58
[laughter] >> Um >> in your house with like four other people. >> Yeah. I I don't know.
47:02
I I I get I get it as uh I I I I I guess I get that that criticism, but just in terms of like the content and the aesthetics, electric >> electric.
47:13
>> Like you get Jensen on stage at the this key moment and he's talking to a bunch of people.
47:18
Like it's just it's just fun if you're learning about startups to go and see these people talk if you're if you're really really new like like if you're if you're and that's what this uh and that's what startup school is for.
47:29
And is it true that Gary Tan did the little yachty walk out with the microphone? >> I think he did. >> Is it true?
47:36
Because I didn't see a video, but >> yeah.
47:38
Uh I did hear that the the pyrochnics budget for this was over a million dollars. >> Wow. >> Yeah. >> Wow. >> Yeah. >> Explosive. >> Huge. Huge.
47:46
Uh enough pyrochnics to level San Francisco if things went wrong. >> Oh wow.
47:52
>> It was sort of like a bet the bet the farm type of moment >> for YC. >> Yeah.
47:57
[laughter] just constant sparklers and fireworks going on. I don't know.
48:00
I was I was into this, but yeah, people are I guess people are not into it. I don't know. Uh oh, hi Sam. I don't know.
48:10
>> I think I think >> I think it's great.
48:12
>> Among our I I I I like it. I think it's fun.
48:14
Um the great AI psychosis hive mind of San Francisco. Wow.
48:18
Yeah, people are all Do [snorts] they all have headphones?
48:21
What are the headphones for? >> Interesting. >> Silent disco.
48:26
So you could listen to the talks. I don't know.
48:29
And then they gave update for the four and a half thousand attendees.
48:33
This can successfully pass through TSA. Thank me later.
48:34
Uh they gave us a portable battery.
48:38
Oh, and it looks like a bomb.
48:40
So people are like uh but people got it through through uh through TSA apparently. Uh pretty cool. Pretty cool.
48:47
Anyway, let me tell you about Figma. Agents meet the canvas.
48:50
Your AI agents can now create and modify your Figma files with design system context.
48:54
Uh, in other news, Izzkervert raised more money for SSI.
48:57
He said, uh, >> time to scale that safe. >> Yeah. >> Super intelligence. >> Time to safe.
49:05
>> Time to scale that safe super intelligence.
49:08
>> So, SSI, we are announcing a long-term strategic partnership with Nvidia.
49:11
Nvidia is making a substantial investment in SSI that will let them 10x their compute over the next 12 months.
49:17
We reached the point where our research is worth scaling and this partnership we will be able to.
49:20
We are honored by Nvidia's >> just another pod guy. >> Guess what he says? >> What he say?
49:26
>> You need to do a podcast.
49:26
[laughter] >> The podcast guy says, "You need to do another podcast." >> Extremely on brand.
49:32
Well, we have the perfect guest to talk about podcasting with because we have Luke Knight and Ronan Chambers from ETN, the European Technology Network. Welcome to the show. How you guys doing? >> What's going on?
49:44
>> Here we go, >> gentlemen. Look at this.
49:46
>> Look at this beautiful. >> Look at this.
49:48
>> Has this ever happened before? I don't know. >> Yeah. Uh, I love the picture. Thank you so much.
49:52
Uh, hit us, uh, kick us off with the fundraising news.
49:54
I want to smash this gong.
49:57
>> Well, you've seen we we we raised, uh, $1. 6 million. Uh, >> thanks. Congratulations.
50:08
9 million post money valuation. $9 million. Fantastic.
50:10
Um, yeah, announced today. Super happy. >> And new studio. It's It's cooking. It looks huge. You got to trust there.
50:17
Graphics are are are on point.
50:20
Everything's coming together.
50:20
Uh, >> can you can you rate the studio? Just >> look at this.
50:24
>> Give us a studio out of 10.
50:27
>> This is a 10 out of 10. This is I don't know.
50:30
[laughter] You have everything.
50:32
There's nothing else that you need.
50:33
There's no ultra finished on that. This is good. No, you got everything. This is awesome. Um, no.
50:37
Uh, I I I love that you guys uh you know, this is hard.
50:40
I think you guys know, we know.
50:42
It looks sort of easy when you just see a clip and ah it's just a podcast but like the to actually stick with it for a long time is hard.
50:49
Uh what has the journey been like?
50:51
What have the hardest moments been?
50:53
What does it feel like to actually getting here where you have shocked you're announcing this in July of all months?
51:00
July in Europe notoriously slowed you to come back in October be like hey we had a great summer joke. Yeah. >> We're back.
51:09
Well, look, I um I actually I actually uh emailed about 600 people from my from like, you know, the last eight months that we've been doing this.
51:18
>> And the amount of out of office emails that I [laughter] got was >> was actually pretty shocking. So, >> so it's true.
51:24
It's it's a little it's a little bit worrying, but no, we'll be fine. That's the whole point. We're ETM. We can figure it out.
51:30
>> We had we had a checklist to do, and I can just I I'll wheel it out. >> Go and grab it. Go and grab it.
51:33
While you're while you're doing that, the last the PTZ, they got everything. [laughter] >> Yeah. Look at us go.
51:42
>> You figured out everything.
51:46
>> Is James Weekes in the studio today or is he remote?
51:49
>> No, unfortunately not.
51:50
>> You got to get him in the studio.
51:50
I mean, >> can you can we go live? >> Can we see that? Bring it. Bring it. >> What's this >> to do? Go on holiday. Go on TVP. >> There we go.
51:59
[laughter] >> That's amazing. Check it off. Fantastic.
52:05
So, [applause] [laughter] I love I love that uh you guys have like so thoroughly reclaimed the whole like Europeans don't work joke that I don't know.
52:17
It feels like it's completely diffused the meme and now I'm just like okay well that's played out. >> You're grinding.
52:21
You're going 5 days a week now. >> You're grinding. >> Yeah.
52:26
>> You got any advice for us?
52:27
>> What about a cheeky long weekend? >> I beat that. I [laughter] beat that. >> I beat that.
52:32
>> A little I beat the weekend.
52:32
You guys are recently [screaming] in France, right?
52:35
How was uh how was the trip to Hold on.
52:38
You went to uh >> the AC was not was nonfunctional.
52:42
>> I I legit that that actually that actually shocked me so much because I you know you hear these jokes about like oh Europeans take long holidays or like there's no air conditioning over there.
52:52
And I always think that it's the Americans going a little bit too far with the bit.
52:56
And so I assumed I was like, "Oh yeah, the AC thing that's probably just like in random places there won't be air conditioning."
53:02
No, like the all of France doesn't have air conditioning. It's crazy.
53:06
Uh >> honestly doesn't have air conditioning.
53:10
I mean London London's been brutal.
53:12
>> So are you talking to startup founders that are thinking about solving this?
53:14
We were there being like, is this just the most obvious business ever?
53:17
Just create an air conditioning company of Europe.
53:21
Kids in the Gundo should start the air conditioning company of Europe and [laughter] just land on the beaches and just start bringing in units. >> Yeah.
53:30
>> Is anyone >> Yeah, they'd have good merch with that name to be fair.
53:32
Well, I know that one of the Collison brothers has put out loads of posts around how people are literally dying >> from the lack of AC and no one's >> no one's thought to to this out like when we had the heatwave recently uh here in London.
53:45
>> Maybe we'll have to get one of our interns to to get on it incubation. Yeah.
53:48
Quick website, you know, get an intern, you know, shipping in some AC units from wherever they ship them in from. >> I like it. >> Like talk to Yeah. Talk to our own >> Whoa. [laughter] >> Okay. >> There we go. I like it.
54:05
>> This is [laughter] great. >> What's up, lads?
54:07
>> Okay, so uh I mean obviously like there are a lot of element down to the PTZ cameras.
54:12
You're clearly standing on the shoulders of of us.
54:14
You have the picture right there.
54:17
Uh and and and it's great because like we've defined a bunch of different uh like patterns that allow this business to work.
54:25
Like when I see the logos at the bottom of the ticker, I'm like that's great.
54:29
That allows you to pay for the studio and the interns.
54:33
Um where do you see the show going?
54:35
Where do you want the differentiation to be?
54:37
Because you're already differentiated just in the fact that Europe is different than the stuff we talk about.
54:41
You cover stories that way way deeper than we do if it's about Europe.
54:45
But are there other are there other things that you're that you're thinking about where you're like, "Yeah, actually like we want to go a completely different direction with this." >> Yeah, sure.
54:54
That's a really good question because um when we we we actually didn't think that we would raise any money.
55:00
Um we're doing pretty well.
55:02
Um as you mentioned the the ads model, you know, what what you guys have have kind of built in terms of a model is is great, right?
55:07
But then um when we figured out how big the opportunity is in Europe specifically um we realized that raising the money was it had it had legs.
55:18
We were like, okay, this thing can be really big because it is the live show, but we see that as like the kind of wedge in the door, the foot in the door to kind of to build the network and then it's a network, right?
55:27
So, think about uh potentially a summit business or whatever it is like that the the European ecosystem needs that.
55:35
So, um and and it's not kind of as developed as as uh the ecosystem over there.
55:40
So it's like if we can kind of you know almost almost kind of piggy back off that uh off that model and then build on top of that I think uh yeah the the sky's is the limit.
55:52
We can we can go very big which is exciting.
55:55
>> I think like longterm you can see it like in a way where the show would just become the advertising department for a huge media conglomerate.
56:03
>> So we could do the summit business.
56:03
You could even open a recruitment model off the back of it.
56:06
You could look at a fund off the back of I mean, you guys have probably gone through all these ideas anyway, and you've probably chosen, let's just nail this.
56:10
Like, you guys were first to do this.
56:12
You were first to create the model.
56:13
So, I don't think there would be a need for you guys to innovate because you smashed it. You don't need to.
56:17
You had first mover advantage, and you you crushed it.
56:19
>> You're thinking, you're encouraging us to rest on our laurels.
56:20
[laughter] >> We did put we didn't put laurels on the merch.
56:27
>> So, [laughter] it's not now.
56:27
Uh, so we >> can we do a breaking TV rafting on Laurels?
56:32
[laughter] you've so so so uh like you've you guys have been successful with like the TBPN for Europe model.
56:39
There's also uh TBPN for car dealerships over here.
56:42
I don't know if you're familiar with this.
56:44
The car dealership guy has a live talked about this.
56:47
>> Yeah, we had him on the show and we've talked about it and it's great because like we never cover car dealership news.
56:52
It's a it's a great it's every once in a while but not not on the dealers and so and so [clears throat] it's great to like take the best practices of like you know what the lighting should look like, what the trust looks like, take what the logos and stuff like learn from the best practices and then take the content in a different direction so that you're offering a differentiated product.
57:10
Uh is there a European car dealership?
57:12
Are there spin-offs of you yet or more submarkets in Europe for like the European crypto ETN?
57:23
>> I think well well when when we first started I think it was just you guys and then I think like Ecom cowboys popped up.
57:31
I think there were you guys you guys cover flash yet.
57:36
>> You guys know flashbang yet? You got to get on that.
57:38
Hey, [laughter] we thought it would come. >> We got the dance. >> Let's go.
57:46
>> Go down to our uh Go down to go down to our frame. Get down to our frame. >> Oh yeah. What?
57:50
What tricks do you have for your sleeve?
57:53
>> You got some uh >> We got a few tricks.
57:56
>> Throw us some 11 Labs out or something. What you [laughter] got?
58:00
>> We can go adming us earlier.
58:00
Wait, can we go ad for ad? >> Yeah. Yeah. What you got?
58:04
>> I don't know if Oh, here we go. >> Let's go. frame build better.
58:08
>> This is a good This is a good stinger.
58:10
>> This is a really well integrated stinger.
58:12
>> We're flashbanging it again. We're smoking it. It's over.
58:14
[laughter] >> I I think How long are your ad reads?
58:20
This uh this stays up on the screen a little too long.
58:22
Do you have to click it to come off?
58:25
>> That's a good question.
58:27
>> I I I think my my feedback would be a little bit tighter on that. A little bit tighter.
58:32
You don't want people getting distracted.
58:33
>> Is someone writing this down? Yeah, it's recorded.
58:36
>> We'll get it on Granola.
58:36
[laughter] >> Are they sponsored, too? >> No, they're not. >> This is day one. >> Not yet. >> Working on it. Working on it.
58:44
>> This is the worst it will ever be, boys. So, it's fine.
58:45
It will always get better.
58:48
>> What was the what was the question? I forgot the question.
58:50
>> Uh the question was just like uh um what else is there is there demand for a ETN for X in Europe?
58:58
So, so there was demand for TBPN for car dealerships.
59:02
There was also demand for like TBPN for crypto because we don't really talk about crypto that much.
59:08
And there's been a few other like spin-offs that have made sense and a lot of them have gone their own ways.
59:12
They don't even look like us anymore.
59:14
There's like all these different things you can do.
59:15
But they adopted like some of the best practices of like the ad market, the ad model and some of the overlays and some of the live.
59:22
But uh what I'm interested is like where what else is going on in Europe that might uh demand a live show? >> That's not >> okay.
