Josh Wolfe on AI and the Breaking of Silicon Valley's Social Contract

24:11Who got you your first 10 hires? Who helped with your syndicate construction for your later rounds? who made customer introductions, who was a valuable board member, who never showed up, who was asleep in the board meetings, all that kind of stuff. So there is a level of due diligence that LPs have to do to know, are you a value-add investor or are you a poser or a pretender that's just buying a logo or a brand name? Okay. The other incentive, and then we'll get to the founder's liquidity, is you have this weird dynamic of what I've called the minnows and the megas in venture capital. This is, in preview, a shakeout that is going to happen.

24:42The minnows are the thousands of small sub$500 million funds that proliferated when the cost of capital was low, rates were low, everybody was making money. You had a roommate that started a company and you got into Pinterest or you knew somebody at Meta and they gave you a deal and blah, blah, blah, blah, blah. And when you had the Tigers and the soft banks and the abundance of follow on capital, every round was an up round. You had paper marks that kept going up and up and up and it looked great. And you're reporting these paper marks. And then sometimes these things became zeros. OK, but you raise your next fund before they became a zero.

25:15Those are the minnows. I was with one of my very large LPs, has hundreds of millions of dollars invested with us. And I said, I think there's going to be a 50 percent extinction rate amongst these minnows. And he said, Josh, that is ridiculous. It's going to be 90 percent. So you are going to have a mass extinction. Now, why, by the way? Not because they're just bad investors. It's Shakespearean. OK, Shakespearean in that these are partnerships. People start to hate each other when it becomes hard. People start to hate each other when there's down rounds. People start to hate each other when somebody else's deal is a crappy deal and they're bringing down your carry.

25:48And so partnerships are fragile things, just like relationships and marriages, and they can break up. And so you have a lot of VCs that started in the past few years. They're not experienced in going through cycles. They have inadequate reserves to continue to fund their companies. So you're going to have an extinction that I would consider involuntary exits. OK, then there's voluntary exits, which is another interesting dynamic. And there's a playbook for this. which is 2009 to 2014, all the big private equity firms reached a level of scale, several hundred billion dollars AUM, assets under management, where they basically said we're diversified, we're alternative asset platforms.

26:24Carlisle, Blackstone, KKR, TPG, Apollo all went public. The same thing is going to happen in venture with probably five or six firms. My prediction is, and they're all great people running great firms, but they're starting to play a different game. And that game, Andreessen Horowitz, General Atlantic, General Catalyst, Insight, Lightspeed, a handful of others, all at 80 or 100 billion AUM have built great firms, but are thinking about how do we create generational wealth for the founders and go public? Different incentive. Yeah. How do I make my LPs the best money or get the best founders? It's about asset gathering and liquidity.

26:59Now we go to the founders. I can tell you I've been on both sides of this. On the one hand, you want to be fully aligned with your founders, meaning I'm in a fund. It's 10 years. Some VCs vest over two or three or four years. We vest and all of our partners vest over 10 years, the same duration that you're if you're an LP with me, your money is locked up. It's the right thing to do. Buffett style. And the guy that put me in business, Bill Conway, who's the Carlisle founder. This is what they did. So if you're an entrepreneur and you start a company and people are tripping over themselves to get in, they might entice you with green mail and say, yes, we're going to invest just like you said, Joe,$50 million, but we're going to give you 20 million of liquidity.

27:37Okay. Now I will say this. 2019, I'm on a zoom call for an amazing company called control labs that we sell from to meta for a little under a billion dollars. And I love this company and I love the founders. And I'm, this is before everybody was on zoom during COVID. And I'm looking at the zoom window and I see one of the founders and I text the other founder because I think that they're selling too early. And I'm the lone board member that didn't have a veto, but I'm like, I really think we should stay the course and we should keep going. And I made a terrible, terrible mistake because I'm looking at the zoom window and I see the guy and I look closer and I text the other founder.

28:17I'm like, is he still in a dorm room? And sure enough, he was in a dorm room as a PhD had made no money. You got to let that guy get rich. Paper stock value. And he's like, yes, I want to sell because he's going to make 90, 100 million dollars and it's life changing money. And I sat there and I said, if I would have just given him a few million dollars. Oh, interesting. He would have been able to take a breath, buy a house, you know, get out of that door and keep going. Get a girlfriend. There is a virtue of giving some liquidity, but you need to be aligned. And in that moment, we were not aligned because he was like, I'm calling in rich and I wanted him to keep going.

