20VC: Scale's Alex Wang on Why Data Not Compute is the Bottleneck to Foundation Model Performance, Why AI is the Greatest Military Asset Ever, Is China Really Two Years Behind the US in AI and Why the CCPs Industrial Approach is Better than Anyone Else's

24:13Do you see that as a core part of your business in the next few years as we scale the education curve? First of all, I think you're right. There's so much value to be generated from AI for sure, but then there's this natural question of where's the value capture going to be, right? It was this fascinating thing. If you go back and read a high output management by Andy Grove, there's these chapters around like, oh, for Intel, first we thought that this is where the value capture is gonna be, but then we realized it was gonna be in this other part of the stack and we had to migrate to that part of the stack and then we had to migrate again.

24:44And it's this incredible case study. I remember reading that and I read it maybe a decade ago in a different era of tech and I was like, this is weird, this doesn't feel very relevant. And then now in AI, you're seeing it once again where it's so new and so nascent where exactly where in the stack value will accrue feels like it's constantly moving. And I agree with you, I think that the models themselves, there's so much competition there. I don't know how much value accrues at literally the model itself, but everything above the model and everything below the model, I feel very confident that there will be value accruing.

25:16So for the infrastructure, I mean, Nvidia's the biggest company built on AI today, like they're the third most valuable company in the world. Nvidia is more valuable, you know, their market gap is higher than meta and Google and Amazon and Saudi Aramco I mean, it's really started like Nvidia is an incredible credible company and that's below the model and then above the model You have all these apps and these services that are gonna be built on top So I was arguing with someone this morning actually on the way here, though, and I was saying like yes Okay, we have notion AI and we have you know box the storage company who are gonna implement AI solutions into their existing storage products So you can extract information better.

25:52Yeah, have you seen the numbers? Salesforce are now growing at single digits, like Mongo and Albury at single digits. Point being, actually the commoditization of these features means it'll be better products for us, but I don't know if you'll get value extraction from that and the form of increased pricing. How do you feel about that? Yeah, so our thesis on this is there was this article that flew around the end of software, right? I saw this Chris Pike. You're from Chris Pike. Yeah, it was an intentionally provocative point of view, I think. So for those that haven't read it, what was the core premise just so they understand it?

26:24I thought it was like a brilliant comparison, but he basically drew this comparison of software companies today to media companies, pre -social media. The rough comparison was in the older days of media, you had all these incredible media companies, there were these high -end shops where there were like all these experts producing this very differentiated content, but then it got disrupted by social media and the internet broadly because all of a sudden you just had the Content distribution cost came down dramatically the world of media consumption turned into this like very broad Constellation where you would consume whatever media was produced by anybody those interesting to you and it was sort of like much more on demand versus being the sort of walled garden of large media producers and Basically this comparison to that's what's about to happen to software which is now the enterprises live with this walled garden of some small number of software providers and what's going to happen now with gender AI and all these other trends is they're going to have this constellation of all these different apps and point solutions and this sort of portal to that constellation of various software providers and This sort of like we're going to move from this current world of like smaller number of walled garden SaaS apps to this sort of much more decentralized Universe to agree with that It's intentionally provocative, right?

27:42But I think one thing that is true is I do think that enterprises and the world at large are going to demand greater levels of customization. They're going to demand greater levels of personalization and stuff that is really purpose -built for their business like a glove. The first tech company that ever did something in this direction was Palantir. You know, they got a bad rap for a long time because everyone thought the Palantir, oh, So there's a consulting company, but Pounder's point of view, which is provocative as well, was like, no, what we're going to do is we're going to go into enterprises.

28:15We're going to understand exactly what their problems are. And we help them build the perfect application for them that's built on the connection of their data and all that stuff. And if we can do that, then we're going to build something that's far more valuable for them than what any other software provider is going to be able to produce. And they did this obviously before, generally, via before all these tools that are going make this this motion a lot more feasible. But I do think there's an element that this is like the way the world is moving, which is now especially that the software production costs and software creation costs are going down so dramatically.