59:32
>> okay. So in so when we when we start started the model start started ETM we were like this could be done in uh you know you you mentioned like car dealerships this could be done in fashion I could get two people to go and you know do a live show for fashion
59:48
show a cooking show whatever it is like >> yeah literally >> yeah yeah yeah so it's like um uh someone could do that get the best designer designers on every day to talk about I don't know how fashion works but like the new jeans [laughter] that they've just like designed or whatever It is right. So like I think that I
1:00:02
So like I think that I think you could go like category uh you know specific and verticalize in a category in Europe specifically. >> Not yet.
1:00:11
I mean we're what 10 months in.
1:00:14
So >> we'll see we'll see what happens like towards the end of the year.
1:00:16
Um you guys were going for I don't know at least I don't know maybe 9 months before before we caught on and we were like look this needs to be done in Europe. This is a great model.
1:00:27
>> What were you guys doing for the first month? >> Vacation. We know the bit. >> Yeah.
1:00:31
You guys should do You guys should do TBPN for Euro Summers. >> There we go.
1:00:36
[laughter] Just day >> we go on the road a lot to be fair.
1:00:37
We did we did Monaco with A16Z which is great.
1:00:41
We saw Anish who I know knows you Jordi.
1:00:44
>> Um uh we had Nico on which was awesome.
1:00:47
So Greece in Pan uh yeah Greece with Panaththenia.
1:00:50
We were at the Louv in Paris.
1:00:53
>> Got you started on on on vacation destination.
1:00:56
Now you're [laughter] >> I mean there are summits in Europe.
1:01:03
We only choose We only choose the destinations where we actually want to like, you know, vacate. Yeah. Yeah.
1:01:06
It's a good model, but do you think we should do an AI pause so that the AI researchers can go to IBA?
1:01:16
>> Well, to let them off for a week.
1:01:18
[laughter] >> I mean, they're all going to do pretty soon anyway. >> Quick one week pause. >> Six Six month pause. >> Six Six month pause.
1:01:23
If you can get if you can get all the Frontier Labs to sign off on that like Jensen did for his uh global >> AI summer. >> Last question.
1:01:34
>> Do you have a do you have a do you have a like an inter an on camera intern?
1:01:36
Our our original intern has evolved into a >> co-host >> into a cohost co-hosting now.
1:01:44
>> Yeah, we we we've not got a we've not got a Tyler yet.
1:01:46
Um, >> we did put a job ad for two interns and we got like 360 applicants and there's people from based in SF that interned at like Tesla, SpaceX pinging us [laughter] to be like, can we work for >> I'm moving to Europe? That's sick. >> Yeah.
1:02:02
Which was which was nuts, but I don't think we can make that.
1:02:05
>> They wanted to eur Yeah.
1:02:05
They wanted to Euromax with us and we thought you probably are too qualified and we couldn't afford you.
1:02:11
>> What what what's the European version of the gong? We just ran.
1:02:13
We should have done a a bell because in America you actually ring the bell.
1:02:18
We randomly went with a gong which is very >> Asian.
1:02:23
To be fair, we did earlier today.
1:02:26
>> Earlier today we did >> we did saber.
1:02:29
>> Oh, you saber a champagne bottle. >> That's good. >> We did.
1:02:32
>> We'll send you the video of us sabering it.
1:02:34
But as you can see it >> we've got the TVPN the lights. >> There you go. Yeah, that's pretty.
1:02:42
The chat is saying confirmed.
1:02:44
Tyler has not been distilled. >> I like this one.
1:02:47
This is a good cyber cue. >> Too long though. >> Oh, wait.
1:02:52
Actually, if you're going to play the whole song for a little bit, then you're good. Then you're good. >> Yeah.
1:02:56
Intros sometimes, I guess. >> Okay. Yeah. Yeah. Yeah.
1:02:59
>> You guys are You guys are like sports tune.
1:03:02
>> Just like uh just like the AI, you guys are like nine six, you know, maybe 12 months behind.
1:03:09
But uh Yeah, we're day one.
1:03:12
[laughter] >> We had to keep it we had to keep it concurrent with the you know the we need to get the uh we need to get the flash going though you guys we're we're happy for you guys to distill the show >> fired shots fired. >> Good.
1:03:26
I like [laughter] that one. I like that one.
1:03:28
>> Hey, don't give them any ideas. They'll take >> Yeah.
1:03:30
No, no, we're going to distill it back.
1:03:32
You know, it's like when you ask what model it [laughter] is in Chinese and it says it's Deep Seek.
1:03:35
It's like goes both ways sometimes. You never know.
1:03:39
No, like I think what's the what's the best is that uh this is this can be a grind like five days a week, a lot of stuff.
1:03:46
There's just a lot of work and uh it just seems like you guys are having fun. Are you guys having fun? >> We're having fun.
1:03:52
>> The most fun we've ever had. >> It's uh it's great. It's great.
1:03:53
We get to talk to cool people and you know, we're two mates talking to each other for a living. It's great. >> That's the best. >> Amazing. >> Best. Exactly. >> Stoked for you guys.
1:04:03
>> You guys are living the dream. So are we.
1:04:04
>> Well, congratulations.
1:04:05
>> Wait, before we go, I want to ask, can we get some Lucy's for the studio? I'd be happy.
1:04:09
I'll send you a whole vending machine. >> Really? >> Yeah. Yeah. Yeah.
1:04:12
We'll see how we'll send it to. I love it. Yeah. It's amazing. >> Oh, yeah. Let's do it, bro. We're European. We need those. >> Yeah. Yeah.
1:04:18
Send me your address and uh Yeah, we'll we'll chat offline, but we'll we'll we'll send you a bunch of stuff. No problem.
1:04:22
>> Maybe you could be coming if that's legal. >> Yeah.
1:04:25
>> Uh great to see you guys.
1:04:26
Congratulations on the new funding.
1:04:27
Congrats to the whole team.
1:04:29
>> We'll talk to you soon. Have a good one. >> Appreciate it.
1:04:32
>> Let me tell you about Cisco.
1:04:32
Critical infrastructure for the AI era.
1:04:34
Unlock seamless real-time experiences and new value with Cisco. What a great crossover. You'll love to see it.
1:04:40
Well, we have Gary Vaynerchuk, creator V, friends back on the show. Third time.
1:04:46
Love catching up with Gary Vee.
1:04:46
We'll go all over the place.
1:04:49
Creator economy AI opensource building stuff. How you doing, Gary? What's up? >> There he is. >> Men. >> Men. >> Men. >> Men.
1:05:00
>> I thought you said me.
1:05:00
You're doing [laughter] a You're doing me >> uh What's happening?
1:05:06
>> Okay, I want to I want to start with some unless you have something to kick right off with.
1:05:10
I want to start with something.
1:05:11
I like I've been seeing these these videos of you from like years and years ago with just these like crazy crazy accurate calls about the future.
1:05:22
What what victory lap do you like to take the most?
1:05:24
Like like what what's the one call when you think back where you're like, "Damn, I really nailed that one.
1:05:32
social like if I'm being honest like like no it's like it's crazy too bad I wasn't making the videos back then like just my complete conviction on Facebook and Twitter completely unearthing and changing the world
1:05:49
>> you know it it's ironic timing I met with someone today I hadn't talked to in like 12 13 years you know retired gentleman I met him early on he's like he's like it's crazy how much you believed in that stuff and how dismissive we all were. Um, but there's,
1:06:02
Um, but there's, you know, I listen, the only one of the few things I really do well in business is I don't let my audacity or my current financial situation or what I would like to happen financially dictate my observations of the consumer.
1:06:27
I don't think I'm smarter than anyone or have a bigger knack.
1:06:31
I think that you have now let me give some flowers to you boys.
1:06:35
You have some of the greatest people on here, right? You guys have crushed.
1:06:38
You've also gotten much better at your actual job in interviewing because you know I'm a day one with you guys.
1:06:44
Like so I just want to give you some flowers.
1:06:45
You guys are getting better and better. >> Yeah.
1:06:48
>> All these brilliant people you have.
1:06:50
>> It's not that I know it better. I don't know it better.
1:06:53
It's that I'm I'm willing to completely change course of what I think is working for me or I'm willing to lose all my money to be historically correct.
1:07:03
I'm not talking about things that I want to happen for my financial interest.
1:07:07
I'm talking about what consumers are actually doing.
1:07:11
>> Do you think you were more bullish?
1:07:13
Well, and the other thing is that >> then like the actual platforms like cuz because like when I look back at some of those calls um about like the pivot away from the there's this one where you're like looking at the newspaper and you're like nobody's going to use the newspaper, they're just going to get their news online from other people and it's like a very accurate prediction.
1:07:28
Um but but it's like that distinctly wasn't coming from like Mark Zuckerberg in 2008.
1:07:37
>> He was just saying like I built this cool website like it's fun.
1:07:39
I'm connecting the world.
1:07:41
Yeah, >> it was connection.
1:07:43
But I, you know, I think that I know when you go read Crush It, the first book I wrote, I wrote in 2008 also in that time.
1:07:52
>> I am fully predicting and you guys know this.
1:07:55
We've talked off like I predict like literally there's parts of the book that talk about what you guys are doing right now. >> Yeah. Yeah.
1:08:01
No, >> we're super into the live streaming too. >> Yeah.
1:08:05
And don't forget we just came out of Fster and MySpace failing. >> Yeah.
1:08:11
So my thesis wasn't necessarily now look I thought Mark was generational because I'd spent some time with him and like I ended up being very right about that and I thought Twitter was incredibly unique.
1:08:20
So I was bullish on those platforms, but I was incredibly agnostic to your point.
1:08:25
I was whether it was called Facebook or Twitter or the many things that failed along the way.
1:08:29
Social Cam, Peach, >> Vine, you know, like LinkedIn or YouTube or Twitch or Tik Tok, it didn't matter.
1:08:41
apps that connected people on top of the internet I knew had to win because of the network effect of scale and no gatekeeper in between.
1:08:50
You think you two handsome young bozos would have gotten on CNBC?
1:08:55
You would have had to wait. >> Yeah.
1:08:58
>> But I knew that you could just do it >> and then it's like sports.
1:09:01
[gasps] >> We love the term bozo. It's like underrated.
1:09:05
good because it's not it's not it's like only slightly derogatory but it's like not totally not a bad word.
1:09:11
>> I do identify as a bit [laughter] of a word it's a great word.
1:09:16
>> You know you guys have become very influential and definitely the people watching are very influential.
1:09:19
Can we all collectively put our hands in the pot and all bring bozo back?
1:09:22
It would be really enjoyable.
1:09:25
>> Bozo golden retrievers are kind of bozos lovable.
1:09:29
We have talk about golden retriever mode. >> Yeah. Yeah.
1:09:32
But yeah, better justation.
1:09:34
Jordy, sorry I cut you off. you going to ask? >> Well, yeah.
1:09:36
I think I think what was interesting about your call is you were bullish on the platforms, but the take wasn't just you should invest in Facebook.
1:09:44
It was like you should just put stuff out every single day and you've been remarkably consistent with that. >> Yeah. >> Yeah.
1:09:52
And it was it was real for three guys like us that could go from zero notoriety to a lot.
1:09:56
And literally the most famous people in the world right now, you know, at least a third of them are either streamers or purely on social. They have no television.
1:10:04
They have no, you know, theatrical.
1:10:06
They have no other platform. >> Yeah.
1:10:10
TV is now coming to them and saying, "Hey, could we work something out?
1:10:13
We you you clearly have demand for your content.
1:10:16
We want to get it on our platform."
1:10:19
>> I started a company a couple years ago called Vayner Watt WAT.
1:10:20
It's a TV production company.
1:10:24
and we are bombarded by the distributors for me to get access to the Steven Bartletts or the Hermosis or the Cody Sanchez's or the you like it's all here.
1:10:34
And what's crazy is like YouTube for example, right?
1:10:40
There's 900 genres that should be doing what you're doing right now.
1:10:43
what you're doing right now. Yeah, we just talked to some folks who are doing this show for Europe specifically and there's one that's for car dealers and there's one for crypto and there's a whole bunch of different sort of like and it's not even like we were the first live streamers obviously we just took
1:10:57
them >> still the funny you know the craziest the craziest thing no one has done TBPN for the market open like you're in New York >> you're in New York you start at >> I know someone that's working on Yeah, we know we know we know a couple people, but the fact that we're 18 months in and no one saw what we're doing, we go live at 11 Pacific. So,
1:11:19
So, we're going live at noon.
1:11:21
The market has been open and >> which is which is an indication of your laziness. You guys should wake up.
1:11:28
[laughter] We do wake up early, but we do a team workout >> and and it's more it's more an indication of our of our fascination with private markets versus public markets and and like longer term uh less quarter by quarter, less dayby-day market moves and more uh 12 to 18month fundraising cycles for private technology companies.
1:11:49
And so I think that my natural interest is in the private markets and the earlier stage technology.
1:11:56
So if I was trying to cover, you know, the dayby day in the market, what oil's doing and how that's affecting, you know, GE and Boeing, I would just be a little bit less sharp than if I'm talking about, you know, private market.
1:12:10
And and honestly, that's what you know, back to Crush It, back to you guys, back to all of this what you're already like the whole theme of this interview.
1:12:16
The fact that people that are watching that are deeply sports like you, the TBPN for sports with talent like you guys is is ESPN's biggest nightmare.
1:12:28
>> Um, they sort of have it, right? Isn't >> Pat? Of course. Of course.