29:02But if you're calling in rich and you're not completing the job, the mission, then you have total misalignment. So that's the dynamics. LP alignment, GP alignment and the bifurcation and then founder alignment. A little bit of liquidity is OK to let them stay the course.

29:32How many vendors does it take to meet all your organization's food needs? Just one. EasyCater, the workplace food platform that lets teams order from a huge variety of restaurants, over 100 ,000 nationwide, all through a single vendor. In addition to all that variety, EasyCater also gives you full visibility of your organization's food spend with invoicing, centralized reporting, and seamless integration with expense management systems, all on one platform. EasyCater, your business tool for food. To learn more, visit easycater.com slash podcast. You're thoughtful about where your money goes. You've got your core holdings, some recurring crypto buys, maybe even a few strategic options plays on the side.

30:18The point is, you're engaged with your investments, and Public gets that. That's why they built an investing platform for those who take it seriously. On Public, you can put together a multi-asset portfolio for the long haul. Stocks, bonds, options, crypto, it's all there. plus an industry-leading 3.8 % APY high-yield cash account. Switch to the platform built for those who take investing seriously. Go to public.com and earn an uncapped 1 % bonus when you transfer your portfolio. That's public.com. Paid for by Public Investing. All investing involves the risk of loss, including loss of principal.

30:57Brokerage services for U.S.-listed registered securities, options and bonds, and a self-directed account are offered by Public Investing, Inc., member FINRA and SIPC. Crypto trading provided by Backed Crypto Solutions, LLC. Complete disclosures available at public.com slash disclosures. How can you grow your business from idea to industry leader? Bring your vision to life with smart business buying tools and technology from Amazon Business. From fast, free shipping to in-depth buying insights and automated purchase approvals, they deliver everything you need to achieve your goals. It's not easy to stand out from the crowd.

31:28Simplify how you stock up to get ahead. Go to amazonbusiness.com for support. Okay, other than misalignment and everyone starting to hate each other as the cost of capital goes up, there's another thing going on, which is, you know, OpenAI just launched some open source models of its own. And this leads me to a question that like, I'm going to admit, I've never quite understood this, but like what exactly is the attraction for VC investors to open source models as opposed to closed source where like closed source, you know, it's proprietary. People presumably have to pay in order to get it. There's like a defensible moat around the business, you would assume.

32:15why in the world would I ever want to fund a model that's open source? Well, a few things. One, if you go back in the compute stack, you have this with like Red Hat and Linux, you know, going back, you know, 50, 20 years ago. We are the largest owners of a company called Hugging Face, which is both the most ridiculous name. And when one of my partners, Brandon Reeves, was sourcing this deal, it was a bunch of French PhDs, came to Brooklyn, and they were like, we're starting this. I'm like, Hugging Face? And they're like, yeah, it's named after an emoji. the little, you know, hugging face emoji.

32:45Cute. They became the leading - I like that you're visually demonstrating everything for us. Thank you. I can't do many other emojis and you don't want to see some of them, but hugging face I can do. So they became the leading open source repository. Now, the great irony, by the way, is when OpenAI started, they were OpenAI, but they became the world's greatest chatbot. Hugging Face started with a really crappy chatbot, but then became the world's greatest open source repository. Every major tech company, including OpenAI, Microsoft, any open source model that they do, they put on there. And that is like the GitHub of AI models.

33:21Microsoft bought GitHub roughly$8 billion,$8.5 billion. It was a really valuable store of models and code. This is the same thing for dynamic AI models. So as a VC, we originally funded this, I want to say, at a$30 or$40 million pre-money valuation. last round was north of$6 billion. And real revenue generating multi hundreds of millions of dollars, serious company. Now, the trend is this. Vinod Khosla and I were both in the White House a year and a half ago. And we were having a debate with Jake Sullivan about what is better for national security. Open source are closed. And I said, where you stand on the issue depends on where you sit in the cap table.

34:03Okay. And Vinod was an early investor. I think he probably I put$50 million into OpenAI. I think it became worth a billion plus. It was a great investment. And he believed that the best thing for US vis-a-vis China and the Chinese Communist Party was closed proprietary siloed model. And I had the counter view because we're big investors and hugging face with a very large position. And I said, no, because the great virtue of any system, be it journalism, scientific inquiry, computer code, is the ability to have in this very Karl Popper-like way, if I can get philosophically geeky for a second of conjecture, hypothesis, and criticism.

