Anthropic's Digital God, Pope vs AI, Job Loss Narrative Flips, Open Source Crackdown Coming?

Okay, we are gathered here today. [laughter]. in holy [snorts] unity, brothers and. sisters, to convene and discuss on this. most holy day, the day the All-In. podcast drops. many topics. AI data centers, China, justice, human dignity, Daario unwinding these SPVS hasn't been. good for the Vatican. We got in at 20. billion. That was a 50 bagger for us.

So, let's get started. >> Jason, I'm pretty sure you believed you. were the vicer of God before the. encyclical. So, this is nothing new for. you. [music]. >> Let your winners ride. [music]. >> We open sourced it to the fans and. they've just gone crazy with it. [music]. I'm going all in. >> The smoke has risen from Tratad's pool.

house [laughter]. and from the poker room. >> He's staying in my pool house. He's been. there for the last 3 days. >> It's been magnificent. He didn't know. You know what? I understand where OJ was. coming from. You know, you put. [laughter] Ko Kalin in your house for. long enough, you just lose your At. some at some point, somebody's getting. whacked. All right, enough with the. shenanigans. Uh, but it's been great. staying at the house because there's. actually Chimant is not aware of this. There's an iPad in the kitchen and. that's logged in to Uber Eats, Door.

Dash, Instacart, Amazon, Laura Piana. Come on, stop. >> No, there [laughter] is. It's literally. every single service. And I told the. house manager like, listen, any packages. that come in the next 72 hours, right to. the pool house, if it says JCAL, right. to the pool house. So, all these. packages have been coming. Then I. relabeled them, gave them back, sent. them to the ranch, and now the house. manager is sending that stuff to the. ranch. >> Laura Piana wants to know why my inseam.

went from 36 to 12. [laughter]. >> Your waist size went from 32 to 36. [laughter]. All right, welcome to the program, everybody. David Saxs is here. How you. doing, David? >> I'm good. >> Chimoth Poly Hopetia is back at the 8090. office. I was at the 8090 office the. last couple days and it's a vibe. It's a. vibe. There's like a great culture going. on. >> If you're a bestie and you show up at. that office though, everybody there is a. huge fan of the pod. So I was like it.

was like being royalty. It's stopped by. everybody. Hey, I'm a developer here. I'm a big fan of the show. Thank you for. giving it to Chimath. We can't give it. to him because he pays our mortgage and. everything, but every time you stick it. to Chimath, we love it. We're cheering. for you in the secret slack room. Um, and. >> there's a secret slack room. >> There is. There is definitely a secret. slack room going on. >> No, but it was great. The vibes were. awesome. You're building a lot of. software. A lot of young talent. I don't. want to say that where your secret.

source is, but there's a secret source. of talent you have. And uh, man, those. are some smart kids. >> I'm happy to say it. Look, when I was at. Facebook, we became the most aggressive. recruiter of Waterlue co-ops. And so, I. went back to the well. Yeah. We recruit. more interns every quarter than we have. full-time engineers, which we do on. purpose because it puts a ton of. pressure on the product actually being. good. >> We had 400 people apply this quarter for. internships.

>> Wow. It's very interesting. Uh with us. sitting in for Freedberg, who's busy. with some potatoes seed this week doing. great stuff at Ohio, the one, the only. Bill Gurley is here. He's been running. down a dream. If you haven't bought the. book, get the book. It's incredible. And. you're off book tour, so now you have. time for us. Yeah. >> Yes. And I, you know, I had told you if. you ever talk about the Pope, I'd love. to hop on. And so. >> yes, you were like, [laughter]. >> well, you know, he Bill's an.

evangelical. I'm a Catholic. So, we do. have some common ground here. Do you you. when's the last time you were at church, Bill? Have you have you thought now that. you're, you know, >> when Jal gets sacriiggious? [laughter]. I got to come on there and make sure JCL. doesn't get out of line with the Pope. >> Listen, the [laughter] Pope is God's. messenger on earth. We should give him a. base level of respect. [laughter]. By the way, that's us imitating Bill. Gurley. This not actually Bill Gurley.

Just for those of you listening, you. think they were confused. [laughter]. >> They were literally they were confused. We don't want to put words in your. mouth, but just point of clarification. But hey, everybody knows you were uh you. know, you uh handed the baton over at uh. Benchmark after a very successful couple. of decades in venture capital. You wrote. the book. You've now got a nonprofit. You're doing your own spin, I think, on. uh maybe what Peter Teal does with his. fellowship. You started your own running.

down a dream fellowship, I understand. >> Yeah, it's uh it's targeted at a. different demographic. It's called uh. rdad.org runningdownadream.org. There's a website we can give a link to. We're going to do $5,000 grants to. people who want to chase their dreams. but need some help. And so there is an. application process like Teal Fellows. and other programs and we've been out. talking to those people. Um but we're. we're we're actually live. We went live. last week for the application. So if you. know people who have read the book and.

are inspired and need some help, have. them apply. >> Yeah. All right, folks. And uh Good for. you, BG. Yeah, great two two other So, I. did a TED talk which will come out soon. that's related to the book. Um I I uh. there's a professor in Miami that's. built a course around the book which I'm. excited about and he's he's he's doing. it in a kind of an open source way so. that other people can borrow that as. well. And so if [snorts] there anyone. out there I'd love to uh help them do. that. >> What's your take on all of this.

dumerism? Like if you're a young person. and you're in college or you're in high. school, is this is this much to do about. nothing or how do you run down a dream. in the face of something like that? >> Yeah. Well, I you know, I started the. book before this happened and I've been. asked the question a lot and it it came. up in the TED talk. I I fear that the a. lot of people are in jobs they actually. don't care about that much. And um. there's a Gallup poll that backs this. up. They came up put that word quiet.

quitters. They're like 59% of the people. they surveyed are kind of ambivalent. about their job. And when you're. ambivalent about your job, you're not. high agency. And so you don't lean in. You know, if you if you look at how. Jason talks about all how they. implemented AI and all of his his. different working groups, you hear that. enthusiasm and that high agency and then. you want to go try these things. And I. think the best way to protect yourself. from AI is to be the most AI enabled.

version of yourself you can be. But if. you're ambivalent about your job, you're. probably not doing that and you could. be, you know, a sitting duck. So I think. it's the mindset that's the problem. >> I created an associate in training. program for my firm cuz we want to like. help people get into venture capital and. we gave them a choice of assignments. One of them was to write coverage of one. of our portfolio companies that's. breaking out. Micro one is the name of. it and just give us like hey here's a. competitive landscape basically write a. deal memo and coverage of that company.

and then we gave them another option to. vibe code a very specific project I've. wanted to have for our venture firm for. a long time you know on competitive. intelligence and I would say I think. like maybe 80% of the students applying. and we had four or 500 people apply for. six positions 80% of them did the vibe. coding and I was shocked I thought it. would be the exact opposite Anybody can. write, anybody can throw in JBT and get. some output. But they they actually. built software and th that's the scary.

thing. The students who graduated, at. least this is my perception, Chimoth, the students who graduated like 5 10. years ago before AI, they're not AI. first. They feel lost in a drift. They. don't have agency. But the group coming. out of college right now that cheated. their way through school using Chad GBT, doing their assignments, like using. those tools, I'm joking, cheating, but I. mean hacking. I I agree with that. >> So they were totally. >> Yeah. And and they're just like, I know. how to use these tools to get through my.

finals. Yeah. >> Girly, I think you're saying something. super important. I said this last week, which is. >> nobody asks the warehouse worker at. Amazon whether they actually want that. job. And so to your point, job. satisfaction isn't some external person. judging your job to be valid and saying. you must be able to have it. I think it. should be asking the person that does. the job, do you like it and do you want. to keep it? Those are two very different. questions. And. >> yeah, >> I think that the all of this AI doom and. gloom was a lot and too much frankly of.

the former and not enough of the latter. And now this whole lie is kind of. getting undone. I think Saxs posted. about it this week as well. The Goldman. Sachs CEO said it. And now in this crazy. twist of fate now that we need to have. trillion dollar IPOs, the entire. Frontier Labs are all like, "Wow, it's. going to be a bonanza of jobs." And. >> Mark Cuban had had a great quote. He. said there are two types of people in. the world. Those that use AI to learn. faster than they ever could before and. those that use AI to avoid learning. altogether.

>> And I I think it's this notion of high. agency or not. That's pretty good. >> Are you leaning in and using this stuff. to be ever more powerful in what you try. and accomplish or are you using it, you. know, as a cheat code? And if you're in. the latter, yeah, you're probably at. risk. You get asked a lot about how to. educate yourself if you're a parent of. kids. so that you can put them on a path to. launch and do well and chase their. dreams. >> You have a good answer for that. question. >> I I mean the the second chapter of the.

book's all about lifetime learning and. it's kind of a requirement that you're. following your fascination because the. lifetime learning comes for free if. you're fascinated with something like. you just constantly soak up and devour. new information. And I I do think that a. lot of kids get exhausted because we've. made high school and college such a. grind that they think the learning ends. the day they they walk out with their. diploma. And as we all know, the best. and brightest in all of our fields are.

on a constant learning journey. And when. something new comes out, they dive in. and try and figure it out, right? And so. and every every single uh person in the. book that we profiled has that kind of. attitude about their craft, you know, in. every day. And so I I think the real. test is if you're not proactively. self-learning, then you're probably not. tilting against something that you. really adore and are fascinated by. >> Sax, you wanted to jump in there. With. respect to new college grads, I was.

going to say that I think the single. most marketable skill in the economy. right now has got to be proficiency in. Claude. If you're going into a firm. right now and you're the only one who. knows Claude, it would be like you're. the only one who knows how to work a. spreadsheet, you know, or word. processor, the advantage would be. enormous. Now, I think that that's. probably a short-term arbitrage because. eventually everyone's going to have to. figure out how to use these tools. But. as a young college graduate right now, you have such an advantage if you're an.

