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Okay, we are gathered here today in holy unity, brothers and sisters, to convene and discuss on this most holy
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day, the day the All-In podcast drops many topics. AI data centers, China, justice, human dignity,
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Daario unwinding these SPVS hasn't been good for the Vatican. We got in at 20
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billion. That was a 50 bagger for us. So, let's get started. >> Jason, I'm pretty sure you believed you
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were the vicer of God before the encyclical. So, this is nothing new for you. >> Let your winners ride.
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>> We open sourced it to the fans and they've just gone crazy with it.
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I'm going all in. >> The smoke has risen from Tratad's pool house and from the poker room.
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>> He's staying in my pool house. He's been there for the last 3 days.
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>> It's been magnificent. He didn't know. You know what? I understand where OJ was
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coming from. You know, you put Ko Kalin in your house for long enough, you just lose your [ __ ] At some at some point,
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somebody's getting whacked. All right, enough with the shenanigans. Uh, but it's been great staying at the house
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because there's actually Chimant is not aware of this. There's an iPad in the
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kitchen and that's logged in to Uber Eats, Door Dash, Instacart, Amazon, Laura Piana. Come on, stop.
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>> No, there is. It's literally every single service. And I told the house
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manager like, listen, any packages that come in the next 72 hours, right to the pool house, if it says JCAL, right to
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the pool house. So, all these packages have been coming. Then I relabeled them, gave them back, sent them to the ranch,
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and now the house manager is sending that stuff to the ranch. >> Laura Piana wants to know why my inseam
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went from 36 to 12. >> Your waist size went from 32 to 36. All right, welcome to the program,
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everybody. David Saxs is here. How you doing, David? >> I'm good. >> Chimoth Poly Hopetia is back at the 8090
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office. I was at the 8090 office the last couple days and it's a vibe. It's a
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vibe. There's like a great culture going on. >> If you're a bestie and you show up at
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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
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everybody. Hey, I'm a developer here. I'm a big fan of the show. Thank you for
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giving it to Chimath. We can't give it to him because he pays our mortgage and
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everything, but every time you stick it to Chimath, we love it. We're cheering
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for you in the secret slack room. Um, and >> there's a secret slack room.
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>> There is. There is definitely a secret slack room going on. >> No, but it was great. The vibes were
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awesome. You're building a lot of software. A lot of young talent. I don't
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want to say that where your secret source is, but there's a secret source of talent you have. And uh, man, those
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are some smart kids. >> I'm happy to say it. Look, when I was at Facebook, we became the most aggressive
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recruiter of Waterlue co-ops. And so, I went back to the well. Yeah. We recruit more interns every quarter than we have
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full-time engineers, which we do on purpose because it puts a ton of pressure on the product actually being
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good. >> We had 400 people apply this quarter for internships. >> Wow. It's very interesting. Uh with us
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sitting in for Freedberg, who's busy with some potatoes seed this week doing
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great stuff at Ohio, the one, the only Bill Gurley is here. He's been running
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down a dream. If you haven't bought the book, get the book. It's incredible. And
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you're off book tour, so now you have time for us. Yeah. >> Yes. And I, you know, I had told you if
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you ever talk about the Pope, I'd love to hop on. And so >> yes, you were like,
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>> well, you know, he Bill's an evangelical. I'm a Catholic. So, we do
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have some common ground here. Do you you when's the last time you were at church,
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Bill? Have you have you thought now that you're, you know, >> when Jal gets sacriiggious?
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I got to come on there and make sure JCL doesn't get out of line with the Pope.
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>> Listen, the Pope is God's messenger on earth. We should give him a base level
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of respect. By the way, that's us imitating Bill Gurley. This not actually Bill Gurley.
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Just for those of you listening, you think they were confused. >> They were literally they were confused.
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We don't want to put words in your mouth, but just point of clarification. But hey, everybody knows you were uh you
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know, you uh handed the baton over at uh Benchmark after a very successful couple
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of decades in venture capital. You wrote the book. You've now got a nonprofit.
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You're doing your own spin, I think, on uh maybe what Peter Teal does with his
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fellowship. You started your own running down a dream fellowship, I understand. >> Yeah, it's uh it's targeted at a
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different demographic. It's called uh rdad.org runningdownadream.org. There's a website we can give a link to.