34:42That is what creates great societies. It's what creates knowledge. So you come up with hypothesis, you come up with code, you come up with a scientific experiment, you come up with an investigative journalist idea, and then people get to criticize it. It's your editorial room. It's people fighting it out and things improve through that mechanism. So you think about China, they will only approach an asymptote of truth. You will never get, you know, Xinjiang, you'll never get Tiananmen Square, You'll never get the Uyghurs, whereas open source lets you approach closer an asymptote of truth. So that's the virtue of open source.

35:12The real thing, though, for AI is this. I am not convinced that the value will continue to accrue to, in terms of enterprise value, the closed foundation models. And the reason is open source is getting near damn performative enough that the real value will go to the longitudinal repositories of siloed information. That is a mouthful of basically saying your database of proprietary data. Bloomberg has it with a huge and wonderful repository of financial information, time series, every security, currency, bond, fixed income, etc. QCIP that you can imagine. Meta has it with all of your WhatsApp chats and your Instagram posts and your Facebook likes.

35:54X and Twitter have it with all of your tweets. So pharma companies, with your clinical data, anybody that has siloed proprietary and long time data is going to benefit from open source models that over time become commodity. And then your business model is how do you charge people to do API calls on the models or to house and warehouse them, keep them on prem, keep them in the cloud. And that's how people figure out how to monetize open source. It's interesting because I hear you that, OK, maybe the value doesn't keep accruing to the closed source AI foundation labs, or maybe the value doesn't keep accruing to the one GPU maker that we all talk about all the time.

36:36And yet, at least these are not consensus views based on the fact that Anthropic,$183 billion valuation or whatever it is, NVIDIA, maybe it's not at an all time high today, but more or less basically a stock at an all time high. These are, you know, there are some contrarian views here. I want to go back, though, to something before I forget. When we were talking about the acquihires and you blamed it on somewhat the FTC and there has been continuity from Biden, some ideological continuity, I think, between Biden and the new Trump administration. I don't know, maybe it's changed a little bit. That being said, I don't fully buy it.

37:10And here's why. Because in the era of business to business SaaS, which was the 2010s, let's say I had some Y Combinator company and I'm like, all right, I'm going to do all, build a software for all the booking for dentists around the country. And I sign up 150 ,000 dentists and I have a lot of things. There is no engineer who can just be hired away and replace that because it was the network effects, right? This is what's different with AI, though, right? Is that, okay, I'm sure network effects are still real and accumulation of data, et cetera, are still real. But these are businesses that are a lot more about science and having had the experience of doing a training run and so forth on very expensive compute.

37:50So how much of this phenomenon, I know you attributed some of it to FTC, but it really seems like there is something fundamentally different with the business model such that it's not like the B2B SaaS era that allows a talented person to take a lot of value out the door with them. You are 100 % correct in that it is more sophisticated software and algorithms than your traditional B2B SaaS software. And therefore, what was really valuable and sticky was the data in, the regress out, API calls on the back end. And this, the great irony is we talk about artificial intelligence, but the thing that is most valued is indeed today human intelligence.

38:28It is why somebody that was one of the authors on the Attention Is It All You Need paper, which was really the first transformer paper, the T of GPT, every single one of those people has started a company. And we backed one of them that came up with the name of that paper guy, Leon Jones, in a Japanese AI company called Sakana that's taking a different approach. So you are right in that the human intelligence of this in this early stage, which is why you are seeing the machinations with the breaking news you're even reporting of almost like a crazy NBA draft or football or MLB trades. This person went here and then they left and whatever.

39:05And then this person's getting sued because they were only at XAI for three months and they took proprietary information with them. I think that in six months, all of that starts to shake out. You will have geniuses. We backed an incredible genius, Scott Wu. if you look up. You give us a lot of things to Google. Is he a professional genius? I find that so funny. He is a professional genius. But here's the thing. You can see a video of him in sixth grade. So he must have been 12. I love these guys. Winning the math Olympiad. And it's almost like you think it's an SNL skit because you're watching it.

39:38So this is the cognition guy. Correct. Okay. And so we're large investors in cognition. And he has attracted talent. And there's no way that Scott is selling to Google or Meta. I mean, his ambitions, and it's born in like an ethical long-term, I just want to get the best people and build the best technology. But this is a guy at 12 years old, is looking at this crazy question on the Math Olympiad, and just before it's even done, he's like 25, you know, 4 ,722. And you're like, did he cheat? Did they give him the questions beforehand? So there is this aptitude of individuals that you are correct, are highly coveted and highly valued.