AI native uh just knowing how to use. these tools. And this thought uh. partially occurred to me when I saw what. our producer Nick has been doing with. using Claude for you know he's been. creating this daily briefing document. >> We've been doing it we've been doing it. for three months actually. >> I just ran it for the first time. apparently. I didn't you've been busy. >> Yeah. Well, I just, you know, I thought. it would just be AI slop and it would. just kind of give me a roundup of news.

that I was getting in my X feed anyway. But actually the thing that was really. impressive about it was that it. predicted topics that I would. specifically be interested in based on. my previous comments on the pod and also. it went back and looked at previous. transcripts and what I had said and then. had updates to those topics based on. specific things I had said. So again it. was highly highly contextual. But then I.

asked Nick, how did you generate that? and he showed me the the custom prompt. that he designed for Claude and then the. skills document and they were very long. and detailed documents. They weren't. written in code but they were very. technical and I just realized looking at. that that the average person is not. going to be able to generate this. I. mean this is why this idea that you're. just going to be able to like throw AI. into an organization and it's just. magically going to generate value is not. true. You have to know how to. >> get value out of it. I mean maybe we. could just show these documents on the. screen. >> Yeah. I mean the the the interesting.

thing uh Sachs is you can you just have. to ask your AI you ask claude or chatgpt. or whatever you're using hey I want you. to make me a mega prompt and you like a. mega pint like give me a mega prompt of. you're an producer of a podcast these. are the four characters on the podcast. what would be a great prompt for me and. it will actually suggest a prompt. >> and then you can refine the prompt so. you actually have a dialogue about a. prompt as opposed writing the prompt.

yourself. like. >> well Nick can you show on the screen to. scroll through the training rules and. then also there's the skills document. that was written on how to be a producer. >> for this podcast which I thought was. really impressive. >> by the way David what you said I think. is true of almost every single job type. like it's not just tech or programming. if you're in marketing if you're in. legal if you're in accounting. Like any role you might have at a firm.

sales, if you're the most AI savvy. person of all your peers, >> you are golden. Like you are golden like. in your. >> 10x more valuable than the next person. who's not basically. >> Yes. Yes. And and and I think that I. don't think it goes away because I think. you learn how to get better at it over. time. So having an early advantage I. think will extend for a while. because you can learn more more and more.

things you can accomplish. >> Should we let producer Nick describe. what we were just looking at there? >> Yeah, go ahead, produce. What? Producer. Nick, explain the process. >> Yeah, once we got access to Claude. Co-work and it had that like further. expanded memory access. I thought it. would be interesting to just start. feeding every transcript into it and. seeing if it could actually. contextualize new stories that were. coming out based on past things that you. guys have said. And I gave it like a. general prompt of what I wanted and I. said, "How would you write a skills file. or some training rules for this?" And it.

wrote all of it for me. >> Yeah. >> Oh, so you were less good than I. thought. [laughter]. >> I thought you were. >> It's a hack. It's a [clears throat]. hack. You use AI to make the skills. Yeah. And. >> but you've been updating that over time, right? As you've been iterating and. learning. >> every single day and every single day. gets smarter and better. >> The recursiveness of this is incredible. >> So you need someone to manage that. process, right? because the four besties. are not going to do that. So you need a. producer of the show to do that. This is. why people think, oh, it's just going to. wipe out all the jobs. No, someone still. has to supervise, iterate, validate, you.

know, all those kinds of things. >> Yeah. And it's. it's really interesting that the the. people who are coming into the workforce. right now are super aware of this and. they're putting the tools to work and. it's much easier for them to get a job. I mean, I I literally looked at the top. nine candidates for this associate and. training program I have, and we're going. to do it every year. Every summer, we. start it. We do it for a year. We pay. you to learn. And um it it it was just.

extraordinary how you could tell. immediately if the person had systems. thinking Sachs like they understood the. the process of venture capital that. there was a structure to it. You had to. source deals. You had to make decisions. on which ones to invest in. You had to. do diligence. you, you know, you had to. double down on investments, they they. just understood the process and then. when if you just talk to one of these. LLMs, it will tell you what to do. So, you can say, I don't know what I'm. doing. What should I do next? And then.

it actually tells you what to do next. So, for people who are intimidated about. this and uh maybe think like, I it I'm. I'm already too far behind, I encourage. you to pop up Claude, go into co-work, and say, "What can I do to be better at. my job?" and just start talking and. literally if the more you talk and you. can use voice uh you know text to voice. I use whisperflow is a really cool. program for this and I have a foot pedal. to do it you just ramble and ramble and. ramble and keep adding stuff you don't. have to be structured it will build the.

structure around the two or three. paragraphs that you give it as. instructions that's the thing people are. getting caught up on now is Bill they. they think they have to type when in. fact if you just blather on and on a. scale I have a unique uh ability to do. You just blather on. It's a superpower. You blather on and the thing makes sense. of it. It is unbelievable what the. blatheron prompt can get in terms of. output. Thanks for coming uh to uh my.

TED talk. All right, let's get started. There's a lot to talk about and uh we. got a big docket today. We're going to. start with the Pope. The Pope is dope. And uh the Pope Leo, he's the 14th, released his first encyclical encyclical. on AI. And it was long. 235 pages over. 42,000 words. Just to give you an idea, Bill Gar, >> when did he write it, do you think? When. did he put that together? >> Well, no, no, I think he used chat GBT.

That's what it says here um in the. notes. No, I mean I I'm guessing. >> how long did it take for him to write. this in between all of his other tasks? I think it's a six-month process to do. this, but I'm sure he had collaborators. >> Bill, your book, I'm assuming, was. >> write it. >> I'm sure there was a team that wrote it. But Bill, your book's 60 70,000 words, I'm guessing. So, this is almost a. literal book, right? >> In terms of how long it is, and it's. called Magnifica Humanitas or.

Magnificent Humanity. In it, he warns. business leaders to safeguard humanity. from AI. His core argument is AI is not. inherently evil, but technology is never. neutral and that technology takes on the. characteristics, wait for it, of those. who build, finance, and control it. And. I don't think he thinks super highly of. that group of people. The Pope called. for regulation of AI companies. Obviously, we're going to have that. debate here. Some of the things he uh. called for I think are not very.

debatable and there's a lot of consensus. around worker retrainment, safety uh for. children and guard rails, a ban on. autonomous weapons. That's the uh Skynet. rule. Don't build terminators with your. AI. But he was joined by anthropic. co-founder Chris Ola. I don't know how. many co-founders there are of this. company, uh but apparently there's. dozens. And Ola is not Catholic. According to a Vanity Fair profile, he. was raised evangelical and now he's an.

atheist. The folks at Amazon, Google, and Meta lobbyed the Vatican on April. 29th to soften the language in his. missive and uh he was not swayed. His central question, Saxs, is will AI. be used to concentrate power in the. hands of a few or will it serve. everyone? Something you brought up when. you mentioned monopolies, duopolies, etc. two weeks ago on this very podcast. What's your take on the Pope and his.

interest and his missives on AI and. promoting a bit of AI regulation? >> Well, I very much agree with the Pope. that the biggest risk of AI is a. centralization of power and then its. misuse against us um in some Orwellian. way. I think it's government that's. going to do that. Um, not necessarily an. individual actor because it's. governments that ultimately have the. power. So, I do worry about the. potential for AI to be used to surveil.

us, censor us, control us as Orwell. described in 1984. So, if that's where. the Pope is going with this, I very much. agree with him. The maybe where we end up in different. places is he thinks that government. regulation is the way to prevent this. And I would just say that we have to be. careful not to empower government too. much because if you give government the. power to regulate or approve AI. development, if you create say an FDA for AI as many.

people are calling on, that will give. government the power to approve models. and and therefore give notes to model. developers. And very soon this. definition of safety will expand because. the government always takes an expansive. view of its powers. And we saw this. during the social media wars where the. definition of trust and safety expanded. to issues like psychological safety, microaggressions,

disinformation, transphobia, and so on. That, you know, again, these social media companies were. told that they had to stamp out all of. those threats to safety. And it ended up. becoming a censorship agenda. So I get. very worried about you know what if some. government agency can give notes to the. model developers and they start telling. the model developers that your. definition of safety is not expansive. enough. You have to again protect the. public from disinformation or you know. psychological harms. So again, I think.

we just have to be careful not to. arandise government because that's going. to be the most likely culprit in terms. of the centralization of of power. And. um I know the um the Vatican likes. Latin. This is a problem of political. philosophy that goes all the way back to. Socrates. It's called quis custodos. custodes which is who will guard the. guardians. In other words, if we entrust. a set of guardians to protect us from a. bunch of threats, what's to stop them.

from becoming tyrannical and from. becoming the new threat against us? And. I mean, this is a the central dilemma of. political power. >> Who watches? >> Yeah. Who watches the watchers? Who. guards the guardians? Meaning, who's. going to protect us against our. guardians if they turn against us? The. genius of the American founding by the. way is that it was a second order. solution to this question. The founders. of America very much understood this and. what they came up with is we have to. have the guardians guard against each.

other. And so they came up with the idea. of separation of powers. We'd have. separation of federal and state. We'd. have um the three branches of of the. government. Even within the legislative. branch, it was a biccameal legislature. So they divided up the powers in a way. that hopefully the guardians would check. against each other as opposed to. becoming tyrannical against us. And that. that is kind of my view on AI is that. ultimately we have to have a solution of. checks and balances. If the AI market.

becomes monopolized and falls into the. hands of one or two companies, I would. use antitrust law very aggressively to. as a check and balance against their. power. Right now we have a very. competitive market. You know, we have. five frontier labs competing very. aggressively. As long as the market is. competitive, I would use that because I. think competition generates the best. outcomes. It helps us win against China. But it also protects the population. because these companies, you know, if. they get out of line, there's some. competitor that can offer something.