28:48We're going to end up moving towards a world where more and more of the software that enterprises consume are going to be customized and custom built and purpose built for exactly their problems. What does that mean in terms of the makeup of engineering teams of large end prices? Do they shrink? Do they focus on different things? Do we just have teams of the world's best prompt is what does that mean in terms of the changing structure of engineering teams? Yeah, well, I think software engineering in general is going to change dramatically. A lot of what developers spend a lot of time on today, it will not need to spend time on going to the future as the models get better and better coding.

29:22But there's certainly big parts of what they do, which are irreplaceable. And over time, I think that the part in particular that's very, very valuable is this sort of like general process of going from water to my customer problems or water the sort of like problems I need to solve and like translating those into engineering problems and scoped sort of like tickets almost that can be solved by an AI engineer. Everyone says that we're going to see the end of per se pricing like he said, Chris had that provocative article but I everyone was by the end of per se pricing. To what extent do you think we will see the end of per se pricing in this next way of software and especially with the data lens where you could see a more consumption based pricing model aligned, do you think that truly takes over?

30:05The reason that Percy pricing doesn't make sense going to the future is that at an enterprise, today, certainly most of the productive work is done by by their employees, done by people. But in the future where you imagine more and more of the work is done by AI agents or AI models, then Percy pricing doesn't really make sense as a provider provider of software, provider of solutions, you want to make sure that you're capturing the value that you're providing to the people, but also the value that your agents or your AI systems are producing. That shifts a lot of the world towards consumption based pricing versus perceived.

30:39One of my biggest worries is obviously we're in London. We specialize in many things here at Long Lunch Break and Regulation. And we're so diminishing on London. But my question to you is, I really worry that we're going to see regulatory provisions which stifle innovation because of consumer data, protection acts, and just unnecessary regulation around data access. Do you think I am justified? And how do you navigate the regulatory access to data question? It's a really important point, and I think that certainly what we've seen in the EU is a very restrictive approach to data. My personal belief, I don't think that more permissive regulations around data are at odds with being a liberal democracy.

31:25More sort of liberal data access provisions are in fact very compatible with being a liberal democracy. And I think that we as a society need to figure out what the right balance there is and how we sort of square the circle. But I think this is a very important question because it's almost like, I think in the United States, there's been a huge amount of effort and real regulatory effort on terms of, how do we ensure we do not slow down chip production? How do we make sure that we can keep manufacturing huge amounts of chips and the US won't be disadvantaged from that perspective. We need to take a similar lens to data.

31:58So how do we from a policy standpoint, both in the US and in the UK, frankly, how do we think about ensuring that as countries, we're not tying one hand behind our backs for future data production for these models? Do you think the US is currently tying one hand behind its back in terms of that? I'll put it this way. We're definitely not taking a pro data regulatory. What would a pro data regulatory stance look like? I've used a few things. I large data sets that do not lend proprietary advantages to specific players that need to be sort of centralized and made accessible to whole industries. So simple examples, safety data in, let's say aerospace, which is a hot topic, obviously.

32:39But safety data in aerospace should be collectively pooled for the purpose of advancing the entire industry forward. Or the data I mentioned before, or the example mentioned before, fraud and compliance in financial services should be pooled together and should build forward capabilities. So I think there's like entire industrial sectors where there should be some degree of data pooling to just push forward the overall industry. And I think what you need is in a lot of consumer facing areas, we need to work through a lot of the existing restrictions to make sure that those don't prevent AI progress.

33:14So one great example here is actually HIPAA in healthcare and all the PII and other limitations. Right now, HIPAA and all the PII regulations will more or less prevent patient data from being used to train AI models. But I think we can agree as a civilization, as a human race. We really want to learn from all of the existing medical data on how do we cure human diseases going forward. And so we need to figure out like how are we going to make it so that like there's very clear non -animization provisions or There's a there's a very clear and obvious way in which you can use existing patient data to improve future health outcomes I had actually the China apparently I come who said this on the show But they said that like two years behind the US in terms of AI progress I had that and I thought that is absolute shit And I think when you look at like data provisions and what the Chinese government will be willing to do in terms of data access and data provisions and regulation.