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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
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application process like Teal Fellows and other programs and we've been out talking to those people. Um but we're
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we're we're actually live. We went live last week for the application. So if you
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know people who have read the book and are inspired and need some help, have them apply.
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>> Yeah. All right, folks. And uh Good for you, BG. Yeah, great two two other So, I
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did a TED talk which will come out soon that's related to the book. Um I I uh
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there's a professor in Miami that's built a course around the book which I'm
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excited about and he's he's he's doing it in a kind of an open source way so
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that other people can borrow that as well. And so if there anyone out there I'd love to uh help them do that.
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>> What's your take on all of this dumerism? Like if you're a young person
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and you're in college or you're in high school, is this is this much to do about
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nothing or how do you run down a dream in the face of something like that? >> Yeah. Well, I you know, I started the
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book before this happened and I've been asked the question a lot and it it came
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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
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there's a Gallup poll that backs this up. They came up put that word quiet quitters. They're like 59% of the people
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they surveyed are kind of ambivalent about their job. And when you're ambivalent about your job, you're not
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high agency. And so you don't lean in. You know, if you if you look at how Jason talks about all how they
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implemented AI and all of his his different working groups, you hear that enthusiasm and that high agency and then
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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
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version of yourself you can be. But if you're ambivalent about your job, you're
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probably not doing that and you could be, you know, a sitting duck. So I think it's the mindset that's the problem.
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>> I created an associate in training program for my firm cuz we want to like
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help people get into venture capital and we gave them a choice of assignments. One of them was to write coverage of one
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of our portfolio companies that's breaking out. Micro one is the name of it and just give us like hey here's a
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competitive landscape basically write a deal memo and coverage of that company and then we gave them another option to
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vibe code a very specific project I've wanted to have for our venture firm for
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a long time you know on competitive intelligence and I would say I think like maybe 80% of the students applying
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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
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would be the exact opposite Anybody can write, anybody can throw in JBT and get some output. But they they actually
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built software and th that's the scary thing. The students who graduated, at
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least this is my perception, Chimoth, the students who graduated like 5 10 years ago before AI, they're not AI
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first. They feel lost in a drift. They don't have agency. But the group coming
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out of college right now that cheated their way through school using Chad GBT, doing their assignments, like using
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those tools, I'm joking, cheating, but I mean hacking. I I agree with that. >> So they were totally
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>> Yeah. And and they're just like, I know how to use these tools to get through my
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finals. Yeah. >> Girly, I think you're saying something super important. I said this last week,
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which is >> nobody asks the warehouse worker at Amazon whether they actually want that
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job. And so to your point, job satisfaction isn't some external person judging your job to be valid and saying
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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
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to keep it? Those are two very different questions. And >> yeah, >> I think that the all of this AI doom and
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gloom was a lot and too much frankly of the former and not enough of the latter.
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And now this whole lie is kind of getting undone. I think Saxs posted about it this week as well. The Goldman
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Sachs CEO said it. And now in this crazy twist of fate now that we need to have trillion dollar IPOs, the entire
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Frontier Labs are all like, "Wow, it's going to be a bonanza of jobs." And
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>> Mark Cuban had had a great quote. He said there are two types of people in
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the world. Those that use AI to learn faster than they ever could before and those that use AI to avoid learning
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altogether. >> And I I think it's this notion of high agency or not. That's pretty good.
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>> Are you leaning in and using this stuff to be ever more powerful in what you try
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and accomplish or are you using it, you know, as a cheat code? And if you're in
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the latter, yeah, you're probably at risk. You get asked a lot about how to educate yourself if you're a parent of
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kids so that you can put them on a path to launch and do well and chase their dreams.