better. >> Consumers can opt out of it. If they. don't trust GPT, they can use Anthropic. or if they don't trust Anthropic, they. can go to Grock. Bill, you had the. number one rated talk at the All-In. Summit in history, 2,851. miles. You have been famously against. regulatory capture. In light of the. Pope's comments of, hey, regulating, what do you think is common sense? Because AI is everything. AI can help. people make boweapons. It can also help. people get their term paper in or do you.

know uh be a better salesperson at you. know Oracle like we're talking about. paper like we're talking about oxygen. here this is like a fundamental. horizontal technology so where do you. think there is a case to regulating AI. if at all and where do you think yeah. free market will figure it out. >> well I have I have two takes one on the. pope and one on anthropic so your. questions your question powerful let's. with the more let's go with the more.

powerful entity. We go you want to go in. reverse the least powerful of the two. go. >> So so this pope said that and I have to. learn how to pronounce all these Latin. words like you that this encyclical was. u was mirrored after one done by Leo I. 13th in 1891 and he invoked that he even. said he chose the name because he's so. enamored with Leo I 13th. Leo the 13th. encyclical warned that the industrial. revolution was going to be bad for. people. So let me tell you what happened.

from 1891 till today. The work week went. from over 60 hours to 34 hours globally. Real wages went up 8 to 10x adjusted for. inflation. The medium worker now earns. more than a doctor did in 19 in 1891. Global GDP per capita went from 1500 to. 20K. Child labor in the US went from 18%. to zero. Workplace deaths fell by 40x. Life expectancy went up 60%. And global.

poverty went from 75% of humanity to. under 10%. All those things happened. because of technology, innovation, and. capitalism, which is exactly what Leo. the 13th was warning against. So he got. it dead wrong. He got the whole thing. precisely wrong. So it's an interesting. thing to say you're borrowing from. >> Yeah. Uh so now on to. >> Yeah. Anthropic and just common sense. around do you think there how would you.

regulate and or protect against maybe. we'll broaden the term here protect. against nefarious uses of the. technology. Obviously we all want. children to be protected. We want to. have truth uh and honesty in terms of. facts and and all of us sharing some. some basic truths and we obviously don't. want people using this technology for. boweapons and the Terminator scenario. >> I have to tell you that that Anthropic. is a mystery to me. I've never ever seen. a company that is both leading their.

field and the most negatively outspoken. commenter on what they do. I I've just. never seen it. And my initial theory was. the regulatory capture theory that they. just want to ensure there's regulation. And quite frankly, I think they're, you. know, very close to achieving that. Like. they have stirred up, you know, a. frantic position, especially in America. American consumers are definitely afraid.

of AI. Um, I think I've talked to you. guys in the past about, you know, the. book that Jonathan Heights written about. social media and there's a whole bunch. of state legislators that think we. should have regulated social media and. so now they're destined to want to get. in front of it. And we know that. Anthropics, one of the most aggressive. lobbying company startups of all time. You know, the the the amount of effort. that they're putting in, the amount of. money at a statebystate basis. So that.

was always my first theory, but then. they just they got so loud that I I've. literally in the past 30 days read. everything I can about anthropic and. I've come up with a new theory. This. this. >> okay new breaking theory. >> This I call it the Dr. Frankenstein. theory. Um you remember when Elon had. that conversation with Larry Paige where. Larry called literally sitting next to. him when he called? >> Explain the story real quick. while we. were at uh a birthday party and and you.

know Elon was like listen humanity needs. to be protected from the stuff at. DeepMind because at DeepMind they had an. example of the AI having tried to break. out to jailbreak out of its computer and. not be turned off and you know had some. sentience or some you know inkling of. sentience and he said you know we have. to protect the human species and he said. well Larry said well what do you think. that's species because you care about. the human species over AI. This is at. least 15 years ago.

>> No, this is right before Elon co-founded. uh Open AI, right? Back in 2015 or. something. >> The actual story here is Elon Hon and. Google had backed Deis and the team at. DeepMind when they were an independent. company. Then Elon was like, "Oh my god, Google's going to buy this." And I. remember having the conversation with. Elon about this. We have to figure out a. way for DeepMind not to go to Google. We. have to block this somehow. But he. begged those folks to not sell to Google.

because Google was running the table on. everything and he wanted this technology. to be independent and he was on the. board of the company. >> and he also said this was his motivation. to launch open AAI as a nonprofit. >> Google got it. He just said we we this. is this technology is too powerful for. any one person. So like once again you. got to give Elon a lot of credit. He saw. the writing on the wall if one person. can and he saw it 15 20 years ago and. him and Sam Harris used to debate this. over dinner. You know what happens if. somebody controls this and they run away. with it. It would be extremely.

dangerous. It has to be available to all. the people. Essentially the pope's. position. It has to be in the service of. humanity, not ruled by one person. It's. far too powerful. >> So the reason I call this the Dr. Frankenstein theory is the more I dig, I've met people who I who I dare say. think it's their responsibility and. they're excited about building a species. that's that's superior to humans. And I. would just encourage people to read, you. know, as much as they can about.

anthropic. Chris Ola worked on this. thing called the Constitution. It's. about 80 pages. It's hard to get. through, but I would encourage you to. read it. Amanda Ascll who is the chief. philosopher has started doing podcasts. I would encourage you to listen to them. and listen to her language. And then. Daario wrote this blog post called. Machines of Loving Grace. >> Loving grace. I read it. >> and it it was based on a poem and the. poem is kind of weird. I we should put a. link to the poem. It's quite short. But.

the last the last stanza of the poem. says, "I like to think of a cybernetic. ecology where we are free of our labors. and join back to nature. Return to our. mammal brothers and sisters." I don't. know what that means. Like we're going. to go live in the fields where the. mammals live. I I And then the kicker. and all watched over by machines of. loving grace. Sounds like overlord to. me. And then in Daario's post he says he.

near the end and it's very long. You. read it Jamal. I mean machines of love. and grace is very long but he's he's. talking about in the future what are. humans going to do because he believes. in the massive abundance and UBI and. that we won't have to work. I don't. believe in any of those things but he. does. And then he says it could be a. capitalist economy of AI systems which. then give out resources to humans based. on some secondary economy of what the AI. systems think makes sense to reward in.

humans. So So that's envisioning a a. deity of sorts that's going to break. ties and discern decide what humans. >> it's a it's a computational reward. function for humans. It decides how much. you're worth. >> Yeah. So, I don't think they think. they're writing software. I think. they're midwifing a deity here. And and. I don't know which one I'm more afraid. of, the regulatory capture or or or or. this second theory I call the Dr.

Frankenstein theory. It it's more it's. more scary to me. I think the second. thing. >> these are delusions of grandeur. Let's. call it what it is. They believe that. they are so intelligent. I know some of. these folks, the Burning Man sort of. offshoot of it, transhumanism. They. believe that they're so powerful, these. individuals, that they can create God. and that by creating God, they are like. this Prometheus kind of species. It. literally is the ultimate level of.

narcissism and delusion of grandeur to. think you can create God and that then. the god you create like you're saying. Bill is going to be so benevolent and. perfect that you create constructed the. perfect God that will give you your. pellet will give you your little. scenarian you know. >> I just would correct you I didn't say it. Daario said it. >> right but no to [laughter] but to your. point of like just taking them at their. word they actually believe that they can. create God and that they'll create a god. so good that it's better than humanity. Saxs, your thoughts.

>> Well, I guess the question then is why. are they pushing for the let's call it. red capture agenda where. >> I know why. >> Go ahead, Jamal. Go ahead. >> That is very reductive game theory. So, if you want to be unexploitable, I think. the best thing that you could do if. you're trying to build a super god is. have three or four entities in a room, close the door behind you, and then. dominate those other three or four. entities, and then you set the rules. And because your counterparty is unable.

to track at the level of technical. capability that you would have, you. create this massive asymmetry that. allows you to exploit them. That's just. simple game theory optimization. And you. know what Bill said is so powerful. I've. read these things and it's laborious and. it takes time, but every time they put. these things out, just take the time to. read it. And what I have said before, Bill, I don't know your point of view on. this, but I initially thought that this. was mostly game theory, that a lot of.

their reactions I thought were less. rooted in their dogmatic beliefs and. more rooted in a GTO approach to either. raising capital or putting pressure on. competitors. Either way, both could be. true. What your framing is and my. framing, although mine's more tactical. than yours to be fair, because I've. always thought that these moves make. sense through that lens. How do you. absorb most of the capital? How then do. you make sure that you are in a position. to disproportionately affect the rules?

And how do you create an oversight body. that is less capable and intellectually. aware as you are about the actual. details because. >> the referees don't understand the game. Right? >> If the refs don't understand the game, you'll run over the game. Yeah. >> By the way, by the way, one thing they. have achieved by doing this is I think. that if you pulled the, let's just call. it the intellectual elites, so everyone. in the media and whatnot and the.

professors and all those, and they were. to rank the different AI players by who. they think is most caring, I think. they'd probably put Anthropic first. because they've been out with the. doomerism talk. And so it's given them a. halo with the people that may matter to. what they want to accomplish. It it's. simultaneous. creating a lot of trouble like with the. data centers and whatnot. Like there's. there's negative ramifications. >> What you're saying is so important.

because on the one hand they create. empathy. and then they write these documents that. expose what they think and nobody. actually connects the dots. >> Yeah. To steelman their position for a. second. I mean, I think probably the way. they think about it is that they are. creating something very powerful, something godlike, and therefore it. needs to be safe. and that they care the most about that. out of everybody. Nobody else takes this. seriously. Remember that Enthropic was. basically a spin out of open AI and they.

felt that Sam and the company leadership. weren't taking their point of view. seriously enough. >> It was the most woke portion of Open AI. >> We're steel Manning. So the most for so. they they see the power of it. They're. the ones who are concerned about safety. >> and they care the most and therefore. they're in the best position to do that. >> Now I think the issue is just you can. see how this can lead to red capture, right? Which is if you brand yourself as.

the safe AI company and then try to. characterize everybody else as a. reckless player and reckless AI needs to. be stopped. you can see how this would. basically further your monopolistic. control over this industry. And if you. see AI through the lens that you know. that really frankly the pope and I see. it which is centralization versus. decentralization I do think that is you. know one of the key lenses we should. have on the technology is whether you.

want this to be a centralized or. decentralized technology. This way of. viewing the world leads to more. centralization and I think that's. dangerous. I mean, if AI is this very. powerful technology, I think it needs to. be decentralized so that all of us can. protect ourselves to some degree, right? We need to be able to run we need to be. able to run the AI ourselves on our own. hardware if we so choose, so we're not. beholden to a single company that might. be in bed with a deep state.

