20VC: Chips, Models or Applications; Where is the Value in AI | Is Compute the Answer to All Model Performance Questions | Why Open AI Shelved AGI & Is There Any Value in Models with OpenAI Price Dumping with Aidan, Gomez, Co-Founder @ Cohere

25:04I kind of bossed, I said, that's about that. To all extent, there's one go actually for that extra incremental 0 .5 % increase, it's another billion dollars. That no longer is efficient. Yeah, I mean, fortunately costs are falling super fast on everything. Like compute costs, dollars per flop, the scale of model. Dollars per flop? Yeah. Like how much a flop cost? Over a flop per dollar. So a flop is a unit of compute and a model. Sorry. Do that. So there's a flop. Like for me and the UK is a good flop. Yeah, like a flop in the state. Yeah, I completely flopped that one. I was like, is this like a new thing?

25:41No. It's a super all thing. as a floating point operations. So it's literally like one clock cycle of a... That's amazing. Glad I clarified. And so if you have like 10 billion parameters, that basically equates to some number of flops. And if you have 10x that, if you have 100 billion parameters, that equates to 10x, that number of flops approximately. So anyway, the price for a flop goes down super, super quickly over time. And so that's what's unlocked much larger models today compared to 2017 and even two years ago. Given that, do you not think that actually it is not too late for a new startup to enter the model space?

26:25Because everyone's like, oh, this is far too late for a startup time to the model space. And actually giving the decreasing cost barrier, does that not mean it's actually more accessible than ever for startups to do? So it becomes cheaper to build last year's model by a factor of 10 or 100 each year, we just get better data, cheaper compute. So, yeah, it definitely lowers the barrier to the previous generation of models. The reality of the matter is nobody cares about the previous generation. Nobody wants them. There's no market for last year's model. It's useless in comparison to this year's model.

26:57Any sort of technological development really makes the last generation obsolete super quickly. I think the difference is like it costs you 10 million dollars to build V1s. I'm just saying it's a software product. And then to make V2 that update a little bit better, another one or two million dollars. But here it's like three billion to build one and then five billion to build two. The increment is not increment. It is order of magnitude. I don't know if it's always the pattern that it's cheaper to build the next generation. I think with chips, for example, and other very complicated pieces of technology, it does get more expensive to generate each new generation.

27:36And we still do it, because it's worth it. Going back to your statement, sorry, because I went off on a tangent, no one gives a shit about last year's model. Well, you were asking, do the improvements sustain? And I was saying, it's getting harder to improve these models. It's getting higher friction. And the second weird effect is that, as these models are getting smarter, each individual's ability to distinguish between them becomes way harder. You can't tell the difference between generations. because you're not enough of an expert in medicine, mathematics, physics to actually feel the change.

28:08The model is already kind of as good as it can get with all the basic level knowledge, which is what you and I have. And so when we interact with it, we get the same experience between generations. But in reality, those generations are changing dramatically in much more specific capabilities, or raw intelligence. And yeah, you were asking, is it worth it? Is it worth it to keep spending so much money to push forward? I think absolutely it is. Absolutely it is. It's worth it to someone, right? Right. Even if for you and I, like as consumers, when we're using this stuff, like we don't care if it knows C -star algebra is in like quantum physics, it doesn't matter to us.

28:43It has no impact on our experience with this technology, but that's really helpful for a researcher in quantum physics. And so we'll make more progress there by providing tools. It's the same question around just technology in general. Like we have abundant food, we have super cheap cars now and we have phones in all of our pockets. We're kind of good. Like we've got, should we really invest in the next generation of technology that focuses on creating a new material for a spaceship so that it can get up into orbit more efficiently? Yeah, we should. And it might not matter to you. Like you don't give a shit if the spaceship gets up into orbit, cheaper, but it matters to someone a lot, and they're willing to pay, and there's a market for it.