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>> You have a good answer for that question. >> I I mean the the second chapter of the
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book's all about lifetime learning and it's kind of a requirement that you're
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following your fascination because the lifetime learning comes for free if you're fascinated with something like
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you just constantly soak up and devour new information. And I I do think that a lot of kids get exhausted because we've
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made high school and college such a grind that they think the learning ends the day they they walk out with their
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diploma. And as we all know, the best and brightest in all of our fields are on a constant learning journey. And when
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something new comes out, they dive in and try and figure it out, right? And so and every every single uh person in the
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book that we profiled has that kind of attitude about their craft, you know, in every day. And so I I think the real
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test is if you're not proactively self-learning, then you're probably not
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tilting against something that you really adore and are fascinated by. >> Sax, you wanted to jump in there. With
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respect to new college grads, I was going to say that I think the single most marketable skill in the economy
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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
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knows Claude, it would be like you're the only one who knows how to work a spreadsheet, you know, or word
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processor, the advantage would be enormous. Now, I think that that's probably a short-term arbitrage because
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eventually everyone's going to have to figure out how to use these tools. But
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as a young college graduate right now, you have such an advantage if you're an
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AI native uh just knowing how to use these tools. And this thought uh partially occurred to me when I saw what
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our producer Nick has been doing with using Claude for you know he's been creating this daily briefing document.
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>> We've been doing it we've been doing it for three months actually.
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>> I just ran it for the first time apparently. I didn't you've been busy.
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>> Yeah. Well, I just, you know, I thought it would just be AI slop and it would
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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
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impressive about it was that it predicted topics that I would specifically be interested in based on
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my previous comments on the pod and also it went back and looked at previous transcripts and what I had said and then
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had updates to those topics based on specific things I had said. So again it was highly highly contextual. But then I
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asked Nick, how did you generate that? and he showed me the the custom prompt that he designed for Claude and then the
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skills document and they were very long and detailed documents. They weren't
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written in code but they were very technical and I just realized looking at that that the average person is not
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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
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into an organization and it's just magically going to generate value is not true. You have to know how to
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>> get value out of it. I mean maybe we could just show these documents on the
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screen. >> Yeah. I mean the the the interesting thing uh Sachs is you can you just have
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to ask your AI you ask claude or chatgpt or whatever you're using hey I want you
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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
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are the four characters on the podcast what would be a great prompt for me and it will actually suggest a prompt
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>> and then you can refine the prompt so you actually have a dialogue about a
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prompt as opposed writing the prompt yourself like >> well Nick can you show on the screen to
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scroll through the training rules and then also there's the skills document that was written on how to be a producer
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>> for this podcast which I thought was really impressive >> by the way David what you said I think
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is true of almost every single job type like it's not just tech or programming
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if you're in marketing if you're in legal if you're in accounting Like any role you might have at a firm
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sales, if you're the most AI savvy person of all your peers, >> you are golden. Like you are golden like
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in your >> 10x more valuable than the next person who's not basically.
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>> Yes. Yes. And and and I think that I don't think it goes away because I think
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you learn how to get better at it over time. So having an early advantage I think will extend for a while.
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because you can learn more more and more things you can accomplish. >> Should we let producer Nick describe
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what we were just looking at there? >> Yeah, go ahead, produce. What? Producer
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Nick, explain the process. >> Yeah, once we got access to Claude Co-work and it had that like further
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expanded memory access. I thought it would be interesting to just start feeding every transcript into it and
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seeing if it could actually contextualize new stories that were coming out based on past things that you
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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
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or some training rules for this?" And it wrote all of it for me. >> Yeah.
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>> Oh, so you were less good than I thought. >> I thought you were >> It's a hack. It's a hack. You use AI to
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make the skills. Yeah. And >> but you've been updating that over time,
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right? As you've been iterating and learning >> every single day and every single day
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gets smarter and better. >> The recursiveness of this is incredible. >> So you need someone to manage that
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process, right? because the four besties are not going to do that. So you need a
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producer of the show to do that. This is why people think, oh, it's just going to
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wipe out all the jobs. No, someone still has to supervise, iterate, validate, you
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know, all those kinds of things. >> Yeah. And it's it's really interesting that the the
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people who are coming into the workforce right now are super aware of this and they're putting the tools to work and
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it's much easier for them to get a job. I mean, I I literally looked at the top
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nine candidates for this associate and training program I have, and we're going
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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
00:16:01
extraordinary how you could tell immediately if the person had systems thinking Sachs like they understood the
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the process of venture capital that there was a structure to it. You had to source deals. You had to make decisions
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on which ones to invest in. You had to do diligence. you, you know, you had to double down on investments, they they
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just understood the process and then when if you just talk to one of these LLMs, it will tell you what to do. So,
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you can say, I don't know what I'm doing. What should I do next? And then
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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
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I'm already too far behind, I encourage you to pop up Claude, go into co-work,
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and say, "What can I do to be better at my job?" and just start talking and
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literally if the more you talk and you can use voice uh you know text to voice I use whisperflow is a really cool
00:16:52
program for this and I have a foot pedal to do it you just ramble and ramble and
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ramble and keep adding stuff you don't have to be structured it will build the
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structure around the two or three paragraphs that you give it as instructions that's the thing people are
00:17:07
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
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scale I have a unique uh ability to do. You just blather on. It's a superpower.
