Uncapped #40 | Vinod Khosla and Keith Rabois from Khosla Ventures

25:48Yeah, you definitely have to be able to tell a story, right? Like at the end of the day, you have to convince people. Like you haven't proven almost anything usually in the beginning. Right. And you've got to convince people to come along on the journey with you. Yeah. Those are investors, early beta alpha customers, employees. You have to retain your employees in a hot market. Like you're doing some version of that constantly. When you look back at like a bunch of like the greatest investments over the last, let's say, 15 years to go back, like an Airbnb or, you know, whatever. There's like a bunch of companies that were like not hot early and like everybody passed.

26:18Is that still the case, do you think? Or do you think that it has become more like has the consensus become more accurate or is it still the case that like it's random signal? I don't think it's random at all, by the way. Go ahead. I mean, I think, for example, like let's talk about like Airbnb. be. To me, it was obvious. Three minutes into Brian's monologue, I was like, this is the coolest thing since YouTube. Literally told him this, told him exactly why. It was so obvious. I needed to meet him. And I didn't like the Arab bed and breakfast name that they were using at the time. So I kept referring the meeting, which was a very costly decision for me.

26:50That's at the end of the day. If you met Brian for three minutes, there was no way of missing this. This team was very special. And he was able to convey a couple, three key things he said in the three minutes that I was like, oh my God, this is really, really amazing. But you saw it, but most people didn't. Yeah, but I'm saying it's not random. Or like you saw OpenAI, like some of the companies we all know. The key investment decision, literally, like if you read our memo, which he sent to the LPs because it was so much of an outlier at the time, was this outside Google and DeepMind specifically, this was the only critical density of research grade people that could possibly pull off AI.

27:27That was the investment hypothesis in like a sentence. Given all the other stuff, like it was a nonprofit, you know, there was no product plan, no revenue plan, just this AI capability. It's the only time in the history of 20 year history of Costa Ventures. We sent an apology letter to our LPs when we made the investment because it was twice the largest investment we'd ever, initial investment we'd ever made. We sent an apology letter. I know it makes no sense, but we're doing it anyway, not asking for permission. It's really that letter is now part of our fundraising deck. Wow. But we sent it in 2018.

28:13Yep. And then here's a good example, too, of Raider Grove. Like, it did help a lot that David, me, and Vinod all knew Sam for a long time, a sustained period of time. So you could see certain lines there and the critical density of talent that he had assembled plus certain traits about Sam specifically led to that investment. Do you think that as time has gone on and like more people are in tech and there's more founders and more investors, do you think that there's any increasing, not from people who can really see it, but from the average reception to investors? Do you think that the consensus hot deal is becoming any more or less likely over time?

28:54You know what I'm kind of - A hot seed? I don't think so. You think it's still the case that like these hot seeds are no better than the non-consensus seeds? Personal opinion? I agree totally. Because it's like - We're talking about like Rocket Lab, which is one of the best investments anywhere. No, I mean, I don't think they would have raised money from anybody. Well, it's worth 40 billion now, but we bought a third of the company for$5 million. Yeah. And nobody wanted to invest in space. Or Commonwealth Fusion probably. Or Conwell Fusion for Fusion or even OpenAI, right? It wasn't, we were the only venture investor in 2018 that committed because it didn't make sense.

29:37I think at the seed level, consensus hot bets are generally around people, not around the idea. Yeah, it's like, you know, if you have two people who left, you know, pick your super hot current, you know, two people leave cursor. or, you know, it's like an engineer and a, you know, designer leave cursor tomorrow. Like what's that going to go at? A lot. But a seed investment around, let's say undiscovered people. Yeah. I think the consensus ones aren't going to outperform the outliers at all. Maybe just talking about like themes that you guys are interested in. I know that you're mostly focused on people, but, you know, you also care a lot about markets and technologies.