34:07I think if they ought to use behind that, we'll very quickly catch up. How do you see China being to use behind and do you agree with that? Two years ago, there were probably more than two years behind. When opening I first produced GP4 in the lab, China were nowhere near that. But just even the past few months, there's a Chinese company, 0101 .ai, that produced a model E large, YI, dash large, that is one of the best models in the world. I think it's just behind, so it's behind GPD40 and Gemini and Plod3 Opus. And it's the next model right behind that in the leaderboards. So it's one of the best models in the world.

34:46So we've already seen them meaningfully catch up. They are like Chinese, LLM and AI capabilities are, I would say right now, pretty close to Neck and Neck with US capabilities. And I think if you plot the path ahead, based on everything we've talked about with data, they have a clear shot at racing forward and racing ahead of us. It comes down to at its core, the CCP's system is incredibly good at taking very aggressive centralized action and centralized industrial policy to drive forward critical industries. And what we've seen even in the past few years or the past few decades, frankly, on solar, how the CCP has been able to make take industrial policy to the point of like being by and large the world later in solar.

35:28And then most recently EVs and how the CCP's system and approaches been able to create very, very cheap EVs. You're seeing this pattern play out over and over again where the CCP approach to industrial policy is not the most innovative. But once an industry has been established and it's about turning the crank, they are better at turning the crank than any other economy in the world. I am totally agree with you. I saw actually a chart. I can't remember who tweaked it yesterday, but I think it was either Elon or Bill Ackman. And it was basically showed countries different kind of creation of EV providers.

36:01and it should like the US. And it was like the US, I mean, without Taster, it would have been in the dumps because it would have only had the end -general notice, but China was like up into the right. Does that worry? It worries me a lot. You know, one of the elephant in the room topics, which I think is an AI community we rarely discuss, is that at its core, this AI technology has the potential to be one of the greatest military assets the humanity has ever seen. Let's say you had a GI, and you have one country with AGI, and another country without AGI, which one will win in a war? Well, probably the one with AGI is gonna figure out how to produce all the weapons, or we'll figure out a brilliant military strategy, or we'll be able to hack the other country systems, and it is potentially one of the greatest military assets that the world's ever seen, but it's even more of a military asset than NUX.

36:48And so, if you think about this, we're in a geopolitical environment that is increasingly tense. The amount of conflict in the world has been monotonous increasing in the past few decades, You're seeing these multiple wars being fought in the world and some of them without very clear paths to resolution And there are totalitarian leaders right now in the world many of them for whom like let's say China or Russia Had a GI today and the United States didn't I would imagine they would use that to conquer That's a really scary outcome for the world writ large and I think it's one that the Western world and he's spent a lot of our thought and effort towards preventing that outcome.

37:26Given that concern, should we not have closed systems? Obviously, open systems have a lot of benefits, but the challenge of open systems is anyone can use them and that means that Russia can use them, China can use them, and everyone has the same levels of access, well, supposedly so. Should we not have closed systems with what Yijia said? I think there's a bit of a dichotomy that must emerge. I think we need to think about the most cutting edge and the most advanced systems, those we will want to ensure are closed for geopolitical reasons, for military reasons, for whatever reasons, like as we develop systems that are genuinely so so powerful, we will want to keep those closed.

38:01That doesn't preclude us from making open, less advanced versions of technology, that frankly just have the ability to produce a lot of economic value. And I think that's where we are with Lama right now. Lama 3 in and of itself is an auto -military asset. yet. And I think that there's clearly a line underneath which I think it's totally fine to have open models. So that's what we need to be thoughtful about is where that line is and when we're getting close to it. Before we discuss some kind of company building principles which I do want to touch on, Tania's time, what does that foundation model layer look like?

38:31Who's independent? Who's been acquired? What does it look like? I think at its core, what we've seen about the foundation model race is that it is incredibly expensive. And it is expensive to the level of, you know, these malls have gone from crossing hundreds of millions to a billion dollars to maybe multiple billions. I think in 10 years time, maybe they'll cost tens or hundreds of billions. There's just not very many entities that have that much discretion in capital to invest into these AI models. So naturally, what will happen over time is AI effort, the foundation law efforts will coalesce around nations or the large tech companies over time.