29:23And that's how progress sustains itself. That continuing progress, we're going back to it, obviously costs, and we'll continue to cost a lot of money. You said before, a really interesting two words, which is effective subsidiaries, and we've seen a lot of companies be kind of bought, acquired, whatever that is, subsumed in. I think everyone realizes now that cloud is the cash cow that keeps on giving when you look at kind of the continuing growth rates and profitability of a zero and Google cloud and everything in between. And actually, you'll just see the majority of those smaller model providing companies bought up by these large cloud providers.

29:58Do you agree with that as a probable likelihood for the next three to five years? Three years, yeah. I think there will be a culling of the space. I think it's already happening. I think a lot of the model builders that weren't adapts going to Amazon. Mayor David on the show, he was fantastic. Love David. He's great. Really, really good. The inflation obviously gone to Microsoft. And I think there's more coming. There's gonna be a consolidation in the space for sure. It's really dangerous where you, when you make yourself a subsidiary of your cloud provider. Why? Well, it's just not good business.

30:32So to raise money as a company, you need to go and convince some investors who they only care about ROI on that capital and they give you the money and you go create some value using it. But when you're doing this raising from cloud providers thing, the math is super different. Do you think venture investors will make money from the modal investments we've seen over last years. Coheres investors will. I like a lot of money. That was an awful amount. I feel great for making these people who believed in your load of money. You're like, fuck, that was cheap in a shend of giving away that much. No, I mean, I think that everyone who was there at that point is still here.

31:09They're still fighting. So our first investor was Radical Ventures, Jordan Jacobs there. He's still on our board. He's still, I call him like the fourth co -founder of Go Here, he's built the company alongside us and is still very active and present in building the company. So I don't regret it. What was the latest price? The media reports that it was a little over 5 .5. Does that cause you stress? You know, when you look at revenues to valuation, I know we're not in that game, but at some point everyone is in that game. Of course. Does that make you fucking out with a long way to go? It's definitely pressure.

31:45It's good pressure. Everyone gets into the revenue multiples game at some point. At some point, it converges to public market multiples. We are actually in a dramatically better position than a lot of our comparables, because our valuation is not at the crazy state that a lot of others are. Let's not believe. We still have to grow into it, but I'm very confident that the market is strong. A lot of people need these models. On the margin side, it's under pressure right now because of price dumping and because of free models being given out. But that will change over time and then cohere our product stack will also evolve.

32:20Which one do you most respect? I would say opening it. They paved the way. Like a just sort of like an irrational conviction to this vision of scaling. I remember talking to Ilya about this stuff way before GPT -1, you know, like in the transformer times or on that time because he was big in the Toronto scene, he studied under Jeff. And this this idea of scaling, it was in his head back then years before. or he actually started pursuing it properly. And that conviction led to the world that we live in today, this objectively magical technology that's emerged and is now sitting available to everyone.

32:56I really admire earlier. Ethan Mollow from Walton set on the show, an open AI really only has about AGI and the pursuit of AGI. And so they abandoned products like code interpreter and a lot of other really useful products because they're focused on AGI. So it's not a criticism, but just like that's their focus. Do you agree with that or do you think they are and she kind of dual -minded in terms of both going for the long -term AGI and also being much more cognizant of creating short -term valuable products for enterprise and for consumers more broadly? I mean, I think lately or in the new OpenAI, they're like a product company.

33:31They're like hardcore building a consumer product. That is their objective and it seems like it and it's working. People love that product. It's a household name at this point. So I think in the consumer space, they're going to be a product company and I think that they have to become one in order to put the bill to build what they want to build. If you look at some of the departures I would say it seems like the AGI effort is starting to take a backseat to To product into the the consumer offer. Something that I worry about is and I use Canvas and example of this Which is like are we going to see companies be able to make more revenue per user from adding AI to that products?