30:14Maybe to like start with AI and then we can go outside of AI. So obviously AI is like in the midst of playing out. I don't know what inning it's in. but it's one of the early ones, probably. You know, I think there have been like a lot of changes to like what, you know, the labs say that they're focused on and maybe like the types of companies that are getting funded is adjusting a little bit if you sort of like just like kind of track every six months or so. I'm curious what you guys see as the lay of the land for like outside the labs, where you think most of the opportunity lives, what you're most interested in, what you think is going to be like a big deal in the next year or two.

30:44Well, that's such a broad surface. Of course, sorry. I think I was counting the 30-some startups in our portfolio that are building an AI worker or some sort. Yeah. An AI oncologist, an AI mental health therapist, an AI chip designer, an AI structural engineer. As many professions as there are, there's that many opportunities. Basically to fully do the work. Do the work. Yeah. So one thing we decided a couple of years ago, probably three years ago, we wouldn't do a lot of co-pilots. Co-pilots had just come out and we said, co-pilots, humans get in the way, let's just do the work. So we love really people doing the work as opposed to helping a human do the work.

31:35Now, there's exceptions to that, but mostly that's true. Mm-hmm. That's a big category. So we haven't invested in any competitor to OpenAI, obviously. And we should come back and talk about it. We are fiercely loyal to our companies. We can talk about loyalty. Well, OpenAI, I think I was the very first one when Sam got fired to come out and say, we'll fund Sam for whatever he wants to do next. Yeah. Is the loyalty, does that stem from sort of like a business? decision or idea? Or is it stemmed from just like, this is how it ought to be? Like a more ethics kind of thing? I think this is how it should be.

32:16It's about ethics. And if I disagree with them, then my job is to sit down, tell them why, and agree that we agree or disagree before taking the right position publicly. Yeah, if we believe on the principles, like for the point, if you have principles and you believe you're on the right side, than we're willing to use our brand capital audience to help. Yeah. But along those, the AI question you were asking, we've invested a bunch in all their other approaches than transformer models that make sense. And we probably have four or five different efforts that they don't have to replace transformer models, but they're different.

33:04Because I think the big labs are doing transform models really well and then doing some other things. So what else do you think is promising? Look, it's too early to have. So I think any of us who pretends we know this technique or that neurosymbolic technique, we have a bet on category theory in math. We have a bet on interpretability that leads to different models. We have diffusion models. There's plenty of others. I'm very excited in real world models. Yeah, I was just going to ask you that. So I think that game hasn't played out yet. It's not clear at all who will win. Yeah. It's very clear what the major labs will do in that area.

33:49And at least the major labs all have efforts. But I think it's completely up for grabs. And you have no doubt it's going to work. It's just a matter of how and what. So I have zero doubt it will work and work increasingly well. And it'll be embodied robots that are... It'll be embodied and more than that. Understanding the physical world. Yeah. Let me give you an example. This is a public clip we showed. Intuition is a very big deal. And I don't think current models embody intuition. So we have a company called General Intuition based on gaming data. And I saw a clip of this live feed of Ukrainian soldiers trying to escape Russian attackers.

34:39And then we gave the AI half the clip and said, replicate the other half. It replicated the intuition of the Ukrainian soldiers trying to escape almost identically. That's intuition. There's many dimensions like that. But there's many obvious ones. You know, we all talk about the fact that frontier models hallucinate. And there's probably not a good way to avoid them. There's ways to minimize them. And the labs will do a pretty good job. But you see the hot agent startups like Sierra and Decagon. They're completely, I think, missing the point. We've focused on customer support agents that do not hallucinate.

35:23If you're a bank, if you're a Visa or MasterCard or insurance, you can't afford to hallucinate an answer, even if it's low percentage. We've heard a lot about mental health therapy, where bots take people down towards bats. Those are all examples. So I think the winning customer support thing will be something that does not hallucinate for a class of applications. Some applications, some hallucination is fine. And are you saying that you think that like a company can't just increment its way from hallucinating sometimes to hallucinating never? And you just need to, you can't just, those companies can't just improve their way to no hallucination?