1:12:32
I mean, >> but they have to pay him like 60 million a year. >> They do.
1:12:37
>> And and Pat had to be lucky enough of all the serendipity that led led to that.
1:12:42
There are 913 Pat McAfee.
1:12:42
And I mean, and Pat's incredibly charismatic and talented.
1:12:47
You guys are as well, but the long tale of knowledgeable or charismatic individuals is quite long.
1:12:55
Now, everyone has a different upside, right?
1:12:57
Like, like again, somebody could replicate this exact show. >> Yeah.
1:13:02
>> And if they're really just much sharper and more entertaining, they will take market share.
1:13:07
That's just how it >> Well, the other the other thing about sports versus business that's interesting is like sports, there's so many people that played sports, whether it's college or professionally, and then they stop being able to play at that level, and they're like, "Well, what's the best thing I should do?
1:13:20
I should just talk about the game that I love."
1:13:23
Whereas in business, you don't get to a point where you're better at talking about it necessarily than doing it.
1:13:29
There's a lot of people that that that could >> So well said.
1:13:33
>> And so well, and there's another thing.
1:13:36
I just turned 50 and like literally this morning like no I'm like am I starting to enter my prime like as [laughter] a operating >> that's such a great philosophy.
1:13:51
>> You're just like I'm having whatever the inverse of a midlife crisis is that's me.
1:13:54
[laughter] >> You know what's funny?
1:13:56
Wait, is the generational run just beginning? >> I love it.
1:14:02
>> But man, I really like and it's funny and I have a funny feeling especially given the incredible nature of your audience.
1:14:09
I think when that was just delivered a few minutes ago, >> there's just a lot of people that really understand it because you know my whole life and probably many others watching here, you wish you were an athlete, >> but if you were an entrepreneur, you kind of realize at 30, you're like, "Wait a minute.
1:14:21
If I was an athlete and I was great, I'd be kind of wrapping it up or like thinking about post and and I own a large sports agency.
1:14:28
My brother and I own a very large sports agency now called Vayner Sports.
1:14:33
>> You know, I feel for these kids.
1:14:33
This is what they were meant to do.
1:14:35
They're 35 years old and they're like, "What do I do with my, you know, like just like really >> in I know it's I I truly I feel so blessed to have always been obsessed with business.
1:14:47
like I never I never came clo I you know I I got very into surfing.
1:14:53
>> Uh but I never like surfing as much as business and being having a love for something that you can do for a lifetime.
1:15:01
Even more so people say like oh you should play tennis cuz you can play it you know you know basically indefinitely but it's like well you can you can do deals for truly for life. >> That's a good segue. Yeah. Yeah.
1:15:12
This is what we were we always we always bring up segue we sorry one second.
1:15:15
We we always we always bring up uh Warren Buffett and Charlie Mer.
1:15:19
It's like the greatest the greatest run of that career happened from like 50 to 90.
1:15:24
It's like that's so long.
1:15:27
>> No, but wasn't it more like 70 to [laughter] 90 or like 80 >> was it was like 60 like that's right.
1:15:31
So segue we just brought up tennis.
1:15:36
>> I've done incredibly well.
1:15:36
I think this is important for a lot of people.
1:15:38
Again I'm always [clears throat] think about the audience.
1:15:40
alternative sports league investing.
1:15:45
>> I think you guys I think there's some more fun stuff you guys could be doing about that.
1:15:48
It's gone really well for me.
1:15:50
>> Yeah, Alexis, we had Alexis on.
1:15:50
He he has the the running running running league, which is cool.
1:15:54
We had the the founder of Enhanced Games on >> Yeah, there's some article in the journal today.
1:16:00
Is Padell the next pickle ball? >> Right.
1:16:04
So, pickle was a huge win for me, right?
1:16:06
I bought a team for 500,000 pre-COVID.
1:16:08
They're trading at 16 million right now in our major league pickleball league. >> Wow. >> Right.
1:16:13
I >> So, do people watch pickle ball? >> Yes.
1:16:16
That's why that's why I invest.
1:16:16
So, I have a little bit of a secret of why I think I'm doing well because I'm doing well with this whiffle ball league that is starting to get some juice.
1:16:23
We got some great owners in that.
1:16:26
>> Whiffle [laughter] balls.
1:16:28
>> Um, I have one little advantage.
1:16:28
It's back to this and we've had some meetings off camera and you guys know I'm like pretty in the weeds with like how communication and marketing works.
1:16:35
The reason I invested in Pickle is Pickle highlights even seven years ago massively overindexed on social. >> Oh, sure. Yeah. >> Right. Like >> Yeah.
1:16:46
But but the but the thing is I do wonder if that's so so Dana White has the the slap fighting league. Forget what it's called.
1:16:57
And that's something that does incredibly well on social, but I don't know anyone, even hardcore MMA fans, it's like can't wait for the card this weekend.
1:17:07
I'm going to watch live things. >> Two things.
1:17:11
>> One is on incredibly well on social.
1:17:13
You have to, you know, when when you because I've looked at that as well and a lot of it is driven by the TKO machine. Yeah.
1:17:24
Much more than, you know, the organic nature of what I was saying.
1:17:27
>> And and seeing somebody that's about to get hit in the face is like naturally scroll stopping even if it's not a good spectator.
1:17:32
>> There's also something that people don't realize about sports that matters if you're going to watch it, which is your capacity to participate in it. >> Yeah. >> Right.
1:17:39
>> Right. like like like people a lot when people try to zing pickle ball they're like yeah everyone's playing it but is it a business and I always like literally those are the articles that were written about tennis and golf 50 60 70 80 years ago it's like it's funny by
1:17:54
the way back to your first question the other thing I do pretty well >> that I hope other people do so I'm saying it out loud is I really use history along with paying attention to people so for example the biggest sports in America in the 20s and 30s were horse racing, boxing and baseball. Those
1:18:10
Those sports were very good on radio, but football is not a great radio sport. >> Oh, interesting.
1:18:19
>> Football exploded with the television.
1:18:21
If you look at the explosion of the football, >> it came along with television. >> Yeah.
1:18:26
>> And so, back to streaming what you guys are doing right now, one of the reasons I'm invested in the sailing league, slam ball, you know, pickle ball, whiffle ball. >> What's ball? Slamball's trampoline. It's [laughter] amazing.
1:18:39
You don't know what this is.
1:18:41
>> Dodgeball and trampoline. >> No, no, no.
1:18:42
Basketball with trampoline so everyone can dunk and do like baths and stuff. It's crazy.
1:18:48
>> All right, I got the >> reason I did it was I knew I didn't need just like you guys didn't need CNBC to be like you're the right on air talent.
1:18:55
>> Our all these alternative leagues do not need ESPN or >> you know Fox Sports to say yes.
1:19:01
People can see this stuff through these platforms.
1:19:06
And that's going to continue in an AR, VR, like we're going into an incredible era of opportunity and meritocracy. >> Yeah.
1:19:15
>> Uh, real quick, what was your reaction to the World Cup?
1:19:18
Do you think that flopping will uh and flopping culture will will forever prevent America from actually getting into uh Do you think that's a bottleneck to growth?
1:19:30
>> No, that's not a bottle. What?
1:19:30
Americans are hypocrites. We love basketball.
1:19:32
SGA is the greatest flopper of all time.
1:19:36
[laughter] >> I have I don't watch enough I haven't watched enough basketball to to to have even seen SJA flop.
1:19:44
But I feel like the I feel like in Europe they appreciate the the drama and it's almost like the acting of it all, but then you watch the replay and it's like, you know, Americans that are used to watching, you know, some cornfed linebacker run through a guy and the guy just gets up instantly.
1:20:02
You know, it's hard to then go watch >> somebody flop and completely fake an injury.
1:20:08
>> I I think that soccer players at this point have this incredible four to 7% Academy Award-like acting capabilities that probably piss people off. But I agree with you.
1:20:19
I'll use football because football is a sport that people hate when they first see it and then they become infatuated with it because it stops and starts and stops and starts.
1:20:30
starts. especially the world immigrants coming to the US when they're used to soccer which is flowing they hate it and then inevitably within a decade they love it because you start falling in love with all the little nuances and I would say for Americans the nuance of flopping is annoying especially with the
1:20:48
NBA it's been a big topic by the way so I think especially this season so I think some of that energy came to it but look I mean I'm a little older than you guys everybody who's over 50 knows this the strides that America has made in its interest in football, aka soccer, over the last 30 years is profound. FIFA, the
1:21:05
FIFA, the video game had a huge impact.
1:21:08
Being able to watch the Premier League in America on Saturday mornings had a huge impact and um and I'm it's a great sport and I I already am excited for the next one.
1:21:19
>> What about What about the intersection of technology and a game like soccer?
1:21:20
I grew up playing soccer, refing soccer. I've refed.
1:21:27
That was like, you know, that was I would spend my weekends when I was 12.
1:21:31
I'd ref like 20 soccer games cuz they didn't cap it.
1:21:33
Like there was no like you can only work eight hours.
1:21:37
It was like you can ref as many games as you want because there was a shortage.
1:21:40
So I'd ref like an insane number of games in a day.
1:21:43
And in watching the World Cup and again I'm a super casual viewer.
1:21:47
I hadn't been watching soccer prior to the World Cup but it was fun to kind of catch up on it.
1:21:51
like, you know, there'd be an offside call and or or maybe there wasn't a call and then they'd run the tape and they'd figured out that the guy's hand, you know, elbow was slightly over the line and they'd call it, they'd take the goal back.
1:22:03
And that that to me, >> like part of part of the part of like what makes the sport great is there's just players that can finesse a situation and just be right on that line so a ref couldn't possibly call it.
1:22:15
And then to have a machine being like, you know, no, you can't you you could beat the ref, but not the machine.
1:22:23
>> Look, I think of this like marketing.
1:22:25
Just I'll make this valuable to the audience who does not like sports.
1:22:29
>> This is Slam Ball, by the way.
1:22:31
[laughter] >> I thought those were the Chinese robots for [laughter] >> No, these are Now we're watching Slamball. Best hits. Look at this. >> Look at this. >> All right. All right. This is electric. I can get behind this. It's so insane.
1:22:47
[laughter] >> That's insane.
1:22:49
>> Is this made to look like it was shot on VHS? What's going on here? Is this other video? >> Oh, okay.
1:22:53
So, it's been around for a while. >> A little bit more.
1:22:55
[laughter] Um, so I'll I'll say I'll answer you like this to make it a little business terms.
1:23:03
Hopefully help some people's marketing.
1:23:05
There's a lot of people watching right now that become two one-dimensional math performance marketers >> and they lose.
1:23:11
In fact, you boys were one of my favorite executions to watch from afar because you guys played like me.
1:23:16
You sell more on brand than [clears throat] on math.
1:23:19
You guys were getting brand deals that were completely inappropriate because you sold on value, not on metrics. >> Yeah.
1:23:29
>> I think that that's how I think about technology and sports.
1:23:30
If we get all the way to full AI robots and everything's 100% black and white, I think the leagues are going to learn pretty quickly that we as humans need a little romance, need a little gray, not black and white, need a little of a balance.
1:23:45
And so, just like I wish in political terms that everyone was purple instead of this garbage red and blue we're in >> with the sports and technology and replay, if they can find purple, I think it's great.
1:23:56
When they go too red or too blue, I think it's a problem. >> Yeah.
1:24:00
Even in Formula Even in Formula 1, there's, you know, the drivers are having issues right now because there's AI is deciding how much, you know, fuel and how much power to to and and they're all just getting angry because they're like, am I am I losing because I'm not as fast as my opponent, or is my is the AI running on my car just not as dialed?
1:24:22
>> It's it's all these analogies.
1:24:22
It's like, is dinner fun without the side dish and and you know the the amuse and dessert?
1:24:31
Like when we get so binary, it we all want a little romance.
1:24:34
We need a little romance.
1:24:37
>> Okay, one more potential league.
1:24:37
I want you to run run this down and and let us know next time you're on what you find.
1:24:44
But I have a theory that when every car on the road is uh autonomous >> that uh like driving on the track is going to have a a resurgence in popularity because people are going to be you know it's so romantic. It's so romantic.
1:24:59
There's so much great history around racing.
1:25:01
Every person >> everyone I know >> uh yeah hit me with the counter.
1:25:06
But but I have a theory that like na like things like net like there's something like a slam slam ball or whatever it is for driving >> and that's the one >> just like demolition derby.
1:25:18
>> No something like rally car I was driving yesterday I was driving a I was driving a dune buggy.
1:25:21
I I was like with my buddy and we were like laugh we were laughing. It was so much fun.
1:25:26
We're drifting around corners. >> Yeah. Yeah.
1:25:29
It's a more dynamic >> counter is I don't know if you know this but we used to ride horses before the cars. >> Oh yeah.
1:25:35
And I don't know if you know there's something called horse racing. >> Yeah.
1:25:40
>> That is pretty out there.
1:25:40
And so the counter would be that we kind of just lived it with horses and horse racing. >> Mhm.
1:25:48
>> But the counter to my counter is what you said, which is I actually think horse racing could be massive in this country if they put a contemporary flare on it.
1:25:56
What UFC showed >> is like it was a evolution of boxing with more >> interesting. Yeah.