39:09Basically you will see the most all these hyper -profitable business models whether that's a nation state or one of the hyperscalers those will be the only entities that could possibly subsidize or underwrite these massive AI programs. In the future already it looks like a battle of giants but at that point it's even more a battle of giants. So do you agree with me in saying that you'll see all of the small players acquired by the large cloud providers who Google your Amazon and you're in video you name of your logic and components, but especially the large cloud providers and how they're integrated in 30 system solutions.

39:39Yes, with maybe an asterisk that there's some of these partnerships that I think it'll be interesting to see how they play out. You know, the opening, Microsoft partnership or the Anthropic Amazon partnership. One of the most interesting questions of this technology era is how do these partnerships actually end up playing out long term? Listen, I do want to touch on some company building principles. Let's start with, I can't remember the exact thing. You said it on PR. It was a brilliant statement. This was it which is the best P .O. is no P .O. What did you mean Alex? At its core, the traditional press industry is not particularly conducive to great companies being built And let me be more specific around that.

40:15A lot of traditional press is oriented around generating clicks And so the traditional press engine will it'll build you up and it'll generate clicks on the way up And it'll tear you down and generate clicks on the way down This is in contrast to I think 20 VC and other direct outlets so to speak, were founders and companies of a direct channel to get their message out and explain what they're working on? You know, I think the other thing, and I actually think it's a little bit unfair, I feel for traditional media, I don't care about clicks. Like, yeah, we have sponsors, respectfully, if we didn't have them, but still we're doing the show.

40:48I don't do sensationalist headlines, I'm not going to put some glossy thing, scale AI, I predict is military devastation, with this episode, because I'm not there to just optimize for clicks. Exactly. Yeah, you're there to genuinely educate and explain what's going on to your audience. It's almost unfethered. Can you imagine if someone said, hey, I'm gonna do scale AI. But I didn't care if we lose money. It would be like, oh fuck, how do I compete with that? Yeah, it's pretty stark. You know, I feel like I've received more fair treatment testifying in front of Congress than I have from various media outlets over the years.

41:24It feels like this totally ridiculous statement, but I think we're in this perverse state of a lot of traditional media where this system itself, you know, because of this sort of like very click oriented approach versus a genuine educational approach, it almost has no way of being fully fair to the companies. And so I think it's the imperative is on the companies themselves to properly tell their story through direct channels and through podcasts and through avenues where their message won't be altered. I completely, I think this is why Founder Brandt's day is more important than ever because if you don't own your means of distribution, it will be contorted.

42:00Exactly. It's kind of a shocking state of the world, but it has that changed your strategy then. Yeah, I think for us, we think a lot about how do we get the direct message out there and how do we develop to your point like, what are the purest ways that we can transmit and explain what we're doing? And this is a great example. You know, you'll ask me a question. I will answer exactly how I believe that I think, and this will go out to your listeners and your viewers. One of the purest forms of getting the message out there. I think one thing that people make a big mistake on those is that they then try and build the direct channels for the companies.

42:30And respectfully, people don't follow scale. People follow Alex. It's much easier to build followings with personalities than to those companies. I think there's just, I think there's like so few companies that can open a eyes one where like, I think OpenAI's and NAD has a lot of meeting as a brand. But very... It does, but if you look at the amount of times that Sam Altman trends versus the amount of time that OpenAI trends, it is disproportionately higher to Sam Altman. People still now more than ever love the cult of personality. Yeah, that's a fascinating thing. I mean, that definitely should be...

43:02And that transcends actually when you look at Lionel Messi at Miami, when you look at Margot Robbie with Barbie, the slabbitization of individuals in organizations or in movements drives everything. That's fascinating. I mean it probably speaks to a deep a deep human need I think we as people we have a lot of circuitry to understand Individuals we have this ability to understand individuals. It's very hard to understand what an organization means There's no intuitive so ship founders give a shit about traditional PL should they care about getting in that traditional press? I would argue no I would argue we're in an era now where they they shouldn't they should think about what is an interesting point of view They can have what is the most pure way to get that point of view across when do you feel the prostrate to tie you down on Fali.