34:07In every company, it's an AI product company now, whether it's their customer support, notion with note taking, canva with design. And it's all AI. And you canva bluntly set on the show recently that they are having margin compression because they don't charge more per seat, but they have AI infused in all of their product. And so you can create anything with AI in their products and obviously each query costs money. It's costing them more money and they're making the same revenue. Will we actually be able to make more revenue per user or will it just create about a customer's parents? Well, I think there's two different camps right now.

34:42Some people are pricing the exact same with AI features and using it to drive expansion in their business. And then the other folks like Microsoft, like Salesforce, like Notion as well, they're charging for the AI features and getting a bigger business as a product. Both of those strategies are fine and super reasonable. For folks like Canva who are keeping the same price, I mean, I think it's a good bet. They want to grow their user base, they want to expand their user set, just give them the most useful product possible. At the moment, don't worry about margins because the cost of AI is falling super super quickly.

35:14I think that's reasonable. On enterprises, Canvas, obviously making a hard push round prize, you sell into amazing enterprises. What's the number one blocker today for when enterprises don't adopt? It's mostly trust in the technology, so security. Everyone is very sketched out by the current state of things, who's training on my data. Very sketched out means concerned. Yeah, yeah. Right. Not like a flop. Yeah. Well, they're hoping that they don't have a flop. So they're really scared that someone's going to take their data, train on it, and put them in some sort of like security vulnerability, or that they'll lose IP.

35:49I think that's a very valid concern, because people have been training on user data. Is there anything you can do to reassure them other than use synthetic data? Yeah. So our deployment model is set up to do that. We focus on private deployments like inside their VPC on -prem. Like what that means is just like, it's on their hardware completely privately. We're not asking them to send data over to us. We'll process it and give you back the response from the model. We're saying we'll bring our models to where your data is. We can't see any of it. Well, we see the movement back to on -prem in this new world.

36:21When I speak to folks, it's super conflicted in financial services. Yeah, people are pulling away from cloud. They're pulling away from cloud. They're building out their own data center capacity. Everywhere else still seems to be, we need to migrate to cloud. It doesn't make sense for us to have these data centers. I think that it probably depends on the vertical that you're looking at. What do they just get totally wrong about AI? I think the enterprise education curve is still very early. What do they just not understand about it? There's a lot of fear around AI being wrong. There's the hallucination in these models and everyone views that as some sort of like, the technology is doomed.

36:58You know, sometimes it hallucinates. It doesn't reflect reality. The models definitely do hallucinate. The hallucination rate's have been dropping dramatically, but they'll always have some chance of making stuff up, or getting something wrong. But we exist in a world with humans, and humans hallucinate constantly. We get stuff wrong, we misremember things. And so we exist in a world that's robust to error. And so I think... We didn't have much imagination. We didn't have much imagination. Benchmarks, they do we? We do, yeah. We do. Yeah, yeah, like Vittara has one and there are other hallucination benchmarks and we're seeing them Decrease at the same level as model progression the same level I don't know about but definitely it's been decreasing Super fast and with rag.

37:36It's like a step change I'm sorry if anyone doesn't know rag is a retrieval augmented generation So it's the idea that you have a model. Oh, thank you for that description Did you have a model which can query out to a knowledge base and that knowledge base might be your internal documents or or a search engine, it might write a query to a search engine, pull back the results, and then use that as part of its answer and cite, cite its sources. So it's saying, I'm making this claim because I read it over here. So now you can audit whether it's correct, and it also has a byproduct of the setup really stops lying as much.

38:08It doesn't have to make up as much because it has reference material it can draw from. And that's the game changer for hallucination, definitely. And also just for like customizing the models, because they've seen the public web, so they know a lot about public information. But for private stuff, I want my model to be able to answer questions about my email inbox, which is something only I have access to. And so the ability for the model to query my email inbox, pull back that information, it just makes it more knowledgeable about the stuff that I care about. And we still need experimental budgets for enterprise.