>> Let's say it very pointedly. If benefits. and compensation and economic support. were all of a sudden tied to some. algorithmic decision, this is a. dystopian episode of Black Mirror that. we're dealing with. And to your point, Saxs, you want 100 or 1,000 or 100,000. versions of what that answer is so that. there's actually a way to refute. a singular answer. A singular answer to. these kinds of questions, which is. effectively what some folks would want,

is incredibly dangerous. >> And this is something that is in. control, I think, of humanity. I've been. talking about AI sovereignty here for a. bit just in terms of how much more cost. effective it is and how you're not. training other people's AIs with your. knowledge and your insights. This is why. it's super important that open- source, open- source agents and local hardware. be able to run these models and that. consumers and companies learn how to. roll their own language models, how to.

make a small language model, an SML, a. VSSML, a verticalized one and run it on. your Apple hardware because Apple. actually has taken a principled approach. historically to your sovereignty for. your data. Data sovereignty now is. privacy. >> Yes. And now it's intelligence. sovereignty. the the intelligent. sovereignty is different than privacy. Privacy is, oh, you can't see my photos. You can't, you know, peek into my notes. app and what I wrote there in my. journal. Now, intelligent sovereignty is. you can't tell me what to think. You.

can't use your AI to analyze my photos, to analyze my emails, to analyze my. messages, and tell me how to interpret. the world. That's actually going to be. the next key piece here. This is why I. think Apple is just the dark horse in. this entire race. there is an. open-source product that can run on this. hardware, the M5s, the, you know, 48. gigs, 128 gigs, the stu new Mac Studio. coming out with supposedly a terabyte. That changes the whole game. And this is. so paradoxical, Bill, that our.

adversary, the Chinese of all people, the Communist Party is leading the. open-source movement and the United. States is centralizing. >> They're leading the openweight movement. It's not open source. Just the. distinction is important. >> Yeah. Yeah. >> Look, I Jacob, I agree with you about. the importance of open source because. open source means software freedom. You. can run the program yourself on your own. hardware. You don't have to share. You. don't have to give up your data. sovereignty. You don't have to give up. your privacy to again to some monopolist.

who's going to be, you know, in bed with. the government or the deep state, right? So that's the thing we're all afraid of. And if that's the only AI that's. available is from the, you know, monopoly or duopoly, then your choices are to live off the. grid and not participate in the modern. economy or give up control, right, to. some social credit system. So I think. the open source is really important. And. by the way, that was Elon's instinct in. creating open AI. He was afraid that. Google was going to monopolize AI. So. he's like, let's create open AI so that.

it's not dominated by a single company. But that that is I think the right. answer here is I know people want to I. think their instinct to the idea of. powerful AI is to clamp down and just. control it. But actually you have to. have multiple players. That's the only. way you're going to be protected is is. to have multiple players. >> This next wave of the market evolution I. think is going to be extremely high. stakes and messy. Nick, just throw this. up because I just want these guys to.

react to it. So this is a company that I. just ran into on X called Rogo. And what. they did was they created a test bench. and a set of evals to be a financial. analyst essentially and tested all of. the frontier models. And it was so. interesting because they summarized I. read their paper that they published and. I quoted the most interesting part. because I see it everywhere now across. all EVALs which is this one phrase there. is no single best model anymore. at the. top of the leaderboard. Opus 47, GPT55,

Sonnet 46 appear almost. indistinguishable, separated by less than, in this case, you know, 3/10en of a percentage point. overall. Read superficially, the results. suggest convergence. Three frontier. systems reaching roughly the same level. of capability. Okay, why is that. interesting? Well, you got trillions of. dollars going into each of these guys to. trying to create these next superb. brain, but increasingly our existing set of. evals and our existing capabilities.

when applied on these models roughly. produce the same thing which. theoretically says that these things are. getting commoditized way too quickly. And then you'd say, well, what's the ROI. on all this incremental spend, which is. a very interesting economic and. investment question. So I don't know. like gurley what do you think happens if. these evals continue to asmtote and we. need more and more and more money for. training. >> some of the smarter people in the open. source community have suggested to me. that we need more open-source connectors.

of types so MCP uh is actually run by. the Linux Foundation and if you think. about any surface area where a model. might interact with other software the. more of those connectors that can be. open sourced and commoditized, it would. lower. This is what Google did with. Kubernetes uh to to try and commoditize. where workflows live off of AWS and to. make it easy to migrate. And so the more.

you can create systems that make that. type of exchange you just described. super easy so that you can plug and play. the model and you have to worry about. things like context and how does context. come in and and data and you know stuff. that like glean and and data bricks do. but how anyway if you can do that if you. can create more of those connectors like. that then the models become swappable. and certainly with the both the model. companies trying to move up the stack. you have massive. desire from the app layer players to try.

and figure this out and we already you. know watched what cursor is doing and. playing with their own model and being. forced to kind of reckon with the fact. that they're coming up the stack fast. So I think that's a really good insight. that this gentleman shared with me and I. think we the founders and developers. that are out there should work on more. of these interfaces and throw them into. the open source world just to make it. more exchangeable, swappable. Is there. an issue right now with we don't have a. good harness for open source? I mean the.

way that like claude is a harness for. >> Yeah. There's people making open-source. versions of this or building companies. around harnessing and building the. integrations into it. But open source is. always like the last to build the fit. and finish around the product. They. focus on the core of the product, right? So like Linux for your desktop never. really took off because the interface. was never polished. The UI was never. like perfect, but there are companies. building that and I'll just I'll show. you one company that we invested in.

This is a company called Abacus and they. had a very simple idea. They came up. with their own hardware stack. They came. up with their own uh platform and now. they are sold out of these boxes that. they're building for insurance, healthcare and everybody wants to run AI. inside their organization and then start. building their own models. We actually. incubated this in our incubator and you. can check it out goabacus.co. They're just basically saying and.

organizations cannot get enough of this. product. It is crazy how. savvy these organizations are getting. and Chamat you're doing it with 8090 as. well I think where they're just like we. have to build headless products so that. we don't get locked into. any one provider. Whenever we go into. the Fortune 1000, we never compete with. OpenAI or Anthropic, they'll have a. preference sometimes of what they want. to see under the hood. So, our control. plane can basically hot swap, as Bill.

said, between one or the other. We've. also started to lay the seeds for open. source and open weights. But the reason is because they don't. want to be tied into one of these. critical frontier labs. They want to be. able to ride the wave of innovation, but. they're afraid of two things. They're. afraid that one technology leaprogs the. other too quickly for them to. participate and they pick the wrong one. And the second thing that they're. increasingly afraid of is terms of. service and being at the sake of a. frontier lab in a political philosophy.

that they may be in the crosshairs of. accidentally. Right? So you're a. hospital system in Canada. You support. the euthanasia laws in Canada, but this. frontier model in America says, "No, can't do it. So now we shut you off.". Right? That's an an example. I'm not. saying one is right or wrong. It's just. to illustrate the case. So a lot of the. folks that we see now in the fortune. 1000 and increasingly the global 1000. They want as Gurley said abstraction. above it. They want to sit as Sach said. in a control plane. They want to see be. at this level and they want to have the.

flexibility because they don't know how. it's going to shake out. They see all. the money being invested at the model. layers but they see the model quality. asmtote. So they're like, "Wait a. minute, what are we supposed to do just. from a risk perspective?". >> And and regula regulated industries are. particularly sensitive to these kind of. issues you're bringing up. >> Hugely hugely sensitive and regul. >> So if you just follow what finance, healthcare, you know, and and those kind. of folks are doing, they're just like. this has to be onrem and they're very. concerned about a data leak and they're.

very concerned about HIPPA compliance. They're very concerned about training a. model. Like what if you know all of a. sudden somebody does you know a query or. or writes a prompt and it pulls some. information from that Canadian. healthcare system and all of a sudden. somebody gets a result and that sounds. farical. Remember stable diffusion. built themselves on Getty on Getty. images. >> and they all of a sudden the Getty image. watermark was in the output like system. you see anthropic and open AI in all of.

these Fortune 1000s at the developer. layer cuz most of the developers have. their own credit cards they're allowed. to sign up for them you eventually wrap. them in an enterprise license so it's a. typical PLG-led market motion like we. saw in Slack we've seen it everywhere. the interesting thing is not that but. it's the unwind that happens then when. you have these huge licenses you have. these huge buckets of spend you can't. really tick and tie it together the CEOs. then wake up and are told by the CFO hey. FYI here's where we are Uber was one.

example a second I don't know Nick if. you have this tweet but from Vivecarpali. the founder of Clover yeah this was just. yesterday overheard from a fortune 20. company CEO asked for a billion in AI. generated OPEX savings at the beginning. of the year so we're 6 months in the. team has spent $200 million on tokens. and with minimal results. And so now they're in this weird motion. now where the CEO is pulling the budget. back and now you're having to cut the.

licenses. You just saw Microsoft. announce that they're killing the claude. licenses. It's a super dynamic market right now. and I don't think we know what the. terminal solution looks like. And by the. way, I would I would add Claude is. really good at product. Like Claude for. Excel is better than Copilot by not by a. little, by a lot. >> And so, you know, anyone that's going to. run against them, they're they are a a. worthy foe, I should say. >> Yeah. I think I think Claude is. exceptional, by the way. I mean, I use.