1:26:02
You want like rally horse racing?
1:26:05
>> Sort of like UFC meets the Kentucky Derby like you can punch the other jockeyies >> or or what about none of that and [laughter] it's more about >> what about storytelling? What about >> Yes. Yes.
1:26:18
A drive to survive that type of thing. >> Yeah.
1:26:20
Or like or even when we're watching an actual horse race on a Saturday that's not the Kentucky Derby.
1:26:26
Like if you turned it on and the bottom of the screen was actually a miked version of every jockey and you're learning like we want layers. >> We want layers. We want stories.
1:26:35
We want to get captivated.
1:26:37
Everything is about that in every aspect of life.
1:26:42
>> But two jockeyies getting up in each other's faces and thrown down after a violence.
1:26:49
>> Okay, here's a here's a hard-hitting question.
1:26:52
Do you think Big Boogie turned it down or was he capping?
1:26:56
>> That is a good question.
1:26:58
>> Do you think he he potentially because we were trying to do the John did the math and he said that if he was going to dental school for [laughter] a decade and he had a bunch of dependents, it's possible the total package could have been in the in the $10 million range.
1:27:13
But you you cover NIL stuff a lot more. >> True.
1:27:17
>> You'll appreciate this.
1:27:17
This is one of the rare moments where I get to do this and I always look for it. So, thank you, men. I'm going to clip this.
1:27:23
The answer is I don't know.
1:27:25
I've just not paid enough attention.
1:27:28
>> I've been in a little bit of a bubble.
1:27:30
I'm very in I'm in a very weird place right now.
1:27:32
I've been in a seven to 10 week cocoon >> around the collectibles industry becoming the collecting becoming the next lifestyle genre. >> Yeah.
1:27:42
>> And so, like my consumption of anything happening in pop culture is at an all-time low the last two months.
1:27:45
all-time low the last two months. I've been in the lab like in the lab >> on this thesis that I've been on for about eight years that I think is about to completely blow the roofs off of >> like for example let me give you instance to give you even more color again always try to think about how to
1:28:02
bring value to this smart show I'm we've started at Vayner Media a collectibles marketing division just like there started just like Coca-Cola started a sports marketing division when the Olympics were getting important as a driver to consumption I believe in 10 years, every Fortune 500 consumable product, apparel, CPG, will have a collectibles marketing strategy. I don't know if you guys saw lines
1:28:27
I don't know if you guys saw lines around the door at Popeye's chicken for the one piece collectible.
1:28:31
People flooding to a Dodgers game to get the one piece collectible.
1:28:35
I think that in differentiation in an AEO GEO, you know, agentic commerce world, differentiation around collectibles and community to get people to stop their normal pattern of what they're just reordering because they want to buy deodorant that has a collectible of their favorite.
1:28:54
I just see collectibles eating up because of what it means for community and analog and value and investment.
1:29:00
investment. AI creates like insane is going to continue to create insane abundance like one example is everyone everyone can have a SAS product now you can make it >> everyone will >> everyone will what's the chain
1:29:17
>> everyone wants to go ahead brother >> what's the chain from people are playing a sport is it watchable then it becomes a a sport with teams professional uh you identified some of the translation effects like uh you know is anybody is anybody going to watch golf? Sure, a lot of people play
1:29:36
Sure, a lot of people play it, but will people watch it?
1:29:38
Obviously, the answer was yes.
1:29:40
And that was true for football before there was a league and there was TV and the Super Bowl, right?
1:29:47
People were just playing.
1:29:48
>> By the way, just for fun, because I'm just nerding out, like everyone said there would never be a professional football league, that football was always going to be college. >> Yep.
1:29:55
>> In Notre Dame, the 20s, the 30s, like >> Yeah.
1:29:58
like smart people that come on every this one and like those people back in the 40s and 50s were like there will never be professional football. >> Yes.
1:30:05
But at the same time there are sports that are played by lots of people.
1:30:11
I'm thinking of like running and running is not a massive there's not the Super Bowl of running even though millions and millions of Americans go jogging and they participate in the sport.
1:30:20
There's something special about competitive football that makes it the Super Bowl. Right.
1:30:26
>> Super Bowl is very special.
1:30:26
But like, you know, the New York City Marathon Yeah.
1:30:30
>> is a very cultural event with good ratings. >> Yeah.
1:30:33
>> You know, >> I think we're in the era where an entrepreneur watching this show right now is like, "Fuck it.
1:30:37
I'm making a running league and it might hit." >> Yeah.
1:30:40
So then talk to me about the translation layer from there.
1:30:41
There's a sport that a lot of people are playing.
1:30:46
If it's watchable, it becomes a big national sport with professional teams that we're all watching.
1:30:51
Uh at what point does it become is there a collectible culture around it?
1:30:56
Because uh we're just in this early stages of like pickle ball has been played by a lot of people.
1:31:03
It's now starting to be watched by people as you mentioned.
1:31:05
When will people be collecting pickle ball cards? Yeah.
1:31:10
>> Your production team seems really capable based on what I just saw.
1:31:13
>> Can the production team before I leave in the next three or four minutes >> put up eBay, type in Anna Lee Waters? Lee is L E I G Hannah.
1:31:22
A N A space Lee L E I G H space waters.
1:31:31
>> Then enter on eBay and then go to completed and sold items and then sorted by most valuable.
1:31:36
If the team can do this for the team, are you just trying to move some Anna Lee Waters merch right now?
1:31:45
You're like and then click purchase and then click check. I'm [laughter] kidding.
1:31:50
But she is the star of our team and we do repay sports. She's my >> for me. She was our Joe Nameoth. She is our Larry Bird. But look at this.
1:32:00
>> Can we go zoom >> now? Hit on the left side. On the left side. Hit completed and sold. >> Yeah.
1:32:06
Real eBay ball knowowers. >> No. Dylan on our team. Big collector. >> Nope. No. No. All the way down. I'm very hardcore.
1:32:17
I'm very in the dirt on collectible culture. The completed sold. >> Where are we going?
1:32:24
Hunting around for Anna Lee Waters. >> Oh, show us this. Show us this. >> Got to log in. Show us the password. >> No.
1:32:31
So, so Dylan on the on our team already got there. >> There we go.
1:32:36
>> And he's seeing >> share screenshot.
1:32:39
>> Anna Lee Waters rookie autograph cards going for $8,000. $5,000 [laughter] here.
1:32:45
5,000 >> and I would argue >> we've done a very good job with Anna Lee. We've made her famous. She's on Fallon. She's on McAfee.
1:32:53
She's the face of the sport.
1:32:55
Ryan Harwood at Vayner Sports deserves a lot of credit. We've crushed with her.
1:32:59
She's the best player in the world.
1:33:01
Pickle ball is the only sport where a female can be the best.
1:33:05
She's the best player in the sport, including the men. >> Wow.
1:33:09
>> Because, you know, that's what's interesting about pickle ball.
1:33:11
80-year-old grandmas are whipping 19year-old grandsons in pickle ball.
1:33:15
It's a different kind of sport.
1:33:15
Anyway, >> there is there is another sport where women outperform men uh certain equestrian in the Olympics makes sense.
1:33:25
I'm sure there's others but this is one that people know >> uh you could see 8 to 5,000 and I will tell you 99% of the audience and everyone on Twitter right now hit me up Gary Be and answer this.
1:33:35
99% of the audience right now has never heard of her in their lives.
1:33:39
So, it doesn't take a lot to get to collectible because collectibles are niche, are tribals, right?
1:33:47
Look what happened with Comic-Con.
1:33:49
50 guys in a weird hotel in San Diego, right, in 1976 to now this last weekend.
1:33:57
Millions of people go into San Diego and it's a cultural phenomenon.
1:34:03
>> So, collectibles is when it flips over to pop culture.
1:34:05
I would argue that athletes that are the most valuable are more pop culture >> than people realize.
1:34:12
They're more superheroes than people realize.
1:34:14
And when you're building a league, whether it's Conor McGregor and Ronda Rousey, whether it's Michael Jordan, Larry Bird, Steph Curry today, like you need a superhero.
1:34:24
Joe Nameoth was the superhero for the NFL early on.
1:34:26
He became one of the most famous people in the world.
1:34:28
The Jets had a huge upset in Super Bowl three and football was on its way.
1:34:37
business uh collectibles.
1:34:41
Where do you think it's going?
1:34:41
We saw Jensen jacket go for about a million.
1:34:45
That was for charity for our friend Justin May's >> uh his grants that he does.
1:34:49
>> I believe collectibles I believe collectibles have eaten up the pop culture energy of what young 20-year-olds would do with public stocks.
1:34:56
So instead of buying 50 shares of Nike like my generation did, they're going to go buy a collectible.
1:35:02
I think it's completely eaten up the oxygen of contemporary art.
1:35:05
So you guys, especially after your nice transaction are, you know, continue to hang around people of wealth at a young age.
1:35:12
Your contemporaries, people in their 30s, 40s, 50s only 25 years ago, 30 years ago are buying the hottest contemporary artist to put the art in the house.
1:35:20
Much of that money is now going into $100,000 million collectibles.
1:35:26
Obviously, Michael Rubin sitting on the top of the Topps empire with all his cultural relevance has brought an incredible amount of pop culture energy to it.
1:35:35
And kids, people forget trading cards are 100 years of collectibility.
1:35:42
Now, this has been a very long-term asset class, but the numbers are just out of control.
1:35:47
numbers are just out of control. You see wearing [laughter] you know like you know this even for you guys that are young definitely people of my generation people that collected cards as teenagers in the 80s and 90s were nerdy people collecting cards are
1:36:04
now cool and once that switch happens it gets really different really fast and we're on that other side and so you'll see collect you know watches [clears throat] >> I want to know what's on your shirt >> I wasn't even I was right there you go look at what the hell I'm wearing Are you are you going to the national? >> Of course. Leaving tomorrow. >> Of course. Leaving tomorrow.
1:36:23
By the way, let me just make this so I can clip it in nine years.
1:36:25
I am building the next Disney Pokemon marble. All in everyone's faces. It's called Be Friends.
1:36:31
>> And because I have 13 different other jobs, no one sees it, and I don't speak about it that often, but >> building an IT business >> during this AI era is going to end up being one of my savviest moves. >> Yeah.
1:36:44
And the generational run is just beginning. I love it. >> Clip that. Clip that in a decade.
1:36:50
>> Clip that in five decades. [laughter] 99 100.
1:36:58
>> Great to Great to catch up. >> Always great, man.
1:37:01
>> Let me know if I can help you.
1:37:02
>> We'll talk luck at the national. >> Goodbye. Cheers.
1:37:05
>> Let me tell you about Console.
1:37:05
Console builds AI agents that automates 70% IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
1:37:13
Up next, Jonathan Jacobe. >> Jacobe.
1:37:18
>> Jacobe coming in hot to the Ultra Dome. >> How you doing?
1:37:23
>> Hey guys, thank you for having me. >> Great to have you. Great to have you.
1:37:27
Uh, let's get right into the gong worthy moment of this segment.
1:37:31
>> Tell us about the news. >> Yes.
1:37:34
So, today we launched a name out of stealth.
1:37:36
um was raising $71 million seed round and >> million.
1:37:45
>> It had been a while since I saw a 70 plus million dollar seed round and I feel more at ease.
1:37:51
>> Rivid capital >> having having so uh yeah yeah what what does the progress need to look like these days?
1:38:00
How uh how mature is the product?
1:38:00
uh how built out is the team to jump straight to that size of seed round?
1:38:08
>> Yeah, so we we're a team of 26 people.
1:38:11
Um actually uh uh grown pretty quickly and today we also launched something pretty unique.
1:38:16
Uh we launched like the first AI robotic experience uh online.
1:38:21
So people can just browse to a website uh to robots.
1:38:23
online and interact with real AI powered robots by our models and our interfaces.
1:38:29
So this is kind of uh um a double milestone for us both, you know, emerging out of stealth and kind of putting our technology out there at the same time. >> Very cool.
1:38:39
I saw the painter, which is a robot that you can control and, you know, paint in the real world.
1:38:43
I was a little bit frustrated because I had uh I I'd written been writing down notes and talking with a few people about somebody should set up a robotic arm with that lets you paint on real canvases and then send it >> like send it to yourself, but you're effectively doing that.
1:39:00
So you you beat me to the punch. >> Yeah.
1:39:03
So where where does the AI start?
1:39:06
Where does the tea operation end?
1:39:09
because uh I believe there's been demos of you know deterministic uh robot like remote control even like a remote controlled camera that you can pan tilt and zoom that's existed for a long time.
1:39:22
Um where does the AI actually come into the process? >> Yeah.
1:39:27
Uh so basically we have robots you can talk to them.
1:39:30
Uh so basically the idea is we put out different interfaces.
1:39:33
Um, one in some of the interface you're going, as you can see here, you can talk to the robot and ask it things and the robot just responds to you.
1:39:38
Um, we're going to also throughout the week, we're going to launch more and more different experiences and we're going to showcase different ways to interact with robots.
1:39:47
So, our company is a research heavy research lab, research heavy company that focuses on uh robotic foundation models, but we also think deeply and care deeply about the experience.
1:39:56
We think novel user interfaces are going to be uh a huge enabler for robotics.
1:40:00
So we kind of wanted to put out something that is very wide to learn how people want to interact with robots and take that learning and put it back to the research.