38:36Everyone's like, no, which is playing with budgets now. It's not far away, actually, moving into mainstream. It's really started to shift. So last year, 100%, it was like the year of the proof of concept. Everyone was sort of testing it out, playing around with it, but recently there's been a big shift to urgency to get this tech into production. I think a lot of enterprises are scared of being caught, flat -footed. They've spent a year running POCs and testing stuff out. Now they're sprinting towards, I wanna put this into production, transform my product, augment my workforce. What's the number one use case for them in terms of what they need or want?

39:11The number one use case. Because it feels that everyone, everybody is saying, hey, what's your AI strategy? And it's like, what does that actually mean? Like is it Klawner who's very much, we want to optimize our customer service and we're gonna do that? Is that like the number one customer service? Is it employee orientation and productivity? I think it's employee augmentation. It's these models becoming like a partner or a colleague to your entire workforce. That's the most popular use case. I think co -pilot is the right way to do that. I think Copilot is great and it's like the right idea of augmenting a workforce with an assistant, But it's siloed again within an ecosystem.

39:48So it plugs into office and the Microsoft suite of products. Enterprise's don't just use Microsoft. They use Microsoft for their email and docs and spreadsheets. And then they use Salesforce for their CRM, they have SAP for their ERP, they have some HRM, they have internal software that they've built for themselves. And if you really want to augment the workforce, you need to have a platform for developing these assistants, these agents that's agnostic to a particular tool set and that prioritizes the tool sets rationally across what people actually use, what the market actually uses. So I don't think that that's going to be done by Copa.

40:24You mentioned what agent, that agent is one of the kind of hottest topics in Inventual land. Do you think it's justified the hype around agents, agentech behavior, what it does to workflows? I mean the hype is justified 100 % that's the promise of of AI. The promise of these models is that they would be able to carry out work by themselves. That just dramatically transforms productivity. Once you have a model that can go off and do things independently over a very long time horizon, so no longer like, I'm going to do this one thing for you immediately and return and I'm done. But like over the next six months, I'm going to be pumping deals into your top of funnel or something like that, right?

41:01Like doing outbound for you. It just completely transforms what an organization can do. The hype is justified, I think my critique would be, is that work going to be most effectively done outside the model builders or within? Who's going to be best positioned to actually build that product? Why would it be best done within the models first? Completely depends on the quality of the model. It entirely depends on the model. Like the model is the reason behind the agent. And you have to be able to intervene at that level. If you're not able to actually transform the model to be better at the thing that you care about, if you're not the one building the model, if you're just a consumer of the model, you're structurally disadvantaged to build that product.

41:37Who do you think is disadvantaged today? Everyone taught us what it is quite cynical about Salesforce. I'm like, I don't know. I wouldn't bow against Benioff. Yeah, I wouldn't know there. He's amazing. And I think he's very cognizant of a threat against them. And I don't think he'll let it happen. So I don't see it going anywhere. The other thing is that you forget how sticky enterprise software is. There's not a lot of like mass displacement of enterprise software. It kind of just stays for decades. It's really hard to displace an enterprise software company. Did you think it was disadvantaged?

42:06There's an opportunity for really transformative new consumer experiences and consumers are far less loyal to one provider. They're going to go where their friends go, they're going to go where they get the best service, the best product. And so if someone can come along and provide something that is considerably better than what exists today using AI, consumers will move. Who do you think has the best researches? Other than Co -Hier, I think it's quite distributed. It used to be very concentrated. It used to be like Google Brain. Google Brain deep -mind. Why would they so behind them? Well they weren't in the sense that like two weeks after we released the transformer paper, we started training language models.

42:46So we like technologically and research wise, Google Brain was certainly not behind. I think what's really important is product vision and the ability to imagine what could be with the technology. It's not just a technological development itself. It's the vision of what you can do with it. Even if you have people inside your organization who see that vision, are you equipped to enable them to execute on it? Or do they have to go somewhere else to execute on it? I think those are the questions that you have to ask. And then lastly, I mean the scaling hypothesis, this idea that models will just continue to get better, the more we pump into them, and that we should be spending, not just 10 times as much on building models, but 100 times, 1000 times as much to build models.