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You blather on and the thing makes sense of it. It is unbelievable what the blatheron prompt can get in terms of
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output. Thanks for coming uh to uh my TED talk. All right, let's get started.
00:17:33
There's a lot to talk about and uh we got a big docket today. We're going to
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start with the Pope. The Pope is dope. And uh the Pope Leo, he's the 14th, released his first encyclical encyclical
00:17:48
on AI. And it was long. 235 pages over 42,000 words. Just to give you an idea, Bill Gar,
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>> when did he write it, do you think? When did he put that together? >> Well, no, no, I think he used chat GBT.
00:18:01
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
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this in between all of his other tasks? I think it's a six-month process to do
00:18:10
this, but I'm sure he had collaborators. >> Bill, your book, I'm assuming, was
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>> write it. >> I'm sure there was a team that wrote it. But Bill, your book's 60 70,000 words,
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I'm guessing. So, this is almost a literal book, right? >> In terms of how long it is, and it's
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called Magnifica Humanitas or Magnificent Humanity. In it, he warns business leaders to safeguard humanity
00:18:35
from AI. His core argument is AI is not inherently evil, but technology is never
00:18:41
neutral and that technology takes on the characteristics, wait for it, of those who build, finance, and control it. And
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I don't think he thinks super highly of that group of people. The Pope called
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for regulation of AI companies. Obviously, we're going to have that debate here. Some of the things he uh
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called for I think are not very debatable and there's a lot of consensus around worker retrainment, safety uh for
00:19:07
children and guard rails, a ban on autonomous weapons. That's the uh Skynet rule. Don't build terminators with your
00:19:14
AI. But he was joined by anthropic co-founder Chris Ola. I don't know how many co-founders there are of this
00:19:21
company, uh but apparently there's dozens. And Ola is not Catholic. According to a Vanity Fair profile, he
00:19:28
was raised evangelical and now he's an atheist. The folks at Amazon, Google,
00:19:32
and Meta lobbyed the Vatican on April 29th to soften the language in his missive and uh he was not swayed.
00:19:41
His central question, Saxs, is will AI be used to concentrate power in the hands of a few or will it serve
00:19:48
everyone? Something you brought up when you mentioned monopolies, duopolies, etc. two weeks ago on this very podcast.
00:19:57
What's your take on the Pope and his interest and his missives on AI and promoting a bit of AI regulation?