it every day. Yesterday, I hit my token. limit on my pro plan. I had to put on my. credit card, spent [laughter] another. couple thousand bucks, and I'm like, I. was so angry, but I did it because it's. so good. >> Yeah. >> Yeah. Go ahead, Sax. Wrap us up here. Yeah. >> Yeah. So, well, just to wrap up, let me. just connect a couple ideas. So, one is. that in terms of the the red capture. agenda that you're seeing in Washington, I think where it's all leading to is an. effort to ban open source models or open.

weight models. >> There's a lot of breadcrumbs leading. here. I think people who want this are. being a little bit circumspect. They. don't feel like they're quite there in. terms of being able to justify it yet. >> Can you explain it? >> Sure. You look at you look at a lot of. the rhetoric around how models need to. have guard rails and that with open. source models, the guardrails can be. removed and therefore they're dangerous. You see this rhetoric already in. anthropics blog posts. So, you know, any. threat that they describe, they kind of. go out of their way to take that shot at.

open source models. you saw it with. respect to cyber for example or with. respect to bio threats things like that. I mean I've seen that type of language. repeatedly that open models lack guard. rails or the guardrails can be taken off. and therefore it's a problem and I think. again they're trying to create ideas or. put predicate facts in the public record. to justify an action later on and I. think it's just a matter of time before.

they feel like they're at a position. where maybe they can push for that type. of ban [snorts]. directly. They're not quite there yet. >> But what does that do then to the rest. of the market? Like let's just say. America bans open source and open. weight. Okay. Well, what about the rest. of the world? I mean, >> it sure it'll put. >> they're going to leap frog us. >> Sure. You'll put the US on an island. Well, first of all, as we all know, what. does it mean to ban a openweight model? It's a file. It's a bunch of numbers, you know, that you can run on your your. laptop. >> Yeah. But what it will do is you think.

about like all the cloud service. providers who run open models like they. will stop doing that because they got to. comply with the law and so all this. infrastructure that's been built up it. will get much harder to use open models. in the United States now the rest of the. world will continue to benefit from them. because there's a tremendous benefit in. terms of cost and customization and. control that you get with an open model. >> and we're on a completely different. price curve. And we haven't talked about.

this yet. There was an economic and. capital mode to training that is going. away. It's going away in two ways. One. is because we're getting these domain. specific architectures at the silicon. layer. And then second, we're rebuilding. all of the core components. I don't know. if you guys saw yesterday, but Elon was. like, we've rewritten the entire. training complex in C and it's an order. of magnitude increase and we can run it. on 220,000 GPUs. at the scale of what. they're trying to do. Those kinds of. innovations are going to make the cost. of model training so much cheaper that.

it's like, why would we stick to the $10. billion training runs when we can have. the $10 million training runs? >> Well, if it got 1% better, just as a. thought experiment, Nick, could you find. Elon? If okay, if it got 1% better, that's the. equivalent of 2,000 GPUs, which is the. equivalent of hundreds of millions of. dollars in compute. So every 1% equals. hundreds of millions in compute. If he. gets 10% 20% more efficient every.

quarter, every. >> look at this speed improvement, the. speed improvement versus jacks for for. training runs is now an order of. magnitude. When you think about then the. capex buildout, the opex, the power, the cabling, the copper, all of it. And now this is a closed source model, but I'm pretty sure that just that tweet. is going to get read by enough people. where there's going to be five or six. open- source stacks for training that.

are rebuilt closest to the bare metal as. possible. >> Yeah. >> Why wouldn't you do that now? And so to. your point, Sax, cutting that off so. that we lose that kind of innovation. makes no sense to me. >> I agree. And and like I said, I don't. know that the forces who want to ban. open source are strong enough or have. made the case or created the predicate. facts necessary yet to ban open source, but I do think it is on the agenda and. it's where all the breadcrumb trails are. leading. So just watch out for that. I I.

agree totally with with what David just. said and I wrote a blog post recently on. open source and and made the exact same. point. >> I read that too. That was a good one too. on above the crowd. >> No, it's not. It was on the Santa Fe Institute. [laughter]. >> Oh, no, it's it's the P3 Institute which. is my new my new institute. Anyway, um I. same same exact conclusion which is rest. of the world ends up running on Chinese.

models if if if they're able to succeed. at what you just said. >> And if you want to know the canary in. the coal mine sacks obviously the place. they love regulation most is the EU. So. EU has already done volley after volley. of proposed regulation for AI and open. uh and open source is particularly in. the crosshairs there because nobody's in. charge of it. So are you going to get a. bunch of open source contributors having. to vet their model with the EU.

regulators like that's obviously not. going to happen. Nobody's in charge of. it. There just a bunch of contributors. But open source is the solution I think. to. >> Yes, I agree. >> It is the back stop. It is the backs. stop. I mean, unless you want to live. off the grid. I mean, if you want to. participate in the modern economy, it is. the backs stop. And let me just make one. other final point. It kind of maybe. leads into our next topic is I do think. that there is the potential for the. monopolization of this market to a. greater degree than people may be. pricing in right now. First of all,

we've seen that every other major tech. category has led to a monopoly or. duopoly situation. Seems to be the the. way that these things work out. But also. if you look at the growth rates right. now, Enthropic does seem to be pulling. away. There's a article in the. information showing the latest numbers. where I think Anthropic's now at they. seem to have pulled away from open AI, which is not surprising and something I. I predicted. Look, if you have one. company that's growing at 10x. year-over-year and another company. that's growing at 3x year-over-year,

within 2 years, the first company will. have 90% market share. This is the power. of compounding, right? is just do the. math on it. 10 * 10 is 100. 3 * 3 is 9. So again, if you just are able to. outgrow your competitor at that rate for. 2 years, you will achieve monopoly. market share. Now there are reasons to. believe that anthropic cannot continue. that growth rate for 2 years. There's. going to be a competitive response. It's. already happened. Also, there may not be. enough compute to support that kind of.

growth. There may be physical. constraints, but you'd always rather be. the company that has that inertia that's. on that totally trajectory than the one. that has to do something different to. then knock that leader off its current. trajectory. >> Did you guys see what just hit the wire? Nick, can you throw it up from Poly. Market? This is insanity. Poly Market. puts out there that an AI consultant. revealed that one of their clients. accidentally spent half a billion. dollars in [laughter] a single month. after failing to set employee limits on.

clock usage. [laughter]. >> What? >> Oh my god, look at this. Look, the 16.6. million per day, almost 700,000 per. hour. Oh my god. Well, there seems to be. there seems to be a new like meme taking. shape that somehow like all this token. spend is is wasteful and basically. useless. And you know, we're constantly. oscillating between narratives like AI. is going to put everyone out of work to. like AI is useless and it's a bubble. The doomers can't seem to make up their.

minds whether AI is going to be our new. god or whether it's basically a total. waste of money and it's going to lead to. a bust. But in any event, yeah, I think. you know the there there's no question. that token efficiency is going to be a. big theme over the next year because the. spend has been ramping up way faster. than enterprise customers thought and. there's going to be a drive for. efficiency. Does that fundamentally. change the dynamics? I don't think so. But it it might, you know, it might. temper the growth to some degree. Well, and they've done a tremendous job making.

people believe that tokens are free by. giving them these crazy deals like $20 a. month, you can do whatever you want. $200 a month, you can do whatever you. want. And it's like everybody's leaving. the hose on, everybody's watering, and. then. >> you get a photo that says you've hit. your usage and it's like, "Come back at. 230." I'm like, "230? It's 10:30. I. can't do anything between 10:30 and. 2:30." And then it says, "Well, you can. put in your credit card." And so I did. >> Yeah. But I mean it's it's literally. like the first the first 10,000 gallons.

of water are free basically and then all. of a sudden it's like okay it's a penny. a gallon and then everybody in the. organization and this has literally. happened in our organization. One person. built like an interface for the founder. university program. Another person built. one. Then another person was like, "Well, those two people got credit at. the management team meeting, so I'm. going to build an interface." And the. next person builds an interface. And. then everybody shipping like interfaces. and I literally had three different. people on the team make three different. versions of like a founder university. portal and I'm like, "We don't need.

three. Can we get coordinated here?" And. it didn't get to the point of like. spending thousands of dollars, but it. certainly got to the point of spending. hundreds of dollars and it would have. gotten to tens of thousands. >> Are we still on the first topic? What. are we doing? Well, no, we kind of. merged like two or three of them. together. >> Oh, we did? Okay. >> And it's super interesting. Trust me, >> it's super interesting. I think what. Gurley said is one of the most. interesting things I have heard. >> in a long time. >> Take people by their word. And if you. read their words, >> if you just read their words and you can.

understand what they're saying, you. don't have to guess about why they want. to have a digital guide. Well, now I'm. not the sharpest I'm not the sharpest. arrow in the quiver, but I can take down. a buck. And I can [laughter] tell you. that this don't make a lot of sense to. me. Even the dullest arrow can take a. buck down. >> All right, let's get back to. It's so great having you here, Bill. We. missed you. >> I [laughter] got you. I got you. >> We missed you, brother. >> We're going to transition to the next. topic. There is some evidence that.

Daario is mitigating his dumer rhetoric. Did you see this? >> Let me get to it. Yeah. Yeah, I got to. it here. All right, we we're going to. have to talk for the 16th time in the. last 18 months about AI's impact on. labor because again this chaotic. schizophrenic. interpretation of the data continues. Cloudfare as we talked about last week, shout out Matt Prince. Shimath's favorite CEO of the year. Letter of the year. >> letter of the year. He cut 20%.