43:29That's like a super risky, uncertain, kind of crazy bet to make. But I definitely don't knock Google for the decisions it made, opening I made, very made good bets. What do you think opening I best bet was? The scale hypothesis for sure, like just that scaling is going to sustain and that we should continue to 10x 10x 10x 10x 10x so many people didn't believe in that. There was so much pushback on it such a stupid superfluous effort to go pursue and they had the conviction to push through. What do you think is the biggest thing that people are not saying about the community right now in AI and how we're looking at the next 12 to 24 months?

44:09What are we all getting wrong? I think there's sort of like a meme that's going around of people saying we've plateaued, nothing's coming, it's slowing down. I actually really think that's wrong. And not just from like a, we need to 10x compute and that type of thing perspective and trust me it'll get better, but from a methods perspective. So when I was talking about like, reasoners and planners and models that can try things fail and recover from that failure and carry out tasks that take a long time to accomplish, These are like for the technologists obvious things that just don't exist in the technology today We just haven't had time to turn our focus there and add that capability into the model for the past year plus Folks have been focusing on that and it will be ready for for production So we'll see that come out and I think that will be a big change in terms of capability So for me is an investor aid and help me you're now an investor with 20 VC Where's the opportunity for us?

45:05I think the product space, the application space, is still extremely attractive. There will be new products that come out of this technology that transform social media. People love talking to these models. The usage time is insane. You think this is good, Aiden? You grew up in a very wholesome natural environment. You mentioned your family also being in the UK. I'm sure you see them all now. You're in the UK. I do not want my kids growing up in a world where they're speaking to agentic systems more than they are humans. I'm like gaining fulfillment from speaking to a model. You might actually be wrong.

45:42I think you might want your children to be speaking to an extremely empathetic, extraordinarily intelligent and knowledgeable, safe intelligence that can teach them things and have fun with them and doesn't get tired of them, doesn't snap at them, doesn't bully them, doesn't pick on them and be them with insecurities. There is no replacement to humans. There's no replacement. There's no world where suddenly we all start dating chatbots and human birth rates plummet. I don't think that happens. I want to have a child. I can't do that with a chatbot. You know, like a human partner. Yeah. Yet, a human partner is way more infinitely more valuable to me than whatever, like however compelling a chatbot is.

46:26A human is so much more valuable. It's the same reason why I don't think will be able to replace humans in the workplace. It'll be an augmentation. Humanity will become more productive and do more. It's not that there will be less humans doing the work. You can't replace humanity. Think about like sales, right? If I'm getting sold to by a bot, I'm not buying. It's that simple. I don't want to talk to a machine. Like for certain, like simple purchases, maybe, but for the purchases that count, the ones that matter to me and my company, I would want a human accountable on the other side of that deal.

47:00When something goes wrong, I need someone, a human, who has authority to be able to intervene. The fears around displacement and replacement. Both on the consumer side where we're all going to get addicted to chatting to these chat pods. And on the workplace, the end of work, there's going to be mass unemployment. I can't see that happening. I think there's always a recognition that there's always this kind of mild displacement in new technology adoptions, which is kind of standard, but you do see some form of displacement, But not the extent where we're like 80 % of us are, I mean, I'm sure you look at your grandparents and say you stick a computer in there with email and they're like, what will we do all day?

47:34It's crazy. And so I completely agree with you that I do worry on the lower end of the spectrum, no being like a corner, losing whatever, 70, 80 % of their customer service team. There will be localized displacement for sure. But in the aggregate, it'll be growth, not displacement. So for sure, there are certain roles that are vulnerable to the technology. It's kind of hard to come up with them. Like customer support is definitely one. But at the end of the day, there still needs to be humans there to do that. Just not as many as there are today. But customer support is a tough role, psychologically ugly.