1:40:12
So in those experiments you're saying you're saying one robot that you can fight with uh like a robotic uh sword fight. Um so here it is.
1:40:18
Uh so one of them is controlled manually like a teley operation and this like which is the user and there is a robot that is an AI robot that responds to the user. So it actually fights.
1:40:29
So this is one way of interaction.
1:40:30
Another one is you talk to the robot something and you see what what it does.
1:40:34
So the painter you give it an association.
1:40:35
It paints it plays like a Pictionary with you.
1:40:37
Um and then after the experience you can like uh um ask it to do some pantomimes.
1:40:43
You can imagine the the brush is anything and it can be a wand.
1:40:47
It can be like cleaning the like as a broomstick cleaning the floor.
1:40:49
So this is where the AI comes in.
1:40:51
This is where our models our foundation models comes in comes into play.
1:40:53
Um and we wanted to showcase both interfaces and the models.
1:41:00
Um, what's your opinion on uh robotics sort of or robotic control coming for free in generalized LLM development?
1:41:11
I saw some demos of uh I think it was Opus 5 controlling a robotic arm.
1:41:17
It seems like a lot of these models uh they don't always need to be trained for something specific and then you wind up just getting some particular uh functionality for free or it's like a quick RL step on top of what the what the frontier labs are already doing.
1:41:34
Is that relevant to your road map or do you think there's a convergence or do you think you'll go off and and carve out a specific niche in robotics?
1:41:41
I mean obviously it's a huge category but how does that all fit together?
1:41:48
Uh it is a huge category. That's true. Yeah.
1:41:50
Um >> so I I seen the demo you're talking about.
1:41:53
I think it was anthropic. Yeah.
1:41:55
So we've seen those demos actually we had from GPT 3.
1:41:57
5 and before that we've had robots controlled by LLMs.
1:41:59
I think the problem that we're seeing, you know, labs such as ourselves um trying to tackle is the fact that this doesn't really either generalize very well or doesn't, you know, fit in with the requirements of like, you know, dexterity or doesn't >> it feels like cool demo but not necessarily commercially?
1:42:17
>> Yeah, it also might just be like it's it's impressive to be like, wow, language model controlled ARM, but if it's like every time it moved it was $20 in tokens and it was 45% accurate.
1:42:25
And if you just like did an actual model for the robot, it's like two cents and perfect.
1:42:34
That would be >> Exactly. Exactly.
1:42:35
[laughter] And and it's kind of one example one of my friends told me was was assume you could have had an LLM like do an ASI art and like paint as if it's ASI art, but we still have image models.
1:42:46
>> Yeah, not the nature like the natural language of of the way the LM work and that's why it's it's a bit off.
1:42:50
But but I do think that I think models for robotics is such as what we're building and what you know some other other labs are doing as well.
1:42:58
I think I think it's going to take a huge part of of how robotics is going to evolve.
1:43:03
And we're also very lucky to >> to be in this you know time of of great um tailwind right there's a great tailwind of research.
1:43:10
So we most of the team is doing research and we have a lot of table from you know LLM's research.
1:43:16
We take inspiration from that or from video models or from world models and that's pretty that's pretty that's pretty unique.
1:43:22
>> Uh time to time to revenue.
1:43:22
How are you how are you thinking about like first commercial application?
1:43:28
Sounds like you're in the age of research but when when do you see opportunity to start commercializing and kind of where? >> Yeah.
1:43:36
So we have partners we're working on working with right now um across different kind of segments.
1:43:41
So from logistics to entertainment to health as well.
1:43:45
Some cool things on that that we might uh uh talk about on those three categories. And there's more.
1:43:49
Um what we're seeing is we want to be able to get as much value to users and customers as fast as possible.
1:43:57
Um and make sure that when we are scaling it up, it's scaled up in the right kind of uh directionally right uh uh approach.
1:44:05
um because you don't want to be way off and then be dependent on um kind of kind of being a in a big tech debt I would say >> um and product debt.
1:44:18
>> Um but but I think I think we're at the point where we're also we're start we're seeing value we're seeing you know value from from from partners and and and it's actually a kind of showing a sign that we didn't expect to to to occur that that fast.
1:44:30
H >> how do you think about uh vertical integration?
1:44:33
It feels like there's robotics companies that are saying, "We're going to build the robot and the model."
1:44:39
There's others that are like, "We're going to build a modular robot and the model."
1:44:42
There's other companies that are saying, "We'll just build the model, and the robot builders will show up."
1:44:48
I haven't seen actually that many new startups that are like, "We're just building a dumb robotic arm that you can load whatever model you want on.
1:44:55
We want nothing to do with the with the actual AI inside.
1:45:00
We're just doing the manufacturing."
1:45:01
Maybe that's an opportunity.
1:45:02
where where uh where do you see your scope growing or staying focused?
1:45:09
>> Uh I think it's a great question because it really is a divergent kind of topic.
1:45:12
A lot of a lot of opinions.
1:45:14
>> Um we see ourselves as so we're a software software like first company right so we think we work with our product our kind of software stack from the models to the interfaces to to talk to them.
1:45:27
We work very hard on making it generalized across uh uh embodiment.
1:45:29
So we want to get to a point that even a new manufacturer comes out and says, "All right, here's a new robot.
1:45:36
I would want I would want to be able to within a week have everything work on that robot as if I had that robot for months."
1:45:41
So we're building a lot of infrastructure to be able to cut like this is part of our research like how to be able to calibrate all our technology across robots easily.
1:45:50
Um we think and we see a lot of vendors and we think doesn't have it doesn't necessarily have to be coupled.
1:45:56
Um, and we see a lot of, you know, great companies around the world that that sell the the hardware.
1:46:00
So, if we could be a good provider for the brain, um, and for the interface of the brain, we think it's a it's a very viable kind of product offering and I think it makes sense as well. >> Yeah. Yeah, that's cool.
1:46:12
I mean, yeah, obviously there are a ton of robotic production or supplier companies.
1:46:16
Uh, there aren't enough startups in that world.
1:46:21
I feel like I feel like we need we we we need like I'm a direct competitor to Cucka or something and I'll make a big robotic arm and they'll make it cheaper or whatever.
1:46:27
I'm sure there are out there. We probably talk.
1:46:29
>> What were you doing before you go?
1:46:29
What were you doing before this?
1:46:33
>> Um so I I worked I worked at a company I worked at a company uh acquired by Whiz and then we got acquired by Google. >> Oh. Um >> congrats. >> Yeah.
1:46:41
Um and actually me and Asaf the CEO of Wiz we go way back.
1:46:44
um when I was when I was uh 17, he he was running Microsoft in Israel and he brought me to join Microsoft.
1:46:54
>> Um and so we have a long history.
1:46:54
So I joined Whiz and and yeah, I think I think the era right now, >> long story short, generational run, [laughter] >> amazing.
1:47:03
Uh well, thank you so much for coming on the show, breaking it down.
1:47:07
Congratulations on coming out of stealth. Great demo. >> Thank you.
1:47:11
>> Very cool way to launch.
1:47:11
Huge >> and we'll uh we'll talk to you soon hopefully. >> I'm sure we will. >> Thank you very much. Goodbye.
1:47:15
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1:47:17
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1:47:20
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1:47:25
Up next, we have Dean Meyer from Sequoia Capital here to talk about America's open model paradox. I love a good paradox.
1:47:34
Also, fun fact, I heard somebody debunking Jevans paradox. It's not a paradox.
1:47:39
It's just just an effect.
1:47:42
It's just an economic effect. Is it a real paradox?
1:47:44
break down America's open model paradox.
1:47:46
Feel free to give a little bit of an intro. >> What's up, guys? >> But how you doing? >> What's up? >> I'm good.
1:47:51
Can you get Can you guys hear me? >> Oh, yeah. We can hear you. >> I hear you. >> Let's go. >> We can hear you. >> What's up, guys?
1:47:59
Uh, great great to be on the show. Thanks for having me.
1:48:01
on the show. Thanks for having me. Um, look, you know, my myself and and and my partner Constantine and Sequoia, you know, we've been riffing on sovereign AI for a while and I think kind of, you know, we wrote this post that went a little a little viral and kind of the
1:48:15
the core core concept was, you know, US is creating this frontier capability that kind of gets leaked into Chinese models and then you have the entirety of the American kind of builder ecosystem which is Neolabs, you know, companies that are somewhat dependent on these Chinese models. And so, you know, today
1:48:30
And so, you know, today there's like, you know, if you're an American lab and you can legally learn from a Chinese model, but you can't learn from a kind of frontier US model, which is what they're doing, then the question is how do we build kind of the, you know, the the legal path almost for this direct route?
1:48:46
Um, as opposed to just having this dependence on Chinese subway models.
1:48:49
Um, and so we kind of address that and and share a few ideas which I'm happy to talk about.
1:48:54
But that's kind of like the overall the overall thing.
1:48:57
Yeah, I mean there's so much uh there's so much news about this particular topic.
1:49:01
Uh the essay was written at the perfect time.
1:49:03
Um >> just just before Kimmy K3, man, it was uh it was good timing. We we had no intel. We had no intel.
1:49:09
Uh but I mean were you but were you a believer in uh in just the fact that uh the open source market generally lags the frontier by six months and that's not changing because there was this graph that was going around for a while that was showing that maybe the the the closed source was uh scaling on a slightly steeper curve than open source.
1:49:31
steeper curve than open source. And this was driving sort of a couple months ago when we were in between open source releases we people were starting to say oh maybe there they will plateau because the training cost will be so high that
1:49:46
you'll have sort of like what happened at Meta that will just happen in China because China will just say yeah like if we're going to spend a billion dollars on this training run it's not worth it to open source it but it feels like they found an economic model that makes sense. Kimmy's licenses out today and
1:50:00
Kimmy's licenses out today and they're going to take a portion of revenue if you're really selling a lot of Kimmy tokens.
1:50:06
And so, um, were were you were you was was this built on an idea that that the open-source and closed source frontiers would always be on the basically the same track? >> Yeah.
1:50:19
Well, I I I think I think look that is that is the question. Um, >> yeah.
1:50:24
>> yeah. And so look, our view is um I mean first of all like the the gap is closed a lot and so kind of the key conversation um online [clears throat] over the past week was you know is distillation the reason for this or is there some other kind of mysterious
1:50:38
reason and the truth is like you know there are two camps like everything you know people are are kind of extremist in in you know when when there's conversation everyone there's a group that are like hey dissolation does nothing and there's a group that's like distation everything. The truth is from
1:50:49
distation everything. The truth is from the conversations we've had um it's somewhere in the middle right like whether it's 20% 30 40 it doesn't really matter as much um it is meaningful that we know we know from the labs you know there's tens of millions of of of queries through these like large scale proxy distillation accounts um we also know on the other hand if you speak to anyone who's like leading in synthetic
1:51:11
data gen on pre or post training at the labs like they will tell you even if you do like hardcore KYC and then like let's say you get access to these kind like you know you don't have all the traces you don't have kind of you know like the chain of thought there's a lot of RL that happens right and you just get the output like let's assume you just get an output from a query from a prompt it is still extremely valuable like that is
1:51:32
100% true and so we know dissolation is real um and then the question becomes well if dissolation is real um you know how do we address the asymmetry that exists between you know if you're a western you know US company or you know
1:51:45
just a western company you're not going to like go and set up you know 35,000 prox proxy accounts with like different IPs around the world and go into stoanthropic for the fear of being sued uh and being called out and and even
1:51:57
being cut you know shutting off access and so there is the structural asymmetry um and and and I think it's something we have to think about >> so you have to create the meme token max yeah go ahead >> have to create the meme of token token
1:52:09
leader >> yeah maybe maybe uh do you think that anthropic or anyone else let's just say a a closed source frontier lab in America if they believe that they've been distilled by an international company. Should they just sue? Even if Should they just sue?
1:52:22
Even if there's no Even if there's no way that on any reasonable time scale that they're going to win a settlement or block anything, would it just throw down the gauntlet to say we're willing to put this into the the the official record under threat of perjury that we believe this is what happened and there's like a signed affidavit of their belief that there is wrongdoing.
1:52:46
I mean I I think they they probably would and nothing would happen like I you know I think nothing would happen and so anyway like you know US companies are are kind of deterred from doing this.
1:52:55
So I don't think it would change too much unfortunately.
1:52:57
Um uh >> it would be very symbolic.
1:53:01
I I I think it would be I agree with you.
1:53:03
I think I don't think anything would would change from the actual lawsuit.
1:53:05
It would cost some amount of money to file this lawsuit.
1:53:09
Uh but at least it would it would h they would have something to point to of like hey look we tried to go through the traditional path and you were able to follow along.
1:53:18
You were able to look at our evidence which was entered into the public record and oh yeah the the CEO of the lab that we're accusing of distilling us didn't show up to court or whatever.
1:53:28
You know whatever the process is the process can can begin.
1:53:32
May maybe this is like a day away.
1:53:34
Maybe this like the lawsuit drops tomorrow. Who knows?
1:53:36
But uh it seems like that's the next logical step because right now there's a lot of there's a lot of uh there's a lot of push back against like hey why do you have a problem with this? Oh maybe it's distilled.
1:53:46
Well, you know that's the next that's the next step maybe. I don't know. >> Yes.