36:09It's possible, but I think if you architect for low hallucination, know when to use no hallucination when you can afford to, giving somebody's bank balance, you'd better not ever hallucinate. Yeah. I think it's pretty important to look beyond normal. Lots of people will do the normal. Extensions of LLMs to lots of applications, massive market, lots of people will do it. Every area will have 10 startups. Keith, are you interested in hard tech as much or do you invest more in like B2B typically? Well, I've invested a lot in AI. So, yeah, I love your quote about AI and how you'd have done it differently if you hadn't joined the Coastal Venture.

36:53This is a great story. Before I joined KB, I joined KB literally two years ago, basically this week. Yeah. I had invested in zero. Rejoined. Rejoined. Rejoined. Rejoined. And literally had invested in zero AI companies before. Interesting. Since then, in the last two years, I'd say it's about 70 % of my investments are AI. And had I not rejoined KV, I think I would either miss the whole wave and been completely irrelevant or been reckless. Neither one's good. Because what I was able to do when I joined is learn by osmosis. So I'd sit in partner meetings and 80 % of the companies that we would discuss in the portfolio of new opportunities would be AI-based.

37:31And I would listen and learn. And then B, as I started meeting founders who were interested in AI that fit my normal standards, I could send the deck to actually three people here, Vinod, Sven, and John Chu, and sometimes actually Kanu too, get feedback, and then actually often have some combination, maybe all four, meet the team. And so when I first started making AI investments, I felt like I had this air cover of like a lot. They could understand how good is the team, B, how smart is their approach, how differentiated is their approach. And then B, is there anything else in the landscape that's even better?

38:07And then that allowed me to start making new investments. And then you develop some taste and some ideas about what works. And then you join the board of the companies and you learn like how these companies are built, what works, what doesn't, what are problems, what are not. And so now I basically do almost virtually all AI. Yeah. I'm actually curious on the topic of how the companies are built. And obviously you're super involved with like company building. You've built companies yourself a bunch. And it's just like something that you talk about a lot. Do you think AI companies are built in any substantially different way?

38:35I think fundamentally different. First of all, they are growing at rates that are unprecedented in the history of technology. And it's a little bit like, to me, it's like running the four minute mile. Once you see someone runs the four minute mile, then no company should have an excuse for not growing rapidly. If like you see all these enterprise companies going from zero to 50 million, you start asking questions. Well, why? Why can't you at least what are the limiting factors? And there sometimes are real reasons, but you start with the question of why? Why not? You know, why not? Versus like, oh, that's impossible.

39:02Like if you had said, we're going to start a company and have 10 million dollars of revenue in year one from launch. You would have said all of us would have said 10 years ago. That's impossible. That is not definitely not the right answer. Now, it doesn't mean every company should do that. But it's an open question. Then the question is, well, what do you do about that? I think the idea of, and borrowing from Peter Fenton here, the idea of PMs does not make sense in a rapidly emerging technology field. What do PMs do? They go talk to customers and they create a sequential roadmap over the next four months.

39:25Well, if the field's evolving and the capabilities are evolving, like literally every month, there's papers published. You probably read papers every week, let alone things that are launched live. You can't have a 12-month roadmap. That makes no sense. And so you have to rethink that. Then also, how does sales work with your research team? Like OpenAI actually pairs, as far as I can tell, like the people doing customer acquisition with the research team. And that's a completely different model than how most technology companies were built. Compensation, this is in the public domain. Completely different.

39:54Completely different. And people haven't even thought through the implications. Yes, there are some companies like Meta that can afford because of how they meant money or Google because of how they meant money to pay things that only professional athletes could aspire to when we were growing up. However, if you're a startup, how you can afford that level of cash comp while you're not minting money. Well, you can't, right? Well, this is, but then you still have to compete with people who can. So you have to think through - Doesn't that go to like your diamonds in the rough type of idea? Either.