48:06You get people screaming at you, like the reality of it, if you've ever listened in on all recordings of what it's like. That's a really emotionally taxing job. Every day you wake up, you go to work, you get screamed at, and have to apologize for hours. That side of things. Maybe we let the models handle those conversations and the humans can come in and help with, you know, the actual customer support conversations that humans would enjoy dealing with. They have a problem that needs solving and they're not angry about it. There's just an opportunity to make this person's life better. What does AI not do today that you think it will do in three years will be completely transformative?

48:41I think robotics is like the place where there will be big breakthroughs. The cost needs to come down, but it's been coming down. and then we need models that are much more robust. Just because a lot of the barriers have fallen away, like before, like, reasoners and planners inside of these robots, like the software behind them, they were brittle and they had to, like, you had to, like, program each task you wanted it to accomplish, and it was super hard -coded to a specific environment. So you have to have a kitchen that is laid out exactly like this. Exactly the same dimensions. Nothing different.

49:13Yeah. So it's very brittle. And on the research side, using foundation models, using language models, they've actually come up with much better planners that are more dynamic, that are able to reason more naturally around the world. I know this is already being worked on this, it's like 30 humanoid robotics startups and that type of thing. But soon someone's going to crack the nut of general purpose humanoid robotics that are cheap and robust. And so that will be a that'll be a big shift. I don't know if that comes in the next five years or 10 years.

49:45It's I want to do a quick far round. I say a short statement, you give me your immediate thoughts. Does that sound okay? Yeah, yeah, let's do it. What if you changed your mind on most in the last 12 months? The importance of data. I underrated it dramatically. I thought it was just scale. And a lot of proof points have happened internally at Co -Year that have just transformed my understanding of what matters in building this technology. The gen out is the quality of data. Yeah, quality. Like a single bad example, right? Amongst like billions. It's so sensitive. It is a bit surreal how sensitive the models are to their data.

50:20Everyone underrates it. How much money do you raise now? In total, about a billion. Fucking hell. I know, yeah. That's all that money. That's all that money. What was the easiest round to raise? Maybe the first one. What was that the fastest as well? Yeah, it was kind of like a conversation and here's a few million bucks. Give it a try. So I think that one was probably the easiest when you're trying to raise half a billion dollars. It's a little bit more involved. And she slightly pens yourself and you see 500 million dollars going in a count I managed funds today, but we get capital calls and so it's not like here's 500 million It's like you call it over several years and you just get woof.

50:57Yeah, yeah, and the interest on it is Yeah, I do pinch myself. I mean I'm asked my brain 25 million a year I don't know what the specific number is, but it's a lot it's a big number my brain is broken Cohe has broken my brain when it comes to economics and money. Half a billion does not feel like a lot. Like relative to my competitors, it's not a lot. Does that worry? No, I mean it's part of our strategy. Like if we wanted to go take that deal, we could go take that deal. But our strategy has been to pursue independence and doing this ourselves. If you can have any board member in the world, who do you have and why them?

51:30Mike will be in Jordan, Jacobs. Mike's existing board members. Why is Mike such a good board member? Many people say this. Yeah, Mike's incredible. It kind of feels like he's seen it all before. Like I can come to him with virtually any problem, and he's encountered that three times before, and the first time it went like this, the second time it went like that, third time it went like that. He just has such good experience and advice. Jeff Hinton, Jan Lecune, which one's your boy? Ha ha ha. Definitely more Jeff. I have a closer personal relationship with him than looking for sure. Do you think Jan is too optimistic?

52:03No, I'm way more aligned with Jan and his beliefs about AI. Jeff is like very doomsday, pilled, thinks that this technology's gonna destroy the world. Yann is much more optimistic, and I'm aligned in that direction. I think that unfortunately Yann has kind of become a Elon reply guy. I think Jeff is my co -founder Nick. He's super close with Jeff. They play chess every Monday. Jeff is so, so smart, so intelligent, and so thoughtful, such a deep thinker. I admire him more than almost anyone in the field. You have teams in London now. You live in London. Everyone talks about the death of Europe.