1:53:49
So so Kimmy came out with their their license this morning and they they in the license it says if uh if you're just running it hosting this yourself for your own use cases that's fine. It's free.
1:54:04
But if you're effectively reselling it as a Neocloud, you have to give us a revenue share.
1:54:07
I can't imagine that Washington is going to tolerate that just just the idea the idea that like a bunch of US neocons are then sending billions of dollars back to to China to support one of their leading labs.
1:54:24
I just to me that feels like it could provoke a response that felt like it was maybe coming last week when different people in the admin were saying, "Hey, we're we're we we we believe dissolation is happening here.
1:54:37
We're we're we're proop against how they were positioning it, IP theft."
1:54:42
>> On the flip side, >> I was very quickly able to find a Bayga Vanetta dupe that comes from China and is effectively distilled on that brand and the government isn't stepping in about that.
1:54:53
you know, and that money is flowing straight to it through Amazon and through other platforms.
1:54:58
Sheen and >> Yeah, but it's not it doesn't have any geopolitical significance.
1:55:04
>> You're not you wouldn't go to war from >> and it's a a caring company. >> Yeah. No, that's true. That's true. Anyway, sorry.
1:55:11
>> No, I think look, I think look, I I was surprised to read that.
1:55:14
Look, the truth is like >> I think it's not dissimilar from the database market where like you know you had Reddus like early on there were range of these companies released really cool open source and like they just got the hyperscalers copied them effectively and like that was the end.
1:55:27
Um I just you know it's impossible to enforce um I I I like I don't think that will work um for for the Chinese.
1:55:34
Um but look the broader question here is like there are two major risks with like depending on a Chinese US e you know Chinese open source ecosystem.
1:55:43
The first one is the dependency risk.
1:55:45
Like the framing we have is, you know, in some sense, you know, at Sequoa, we always say we're only as good as our next investment, which we actually believe.
1:55:52
Um, and I think in some sense the analogy is like you're only as good as your next model.
1:55:58
And so, as long as you're dependent on the Chinese to give you the next like hit of, you know, of of the thing, you you're kind of you're kind of in a in a bit of a in a, you know, in a bit of a weird position where you have this dependency.
1:56:10
And then the other thing that I don't think people are kind of well calibrated on is just the risk of back doors.
1:56:15
And I'm not saying like just to be clear, I'm not saying that all Chinese openweight labs are backdooring models.
1:56:21
But the truth is we know for sure and there's like a lot of research on this both from the labs and outside the labs in academia.
1:56:27
It is like an NP hard problem to know if there is a back door in a model that we know.
1:56:31
So it's impossible to verify.
1:56:33
And on top of that, there's like a ton of crazy evidence that shows you can you can like time pull a model which basically you know one way of saying is like a model you could do all the evals you want um and suddenly like the you know it gets a certain input and the model literally changes behavior.
1:56:50
It will start like excfiltrating data and doing some crazy stuff and like this this stuff's real like this is not science fiction.
1:56:56
like this is not science fiction. we know um and so kind of the analogy I would give you guys is like I think the state of AI security today is like very similar to that of you know early days of the internet when like you know in in in in 2001 like Wi-Fi was like you know
1:57:12
Wi-Fi encryption was effectively broken like publicly broken and still like no one did anything um and I don't even think we're at that moment yet >> um and it's going to it's like it's going to get really bad if we like one don't better understand how to secure these things and two like build our own kind of independ dependent ecosystem. Um, and so yeah, those would be like
1:57:28
Um, and so yeah, those would be like some some thoughts as well.
1:57:33
>> There's so much more we could go into here.
1:57:35
Uh, we got to have you back on the show and talk more because like there's there's so much going on.
1:57:38
But thank you for writing the essay.
1:57:40
We'll let the audience go and read the full piece.
1:57:41
U great to have you on and come back soon.
1:57:45
>> I'm looking forward to the next one because it feels like uh the the conversation has already advanced so many different directions.
1:57:50
Uh we didn't even get into the the the the politics of anyone having a cyber weapon in their pocket.
1:57:57
There's all these different scenarios to play out beyond what you just mentioned which are a bunch of other considerations.
1:58:02
So uh it's a fun interview on uh we'd love to talk to you. >> Thank you so much.
1:58:06
>> Yeah, this was awesome.
1:58:06
Have a good rest of your day. Talk to you later. Bye.
1:58:11
>> Uh let me tell you about public investing for those who take it seriously.
1:58:13
They got stocks, options, bonds, crypto, treasuries, and more with great customer service.
1:58:17
Our next guest is Brent Franson from Death Clock.
1:58:20
He's the founder and CEO.
1:58:24
Welcome to the show, Brent. How you doing? >> I'm well. Thanks for having me.
1:58:30
>> Please introduce yourself and the company.
1:58:31
Tell us a little bit about death clock.
1:58:34
>> Yeah, so uh we trained an AI on 1200 longevity studies to predict how long you're going to live originally and then the model was predicting the exact day you would die.
1:58:44
And so we started sharing that and people like, you know, people either love it or hate it.
1:58:49
They want to see the exact day they'll die.
1:58:50
But more importantly, the model builds a plan, you know, to live longer.
1:58:55
It's not just about >> when you're going to die.
1:58:58
>> Is this a nod to Metal Aocalypse from Adult Swim? >> No, it's not.
1:59:04
Although that's one of the most the most common questions on the most common responses on social about Metal Aocalypse. Yeah.
1:59:10
And then just about like religious, you know, only God can tell you when you're going to die. >> Yeah. Uh is this rage bait?
1:59:15
Are you intentionally framing this?
1:59:19
Because you could have called it like like the longevity optimizer, but death clock it >> I don't think they would have gotten nearly as many users.
1:59:27
>> I agree, but what what what are your opinions about I mean I've literally like lived this as well.
1:59:31
So, I'm not uh I'm not actually uh you know saying that this is bad or anything, but I'm just wondering about how conscious the decision is to to use a word like death because liquid death, same thing where it's this aggressive name. It draws in attention.
1:59:46
What are your thoughts on on that as like an attention mechanism? >> Yeah.
1:59:52
I mean, I think there's a stoic component to it and so I do think that there is some I don't know, some good reason to be honest with ourselves about the fact that we're going to die.
2:00:00
But the real answer is I don't know.
2:00:04
Distribution really matters. It's hard to make noise.
2:00:07
And so we wanted to be really provocative.
2:00:10
So our goal is very much, you know, I don't know, the Howard Stern ilk of look, love us or hate us, just don't be apathetic about what we're doing. >> No, no.
2:00:20
I I I I think it's a good strategy for the modern era.
2:00:23
>> Talk about the new launch.
2:00:23
You launched free nationwide blood testing. Sounds good. Too good to be true. What's the catch? >> Yeah, it's not.
2:00:31
You know, people are really concerned about their data, and I get it.
2:00:34
We don't do anything with the data.
2:00:36
We don't share or sell the data.
2:00:38
But I think what's happened is we have a lot of these blood testing companies that do all this kitchen sink blood testing, and they charge you a lot of money.
2:00:46
>> And the reality is is blood testing is commoditized.
2:00:48
LabCore and Quest have existed for a long time.
2:00:50
These tests are not that expensive.
2:00:53
And the set of tests that you really need to understand heart health, metabolic health, inflammation, those are pretty inexpensive tests.
2:01:01
And so from an acquisition perspective for us, it made sense to say, look, let's give away a test.
2:01:08
You can get a sense of the platform and how good the plan that it generates for you is.
2:01:15
And then we think you'll do more testing and you'll go deeper and you'll convert to premium.
2:01:21
But, you know, giving away a basic test, it's in the tens of dollars.
2:01:23
The stuff is not as expensive as people think. >> Okay.
2:01:27
And and how many biomarkers is does the free test give you?
2:01:33
>> The free test gives you about 50.
2:01:33
But this whole number of biomarkers thing, it's the wrong way to think about this kind of testing.
2:01:39
And so, I think we've gotten into this place we think, okay, you know, 150 biomarkers is better than 50 biomarkers.
2:01:45
And that's not necessarily true.
2:01:47
I mean, when you run these blood tests, they've got about a 95% accuracy rate.
2:01:51
So, when you start just testing for everything, even asymptomatically, you're cranking up the odds of a false positive that you've got to go chase down with your doc.
2:02:00
And then you're in some diagnostic process that actually carries some risk.
2:02:06
>> And so, it's 50, you can do all of that testing with us, but it's more about getting the right tests.
2:02:10
I mean really understanding the right things about your heart health, your metabolic health, making sure you're doing the right cancer screenings.
2:02:17
So I wouldn't get you caught up.
2:02:19
>> There's like a power law in efficacy of biomarkers and there's also probably a lot of correlation between some of those longer tail biomarkers. >> Okay.
2:02:28
So so someone comes in technically you're you're having to fork over tens of dollars to get them a free test and you're betting that some meaningful percentage of them will be like this service is cool.
2:02:40
I'll stick around and access other services.
2:02:42
So, um it sounds like close as close as possible to a free lunch, which uh which I like. [laughter] >> Yeah.
2:02:51
I mean, it really is free.
2:02:51
There's no Yeah, there's no gotcha in it.
2:02:53
I mean, you do have to say no.
2:02:55
I don't want to I don't want to take um an Alzheimer, you know, I don't want to look for the Alzheimer's gene.
2:03:00
I don't want to do more advanced cardiac testing.
2:03:03
All of those things require you to upgrade.
2:03:06
But I think I think the future is one in which we're kind of acting as our own personal doctors.
2:03:13
We've got an AI that's got all of our health data and then we order the tests very surgically that we need at the times that we need them.
2:03:21
We're not just kitchen sink doing 15 vials, you know, every six every six months like, okay, I should go look at my liver health because of a medication I'm taking.
2:03:29
And you shouldn't need a doctor to do all of that.
2:03:33
And so that's what we're trying to make available mass market.
2:03:34
We're not going to be the high-end solution.
2:03:39
>> What what legally can can only a doctor do these days?
2:03:44
>> Well, medications, cancer screens, but I mean blood testing.
2:03:47
So, there is a >> blood testing.
2:03:50
I mean, obviously blood testing happens with labs, so those are licensed.
2:03:53
But then in terms of the interpretation of the tests that can sort of be democratized with AI and and individual uh like self-s serve products. >> Yeah.
2:04:04
I mean, you know, we have to disclaim that we are, you know, we're not a doctor and you need to speak to your doctor about any of these results, >> but there are, you know, the barriers are coming down in in lab testing.
2:04:14
I mean, so we every lab order that goes through death clock, it has a doctor's name on it, like it goes through an approval process, >> but it's very fast and you don't need to speak directly to the doctor.
2:04:28
>> Um, because there's no there's really no risk for most of these tests.
2:04:30
What were you doing before this?
2:04:34
>> I was the CEO of a company called Uclid Analytics, a benchmark and NEA back business that was acquired by Weiwork about 6 months before we work imploded.
2:04:44
It was a crazy crazy ride. >> That's wild. >> Wild.
2:04:47
>> Well, I'm so curious what uh Adam Newman had in store. We health maybe. >> Oh, yeah. >> I don't know.
2:04:55
He was a he was a he was a crazy charismatic guy.
2:04:58
He was one of those guys.
2:05:00
He's still alive, by the way. >> Yeah. Yeah.
2:05:02
He's still in [laughter] like he's dead.
2:05:06
>> But you would go sit and he would talk for two hours in these all hands. Wow.
2:05:10
>> And it would feel like it was 15 minutes.
2:05:12
But the day he showed up to an all hands in a suit, we all looked around like, "Oh, we're screwed."
2:05:18
[laughter] >> Talk to him. >> Question. Biological age.
2:05:25
How should consumers read into it?
2:05:25
It seems like there's this race to the bottom in biological age where the platforms have an incentive to to to rate someone as a lower biological age because they're more likely to flex it on social media or to their friends.
2:05:39
And then the other question I have is is that just comparing your that's just comparing your your labs to the average American and we know the average American is deeply unhealthy.
2:05:51
So, is it even when if I'm like I'm I'm 30 years old.
2:05:56
If my biological age is 25, is that basically just saying like you are healthier than the average American who is deeply unhealthy?
2:06:04
>> I recently did one of those tests and it said I have the mind of a 5-year-old >> biologically.
2:06:10
We [laughter] told this joke about it's funny every time.
2:06:12
>> It's every it gets >> it gets every time.
2:06:15
>> So, it is it is gamed and I think there are some companies that are pretty reckless with that.
2:06:18
they're telling you that you're young, that you're younger than any real, it's called a phenotypic age is what would be kind of the fancy name for it would actually tell you.
2:06:26
And so I I think that's a little concerning that people are doing that.
2:06:30
um the where it comes from there's a researcher at Yale who produced the most valid um calculation of biological age and it takes nine biomarkers and it's a little bit more it's a little bit fancier than just comparing you to average but I think that's directionally right and so I wouldn't put too much stock in biological age I would take very seriously heart health markers metabolic markers inflammatory markers and these are the basics.
2:07:02
It's like know what your LDL is, know what your hemoglobin A1C is, know what your HSCRP is, C reactive protein is going to give you a sense of inflammation.