40:20Well, that's one possible solution. Or you've got to hire people that don't care about short-term cash comp and have a different missionary zeal or different orientation. Or you've got to take costs somewhere else, a lot of money from somewhere else that you're not paying for. like but no one's really yeah very few people have thought through company building from scratch if you need research grade talent yeah and you have to compete with a market how do you reorient the entire p l of a company yeah do you have like well i think it depends what you're trying to do like depending on what market you're in and who you're competing with and how much cutting edge ai talent you have do you need one person do you need a team 10 yeah those are all very different you know financial there's a lot of financial consequences to those yeah how different do you think it is for like let's say like a i don't know somebody who's building like a new like ai centric system of record or something like that like how different is like the first 30 hires look like what or like yeah could you just sort of like guess what you think that might approximately look like i think it's very different yeah first the whole idea of systems of record is going to change pretty dramatically and it may be the old system of record don't go way, but the operating substrate is wholly different.

41:32In fact, most likely that'll be the case. Take ERP, a hot area. It's really becoming unbundled. So there's procurement, and then there's finance, and then you can go through the various modules in this ERP system. If you don't have the right substrate to have it operate under an agentic architecture, you're not going to have huge success. Used to be in an ERP system, it's what features does it have? I'm a manufacturer. Do I have manufacturing features? I think now it's about how do I reduce the number of people I need in accounting or supply chain or others. Yeah. So one of my favorite examples, we invest in dual entry.

42:23They have a client called Slash, small business lending, complex business. It's both regulatory complex and credit scoring and all our complex areas. A$150 million ARR company with only one person in accounting? That was my reference when we invested. Why? Because the architecture is right. And by the way, these aren't founders who are credentialed. I think they're from Venezuela. Really great people. Loved the entrepreneurs. That was number one agreement. We loved the entrepreneurs. Two, loved the architecture. Three, loved the impact. The benefit is very different. than a feature list. Another difference is, so for example, traditionally when you build an ERP-ish system of record or whatever, you think about like your defensibility would be around the number of integrations you would do.

43:16Like think Rippling. We have all of these integrations, blah, blah, blah, and creates a big moat. With things like Cognition, Devin, doing 100 integrations, it's something you could actually feasibly do in a month at very low marginal cost. Like a company like MuleSoft makes no sense now. Yeah, well, exactly. So a lot of these incumbents are much more vulnerable, I suspect. So given that you've got all these different intentions for the company, the way success is measured, it's like the building, the way you build a company, like the old playbook, to whatever extent those ever were any good or definitely no good now.

43:47Have you found that retraining, for lack of a better word, experienced execs who came up in pre-AI ports over well? Do you have to be more cautious with that as you're bringing higher execs into new companies? I think it's fun and challenging. So I'll give you a good example. One of the best companies ever is going to be Ramp. But Ramp started in the pre-AI era. And we're very AI forward. We talked about this publicly. There's stats about it. We're leaning in. We're hiring AI native people constantly. We have the best intern pool on the planet for the last three or four years in a row. But we actually have to rethink the company because we really started in 2019.

44:26And so we have a lot of things that were based on doing the best possible version of a technology company in 2019. And that's changing. And it's an interesting board level conversation that we have of like, wow, should we rip up everything we've learned or which pieces should we rip up so that we can be the best company in the next 10 years? Yeah. And if Ramp's doing that, imagine what every other company should be thinking. You know, my way of explaining this, most experts are experts in the previous version of the world, not the one you're trying to create. And so fast learning, and I come back to that, is much more important than lots of experience in this AI world.

45:03Even how you do anything, computer architecture, system integrations, marketing, customer support, all that is so radically different. You want rapid learners, whether they're experienced or fresh. Yeah. Let me give you a mundane example. So like Think Lattice, back in the Lattice days. Right now in enterprise, because of the hype of AI, top-down sales can work extremely well. The CEOs feel pressure from their board to be AI forward. where their executives feel pressure to be leaning into AI. Historically, not the best way to build a company is to depend upon top-down CEO sales. But it actually does work in certain verticals right now extremely well.