52:40You know, I had the wonderful Dalyan from Founders Fund on saying that Western Europe would be a third world state or kind of collection of countries soon. And negativity is quite real here at Fields. How do you feel now building incredible engineering research teams in London and Europe? England stands out from the rest of Europe. There's a technology optimism that exists here and a willingness to invest and make the changes is necessary to support developing an ecosystem. In Europe proper, by the way, my mom is British, my dad is Spanish, and I have both citizenship, so I'm also very much European, spent my summers there, like family is there.

53:16Unfortunately, the culture is just hostile towards tech. Tasta, like the solution to tech is regulation. In the European mind, I think there's pressure to change, though, and France is becoming much more ambitious and making a lot of noise on the European stage, as well as a global stage about we need to be more progressive. It might take a decade though. In personal remote. So here was like born in the pandemic and so we're totally remote. We're all over the plate, not totally remote. We have offices in Toronto, London, New York, SF. Those are definitely the centers of mass of the company. And people come in every day.

53:52Yeah. In person is just so much better. You can't even quantify the productivity lift from in person. What question are you never asked that you should be asked final one? I don't think I get asked enough where do you want things to go. Like I get asked a lot where will things go? I get asked a lot about the downside risks of the technology. There's so much beer in people's minds when they think about AI and so little discussion about the opportunities we have. And I don't think people talk about that nearly enough. Where do you want it to go? I think that the world is super supply -constrained and pretty much every luxury we have today has come from technology that has developed to increase productivity, boosts the supply of things, make them more abundant, make them cheaper.

54:39And so what I really care about with this technology is driving productivity for the world and making humans more effective, able to do more. And I think it's so unsexy. Productivity is just like so underhyped. But if you apply like a 5 % productivity gained to the NHS, which is obviously our health cost system here, that is a seismic needle moving shift to the state of the country, the state of the country's budgets, the health care in this country, millions of people's lives every day. Like in Canada, real GDP hasn't really been increasing. Someone called it the like the last decade, people aren't getting wealthier.

55:14Things are not becoming more abundant, you can't afford more for a decade. And so that sort of stagnation, you start to get a lot of social turmoil. Things start to be it's not a growing pie, it's a fixed pie that you have to fight for your slice of. And I think those dynamics really concern me. Our priorities as a society right now should be on productivity and growth. Listen, I've loved it. And thank you so much for putting up with my at times rather based questions on rags and flops. And at times, prime questions on fundraises, but you've been fantastic. Thank you so much. This is so fun. I mean, shows like that of just why I love what I do so much, getting to speak to the most incredible people at this moment in time is just fantastic.

55:55If you want to see the full episode, you can check it out on YouTube by searching for 20VC, that's 2 -0 VC. But before we leave you today, when a promising start -up files for an IPO or a venture capital firm loses its marquee partner, being the first to know gives you an advantage and time to plan your strategic response. Chances are, the information reported it first. The information is the trusted source for that important first look at actionable news across technology and finance, driving decisions with breaking stories, proprietary data tools, and a spotlight on industry trends. With a subscription, you will join an elite community that includes leaders from the top VC firms, CEOs from Fortune 500 companies, and esteemed banking and investment professionals.

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57:54Since forming the first venture fund in Silicon Valley, Coole has formed more venture capital funds than any other law firm in the world with 60 plus years is working with VCs. They help VCs form and manage funds, make investments and handle the myriad issues that arise through a fund's lifetime. We use them at 20 VCs and have loved working with their teams in the US, London and Asia over the last few years. So to learn more about the number one most active law firm representing VCs backed companies going public, head over to coole .com and also coolego .com. Coole's award -winning free legal resource for entrepreneurs.

58:30As always I so appreciate all your support and stay tuned for an incredible episode coming this Wednesday.