>> award for the letter of the year. >> making friends every week. here on the program. So they both blamed. AI spec explicitly and specifically and. Zuck then paired his 8,000. cuts at meta with the fact that he has. put uh spyw wear on everybody's laptop. to study every employee to make their. training data better. That got leaked. and people thought, hey, that's a Black. Mirror episode. We're we're working at. Meta in order to, you know, get our.

two-year severance package. But on the. other side of the table, Goldman Sachs's. uh CEO, David Solomon, wrote an op-ed in. the New York Times. I'm the CEO of. Goldman Sachs. Period. The AI job. apocalypse is overblown. Period. Obviously, he might be fighting for that. anthropic or open AI IPO in the coming. months, or maybe is doing it right now. He made three points. AI won't eliminate. 25% of jobs. It's going to automate 25%.

of work hours and workers will fill that. time with higher level tasks. Obviously, that didn't happen in the case of. Zuckerberg's layoffs. Just because a job. can be replaced doesn't mean it will be. Bank tellers increased after ATMs. Live. entertainment became more popular after. TV. And the US labor market creates and. destroys 25 to 35 million jobs annually. And the gross churn dwarfs net losses. New categories like agentic AI. management are already hiring yada yada.

yada. Uh a publication called Fortune is. apparently still publishing AI slop and. they say both Sam Wman and Daario have. walked back their AI job apocalypse. predictions as they gear up for an IPO. sax have at it. You know you've been. saying uh and your prediction was you. took the other side hey we're going to. create more jobs. There was a a recent. one of the job boards put out some stats. that the number of software jobs is. going up, the number of listings of. other jobs going down. So, I guess.

you're probably in the camp of creative. destruction and churn at this point, Sax. >> Well, I mean, I think you should be. giving me more credit than that cuz my. most contrarian take back in January on. our prediction show is that AI would. lead to job gains, not job loss. And. over the past week, you've now seen the. narrative shift, I would say, almost. completely towards that position. So, you have the CEO of Goldman Sachs right. in this in the New York Times. You know,

I don't think he'd be doing that if he. felt like he was completely stepping out. on a limb. Maybe even more importantly, you had Sam and even Daario now walking. back their claims of massive job loss. And they explained why Daario said, it's. kind of like the 25% of work hours. thing. He said that AI might automate. away 90% of someone's task, but the. other 10% will expand to do a whole. bunch of new new tasks and new things, which is very similar to the the types.

of of arguments that people like me have. been saying and actually that Jensen's. been saying that just because you. automate away some task doesn't mean. that you automate away the purpose of a. job. But now the worker is freed up to. do new things, to do the higher. complexity tasks that David Solomon, the. Goldman CEO, is talking about. So the. fact that Daario is now walking this. back and coming around to my position, I think that that's kind of amazing. And.

uh where do I go to get my apology? You. know, >> well, we're going to have an ap. [laughter] we're going to have an. official apology form that you can fill. out. It's got check boxes. I was wrong. I mean, some mornings I woke up. thinking, why am I going out defending. these guys? You know, these idiots. I. mean, they're scaring the public with. all these dire predictions about an. apocalyptic future. There was no data to. support that. I mean, we can all debate. what's going to happen in the future, and we probably should be humble about. what is going to happen in the future.

because we don't completely know, and. this industry is very dynamic. But you. have to look at what is the data that we. have so far in the current situation. And we do not see data that supports. massive job loss. You can cite this. layoff or that layoff Jcal those are. anecdotes and the plural of anecdotes is. not data. If you look at the actual data. like Yale Budget Lab did they said no. discernable disruption in the labor. market in the last 3 years due to AI. they've done a comprehensive study. You. look at job postings for software. engineers. It's up 15% year-over-year.

Their job postings for software. developers have hit a new three-year. high despite the fact that coding is the. single breakout use case of AI this. year. So if AI has not caused job. elimination for software developers, what category has it caused? I mean code. is now the number one use case I think. of AI in the enterprise. >> Okay, >> let's be honest. Over the last five or. 10 years, a lot of companies overhired.

They mishhired. These CEOs did not have. a good handle on it. Their opex budgets. completely got bloated, inflated, and they need to sort of get back to. where they were, get back to a fighting. weight. And it's this old adage of never. >> never waste a crisis. >> Never let a good crisis go to waste. Exactly. And so they point to this. thing. It's very simple to say. It's AI. It's two letters. And say we're going to. fire people. But underneath that is not.

AI because we know this. It hasn't done. anything measurable yet at the end. consumption of these tokens. Nobody is. standing there and saying look at my. filing. here is the lift that I have gotten. Nobody has said that yet. That's very. important to observe. And so instead. what people are doing is realizing okay. I have this cover now to go and clean up. what was very poor management and. mismanagement over the last 5 and 10. years where I overhired and I mishhired. That's what's happening today. >> Okay, Bill Gurley, I'm going to let you.

chime in here. You've got two besties. saying, "Hey, this is all hogwash. It's. AI washing. These jobs were just, you. know, the strategy obviously in Silicon. Valley was. >> they need a scapegoat. They need a. scapegoat. >> They're hired two years ahead of time. Build for the future and it was a vanity. metric and you were blocking talent from. working on other startups or. competitors. The Google strategy.". >> Hold on. Wait, wait, wait. You just said. the critical thing. That is exactly why. they did it. >> Yes. That was the explicit strategy from. >> the actual strategy. These guys were a.

wash in cash. And so part of it is you. were just hoarding talent or what you. thought was talent. >> Yes. And just keeping them off the. market. >> And now you're jettisoning it because. the reality is as companies get bigger, their growth rates monotonically. decrease and you get to like a GDP plus. some number and your valuation. frameworks change and there's nothing. you can do to fight that law of gravity. in the public markets. And so as each of. these CEOs who at some point thought. they were different and the rules didn't. apply to them are now realizing you're. just like everybody else. Okay, we have.

to stay humble as Sax said, but Bill. Gurley, would you like to apologize for. Sachs andor give him credit for his. incredible non-conensus? >> He wasn't the Hold on. He wasn't the one. promoting the jobs apocalypse. >> It was. you. [laughter] I will give my thoughts. in a moment. You're the for the mainream media. >> I'll give mine. >> You always represent the legacy media on. our show. Jay Cal, you have been in the. fourth. >> I represent the legacy media represent.

You're the New York bluehaired. >> I'm just giving you the statistics, guys. I'm just presenting the numbers. Now, let's remember anecdotes. >> Let's remember. >> Actually, let me give you an important. statistic. Let me give you a very No, no. This is really important. >> We have to let Bill Girly comment. Then. you can really important. Do you use. ketamine? I don't use ketamine. That's. the terrible drug. Do not use ketamine, folks. >> Bill Gurley, you have the floor. >> I would just touch on two things that I. already said earlier. One, you know,

historically innovation has led to more. prosperity for humans. And I gave those. numbers from 1891 to today. I see no. reason why that won't happen here. In. the short run, from a bottomup. perspective, every human that wants to. protect themselves needs to be the most. AI enabled version of themselves they. can be. And the people that might be a. threat of job loss are someone who like. stands hard, fast, and refuses to use. AI. And I would just say that's simply.

like saying, "I'm not going to use. email. I'm not going to use a. spreadsheet. I'm not going to use a. computer." And and you know, you. probably are at risk. >> Yeah. Yeah. The paradigm will shift to. give you actually my position which is. >> Would you like me to give my position or. just want to jump? >> Yeah, I do but I I never got to finish. that point. So, but I can do it after. you. >> Yeah. Yeah. So, I I will give my. position on this which is there and it's. always been the same which is there's. going to be a massive job displacement. that occurs and that massive job.

displacement is going to come because. CEOs in many cases believe that this. technology is going to make people more. efficient. they can do more with less. and they will be rewarded by the public. market by just having higher earnings. and we see that for every single. company. Now I fully concur it was. because of bloating and I gave my. position there. I know specifically that. Sergey and Larry took that strategy of. taking talent off the market so there. wasn't a Google competitor that was. literally explained to me by those.

individuals. We hire people and then we. figure out what to do with them later. That strategy permit just became the. standard in Silicon Valley and now it's. being reversed. Now there will be wholesale jobs that. will be retired. If you look at. self-driving that's obviously happening. with Whimo with 3,000 vehicles and and. there'll be many more on the roads. That. job will be eliminated. We will be. sitting here in but 5 10 years and the. idea of somebody driving a taxi is going. to seem silly and dangerous. We will see.

the same exact thing happen with. Optimist. You may have seen the figure. robot sorting packages. All those. sorting jobs at Amazon factories are. going away. Amazon themselves, these are. the savviest people in the world said, "We are going to eliminate 600,000. future positions and we are going to cut. positions." And Andy Jasse said, "This. is going to be a reoccurring theme. As. we deploy AI, we will do more with. less." You will see the headcount at all. these big companies dramatically. decrease or stay the same as earnings.

massively increase. And you can take the. position, Saxs, that oh my god, the. numbers are in my favor. They're not. The numbers are in my favor. The job. loss is tremendous. And there are. numbers associated with that. 8,000. people at Meta after 20,000 before that. And if you look at the steady state of. these companies, they has nothing to do. with AI. Let me finish. >> They overhired. >> No, no, no. We are beyond that. We are. beyond that. They are now getting rid of. people. When they say they're getting. rid of measurers, you can take them at. their word. When they say they're.

getting rid of middle managers, you can. take them on their way and. >> scapegoating. That is you've given your. position already. I'm giving mine. My. position is they are obsessed with this. technology, they're obsessed with. earnings and they will continue that. Now on the other side of the ledger, I. believe we'll have a Cambrian explosion. in startups and all these this talent if. they embrace the tools to Bill Gurley's. point are going to be able to solve more. problems and create small companies of. five or 10 people who are laid off from. Amazon or Meta and make double their. salary or have a better job that they.