45:45So the whole go-to-market playbook, you have to rethink too. That's funny, like in legal or like a couple other categories, it's like they just want to buy AI. Like is it more than what the specific solution is? Like we have a big budget for AI. In the short term, they have the budget. They may not care about the impact. Long term, it'll harmonize. You have to produce results. Ultimately, we care about that. We evaluate. When we look at application level companies, what is the actual impact you're driving for your customers is a key input for every stock. But I assume if you have a founder you love and there's this crazy market pull, even if they haven't worked out all the pieces later, like that's a good enough starting point to bet.

46:19If they really understand that they need to versus just chase revenue. Yeah. Outside of AI, you said 70 % is AI. So like there's other stuff you guys are interested in. I know we've talked about like robotics last year. We've talked about... Robotics is AI. Yeah, of course. But pretty big on robotics. Yeah. Well, one thing people know less about us, but we've been consistently excellent at across the history of the fund is in financial services. We have this point we make to LP is that in every single fund we've had, we've returned the fund solely on one, just on one financial services investment.

46:49That's a crazy stuff. So we love things like Square, Stripe, Affirm, just examples in the modern stuff. First investors in all of those, except Stripe, we were second. We have Avon, which is a very excellent company. It'll be the next surprise strike. Upstart was incredibly successful. We did some of the seed, led the A. Has finance gotten less AI-ified than other areas? People are using it, I'd say, maybe not as strategically yet. You think it's because people are a little scared? Or rightfully scared? Because I do feel that the fintech companies of the last era I've seen more, they seem more insulated from the AI wave and threats.

47:30And like, I haven't seen as many like. Well, there may be some hallucinations. Good example of, well. Well, some of the hallucination concerns. Yeah. But even as good example of a company that's deeply using AI in every aspect of it. That's why you can get a home equity line of credit and consolidate all your credit cards onto a new credit card that you get that has 10 points lower interest rate. And then they have your credit card. Well, they issue a credit card based on your home equity line of credit. They can get it done in an hour. Normally that's weeks and weeks. And AI is what makes it possible to go so fast, which makes it fit in the right way into like the process.

48:14It ramps using AI very aggressively. But I think it hasn't been quite as transformative across the broad set of legalism. Well, you know, the thing is, there aren't too many great fintech companies. I would venture to guess Ramp and Avon will end up being two of the best of the new breed started in the last five years. Yeah, I agree with that. And so that may be true. Like once every so often, there's an amazing fintech opportunity, at least in the United States. There's been like Nubank and a company in Germany, Trident Public, they're awesome, Revolut. But in the United States, it's once every two or three years at most that you have a true iconic company.

48:59That'll get to tens of billions or 50 billion or 100 billion in market care. There's not that often. And so I do think the next generation will use AI in a very significant. Yeah. So fintech is a really interesting area. We still do a lot of sustainability stuff. I am really bullish on energy. We are very, very bullish that that area will keep sustaining. Actually, so maybe this is a good moment to talk about this. By the way, manufacturing, another area we haven't talked about. Huge interest for us. Defense is another huge interest. What in manufacturing? I think applying AI to completely change the paradigm of how manufacturing is done.

49:44As part of that, you can onshore stuff that was offshore. So it's these two trends colliding. Is robotics part of that too? It is part of that. It's not the most essential part. What's essential? Essentially, reducing labor costs in other ways. Not by a robot do the job. Got it. But running a system in a way, an iPhone assembly line, would have a few thousand manufacturing engineers. If you can do that function with AI, then you have a pretty large advantage manufacturing onshore. How much of the opportunity is at like the points of creation of goods versus like the operations and logistics around a manufacturing company?

50:35Both. We are seeing both. Yeah. Supply chain was sort of a minor part of all ERP, we talked about that. There's going to be lots of opportunities to replace supply chain software with new AI software. Yeah, and then in defense, I guess, like obviously with like Anduril, SpaceX, like, you know, obviously like now there's like huge inroads here. Is your guys sense that there's a lot more opportunity for those flavor of companies to be built? Will those companies dominate in their markets? Like, how do you think about what those markets will play out like? I think there's room for lots of new startups.