43:43We've had, I would say, that almost precisely we've had this story where we had an incredible rise up and an incredible come up. Maybe we initially became a unicorn back in 2019 and for the few years after that, it felt like smooth sailing. And then starting in about 2022, when the entire media narrative was tearing down tech companies. because in some ways it was very fair. Many, many tech companies received very high valuations. There was an incredible amount of excitement in tech and then the markets all crashed. That, in starting in 2022, was when I noticed for us specifically, the tone entirely shifted, where it was the media engine pointing itself towards pointing out all the missteps from companies like us or a lot of our peers versus trying to take a balanced perspective.

44:33And there were even another example of this is So starting in about 2020, we began working with the US military and the US DOD. This is obviously long before the current defense tech hype wave and long before all that, but it was driven by an intrinsic belief that we had as the I had and we had as a company that it's important for the United States DOD to have access to incredible AI technology. That was like a fundamentally important thing for the future of the world. And in the years after that, by and large, the traditional media engine actually tore us down for supporting the US government and supporting the military versus taking a broader view that maybe this is a positive thing actually to support the US military.

45:16This almost goes to what I was saying about the dichotomy and treatment and, you know, testifying in Congress versus with the media. I testified before Congress about AI's use in the military. I would say the treatment I got there, I think, was a properly broad one. It was, hey, obviously this is powerful technology that we need to be thoughtful of, but it is so important that America leads in this. And thank you for everything that you're doing. That, I felt, was the response. Whereas in the media, it's this incredibly scornful perspective around, is this a good thing? Do we trust this company?

45:47Like, what does this mean? I mean, it's this shocking. But I think it goes back to the incentives to our outcomes. And what is the incentives of media versus the incentives of Congress? Congress will not let us sell you or clicks. Then I hopefully get to an informed decision on the best outcome. Exactly. Yeah. Okay. On the incentives to our outcomes, I loved something. You also said, you said, why hiring people who give a shit is harder than it sounds. What do you mean? And how do you think about that when hiring? If you hire people who we say give a shit internally, but who really, really care, you their work product, they really really care about the quality of their work.

46:22They really really care about the organization. They care about making sure that the company has an impact. They just really care. And what that means, how that manifests is they're willing to sweat every single detail. And if they get road blocked or there's like something in their way, they'll spend the extra, they'll go the extra mile to make sure that they get through those things. That's how startups work. These small teams of people who each care ten times more than the average employee, ten or a hundred times more than the average employee inside a big company, You end up just solving so many more problems than than the big company.

46:51How many people do you have in scale today? We are about 800 people. 800 people. You are now getting to the kind of bigger company size. It is harder, you know, the kind of only higher A++ or A++. A++ by definition, a rarer. Can you have 800 A++? I think the answer is yes. You know, what we say a lot internally is how do we hire the Navy seals, not the Navy? Not there's anything wrong with the Navy, but how do you have, you know, a really small elite group where you're really hiring the cream of the crop. And this goes down to process. You know, for us, at this point of the company, still I approve every hire.

47:25I will either indirectly interview or look at the interview feedback and look at the understand every single person who we hire to ensure that we're keeping an exceptionally high bar. And that way, if there's... What percent of the time will you go against the recommendation of the team on a new hire? Maybe on average, 25 to 30%, like a lot. Wow. Like a lot. And I think usually it's due to, you know, maybe there's a new hiring manager who, you know, needs to get calibrated or it's like an edge case of various forms. But to me, the way I think about this is like, I, as the founder of the company, I have seen everybody who's come in and I've seen who succeeds and who fails.