2:07:11
And if you're paying attention to those things, you're going to do way more than, you know, caring too much about a about a biological age. >> What's your date? >> Oh, yeah. How long? >> Oh, my date is Yeah. So, mine's at 78.
2:07:25
It's like February 16th of 2065 or something.
2:07:29
is weird to get um an actual date, but the average user has 10 to 12 years that they can add.
2:07:34
So the model's also producing how much longer it thinks you can live.
2:07:39
And then anytime your health data is updated, the calculation it recalculates.
2:07:44
So my date changes every day, but when I when I started it was 78.
2:07:49
I partied a little too much.
2:07:51
>> Have you pitched a partnership with Nas Daily?
2:07:53
Are you familiar with this YouTuber, Facebook creator?
2:07:54
He wear he's obsessed with this concept.
2:07:59
He wears a t-shirt that has a percentage loading bar for how far he is through his life based on life expectancy and it's all a message about you know like enjoying every day.
2:08:10
But he gets like hundreds of billions of views or millions of lots of views.
2:08:15
Very very popular creator.
2:08:15
Uh would be a very logical uh sponsorship maybe one day.
2:08:21
>> Yeah, we should talk to them.
2:08:21
I mean, I think the the reality is is like we're all going to die and we're going to just be >> not me built different, but continue.
2:08:29
>> We are all going to die no matter what people are going to tell you.
2:08:32
And there are things you can do to live longer.
2:08:35
But >> no, [laughter] sorry.
2:08:41
We're having too much fun. >> Money never sleeps. You should either.
2:08:45
>> I I hope you're right.
2:08:45
Actually, [laughter] I really really hope you're right. I say you're not Agi. Yeah, not Agi.
2:08:53
>> [laughter] >> We're going to cure everything.
2:08:53
No, I I I I think you're right.
2:08:55
And I think just reframing mentally around what it means to be healthy, giving it people another visualization on what is typically just a bunch of random nanom nano nanom liters to decillers.
2:09:09
Like it's a bunch of random stats.
2:09:12
>> Also, people are people are, you know, getting health information constantly. At least I am.
2:09:16
Take this some do this or that.
2:09:19
I've always been into into um experimenting with with different protocols and things like that, but um sometimes you need to kind of jolt people. Yeah.
2:09:28
>> You know, so >> Well, I think it's fine if you're experimenting so long as you're as you're getting the basics right.
2:09:33
I mean, I think if you're getting a full body scan but not getting colonoscopies, that's wrong.
2:09:39
I wish I could throw, you know, throw the X up. Mhm.
2:09:42
>> But if you're like you've done the colonoscopy and you've done the mammogs and you've done everything then like okay fine maybe get the full body scan.
2:09:51
And then on the experimenting you got to be careful.
2:09:53
You know the story of theolyomide the doctors were prescribing that off label to pregnant women and then the babies were being born with like hands on their on their stomach. >> Really really gross. Really gross. >> Yeah.
2:10:03
So you got to you know the experimenting can be a little bit I think we're a little casual about the experimenting.
2:10:08
I'm not saying don't do it but >> yeah.
2:10:11
Well, thank you so much for taking the time to chat with us.
2:10:13
Congrats on the progress.
2:10:15
>> Thanks for filling us in, man. >> Fascinating company.
2:10:17
>> And yeah, free free blood tests out there.
2:10:19
Go >> death potentially a skill issue. Don't do it.
2:10:22
Anyway, thank you so much.
2:10:22
We agree we we'll agree to disagree on that. >> Have a guys.
2:10:28
We'll see if we die or not. I hope you're right. >> Yeah.
2:10:31
See you back here in 70 years. Goodbye. >> Cheers, Brent.
2:10:35
>> Let me tell you about Shopify.
2:10:35
Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
2:10:44
And our next guest is Mate from Adrian. How you doing? Welcome back. >> Hey, good. Thanks for having me on.
2:10:54
>> How are you guys doing? >> We're doing well. >> Great to see you.
2:10:56
We met at uh a long journey dinner forever ago at this point.
2:11:02
>> I think you've been on the show. >> We did.
2:11:03
And uh we also met at the the ramp dinner.
2:11:05
I think I was the infamous founder that snapped that phone if you guys remember that. >> Right. >> Oh, I missed that. >> This was this story.
2:11:11
I'm not going to say the guy's name cuz cuz uh he's a friend and and it's funny and it makes him look really silly.
2:11:18
But this this guy is sitting there.
2:11:21
He's got the new iPhone Air.
2:11:22
He's he's telling everyone in the room, you cannot possibly break this phone.
2:11:27
This phone is indestructible.
2:11:28
Anybody out anybody here try to break my phone. Try to break my phone. This guy goes, "Okay."
2:11:33
Just bends down, just snaps it in his [laughter] hand.
2:11:38
And the guy's the guy's standing there just being like just in shock and disbelief.
2:11:43
I thought I was told and he and he was saying he was saying uh I'm going to I'm going to email Tim Cook about this.
2:11:50
I [laughter] like I'm pretty sure that Apple never promised >> they never ran an ad was like it cannot be broken >> by a guy from the Gundo.
2:11:56
[laughter] >> So So So you are in the Gundo.
2:12:00
Tell us what you're building.
2:12:03
Yeah, we're uh we're in the greater South Bay area.
2:12:05
I guess you could consider it the Gundo.
2:12:06
I mean, we're super excited to announce our series A.
2:12:10
Uh but >> how much you raised?
2:12:12
>> Uh we raised $18 million.
2:12:20
>> Um yeah, Inum builds scalable sensing infrastructure for under sea domain awareness.
2:12:25
So think about like hunt for red October, finding submarines, unmanned underwater vehicles, semi-submersibles and so on.
2:12:30
So >> I'm going to maybe put it too plainly, but we don't really know much of what's going on out in the maritime domain. Is that correct? >> Yeah.
2:12:41
I mean, the maritime domain is getting more and more contested like daily, right?
2:12:44
Uh I think we have a good understanding of what happens on the surface of the oceans.
2:12:48
There's cameras, surface boats.
2:12:50
Uh but everything's kind of shifting into the undersea quite quickly.
2:12:54
You know, it's one of the most uh unexploited gaps that we have.
2:12:56
uh and a lot of nearpeer adversaries and terrorist organizations and so on so forth are starting to move under the waves.
2:13:04
So like this entire push of you know the US for example funding unmanned underwater vehicles our adversaries are doing the same thing and so the big question is like how do we find those things intelligently quickly give ourselves awareness of what happens around you know various parts of the ocean as well as like our strategic bases and so on. >> Makes a lot of sense.
2:13:26
talk about uh traction since the last time we chatted.
2:13:30
What kind of progress have you guys made?
2:13:31
Obviously, the new funding, I'm sure you have some great momentum, but uh what's been uh what what have you been actually executing on?
2:13:39
>> Oh my goodness, so many things.
2:13:39
So, I think from the the hardware and software side, like I mean, we've gone through three generations of hardware and since we last talked, uh we've been moving at breakneck speeds here at Andreum.
2:13:50
Uh we fielded it out across like numerous exercises.
2:13:54
Most recently, we just got back from a 3 and a half week deployment with uh UV group up in keyboard, Washington.
2:14:00
So, they're all the guys that run and like dictate how unmanned underwater vehicles run.
2:14:04
So, we were up there alongside with a few other folks.
2:14:08
Uh no mission ending failures for a three and a half week deployment.
2:14:10
Um obviously constantly testing here off the coast of California, building up our repository of sonar signatures.
2:14:15
Uh and we do have some things that are going to be coming up quite soon that we're super excited to announce when they hit. So, >> stay tuned.
2:14:23
What does integration with other defense tech companies look like now or in the future?
2:14:29
Like you know there's been like Anderol has a platform, Palunteer as a platform.
2:14:34
I'm sure a lot of different uh units have bespoke systems for command and control and all sorts of different things. Does that come for free?
2:14:44
Is that something that people are just like vibe coding integrations or do you have to go and like do a deal and and actually uh figure out how you integrate or or do you ultimately want to be you know your own platform that you know runs as like the operating system.
2:15:03
>> Yeah, I think it vastly depends on the type of technology that you're building, right?
2:15:07
right? specifically for us like sonar information is so classified and compartmentalized and uh it's it's very tricky to get access on data that has been compartmentalized such as this because you have numerous third party integrators that also own that data itself as well and so that is really the
2:15:24
reason why we went out and built Pearl which is our passive sonar buoy right as well as Obsidian which is kind of like you could call it a C2 but really it is like the platform that ingests all this information there's a bunch of like super sophific sophisticated machine
2:15:38
learning uh and effectively putting dots on a map for end users but uh the C2 in itself like there's various abstractions of it you know you have the god C2s that kind of live on top you mentioned those companies names uh we really are trying to own the undersea domain and by
2:15:53
building the hardware we're building up this massive repository of sonar signatures and that'll give us the option to then give that data to those other C2 platforms if necessary right so it really is like a a fine like a fine balance of what we have to be doing with regards to C2. But ultimately like every
2:16:09
But ultimately like every defense tech company that's out there needs to play well together because we all have to provide an integrated solution to the end user, right?
2:16:16
And we do have those relationships with primes and with other kind of startups as well. >> Yeah.
2:16:22
You mentioned that the data is hard to get generally you're doing machine learning which is obviously very data heavy.
2:16:27
Uh is there like a scale AI like a mer for this type of data yet?
2:16:34
Are you like buying data from like fishing boats or like is there some world where there is a scaled data benefit even not in a in a uh military context but maybe you just want to get a bunch of data on how sonar performs in a swimming pool or a lake or something that's more controlled and then you can transfer learn that into like the actual uh viable domain in the final application.
2:17:02
Yeah, sonar is super super challenging in the fact that you can't necessarily translate environmentals uh to where you are deployed, right?
2:17:10
So like with radar for instance, you just have air and it's pretty linear like the ocean does a ton of weird things with regards to performance of sonar.
2:17:17
And so you really have to be deployed and you have to understand kind of the environmental factors such that you can perform this highly complex math that goes behind all of it.
2:17:26
That's really the reason why we did build Pearl, right?
2:17:28
like that delivers that information in real time like we kind of get this information in sub 3 seconds worth of latency and we process it and we put dots on a map for end users.
2:17:39
We have that environmental feature kind of built into Pearl itself.
2:17:44
Um and you can do base level extrapolation kind of across the board with a lot of that but it's not super super applicable everywhere.
2:17:50
And so yes, there is data that we have accessed uh that is more offshelf for instance like how do whales sound right?
2:17:57
Various different types of whale things and at least in our you know kind of hot dog no hot dog paradigm we can say uh this is a whale this is not you know a submarine or some something like that.
2:18:08
So it definitely adds a little bit more kind of featurerich uh environment for the end user.
2:18:15
Uh but most of it is really hinged on the hardware that we're developing and building. Right?
2:18:19
So in this world of AI, you can't just access a massive repository of data and do a ton of AI on it.
2:18:26
You have to build it yourself, which is really like the reason why a lowcost scalable hardware solution is super super important for us to deliver that data in real time.
2:18:36
>> What does actually deploying a buoy look like?
2:18:38
Do you have to call the government before you do that?
2:18:44
because I I love the idea of moving fast and doing R&D and just dropping something in the water and that's probably fine, but at the same time like you're you could accidentally be spying on like a US submarine and they might not want you to be spying on them even if you're like a friendly, right?
2:19:00
So like what is the flywheel to get the permission to, you know, do the test that you need to do before you get the contract to prove that you can do it?
2:19:09
Like what's the sequence of events?
2:19:12
Yeah, I mean we're working handinhand with with a lot of these folks at the government, right?
2:19:15
And so like I I detailed the the deployment um in Keyport, Washington.
2:19:19
That is something that we scheduled prior going up there.
2:19:24
You know, we do a lot of verification and validation testing here off the coast of California, but it's kind of just like put it in the waters, see if it works, check it out, pull it out, and then ship it to the location with the end user and test alongside them.
2:19:33
We've done that kind of across the coast, right?
2:19:37
So we were in San Diego at a large fleet exercise at the beginning of this year as well.
2:19:41
And so it does require coordinating with end users, right?
2:19:44
But that's ultimately what we're looking for anyway.
2:19:46
Like what are the feedbacks that these folks give to us such that we can iterate much more quickly.
2:19:51
We could do that in our own engineering vacuum where we could just be talking to these people directly.
2:19:54
And that's what we really want to strive to do.
2:19:57
Um and we've gotten really positive feedback from them, right?
2:19:59
Like um other people build buoys. They're very large.
2:20:04
Uh it takes a lot of effort to put these things out like gigantic research vessels, you know, barges.
2:20:08
It takes a week to pre-eploy.
2:20:10
We just kick ours off the side of the boat, right?
2:20:13
And so when we give these things, these buoys to the end operators, we say, "Break them, test them, go deploy them yourself, give us the feedback such that we can put that into our loop of iteration." Uh and they do that.
2:20:25
They're super happy to break things, right?
2:20:26
And I think that's the most valuable thing that we can ask for. >> I love it.
2:20:30
Well, congratulations and thank you so much for the show. We'll talk to you soon. >> Great to see you. >> Keep snapping.
2:20:37
>> I was going to say don't snap any more iPhone airs, but >> No, keep it going. >> Keep it going.
2:20:41
>> Anyone has an wants an iPhone snapped. It's your guy.