51:08I mean, we are big investors in Hermes. Now, that was not started in the current fashion. It was started five years ago to do supersonic aircraft. I think that'll be an important part of national defense, become even more prominent because Russia has used supersonic aircraft missiles in Ukraine and we don't have any. Yeah. So that's an important area. we did a while ago. Then many other areas. Keith, you can talk about Mark and some of the others. Yeah, so we've been in that. Well, we've been concerned like politically, geopolitically about the threat posed by our adversaries, the CCP, et cetera.

51:53Minoune got involved in Hill and Valley Forum before it was cool. One of the first 20 people like when, you know, was setting up to alert. By the way, under a democratic. Yeah, under a democratic administration. Because it was a common concern. Because the country needs to take advantage of the best and brightest in technology and the cutting edge technologies, or we are going to sacrifice our way of living to people who do. And we started investing in things like that ahead of the curve. There's now more interest among VCs because some companies are perceived to be doing quite well. VCs are always like a herd.

52:27But we invested in Varda, which has a significant defense component. Mach Technologies is a very high potential. Rocket Lab, many, many years ago. Yeah, all of these were before was kind of cool. Now, also the country needs to take advantage of technology. The country has more threats and has more potential adversaries to worry about. It has to do with less money. It has to survive or thrive with less money. Technology is a great magic wand. It has been for consumers for 40 years. It's like magic wand, you get more for less. The government needs to embrace that. And this administration is in putting people like Emil in place.

53:04hopefully to catalyze a new world order where we take advantage of technology and make America better. Yeah. I guess on politics, like both of you are like pretty willing to like get into politics stuff on Twitter and stuff X and you have very different politics, obviously. But I guess my first question is like, um, you both are like willing to just sort of like get into, I don't say fights, but like fights on X about politics and stuff like that. Clear. It comes from like strongly believing in what you think, why spend the cycles on it? Like, why do you? I'll give you my answer. I don't actually know yours.

53:36Mine was like, yeah, through technology, I developed a following. And I woke up one day and said like, look, I don't want to die one day and regret that I didn't use my audience to proselytize about ideas and things that I find important. So if I can surface new ideas or rebut bad ideas, I want to, you know, finish my life thinking I did the best I could to have influence and I have a platform. So I started using it that way particularly on like topics related to politics um and so i was just like i don't want to regret having not tried to change people's opinion are you stressed at all when like when you're like getting into it on x with somebody are you like feeling anything about it or are you just like i'm just saying what i think but i'm well there's times where you should have more time to like research like if i was doing nothing else if i didn't have like a day job yeah you know there's times when like i know how to construct an argument i know where all the evidence is I don't have time to go do that.

54:27Like my friend David Sachs back in the day hired a research assistant secretly before, you know, to help him. I don't have time to do that. So there's times when I happen to know the answer. I used to be very involved in politics. I know a lot of details, but I do wish sometimes that if I wasn't doing a real job, I would be spending more, more care in marshalling more evidence and probably be more effective. Actually, one other bit that I'm now curious to ask, because I think it's kind of funny is you're like kind of harsh on Twitter, but you're like really friendly in person. Is that just like how you write?

54:57Or like, do you mean to like, are you doing it for the best? Well, I also had this crazy idea. This is a dumb idea. Like a decade ago, I was like, I'm going to combat every bad idea on the internet. With the worst idea. Like I was like, well, if someone puts a bad idea or something wrong or false out there, nobody responds. People think it's true. Yeah. Like LLMs are going to pick it up and think it's true. I was like, I'm just going to respond. So at least there's a written record. But like there's so many bad ideas. There's so many dumb ideas in the world that this is like the worst idea I've ever had in my life.