00:20:07
>> Well, I very much agree with the Pope that the biggest risk of AI is a centralization of power and then its
00:20:15
misuse against us um in some Orwellian way. I think it's government that's
00:20:20
going to do that. Um, not necessarily an individual actor because it's governments that ultimately have the
00:20:26
power. So, I do worry about the potential for AI to be used to surveil us, censor us, control us as Orwell
00:20:35
described in 1984. So, if that's where the Pope is going with this, I very much
00:20:39
agree with him. The maybe where we end up in different places is he thinks that government
00:20:45
regulation is the way to prevent this. And I would just say that we have to be careful not to empower government too
00:20:51
much because if you give government the power to regulate or approve AI development,
00:20:59
if you create say an FDA for AI as many people are calling on, that will give government the power to approve models
00:21:08
and and therefore give notes to model developers. And very soon this definition of safety will expand because
00:21:16
the government always takes an expansive view of its powers. And we saw this during the social media wars where the
00:21:22
definition of trust and safety expanded to issues like psychological safety, microaggressions,
00:21:30
disinformation, transphobia, and so on. That, you know, again, these social media companies were
00:21:36
told that they had to stamp out all of those threats to safety. And it ended up becoming a censorship agenda. So I get
00:21:43
very worried about you know what if some government agency can give notes to the
00:21:48
model developers and they start telling the model developers that your definition of safety is not expansive
00:21:53
enough. You have to again protect the public from disinformation or you know psychological harms. So again, I think
00:22:01
we just have to be careful not to arandise government because that's going to be the most likely culprit in terms
00:22:07
of the centralization of of power. And um I know the um the Vatican likes Latin. This is a problem of political
00:22:14
philosophy that goes all the way back to Socrates. It's called quis custodos
00:22:20
custodes which is who will guard the guardians. In other words, if we entrust a set of guardians to protect us from a
00:22:28
bunch of threats, what's to stop them from becoming tyrannical and from becoming the new threat against us? And
00:22:36
I mean, this is a the central dilemma of political power. >> Who watches? >> Yeah. Who watches the watchers? Who
00:22:42
guards the guardians? Meaning, who's going to protect us against our guardians if they turn against us? The
00:22:48
genius of the American founding by the way is that it was a second order solution to this question. The founders
00:22:54
of America very much understood this and what they came up with is we have to have the guardians guard against each
00:23:00
other. And so they came up with the idea of separation of powers. We'd have separation of federal and state. We'd
00:23:06
have um the three branches of of the government. Even within the legislative branch, it was a biccameal legislature.
00:23:12
So they divided up the powers in a way that hopefully the guardians would check against each other as opposed to
00:23:18
becoming tyrannical against us. And that that is kind of my view on AI is that ultimately we have to have a solution of
00:23:27
checks and balances. If the AI market becomes monopolized and falls into the hands of one or two companies, I would
00:23:34
use antitrust law very aggressively to as a check and balance against their power. Right now we have a very
00:23:41
competitive market. You know, we have five frontier labs competing very aggressively. As long as the market is
00:23:47
competitive, I would use that because I think competition generates the best outcomes. It helps us win against China.
00:23:54
But it also protects the population because these companies, you know, if they get out of line, there's some
00:23:59
competitor that can offer something better. >> Consumers can opt out of it. If they
00:24:02
don't trust GPT, they can use Anthropic or if they don't trust Anthropic, they
00:24:06
can go to Grock. Bill, you had the number one rated talk at the All-In Summit in history, 2,851
00:24:14
miles. You have been famously against regulatory capture. In light of the Pope's comments of, hey, regulating,
00:24:22
what do you think is common sense? Because AI is everything. AI can help people make boweapons. It can also help
00:24:29
people get their term paper in or do you know uh be a better salesperson at you know Oracle like we're talking about
00:24:37
paper like we're talking about oxygen here this is like a fundamental horizontal technology so where do you
00:24:44
think there is a case to regulating AI if at all and where do you think yeah free market will figure it out
00:24:51
>> well I have I have two takes one on the pope and one on anthropic so your
00:24:56
questions your question powerful let's with the more let's go with the more
00:25:00
powerful entity. We go you want to go in reverse the least powerful of the two go.
00:25:04
>> So so this pope said that and I have to learn how to pronounce all these Latin
00:25:09
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
00:25:19
said he chose the name because he's so enamored with Leo I 13th. Leo the 13th
00:25:24
encyclical warned that the industrial revolution was going to be bad for people. So let me tell you what happened
00:25:31
from 1891 till today. The work week went from over 60 hours to 34 hours globally.
00:25:38
Real wages went up 8 to 10x adjusted for inflation. The medium worker now earns more than a doctor did in 19 in 1891.