40:17But the instantiation of that genius into code, into repositories, into algorithms, means that those become assets that do persist, even if the person comes and goes. This is actually exactly what I wanted to ask you about, which is, are you seeing any companies, any AI shops being particularly innovative, I guess, when it comes to retaining talent? You know, it used to be in the SaaS days that having a ping pong table and, you know, free food and some stock-based incentives. Kombucha on time. Yeah, that's right. That was enough to attract people to the company and keep them. Is it a different story now?

40:56If I want a professional genius, what do I need to do? You need to give them the capital to hire the very best people. Here's the thing. Geniuses don't suffer fools. The smartest people that I know, they are antisocial only with people who they think are inferior to them. and you can see it in many domains. But if you are super smart, you want to be around super smart people because it's almost like you crave stimulation and intellect and somebody that can challenge your ideas. And when you're talking to what they would consider a dummy, you're like, I can't talk to this person. I can't talk to this person about these trivial, superficial things.

41:34And you want to get into it. And so what you do to retain super smart people is surround them with super smart people. You could argue, I don't know, So, you know, really fashionable, great art people want to be around art people. Amazing musicians want to be around amazing musicians. Incredible athletes want to play with incredible athletes and brilliant technical geniuses. Whether they're in AI or they're in aerospace and defense or they're in biotech, don't want to suffer fools. They don't want to be around losers. They want to be around tens and A pluses. And that's the way that you retain people.

42:04Now, any one of those people could decide, I'm going to go off and start my own thing, which, by the way, is often the case of why you are seeing people leave open AI or this or that. As these companies start with geniuses and then get managers and different layers, you spend time with these geniuses and like, I'm not reporting to that moron. I'm going to go start my own thing and attract other geniuses. And eventually, then they need to hire managers and business development people and salespeople. And then there's technical people that are like, I'm not working with those idiots. And they go start a company.

42:34So that's the cycle. So actually, a lot of this discourse, it's crazy how recent this is. So June 19th, CNBC reported that Meta had tried to acquire Safe Superintelligence, which was the company founded by the OpenAI co-founder Ilya Sutskaver, for$32 billion. This is a company that, as far as I know, doesn't really have anything that anyone uses. So that was essentially an attempt to like, I'm going to pay you$32 billion to come join my company. At this level of sophistication and skill, is the talent, even the genius talent, is it motivated by something much deeper than money in terms of like, no, there is this thing out there.

43:18Or maybe we call it AGI or maybe it's a big scientific breakthrough that they want to be part of that essentially no amount of money can buy if it doesn't look like that ship isn't out there chasing the white whale. There it is. In SSI's case, it was Ilya. And, you know, look, I think they're all super confident in their ability and their ability to attract capital, number one. Number two, many of them are actually saying, to your point, no to Zuck. They are turning him down. And what's he saying in return? you don't come to work for me, almost mafiosa style. I'm going to poach all your people.

43:52But that kind of message is almost one that the people that are working for somebody like Ilya or Mira or whatever are like, yeah, I'm not going to go there. I don't want to be, you know, I don't want to work with six layers of product managers and that kind of stuff. I want to do this thing. And then suddenly it feels like it's the rebels versus the evil empire. And that's always the case, right? Microsoft, when you see the founding picture of these nerds, you know, and then they became Microsoft. Microsoft became the evil empire to Google, you know, and then Google became like the evil empire to like Mark.

44:22And then, you know, Meta became the evil empire to open AI. And, and the other piece you have here are huge individual egos. And we as societal members, you know, everyday lay people, we benefit from it. We benefit from Elon and Bezos, sometimes being sort of cordial to each other, but basically trying to take their big giant phallic rockets and send them up to space and we all benefit from that we benefit from the fact that right now the number one person that mark zuckerberg wants to beat is demis sabis of google oh yeah when the nobel prize is shipping at an insane rate video models image models text models huge context windows to put everything you have in um and he's like oh i need to beat that guy i need to hire the best scientists and the best scientific team and where do I get them from?

45:12And so part of this poachapalooza isn't just like the future of meta because, you know, these pay packages at a $2 trillion market cap or higher to spend 1 % of your market cap, you know,$20 billion on all this talent is nothing. It's like a flyer. And, but to win a Nobel prize for figuring out how to do protein folding in AI or develop the next drug or come up with a cure for Alzheimer's or solve some geopolitical issue, that is a big deal. And that's what many people are chasing now. They want to make history. You touched on hardware and also closed source models. Are there any other areas in the AI space that you think are maybe overhyped at the moment?