55:24Yeah. But you get addicted to trying to fix every mistake on the internet. I like the ones where you don't even like explain what's the problem. They're just like wrong. Yeah. Well, that was a funny Square joke. That was an old Square. We had this critic at Square named Marquesh. And he used to just like constantly complain about like Square. Square was never going to be successful and need new payments for 20 years. He's a canonical expert in payments. And so sometimes I'd engage and write back like substantively. But sometimes you'd be like so far off. I just, so wrong. So it became like this internal square joke to Rakesh and it became like a meme.

55:55That's good. That's where it started. That's good. Why are you motivated to like get into it online? You know, I don't spend very much time. All of social media, I probably spend less than an hour a week. That's good. So if I incidentally run into something that is blatantly wrong, then I'll express an opinion. But I won't even have the time to read the replies I guess. So like if you're if you're like fighting with somebody on X about whatever and you're getting all these replies or you're just like, I can't like you're not like bothered. I'm not bothered. Yeah. But if something's an important idea or something, you know, usually it's some principle somebody is violating.

56:32Like this weekend, I happened to run into a tweet by Bill Ackman that was sucking up to Trump on capping interest rates at 10 percent. You know, he's sort of recommending that idea and then saying, well, maybe there's a market approach. Hedging the truth is clearly a market person. So I replied to him pretty bluntly. I like Bill. He's a good guy. Know him. But I just couldn't let that pass of sucking up to Trump, which on a truly bad idea of capping interest rates, almost like Trump and Trump and Harris would have the same idea, price controls. It's like, come on, speak up. Don't be dishonest about your opinion.

57:28And he was being dishonest. So when it bothers me, I reply, but I don't spend a lot of time and I don't have a lot of time. Otherwise. Yeah. Yeah. I do mostly like I'm in an Uber. You know, you have these moments where it's really hard to be effective. Yeah. Like I just use it as like sack while I'm like in an Uber ride. I'm not going to be able to schedule a call while I'm in an Uber ride, you know, et cetera. So I kind of like. Get on there and dunk. Or sometimes I do it when I'm eating, which is a bad habit. Yeah. Like I'm having breakfast. I'm like on Twitter or something. But I started, you know where I started?

57:57It was actually a business reason. I was kind of famous back in the day at Square. I read every single tweet, every single day about Square for years. Because occasionally you'd see a gem, like either a great story that you could reshare, like a positive experience, like you helped my life and you get this great anecdote. Or you'd see like a customer complaint and you could route it, you know, directly to someone. Or you'd see a product feature. So I literally read every day, started every single day. But then that gets you in this trained habit of like, you have to read everything and, you know, maybe not the best.

58:24You were like 10 years ago, maybe let's say you were like sort of like one of the first sort of like vocal conservatives. Maybe the only one. Maybe the only. And I think now you're maybe like one of the only vocal, like at least like liberal leaning. Maybe that's like too strong. I'm an independent. You're an independent. For the record. Yeah. I've never been a Democrat. Oh yeah. So what was the political journey? I used to be a lifelong Republican over fiscal issues and switched to independent over climate issues. And I've stuck with that pretty consistently. and then principles matter a lot.

59:03So, you know, my fight against Trump is his values. He has none. We can disagree or he tries to go to extremes to get his constituency rallied around him. Either way, I don't like the idea that people don't mind lying about things. Yeah, when you watch that and like, so it's like violating your principles, you're seeing like everybody around you. Like what's your, what is your like assessment or read on the situation? Because like, obviously 10 years ago, this wouldn't have been the dynamic. Clearly people have changed their affiliation to be for convenience. Doing things for convenience is a bad idea.

59:42Now I realize some CEOs have responsibilities other than to others than themselves. but some are just will change political affiliations and if the next president is bernie sanders they'll become liberal again that i hate so i agree by the way i don't like the convenience i believe in principles i think a reasonable fraction of people i think that's true and then i think there are some who like watch the evidence of just like there's a lot of things let's say the last administration did badly and made jeopardize the country in some ways and then some things that Trump has done have clearly worked or seem to be working at least you know etc and some people it is fine to change your mind based upon evidence I would say there's an element of convenience too there's probably a mix it's hard to sometimes you know who's who and what camp and all that stuff and then there are some who have customers and employees that they have to represent absolutely and you know that's an important consideration like so for example if you have a significant government contracting revenue you know yeah you do have to think about, like you're fueling your families, your employees' families.