control. I believe that is going to be. the ultimate solution. But that. transition is going to be extremely. painful and we should have some humility. on this podcast for the people. impacted. Every cab driver is losing. their job. Every truck driver is losing. their job in the next 10 years. Anybody. sorting packages losing a job. Now you. can say all you want. You can say all. No, let me finish my thought. You can. say all you want, Chimov, that those. people don't want those jobs. But they. may need those jobs. >> and you are an elitist by definition. We. are all elitists on this program. We are.

elite performers. [clears throat]. >> And these people are gonna lose their. jobs and they may not get a job very. quickly. By being able to call something. what we think it is. is not being elitist. It's actually. telling the truth. Meta over hired. Okay? You could have stopped the company. at 3,000 people when I left and it would. not have changed the outcome of that. company. There was no need to go to. 90,000 people and burn $50 billion on. VR. They did it because they had the. freedom to do it. That's allowed. It's.

capitalism. Okay? They're coming back to. realize that there's a more efficient. version of what they are. That has. nothing to do with AI. That's the only. point I'm trying to make. All you have. to do is just say that. >> I think you're wrong. And let me explain. to you why you're wrong. I believe. you're wrong. I believe Zuckerberg is. putting that software on people's. computers in order to to find more jobs. to eliminate to increase it. And the. surface area of problems in the world is. not decreasing, but what is uh.

decreasing is the number of humans to. take on the next opportunity. And that's. going to continue. And I think the. companies that will be rewarded and. their stock prices will be rewarded are. the ones who do much more with much. less. And they're going to keep. eliminating these jobs. And I take them. at their word. >> You don't have to explain everything. with conspiracy. Maybe they just. mismanaged for a period and they could. agreed on that. I I think that explains. the postcoid two or three years. I think. what we're seeing this year is actually.

the tools working. the tools are working. and there are jobs that are no longer. needed. The measurers as Matthew Prince. pointed out or product managers or. designers, those have all been. consolidated into one job. Somebody who. ships a product and it doesn't require. 12 people. It requires two people now. I. know. >> I don't think that's been consolidated. I see it in Fortune 1000 companies all. the time. I don't think what you're. saying adopters. You're talking about. the slowest adopters. I'm on the front. line with. >> startup. These are where all the jobs.

are. But I'm sorry, but a startup is not. going to go and enter a regulated market. and put JP Morgan out of business. Not. gonna happen. >> They will eventually uh displace those. companies. It happens all the time. >> Not going to happen. >> We're going to agree to disagree. >> Good luck to the startup trying to. disrupt Boeing. Good luck. I'm going to. take Boeing. >> Okay. Well, some people might take. SpaceX. So, >> good luck making drugs out of an Excel. spreadsheet. I'll take the regulated. pharma company. Good luck. >> Sure. Listen, there are some industries. that are so much to one and you're going.

to show up at the FDA and like, okay, where's your team? Oh, it's just me. I. do it all. >> Me and my model. Look at this. >> You joke. Somebody just did that in. >> It's not a joke. It's not a joke. And. it's not going to happen because that's. not the way society wants safety, predictability, governance, auditability. to work. >> Yeah, I there's a distinct difference. between, you know, drugs and software. and services in the world. I think we. can agree on that. And listen, a regula. with truck driving is one of the most. regulated industries out there. So is. cab driving and taxis as Bill and I well.

know and those jobs are being. eliminated. Bill, I'm gonna give you the. final word, then Sax, I'll give you the. final word. >> A chance to respond. >> Let's do Sax. >> Okay, Sax, then Bill, go. >> Well, first of all, Jake, you remind me. of the Troskyite who when confronted. with the fact that none of Trosky's. predictions had come true that simply. proved how far-sighted Trosky was. >> I didn't go to graduate school. You're. going to need another reference. >> In other words, none of your predictions. about job loss have come true. In fact, the data. >> none zero data. >> except for what M just did last week.

But go ahead. >> That's an anecdote. That is not. >> It's not an You're calling 8,000 people. losing their jobs an anecdote. >> You don't hear yourself? >> Hold on. >> Do you hear yourself? It's not an. anecdote. 8,000 people lost their jobs. >> Can I make my case? I heard you about. the the meta data point. First of all, those jobs that job loss was not. directly attributable to AI. It just. wasn't. That's something you've invented. and put in the data. >> Something Zuckerberg said. No, they they. clarified that. Okay. Okay. Sure. >> He said it was related to they were.

trying to balance additional spending. capex, but it was not directly related. to AI. But even if it were even if it. were 100% the case that was due to AI, you're not netting those jobs against. all the other jobs that are being. created because of AI and all the new. companies that are being created right. now because of AI. So, you're just. cherrypicking one statistic. You're. attributing 100% of that to AI and then. you're not basically netting it and pre. presenting a balance. You've got. >> I'm not cherrypicking it. I am reading.

the news and I'm describing what the CEO. said. Jack at Block said he's doing this. because of AI. Matthew Prince said it's. AI. Zuckerberg said it's AI. >> I'm just taking them on their word. >> Yes. Exactly. So Jack Dorsey came out. and said that he was going to do a 50%. elimination because of AI. Okay. And. within 24 hours, all the financial. analysts on X said that Jack was AI. washing and that block had horribly. overstaffed during COVID. It was running.

much more inefficiently than all of its. other peers in this category. And. they've needed to do a 50% job cut for a. long time. So pretty much everyone. thought that was pure AI washing. In. fact, you've just proven my point. And. what exactly are the efficiencies that. Jack is getting? I mean, this is the. most handwavy thing ever that, oh, we're. just magically going to be able to. eliminate half our cost structure right. now. >> Okay. So, Jack, Matthew Prince, Zuckerberg, and Andy Jasse are all lying. and doing awashing.

This was due to AI. He just did it. >> That's that's your reading of it. But. like I said, even if you attribute those. specific job losses to AI, which is. questionable, you're not netting it. against all the job creation that's. happening and also the new company. creation. Furthermore, let me just give. you some I specifically attributed that. the future and the new jobs will come. from startups. So don't misrepresent my. point. Thank you. >> Okay, we currently have a 4.3%. unemployment rate in the economy.

Economists consider 5% to be full. employment. So basically unemployment is. at or near record lows right now despite. the of our lifetime despite the fact. that we're over three years into this AI. wave. Second and again this is the point. I wanted to make earlier with respect to. coding. Coding is the single job. category most impacted by AI right now. We are at the point where AI is writing. most of the code. We have almost. complete automation of codew writing. You would think that if you could look.

at this in a simple Malthusian way, all. the software developers would be getting. laid off right now. Is that happening? No. No. Software developers are not. being laid off on net. In fact, job. postings, job wrecks for software. developers are at a three-year high, growing 15% year-over-year. Now, why is. this? I think the explanation is really, really important. Okay, you look at code. commits on GitHub, which is the leading. code repository. There were 1 billion.

code commits last year. In the past. month, there's been 1.1 billion. So, in. other words, >> make something easier, more people do. it, >> right? We have basically a 14x. year-over-year increase in code. generation. That code has to be managed. by somebody. You still need humans to. look under the hood. And when the amount. of code explodes and you get 10x or 100x. more code, the complexity also rises as. well. So look, we're not hiring 10 times. more engineers, but you do need more.

engineers now to manage all of that. code. The other thing that's happening. is that there's been an explosion of the. use of code across the economy by. different businesses, different. applications, and different use cases. I'm hearing from people who are now. hiring software engineers who never. would have hired them before. I was. talking to a fund manager, and he said. that his next two hires were not going. to be data analysts. they were going to. be software developers because they're. now deploying code for the first time in. ways that they were not before. This.

goes back to my point about claude. proficiency being the most marketable. skill right now in the economy. People. are using these tools in entirely new. ways. I think that we're at the outset. of a boom right now caused by bespoke. software proliferating throughout the. economy and being used by firms that. never thought of themselves as tech. firms before. All of which is leading to. more productivity and that leads to a. healthier economy and that leads to more. job creation. And you're seeing that. again in the aggregate numbers and that.

doesn't even include the bluecollar boom. that's happening right now with the. development of all this infrastructure, the data centers and the new energy and. power generation. We are seeing hundreds. of thousands of new construction jobs. being created among bluecollars. Jan, I'm sure you don't want them losing. their jobs by turning this boom off. So. again, >> no I I never advocated you misconrue you. like to misconrue my position. I am very. clear there's job displacement going on. and the job displacement is related to.

AI but net I do think the economy will. grow. Bill Gurley. >> maybe at some point in the future you'll. be right like the Trosky eye communism. has never been tried. Maybe it'll work. >> Nobody knows your Trosky references. Okay you lose you lost 95% of the. audience. Just speak like a normal. person. >> Chimath laughed. Chimath understood it. >> Okay great. I know the artist is smarter. smarter than you give them credit for. >> Okay. No, I just think you're just. making these deep polls to try to sound. smarter than you actually are. Uh the. reality is the reality. These people are. being laid off because of AI. Bill.

Gurley, of 20 million people in the. United States driving cabs and trucks. and doing that as a job right now, how. many of those do you think will lose. their jobs to self-driving in the next. decade or two based on just being in. there? And I'm not trying to lead the. witness here in any way. Obviously, some. people prefer a human driver, but what. what's your take on on that specific. part of the economy? >> I think it's impossible to go with a. 100% automated uh solution. because the the economics don't work. well. And so, I think like some of the.

other examples that were given, ATMs and. whatnot, I I think the the use of. nonownership. cars is going to go way up. So, it's. going to keep growing through this and. humans are going to be used for like 50%. of it instead of a hundred. And so, I. might not be surprised if the number. actually stays the same or grows. And. let's remember these jobs didn't exist. before because regulation had limited.

what the taxi market was capable of and. and getting around that actually led to. job creation. And so I I'm not a big fan. of the doomerism because around jobs, you know, there's a word lite that that. kind of is used to to talk about it. And. I don't have high confidence in any. government program for skills. retraining. So it's not clear to me what. okay yes it's happened. What do we do. now? It's not clear to me. I think the. thing you can do the most one we already.

talked about use the new tools. Know. what it's capable of in your field. like. get out there. And then two, if your job. is going to go away and maybe it's a job. you don't care about, start thinking. about where there are opportunities. Everyone's talking about it. The skilled. trades are like we're we're short of. people. >> Shortage for plumbing, electricians, HVAC, all that. Yeah. >> It's amazing how Jay uses facts that. haven't happened yet as like support for. his argument. Like you just state that,

oh, all the truck drivers are losing. their jobs. All the drivers are losing. their jobs. And then you say that this. proves my take. Yeah, I know it's your. belief, but that is not proof. Do you. understand? >> The proof I gave was Amazon and Andy. Jasse, Shopify, they were doing that before Mark Benny. off automated Amazon. Let me ask Bill. everybody knows our Amazon car being. delivered so you cherry pick anecdotes. and then misattribute them to AI. >> They literally have a self-driving. division. It's called Zuks. >> You're the biggest AI washer there is.