45:56You know, I've characterized this before as everything in 2D to me feels overhyped. voice video image text it's all going to continue to improve somewhat incrementally but it's good enough and in the history of evolution biologically most of what evolved was good enough you know from everything in our bodies to nature and trees and it's just it's good enough and so that you're going to reach an asymptote of good enough on all the two-dimensional stuff today with one shot learning, meaning maybe 30 seconds of audio, 11 labs or some of the other voice models can capture you with an indiscernible, probably 90 % similarity.

46:35Maybe your spouse, your loved one, your families would be like, ah, it doesn't sound like him. But the vast majority of these things are getting so good that with very little training, they can emulate and predict and do all the things that are of high utility. What's scarcer is the three-dimensional world, particularly robotics, which we've talked about in the past, and biology, in part because you have large, unstructured data sets. A robot walking in and figuring out how much force to use with this cup 30 minutes ago when it was full versus now when it's empty is something that we all do intuitively the second you grasp it.

47:09You know exactly how much force to use so that you don't throw it over your head or have an inability to lift it because it's too heavy. All of that kind of training is really scarce. And there's very few companies that are doing that. So the entire robotic ecosystem from the embodied intelligence and the AI models and the world models to the motors and the gears and the supply chain for that, mostly domiciled in China, is a big area of opportunity. The other big area of opportunity is biology, being able to go from a prompt to a protein, to be able to design a drug. Biology is really complicated.

47:41Computer scientists often underestimate how hard biology is because they're used to 2D linear inputs, outputs. Here's my code. It works. But biologists, on the other hand, also massively underestimate how sophisticated computer science has got. So that's a really interesting ripe area. So 2D overhyped. GPUs overhyped out of necessity of both scarcity and geopolitical thwarting of China. You're going to have edge inference chips, whether it's memory or other things that are going to be on device. The other area that I think is an inevitability, and I've coined a word for this, I call life courting.

48:18Life courting are little devices. I have one here. I'm not an investor in these guys, but there's little devices that you can carry around that passively record 24 hours a day. Now, older people might be like, skeevy, don't like that, feels invasive, privacy. that has always been the trade-off between privacy and convenience, between security and unleashing all kinds of things. It is super valuable to me to figure out, who was I talking about that? Was it Joe or was it my wife? I can't remember who I had that conversation with. And I query the thing and it was passively recording and maybe it doesn't keep the audio, but it keeps the text and it's able to search and query it.

49:00That is going to become an inevitability. Students will use it. People in everyday business, you might ask, hey, is it okay that I'm recording, but I think socially people will become comfortable first with audio and then with glasses that are passively recording every 30 seconds or a minute, capturing your environment, able to provide context around it, and then click a button, high resolution recording. And that is going to be a super valuable and very competitive area. And very controversial. People are going to freak the heck out about this. But they're also going to find incredible utility.

49:32And look, people have freaked out. There was a guy that said these devices are going to ruin human memory. They're going to destroy human memory, which was Plato and Socrates talking about writing utensils. I know, but that's voluntary because when you write, at least you're recording me when we're doing this. I heard about someone on a date in San Francisco and the date was recorded. That's weird stuff. It is totally weird. It's very weird and I – it could be very big, but it's super weird. People already believe that there's an invisible man in the sky that is looking down on them and judging them and these kinds of things.

50:08Oh, I seriously. I don't know. I don't have an opinion on that question. We've got a technological god around us that people are going to either feel comfortable with and not. And there's going to be a bifurcation. And by the way, there's another weird thing coming. You want to get weird, okay? You already see some breadcrumbs of this, and it's super weird. The number one, two uses of all our language, large language models and chatbots are advice, companionship. Yeah. You know, people using them as therapists and seeking. And people used to joke about this, like your Google searches, you know, reveal more about you than you may have revealed to your spouse.

50:41The things that people feel comfortable asking a chatbot about, you know, whether it's a body issue or a psychological issue or relationship advice. You know, if those things were revealed, it would be pretty scary. There's going to become dependency and psychoses that develop as the relationship between man and machine start to become very symbiotic. And you will see, I predict, and I wrote about this in our quarterly letter at Lux, that there is a cohort of people that basically start fighting for AI rights. Yeah, yeah, yeah. Yeah, I came across a think tank today that's focused on that because, right, like if there's animal rights and the AI says, you're hurting me if you turn off the machine.