48:01I have, as an algorithm almost like, developed the most fine grain data set of understanding what it looks like for people to be successful at scale and what it looks like to have the Navy SEALs versus the Navy. and it's my job as a founder to help ensure that we as an organization are actually utilizing all this knowledge and utilizing all this learning that's been happening over the past eight years in the organization and carrying that forward. Finally what, what was your biggest management leadership fuck up? So for an example, for my name, people act out of fear or freedom. You know when you bring someone in, some people act out of like you have to perform, you have to perform, and other people act out of hey I trust you, I and you just have to identify which camp someone's in and then hopefully if they're skills there, they should operate to their best.

48:48I wish I'd known that when I started and I didn't and I just tried to act out of fear for everyone there. What do you know now that you wish you'd known and why did you fuck up? The biggest one was actually, you know, in the same era of like 2020 -2021, was thinking that hypergrowth is a company meant that you had to hypergrow your team. In those few years, we did were a lot of tech companies it. We like double triple the team here on year in 2020. We were about 150 people by the end of 2022. We were over 700. It was this insane amount of hiring and this incredible amount of hyper growth as a team.

49:26What I found out is when you hire that quickly, it is impossible to do what we just been talking about, which is maintaining this high bar and maintaining this feeling of excellence within the team. Did you see the reduction of that bar in real time? It was kind of subtle. It was something where you would hire all these people in and you'd notice it like the next year or the next six six months later. You would notice it slowly and that the organization, you know, there were challenges that the organization used to be able to to deal with and solve that slowly just calcified and we weren't able to we weren't able to get around.

49:58And so you'll notice, you know, from the end of 22 where I said we were 700 people to now we're 800 people, team has mostly kept the same size. But the company the revenue of the company has grown dramatically. It's funny, companies have like brand inflation points, they go hot, they go cold, they go hot again. Do you know what I mean? It feels like from the outside, scales hot again. Well, that's uh... I don't mean that like to be super nice or not nice, I didn't mean it when saying you're cold, but it's just weird how brands have moments of heat and not heat. This is a fascinating thing actually.

50:29I actually asked Patrick Carlson this question as well, and Stripe obviously is an incredible company that has, for a lot of their lifetime, I think it's been one of the iconic Silicon Valley companies. And I asked him whether or not he thought that the fact that they were such an iconic company was beneficial in all the hiring they did. And he made an interesting point which was that the best people they hired, he thinks would have been people who would have joined whether or not they were the hottest company in Silicon Valley. It was the sort of like off the beaten path people who were actually the best hires they could have gotten.

51:04And a lot of the people who joined because they're with the hottest company in Silicon Valley for one reason or another weren't necessarily the most valuable employees. And so there's this there's this element where I think the common belief and the common narrative is like you want to be the hottest company so you can track the best talent so you can hyper grow So you can then go keep growing and anything that's often so so difficult and it's much more about like How do you develop an ecosystem of talent that is like very self -preserving? Keeps a very high bar and always seeks out and searches for the best people and then an independent of whether the company's heart or not heart because you will have to your point.

51:37You'll have moments where your heart wants to your not heart, moments where your heart not heart. And you need that talent ecosystem to be self -preserving independent of that to drive the best out. I also think it depends on functioning. Like when you look at a lot of go -to -market functions, traditionally for sales, they do like concentrate towards hotter brands. And actually if you can get a concentration of incredible sales people, especially as you expand yourography, something about open AI is kind of go -to -market team in London. Unbelievably good, one on the best in London. And it's because they have an amazing brand.

52:02GCO, I mean, so it depends on how close you are to the nucleus and what function you're in. Yeah, I think that's right. Yeah, yeah. But then if you look at core technical development of OpenAI, a lot of that is still driven by people who have been at OpenAI since before they became the hottest company ever. You know, another company that I think experiences to go through this is Airbnb, Brian Chesky, right? And I think that, you know, he's talking about this publicly after the pandemic, he all of a sudden realized like, hey, I have to kind of rebuild be built the entire company. And he massively shrunk the team, he invested a lot more to talent density.

52:35And then he built the team to remain small. And I think that they're even now the most or one of the most profitable companies per head in all of tech. And that's because of this sort of this realization that he had that he didn't need to keep growing that team to see the financial gains or the financial output. At least I want to do a quick fire. So I'm going to say a short statement, you give me your immediate thoughts. So that's not OK. Yes, it's OK. So what if you change your mind on most in the last 12 months. I think it's actually everything about this hyper growth stuff that we've been talking about.