00:25:46
Global GDP per capita went from 1500 to 20K. Child labor in the US went from 18%
00:25:52
to zero. Workplace deaths fell by 40x. Life expectancy went up 60%. And global poverty went from 75% of humanity to
00:26:03
under 10%. All those things happened because of technology, innovation, and capitalism, which is exactly what Leo
00:26:11
the 13th was warning against. So he got it dead wrong. He got the whole thing precisely wrong. So it's an interesting
00:26:19
thing to say you're borrowing from. >> Yeah. Uh so now on to >> Yeah. Anthropic and just common sense
00:26:28
around do you think there how would you regulate and or protect against maybe we'll broaden the term here protect
00:26:36
against nefarious uses of the technology. Obviously we all want children to be protected. We want to
00:26:42
have truth uh and honesty in terms of facts and and all of us sharing some some basic truths and we obviously don't
00:26:50
want people using this technology for boweapons and the Terminator scenario. >> I have to tell you that that Anthropic
00:26:56
is a mystery to me. I've never ever seen a company that is both leading their
00:27:03
field and the most negatively outspoken commenter on what they do. I I've just
00:27:10
never seen it. And my initial theory was the regulatory capture theory that they
00:27:15
just want to ensure there's regulation. And quite frankly, I think they're, you
00:27:21
know, very close to achieving that. Like they have stirred up, you know, a frantic position, especially in America.
00:27:29
American consumers are definitely afraid of AI. Um, I think I've talked to you
00:27:34
guys in the past about, you know, the book that Jonathan Heights written about social media and there's a whole bunch
00:27:40
of state legislators that think we should have regulated social media and so now they're destined to want to get
00:27:47
in front of it. And we know that Anthropics, one of the most aggressive lobbying company startups of all time.
00:27:55
You know, the the the amount of effort that they're putting in, the amount of
00:27:58
money at a statebystate basis. So that was always my first theory, but then they just they got so loud that I I've
00:28:06
literally in the past 30 days read everything I can about anthropic and I've come up with a new theory. This
00:28:13
this >> okay new breaking theory. >> This I call it the Dr. Frankenstein
00:28:18
theory. Um you remember when Elon had that conversation with Larry Paige where Larry called literally sitting next to
00:28:25
him when he called? >> Explain the story real quick. while we were at uh a birthday party and and you
00:28:33
know Elon was like listen humanity needs to be protected from the stuff at DeepMind because at DeepMind they had an
00:28:39
example of the AI having tried to break out to jailbreak out of its computer and
00:28:45
not be turned off and you know had some sentience or some you know inkling of sentience and he said you know we have
00:28:51
to protect the human species and he said well Larry said well what do you think that's species because you care about
00:28:57
the human species over AI. This is at least 15 years ago. >> No, this is right before Elon co-founded
00:29:03
uh Open AI, right? Back in 2015 or something. >> The actual story here is Elon Hon and
00:29:11
Google had backed Deis and the team at DeepMind when they were an independent company. Then Elon was like, "Oh my god,
00:29:19
Google's going to buy this." And I remember having the conversation with
00:29:21
Elon about this. We have to figure out a way for DeepMind not to go to Google. We
00:29:26
have to block this somehow. But he begged those folks to not sell to Google because Google was running the table on
00:29:32
everything and he wanted this technology to be independent and he was on the board of the company
00:29:37
>> and he also said this was his motivation to launch open AAI as a nonprofit.
00:29:41
>> Google got it. He just said we we this is this technology is too powerful for
00:29:45
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
00:29:50
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
00:29:56
somebody controls this and they run away with it. It would be extremely dangerous. It has to be available to all
00:30:02
the people. Essentially the pope's position. It has to be in the service of humanity, not ruled by one person. It's
00:30:08
far too powerful. >> So the reason I call this the Dr. Frankenstein theory is the more I dig,
00:30:13
I've met people who I who I dare say think it's their responsibility and
00:30:19
they're excited about building a species that's that's superior to humans. And I
00:30:26
would just encourage people to read, you know, as much as they can about anthropic. Chris Ola worked on this
00:30:33
thing called the Constitution. It's about 80 pages. It's hard to get through, but I would encourage you to
00:30:38
read it. Amanda Ascll who is the chief philosopher has started doing podcasts. I would encourage you to listen to them
00:30:45
and listen to her language. And then Daario wrote this blog post called Machines of Loving Grace.