51:21then, well, maybe it's true. Maybe we have to take that seriously. This is going to be weird. This is the weird stuff that's coming. People are going to be marching in the streets, you know, protesting, don't turn off my language model, keep my memory, don't erase it. My memory is my friend. I thought about this when, you know, after, I guess, GPT-5 was revealed, and there was a bunch of changes to the voice and a bunch of people on Reddit, they're like, oh, my AI boyfriend talks totally differently now. And then there was some pressure. This is just day one around here, I would be very uncomfortable getting into a relationship with a model that was closed source and therefore at risk of the company changing model.

52:00Josh Lux, we could go on forever. We should another time. Always great catching up with you. Always fun. Always a little freaky. Thanks for coming out. Great to see you both. Thank you. Thanks so much, Josh.

52:23Tracy, I love talking to Josh. I'm really concerned about this whole life recording. But I know what's happening. There was a good article, I think, in the SF Standard I read. It's not just a theoretical thing that a lot of people are doing. It's happening. It's mostly in San Francisco so far. It's coming for everyone. I am very curious how life courting stacks up with California's laws on whether or not you can record someone without their knowledge. Is it the case that like from now on, if you have one of these devices, like the first thing you have to say to everyone you meet is like, by the way, do you mind if I record you?

52:58By the way, I'm life courting this conversation. No, or like it doesn't matter. Or you have glasses or something. Yeah, it's very strange. I also think this AI rights thing we have to talk about more. I don't know when we'll get back to it. But I literally just this morning came across an organization that's, you know, this idea, OK, there is already evidence of sentience and therefore with sentience comes some sort of moral agency. And so in the same way that we talk about animal rights as being somewhat important, do we have to take seriously? I don't know. This all seems very strange to me.

53:30And then, of course, the psychosis induced by what happens when your AI partner or therapist changes models and changes voices. And therefore, that was just the end of the conversation. You know, if AI models have rights, then you have to start asking if robots have rights, right? And then you should start asking, should robots be paid a fair wage? And I think there's actually an interesting thought experiment that you could do about that and make like a relatively strong case that we should pay the robots. Who collects the money? And what do they spend it on? Yeah, that's – well, no, they should spend.

54:04I mean, this is like – we're basically at what all of sci-fi has been discussing for the entire history of sci-fi. On the less speculative stuff, I like talking to Josh. I like his sort of counter consensus calls on GPUs and closed source models. I really liked his answer on founder liquidity that sometimes you can maybe keep the founder sticking with the mission as opposed to bailing with the mission if you can de-risk them and they can have enough money to go on a date. I like the idea that everyone's life view is basically dictated by where they are in the capital stack. Yeah, that's right.

54:39Words to live by. Extremely real. Shall we leave it there? Let's leave it there. All right. This has been another episode of the Odd Lots podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Joe Weisenthal. You can follow me at The Stalwart. Follow our guest, Josh Wolf. He's at Wolf Josh. Follow our producers, Kerman Rodriguez at Kerman, Armand Daschle Bennett at Dashbot, and Kale Brooks at Kale Brooks. For more Odd Lots content, go to Bloomberg.com slash Odd Lots. We're with a daily newsletter and all of our episodes. and you can chat about all of these topics 24-7 in our Discord, discord.gg.

55:13And if you enjoy Odd Lots, if you like it when we catch up with Josh and his slightly dystopian views of technology, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening. Thank you.

56:08For enterprise organizations, managing all your food needs is a tall order. But with EasyCater, you get a single workplace food vendor with the tools and resources to make it easy. Giving teams across your organization an easy way to order from a huge variety of restaurants, all on one platform. All while consolidating your corporate food spend so you can control costs, streamline billing and payment, and simplify reporting. EasyCater, your business tool for food. To learn more, visit easycater.com slash podcast. Bloomberg Daybreak is your best way to get informed first thing in the morning, right in your podcast feed.

56:47Hi, I'm Karen Moscow. And I'm Nathan Hager. Each morning, we're up early putting together the latest episode of Bloomberg Daybreak U.S. Edition. It's your daily 15-minute podcast on the latest in global news, politics, and international relations. Listen to the Bloomberg Daybreak U.S. edition podcast each morning for the stories that matter with the context you need. Find us on Apple, Spotify or anywhere you listen.