They are the largest. user of robotics in the world. So yes, Chimath, they are pursuing robotics. massively more than anybody and they are. pursuing self-driving. >> You just you just like all these words. together. At one point it's a warehouse. worker, then it's a driver, then it's. Amazon. It's just. >> it's not it's not you can you can. personally attack me all you want. The. the issue here is self-driving is going. to take away I believe the majority of.

>> Okay, that's the key word. Great. Let's. put it there as a belief. Who knows? You. don't know and I don't know. >> Okay. And I think the same robotics. But. I will take people I will take people at. their word. I'm curious, Bill, your take. on. >> these large enterprises. You've heard. two positions here. >> I have a question for you. >> I have a legit question for you. >> Can I just let the guest be involved, please? Sax your monopoly. actually. engaging with your with your. perspective. Explain to me. No, no. This. let me let me truly ask you. >> Okay. >> Explain to me why job postings for.

software engineers are up 15%. year-over-year despite the fact that. code has now been fully automated. >> Oh, I think there's a Cambrian explosion. in uh software. You're absolutely. correct. And I believe people who know. how to vibe code or to like who are. non-developers are making bespoke. software. I've said that a hundred times. on this podcast over the last few years. and I predicted it. So absolutely I. believe that will be an area of job. growth. I believe the positions that are. being removed or I just I know based on. what we're hearing is product managers,

middle managers, what Matthew Prince. call measurers, what other people call. mid management. Everybody believes that. the recording and this daily standups. and the uh zoom calls all of that is. turning into people management is being. done better by AI and people are more. self-directed and then the stack of. people to build products is being. consolidated right it's like the the. typical designer can now vibe code the. developer can do front-end design and UX. and they can project manage themselves.

so I there there are a series of jobs. that will increase and a series of jobs. that will be eliminated just like the. mail room got eliminated and mess bike. messengers got eliminated. that. >> got on net on net do you think there'll. be mass. >> do you think there'll be on well your. position is shifting a little bit do you. think on net do you think on net. there'll be mass job loss. >> uh I think there is a chance that we're. going to see uh job loss increase in the. short to midterm and then eventually.

the displaced people are going to have. to learn or leave the workforce, which. is what happened during other. revolutions like this. Some people went. with the paradigm and adapted and some. people didn't and just retired. That I I. saw that firsthand in the PC revolution. as but one example. Some lawyers just. would never use these tools and they. just retired at 55 65 and they moved on. And then other attorneys were PC first. and they just took that. >> By the way, did you guys see the news. that Kirkland Ellis is going to spend. half a billion dollars to roll their own.

Frontier model? >> Makes total sense. That was like to our. earlier point today is that people are. doing on prem and going to make their. own models. Bill, I have one specific. question for you and thank you for the. good engagement there, Sax. It was it. lacked the ad homonym that usually uh. starts every conversation we have. >> I don't usually call you an idiot. >> That's because it's in our minds. Okay, we're thinking about it. We're just not. saying it. >> Good. I like it better. I like it. better. Um Bill, specifically when Andy. Jasse, you know, uh last spring said, "Hey, we're going to do more with less. We're going to be AI first." and they.

said, "We're not going to hire these. 600,000 jobs." When you see Tubby Lucky, he say, "You have to do AI first before. you ask for a headcount and prove to me. that you tried AI first before hiring. somebody." Do you think this is. a sign that these organizations are AI. washing or do you think these recent. ones are more, hey, we're going to do. more with less and and the size of these. companies will be smaller uh because of. AI? One thing that that I think that. last question misses and I think a lot.

of the the AI dumerism stuff misses is. that competition exists. And so if you I. don't think there's any scenario where. you just do more for less and all of a. sudden everyone has 70% operating. margins. That's not going to happen. Someone else is going to come along and. do more for less and lower the price. And so the thing that could happen is we. could have a productivity boom from. lowerpriced goods and services and the. basket of goods that humans are able to.

buy gets cheaper and cheaper and cheaper. and that's been true in many categories. Unfortunately, it's offset by what. happens in healthcare and other. regulated industries. >> Yeah. Education. But but yeah, so I. expect products to get cheaper and. people to be able to create more with. less. But I don't think it leads to. obscene. profits. >> because it'll be whittleled away in. competition. >> Okay. >> By the way, just just on this AI washing.

point, there's a a trial lawyer named. Donnie King. He's a securities. litigation partner at a firm called. Acriman. He and his colleagues have. started to warn that we could start. seeing shareholder lawsuits against. companies that engage in this type of AI. washing cuz he thinks it's a type of. puffery, right? Because essentially what. the company is doing is attributing. their own non-performance or their. operational issues to AI when in fact. there are real problems in the business.

and therefore it could be a form of. securities fraud. >> Wait, securities fraud? Yeah. >> I want to double click on this. Did you. see the CEO of Whisk today on his note. about layoffs? >> No. Who's Wisk? >> Find me the AI washing in there. Wix. >> Oh, yeah. Those that's the website. builder. Yeah. I mean, you can build. websites with Claude. Yeah. The whole. website business is challenged. Yeah. >> Interesting that he just he just talked. about operational details. >> Did he? I I didn't read the note. >> Of course, you didn't read the note. >> Well, I mean, you said it just happened.

[laughter]. >> I I will read it. Uh, this is I'm just. this broke at 9:25 this morning. >> I think it's really interesting that. this lawyer thinks there's so much AI. washing going on that he thinks it could. constitute securities fraud and he's. warning clients not to engage in it. But. look, Jake Al, you're like the last. person who hasn't gotten the memo on. this. There was a huge narrative shift. this week. Sam is backing off this. Even. Daario's walking it back. You got the. Goldman Sachs CEO. [clears throat]. You got the explosion in job postings.

Everyone's coming around to the idea. that the job apocalypse is massively. overblown. >> I mean, it could be overblown looking at. the stats. >> Your apology, I'm happy to accept. >> No need for an apology. I mean, my. position has always been apologize. >> It's displacement. You're going to have. some displaced in the short to midterm. and then eventually there'll be more. problems to solve and people will have. to reallocate. I do think we're being uh. uh, you know, I think the tech industry. itself doesn't have enough empathy or. enough thoughtfulness when discussing.

this because these are real people. losing real jobs and you can point at. statistics uh and you think they're. spinning, but these are real people. losing real jobs who may not make the. transition. >> Jason, I got I got. >> Do you think it's more empathetic to be. scaring the be Jesus out of people that. they're going to lose? >> I'm not in the scaring camp. I'm not in. the scaring camp. I I I am in the. enabling camp. That's why I keep saying. if you've been laid off, you should. start a company and you should embrace. the tools. So, I I'm I'm all about. empowering people. I think they if they. learn the tools, they'll have 10 job.

offers. Uh and they'll start their own. companies. So, I do think there's a. solution to it. I just think we're going. to go through, you know, low millions of. jobs being lost or being retired and. transitioned out over this next couple. years. >> I was just going to be empathetic and. offer some solutions. So we talked about. the skills trade deficit of of people. working in that. Micro has a foundation. called Micro Works where they fund they. funded $16 million 2600 people get a.

free scholarship for to be become a. plumber, welder or electrician. So go. check that out if you want to reskill. I. think. >> generation tool belt. Yeah. >> I think it's better than you know having. the government fix things. And then, you. know, as as we started and talked about, I've got a new uh grant program myself. to help people. >> Yes. >> kind of tilt their career in a different. direction. Go do something you love and. and apply and maybe I can help fund your. you moving in that direction. >> And and as to your vibe shift, I think.

it's because candidly people's houses. have been Molotov cocktailed because. they're doomerism. And people. specifically are citing that when they. shoot at their houses and throw Molotov. cocktails at them twice in the same. week. And if you're IPOing and you're. coming out saying, "Hey, jobs are going. away. Jobs are going away." That's just. a really bad look. >> And or it's because we called it out and. they got cut and so now they were. telling the truth. >> All right, everybody. This has been. another amazing episode of the AllIn. podcast. Thanks for coming.

>> No, no, no. Sorry. I need to do one. thing. >> just doing at the end of this. >> Yes. >> She's a friend of ours. I just want to. just give a huge shout out to Tulsy. Gabbard and specifically her husband. Abraham. is tragic. >> Going through some really tough stuff. with cancer. He is going to kick its. ass. I just wanted to say we love you. >> Yeah. Uh Tulsi is great. >> Cheers everybody. Uh that's episode 275. in the can. We'll see you next time. Bye-bye. Love you Blues. [music]. >> We'll let your winners ride.

>> Rainman David. [music]. >> We open sourced it to the fans and. they've just gone crazy with it. >> Love you. Queen of Kino. [music]. >> Besties are gone. >> That is my dog taking notice in your. driveways. >> Oh man, my appetiter will be. >> We should [music] all just get a room.

and just have one big huge orgy cuz. they're all just useless. It's like this. like sexual tension that we just need to. release somehow. [music]. >> Wet your feet. Wet your feet. her feet. [laughter]. >> We need to get mer. [music]. I'm going all in.