1:00:50Like, yeah, you know, there are real responsibilities. There are responsibilities. You see them from a number of companies where they clearly fundamentally haven't changed their principles, but they have to take the responsibility of the role or get out of the role. It's also interesting because it's like it's new for tech to even be reasonable for tech to care about politics. Like it just didn't matter in the past. And also it was like not possible. like tech was much more monoculture on the left before and then also there just like weren't like government related tech startups some of the government is obviously you know founded much more interesting what tech's much more variety good and bad reasons probably and you know you could argue that it was best best thing ever was the tech was built mostly on the west coast far away from washington allowed tech to thrive and you know invent itself without a lot of scrutiny because generally speaking government scrutiny early in emerging technologies is not This is why I'm afraid of AI regulation.

1:01:45I'm like, what are the odds of getting it right? It just seems hard to do. Well, I think that's a real risk with emerging technologies. The government is less likely to be right than wrong on something that's rapidly emerging. Maybe when something stabilizes, the government might have a better predictive accuracy record or something. Yeah. I mean, you obviously need regulation at some point in these journeys. But then you also have to think about the rest of the world. And the node, even though it's probably a little bit more pro-regulation, generally speaking than I am, has been very concerned about losing AI to China and what that would mean to this country.

1:02:15Yeah. And if you have a threat, you have to think very carefully about regulating a new technology if you know a very serious adversary is putting the pedal down and doesn't, you know, isn't less regulated. They're really good at robotics. They're really good at manufacturing. They're really good at robotics. Look, it's very clear. And three years, four years ago at the Hill Valley Forum, I talked about we are in a techno-economic battle with China. We must do everything to win and everything we can to disadvantage them. It's just the truth. What does that look like? What does need to happen there?

1:02:48So I think too much regulation in AI would be a really bad thing. State level regulation is a horrendous idea. Just generally? Because they don't understand the global implications. You know, not everybody abides by American rules. The Chinese for sure don't. So I think we have to be realistic and pragmatic about what battle we are in. Over the next 10, 15 years, economic superiority is up for grabs and we gotta win or we'll live under President Xi's rules. Yeah, I mean, obviously, you've talked about this a lot too. Yeah, but it was a bipartisan effort back four or five years ago um and fortunately um it was very effective it started changing people's mind like there was a lot of people that were very naive about the threat yeah um five years ago and i think if we'd waited too long and there's still debate about like should we export this chip or that chip yeah you know what should the restrictions be on different technologies like there's a lot of nuance to this but at least the central idea that we just cannot lose this race yeah for ai is pretty mainstream now.

1:04:02Yeah, it's part of why a lot of the America-centric companies and investment firms, it's really resonant for people. People want to work at those. There is a growing patriotism out of necessity, I think, probably. I have a final question for you, Vinod. Did you see the report that Keith went to Barry's 2 ,000 times last year? That's an exaggeration. Too many times. Yeah. It's only 438. You're just trying to get a hold of Keith. He's just like... The interesting thing about it is, though, literally this morning, I went to Barry's 7, 10 a.m. and a founder comes up to me after class. And he says, you know, I run, nice to meet you.

1:04:33And I was like, what do you do? He's like, I run an AI detecting cancer funded by A16Z. And I was like, that's cool. It's interesting. Who knows if, you know, who knows if one day we'll invest or whatever. But he said, thank you so much. I said, what are you talking about? And he's like, I started getting myself in shape by going to barriers because I read about you doing it. And so you change someone's life indirectly through that. Like that's actually really rewarding. It's like a bit much, but it's good. No, it's just this morning. That's great. All right, you guys, thank you very much for doing this.

1:04:57I had a great time. Really appreciate it. Thanks a lot.