2:20:43
Um, they're saying, >> "Who wants that? >> Who wants that?"
2:20:47
>> Sometimes I want my iPhone snapped.
2:20:47
Uh, Diego said, "John needs someone to clear his desk of Diet Coke every 20 minutes."
2:20:54
>> Can I get a recycling bin over here?
2:20:55
>> You're only on your third.
2:20:57
>> This is a typical typical day for you.
2:20:59
>> That's an important day.
2:20:59
We have Justin from Nvidia.
2:21:01
He's the VP of enterprise AI here to talk about NVIDIA launching the open-source AI alliance.
2:21:06
Justin, thank you so much for taking the time to come talk to us.
2:21:10
[applause] >> Yeah, thanks for having us.
2:21:14
>> So, can you uh start by giving I mean the we we we discussed the letter.
2:21:17
the we we we discussed the letter. I think a lot of people have read it but uh what what is your elevator pitch for the open secure AI alliance the letter how they interact like the overall project here the goals >> yeah I think um let's just say there's been this moment in the industry >> uh especially with this incident that
2:21:36
happened at hugging face where there's just this collective awareness across all the industry leaders that you know doing a lot of the work in cyber security out in the open where we can look at open models open harnesses is open uh safety evaluations >> as an industry is going to give basically the the broadest collective defense uh of our organization. So
2:21:55
So >> um that's why we put the letter out there.
2:22:00
That's why all these companies are kind of rushing in to talk about sort of the importance of uh of this initiative.
2:22:06
>> It seems like it's going extremely well. I I totaled it up.
2:22:09
I think 18 bill 18 trillion dollars of market cap has signed on across something like 35 companies and more.
2:22:16
Um I'm interested in what you are there any other outcomes or is this purely just avoiding a bad outcome because the whole framing is is basically uh don't ban don't do something.
2:22:30
It's don't take an action here allow the status quo to continue.
2:22:34
Is that the correct formulation of the of the proposal?
2:22:39
Well, I think it's a recognition that you always want to give the defenders of uh enterprises across >> really critical industries, financial services, energy, telecommunications an asymmetric advantage to protect their infrastructure.
2:22:52
And the best way to do that is you give them, you know, state-of-the-art frontier open systems uh that they can, you know, scan, remediate, patch their infrastructure.
2:23:02
Now, they should always have the advantage because they understand the code, the configurations, and how they have their infrastructure running, but they need access to the tools to basically get ahead of uh of any potential security issues. >> Okay.
2:23:17
Um I guess like the the steelman of the other side is that uh this isn't an asymmetric advantage to the to to the to the organizations that you described.
2:23:31
It's actually a perfectly symmetric advantage.
2:23:33
Uh the attackers will also have frontier open-source like great open source tools and uh if we if we allow open source to proliferate at least it will be balanced but can you explain a little bit more about where the asymmetry on the defender side comes because that sounds amazing.
2:23:49
We want the defenders to win but it feels like if everyone's using the same tools it's actually just a level playing field and this could just be a battle.
2:23:56
could still win, could be fine.
2:23:58
But what's driving the asymmetry? >> Yeah.
2:24:02
You gota remember when when you're running a service >> and you have terms of service, like you know who's who's accessing that service. >> Yeah.
2:24:10
>> Um and there you're putting additional guardrails on there on on safe use.
2:24:14
>> Uh you can also if there if people start to misuse the service, uh you can uh quickly patch guardrails uh and basically ensure that people are using uh the service appropriately.
2:24:24
So, so that in in and of itself should give the defensive teams uh the ability to run I'd say these these better capabilities to clean up their infrastructure, patch their infrastructure and then service providers that are hosting any of the models um you know should should run them with appropriate guard rules.
2:24:42
H how do you think uh the the equilibrium plays out if sort of you know the companies get like big companies get access to advanced open- source models.
2:24:57
So they're patching their systems.
2:24:58
There's they're doing stuff but there's still a lot of attackers out there.
2:25:00
Uh and there's this weird scenario that people have been talking about where uh a small business that might have a credit card stored here or some piece of personally identifiable information stored in a less secure system.
2:25:13
Uh now they're responsible for spinning up an open- source cyber security defense system.
2:25:21
Like what's the equilibrium that keeps uh the the long tale of organizations secure?
2:25:27
Yeah, you've got to still pair, you know, openness with strong safeguards like rules on malicious use. >> Sure.
2:25:36
>> Uh laws that prevent against milit malicious use and then obviously rapid remediation of anything that you know that's going on and um you know that the the conversation around open models is no different than the conversation around uh I mean I think open software. Yeah.
2:25:50
Yeah. uh and you think of open software whether it's uh Linux or Kubernetes or PyTorch um that that open software you know built the foundation of our economy 80% of our digital economy is powered by open source >> uh and uh I'll say good stewards of open source software can sort of debate open standards
2:26:10
>> uh in an open way they can look at evaluations they can look at uh patching and remediation uh and they can work collectively for the defense of uh of the US economy and I think we got to look at you know models the same way um you know as soon as models are out there in in the I'll call the public domain
2:26:27
you can fork them you can patch them uh and you can remediate any issues that you know cyber security people find uh in those models and so you know the goal of this organization is to have those conversations out in the public I think it's uh you know it's a an important conversation for all of us to have uh
2:26:44
but we want to make sure again that you you have uh I'll say a diverse set of tools at your disposal as a um as a cyber security defender so that you know if a model uh refuses to do the work that you needed to do you have other options to continue to defend your organization. what uh what like who
2:27:00
what uh what like who do you think will step into the role of like model evaluator or model tester because uh we were we were just talking with Dean Meyer from Sequoia Capital and he was uh uh you know illustrating a possible scenario where there's like a backdoor in a model or some nefarious thing sort of hidden below the surface.
2:27:24
So the model still tests well on benchmarks, you deploy it and then over time it does something nefarious.
2:27:27
Um it feels like again that's another big burden to potentially put on a small business.
2:27:36
But if there's some sort of you know American company that steps up and validates and tests maybe there's an even balance there.
2:27:44
How do you see that playing out?
2:27:47
>> Well I I think uh you know organizations like uh Red Hat have done this open source software right where they >> clear of CVEEs they they provide the commercial support to enterprises.
2:27:55
I feel like it creates an opportunity for businesses to step in and be able to do the same thing with open open models and provide the same commercial patching and support into into enterprises.
2:28:06
So I think that's a market that will emerge as we go forward.
2:28:10
Um but uh but ultimately I think uh allowing I'll call it cyber security professionals to continue to pentest and understand the limits of these models is what's going to allow us to you know build that life cycle to do uh patching and remediation of any vulnerabilities that can exist in these model weights.
2:28:28
Now the fact that they're open means you can test them and and understand the the limits of them.
2:28:34
The challenge is with a lot of the the model weights that might be hosted uh the terms of service prevent cyber security people from researching uh for and looking for any back doors in those as well.
2:28:45
So the problem doesn't go away whether it's hosted or open. Sure.
2:28:49
>> Um they can exist and I think the the spotlight of having more cyber security professionals you know evaluating these things is just going to lead to better collective defense.
2:28:59
Uh I don't know how much you can speak to the to what the Neotron team is doing but broadly what should organizations expect from from Neotron uh the family of models over the next uh let's say 6 months.
2:29:13
>> Oh man I uh I don't know that uh [laughter] I can I can talk about where we're going but you know generally our approach has been um has been like let's again do it all in the open.
2:29:24
Let's uh basically put the data sets out there that we're training into these models so people can understand the the data that blends that went into the models.
2:29:32
Let's put the model weights out there.
2:29:33
Let's put the training techniques out there and the evaluations out there and and basically use that as a foundation for building you know custom intelligence into enterprises.
2:29:43
enterprises. I mean that's the other part of the conversation that's lost is these open models are uh critical for enterprises uh basically building their own intelligence and basically maintaining I'll call it a reinforcement learning wheel uh or flywheel on uh
2:30:00
these open models so they can maintain their competitive advantage and so um so providing that foundation of uh data and open weights and data blends gives enterprises that now uh with Neotron they're really language models uh but we have a bunch of other domains of models. We have you know cosmos which is world
2:30:16
We have you know cosmos which is world foundation models.
2:30:18
We have alpio for autonomous driving.
2:30:20
We have Groot for v uh vision language action models for robots.
2:30:25
And so I think uh across industries the the idea of having these open models to build the startup ecosystem uh allow enterprises to domain adapt them and build their own intelligence is really uh important really for the for the future growth of our industry.
2:30:42
how important or can you give us some context on what you're seeing or hearing from uh other business leaders about the value of open source purely economically just we went through this token maxing boom I think every enterprise leader feels that AI is valuable but it can be very expensive um how are they thinking about efficiency right now with the current costtobenefit trade-offs and how Does open source change that?
2:31:13
>> I mean, I can I can put my Nvidia hat on here.
2:31:15
Uh we we are the same way, right?
2:31:17
We use all the Frontier models.
2:31:17
We love the Frontier models. Yeah.
2:31:21
>> Uh they are they're amazing uh for for driving efficiency and how we do, you know, software development and chip design and how we run a competitive business.
2:31:29
Um but you the the modern way to build applications now are really an ensemble of models where you want to use the frontier for where they're unique and they add, you know, differentiated value.
2:31:40
So like a really complex agentic plan, you want to run through the frontier model and then you want to use the the open model weights uh for things that are more trivial like document summarization and the two can complement each other to drive a lot more costefficient applications across the enterprise. >> Yeah.
2:31:57
And then anything that's been fine-tuned on your particular data that example from thinking machines with Bridgewwaterat like information pipeline obviously they got incredible performance at great at very low cost uh because it was a a unique use case that was going to run on a continuous basis and so they were able to get a lot of value. common sense.
2:32:16
It wouldn't make >> it wouldn't make sense to to hire you and then have you just be a BDR doing cold email, [laughter] you know, like you sort it wouldn't be a very efficient use of >> That's a great analogy. [laughter] >> Sorry. >> Yeah, sorry.
2:32:32
I was just going to say, yeah, I think um I think your point's spot on.
2:32:34
I think um you know there's a bunch of other uh you know model makers uh like like TML is a great company uh reflection um you know uh runway uh you know many different model makers across different domains and I think you want a rich ecosystem here uh you know of startups um you know building the future of what's possible with uh with this industrial revolution going on with AI.
2:32:57
So, um, we're just happy to, you know, advocate on behalf of, uh, the open ecosystem, but really it complements, um, you know, the closed ecosystem and, uh, all of it sort of has its its unique value here.
2:33:08
>> Uh, so the alliance is like pretty huge at this point.
2:33:10
Do you want to grow it a lot bigger or is this a solid enough base to go where you want to go next or will this be something that just continues to grow? What do you think?
2:33:22
uh you know I think uh the the the inbound requests around this is uh is is kind of blown us away uh by the the appetite and the interest.
2:33:31
Um I I think ultimately what we want to do is kind of work as a as a community uh and share sort of you know best practices.
2:33:38
know best practices. We also with this we put out a new agent harness um that we think is phenomenal at you know reasoning uh it's great at uh coding um and it's and it's great at cyber security tasks um and so if we all sort of share advancements in the open uh we can build you know the best uh
2:33:57
technology together and um and and you know I think some of the things that we'll keep working on as an ecosystem is I mean to your point what are the evaluations uh that we should be building um you know how do we test uh and you know I'll call it open models and and look for uh I'll say safety issues in those models. How do you start
2:34:14
How do you start to build um I'll call it more uh cyber ranges uh that you put agents through to understand how truly capable they are.
2:34:22
I mean I think part of the part of the challenge with uh this cyber security discussion is it's it's it's been overindexed on um I'll call it uh you know benchmaxing for um you know vulnerability discovery and vulnerability discovery is not the same as um you know like going through an an attack chain.
2:34:44
So, um, you know, I think we've just got to have more more, uh, like sane conversation in the open as an ecosystem on, you know, what are the right ways to, uh, safeguard this stuff, uh, and and put it to work, uh, and to drive the efficiency that it can bring us, um, you know, across every business.
2:35:01
>> Thank you so much for taking the time to come.
2:35:02
>> Yeah, great to meet you, Justin. >> Great to meet you.
2:35:03
We'll hope to talk to you soon.
2:35:05
>> Have a good rest of your day. Goodbye.
2:35:09
>> That's our show, folks.
2:35:11
>> Thank you so much for tuning in.
2:35:11
We will see you tomorrow.
2:35:13
There's a lot more news, but we can go through it tomorrow.
2:35:17
Uh, Starship launched and there's a beautiful video that somehow got taken down, so we can't even share it.
2:35:20
But, uh, you can go find it.
2:35:23
There's some cool stuff there.
2:35:24
Uh, anyway, go have the best afternoon.
2:35:28
>> Go have the best ever.
2:35:30
>> Have the best Monday afternoon ever.
2:35:33
Thank you to Cooper for always coming in at the market close. >> Good crew. The chat.
2:35:37
Thank you so much for tuning in and chatting. We do read it. It's a lot of fun.
2:35:43
Leave us five stars on Apple Podcast and Spotify.
2:35:45
Sign up for our newsletter at tbpn. com.
2:35:46
And we will see you tomorrow at 11 a. m. >> Goodbye. >> We love you. >> Goodbye. >> Goodbye.