53:03And it's really around divorcing team hyper growth from company hyper growth and extra investing into quality and excellence. What's the biggest misconception you hear most often about AI? I think the biggest one today is all that's between us and EGI's compute and I think we need data to get there too. Tell me, you can have any board member in the world who you don't currently have. You have an amazing board, but you don't currently have. Who would you choose as your next ball member? This is a great question. You know, I think, obviously I don't think this is practical, but I do think Satin Adela has been one of the most brilliant business strategists of the modern era.

53:43What he has accomplished at Microsoft is just staggering, and I think any board would be very lucky to have him. Unfear one for me to ask, but I actually like it, which is, What question are you not asked or are you never asked that you feel you should be? That's an interesting one. The interesting one is like how My perspective on AI has changed in the successive eras and I mentioned this because I started the company in 2016 The first three years of the company were just full focus on autonomous driving Not autonomous vehicles and then in 2019 we actually started working on a gendered AI We started working on the opening eye on GPT -2 and so we are one of the few AI companies that I think has seen multiple eras of the technology and has seen the sort of the first boom and bust cycle with autonomous vehicles.

54:29I think it's an interesting one which is like what's the same in these six different and what's different. That's an interesting question. How's your view changed? Are you most excited now? I'm quite excited but I think there's also reasons to be cautious. In autonomous vehicles one of the things that happened in the autonomous vehicle craze. There There were a lot of promises that were being made that were divorced from the technical reality. So a lot of the prominent automspilko companies, a lot of the prominent organizations were making bolder and bolder promises to be able to raise money. Those were at first they weren't super divorced but over time they became more and more divorced from the technical realities.

55:09That resulted in this very painful trough where the promises weren't met and so it felt like the entire industry is falling apart. And actually, at the end of the day, you know, now we have Waymo's driving on San Francisco, perfectly proper L4 autonomous vehicles driving around. Tesla autopilot has gone really good. If we had more measured promises along the way, I think now we would feel amazing about autonomous vehicles, whereas instead we went through this huge up, this big down, and maybe it's sort of like on the upswing again. I think this is one of the big concerns I have about generative AI, which is, I hope not, but the same thing might happen again, which is that we have these really big promises that are starting to get made about the technology that get divorced from technology reality.

55:53And then that creates the sort of gap that is bound to cause a hangover. Will Trump win the ultimate one? I still think it's a toss up actually. US elections are so strange to think about because it always gets decided by the swing states. Frankly, I don't trust anyone on the coasts to have any fine -grained understanding of how the swing states will play out. I have no idea. I don't think anybody should listen to anybody who lives on the coast to understand what's going to happen It always boils down to the swing states. Final one for you my friend. What scale in 10 years time? You know hopefully doing something very similar what we're doing now Which is continuing to be the data foundry for AI and serve the data pillar for AI progress.

56:33Would you like to go public? For sure. Yeah. Well one thing I think a lot about is how do you solve problems that will never go out of style? Like would you like to be the CEO of a public company? Do you know what I mean? if you were Stripe. There's clear benefits to being a public company for sure, but I think Stripe is an incredible company in that they can be incredibly profitable and they can accomplish all their core financial goals without needing to go public. There's an Alex, I love to have you on the show. Thank you so much for joining me. Alex said it's so nice to do this in person. I'm sorry for the many kind of meandering pivots and tards, but this was fantastic.

57:06Yeah, this was a lot of fun. I have to say I absolutely love doing that conversation with Alex. I want say a huge thank you to him for being so open and honest with quite a few of those revealing questions. If you want to watch the full episode live in the studio and you can jack it out on YouTube by searching for 20 VC that's 20 VC on YouTube. But before we leave you today, as face it, your employees probably hate your procurement process. It's hard to follow, it's cobbled together across systems and it's a waste of valuable time and resources. And as a result, you probably are facing difficulties getting full visibility, managing compliance and controlling spend.

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