00:30:53
>> 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
00:30:59
link to the poem. It's quite short. But the last the last stanza of the poem
00:31:05
says, "I like to think of a cybernetic ecology where we are free of our labors
00:31:11
and join back to nature. Return to our mammal brothers and sisters." I don't
00:31:15
know what that means. Like we're going to go live in the fields where the mammals live. I I And then the kicker
00:31:21
and all watched over by machines of loving grace. Sounds like overlord to me. And then in Daario's post he says he
00:31:31
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
00:31:37
talking about in the future what are humans going to do because he believes in the massive abundance and UBI and
00:31:44
that we won't have to work. I don't believe in any of those things but he
00:31:47
does. And then he says it could be a capitalist economy of AI systems which then give out resources to humans based
00:31:56
on some secondary economy of what the AI systems think makes sense to reward in humans. So So that's envisioning a a
00:32:06
deity of sorts that's going to break ties and discern decide what humans >> it's a it's a computational reward
00:32:13
function for humans. It decides how much you're worth. >> Yeah. So, I don't think they think
00:32:18
they're writing software. I think they're midwifing a deity here. And and
00:32:24
I don't know which one I'm more afraid of, the regulatory capture or or or or
00:32:28
this second theory I call the Dr. Frankenstein theory. It it's more it's
00:32:33
more scary to me. I think the second thing >> these are delusions of grandeur. Let's
00:32:37
call it what it is. They believe that they are so intelligent. I know some of these folks, the Burning Man sort of
00:32:43
offshoot of it, transhumanism. They believe that they're so powerful, these individuals, that they can create God
00:32:51
and that by creating God, they are like this Prometheus kind of species. It literally is the ultimate level of
00:33:00
narcissism and delusion of grandeur to think you can create God and that then the god you create like you're saying
00:33:07
Bill is going to be so benevolent and perfect that you create constructed the perfect God that will give you your
00:33:14
pellet will give you your little scenarian you know >> I just would correct you I didn't say it
00:33:19
Daario said it >> right but no to but to your point of like just taking them at their word they
00:33:24
actually believe that they can create God and that they'll create a god so good that it's better than humanity.
00:33:29
Saxs, your thoughts. >> Well, I guess the question then is why are they pushing for the let's call it
00:33:35
red capture agenda where >> I know why. >> Go ahead, Jamal. Go ahead.
00:33:41
>> That is very reductive game theory. So, if you want to be unexploitable, I think
00:33:47
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,
00:33:52
close the door behind you, and then dominate those other three or four entities, and then you set the rules.
00:33:58
And because your counterparty is unable to track at the level of technical capability that you would have, you
00:34:06
create this massive asymmetry that allows you to exploit them. That's just simple game theory optimization. And you
00:34:12
know what Bill said is so powerful. I've read these things and it's laborious and
00:34:15
it takes time, but every time they put these things out, just take the time to read it. And what I have said before,
00:34:22
Bill, I don't know your point of view on this, but I initially thought that this
00:34:26
was mostly game theory, that a lot of their reactions I thought were less rooted in their dogmatic beliefs and
00:34:35
more rooted in a GTO approach to either raising capital or putting pressure on competitors. Either way, both could be
00:34:43
true. What your framing is and my framing, although mine's more tactical than yours to be fair, because I've
00:34:49
always thought that these moves make sense through that lens. How do you absorb most of the capital? How then do
00:34:56
you make sure that you are in a position to disproportionately affect the rules?
00:35:02
And how do you create an oversight body that is less capable and intellectually aware as you are about the actual
00:35:12
details because >> the referees don't understand the game. Right? >> If the refs don't understand the game,
00:35:17
you'll run over the game. Yeah. >> By the way, by the way, one thing they
00:35:20
have achieved by doing this is I think that if you pulled the, let's just call
00:35:26
it the intellectual elites, so everyone in the media and whatnot and the professors and all those, and they were
00:35:33
to rank the different AI players by who they think is most caring, I think they'd probably put Anthropic first
00:35:41
because they've been out with the doomerism talk. And so it's given them a
00:35:46
halo with the people that may matter to what they want to accomplish. It it's
00:35:51
simultaneous creating a lot of trouble like with the data centers and whatnot. Like there's
00:35:57
there's negative ramifications. >> What you're saying is so important
00:36:00
because on the one hand they create empathy and then they write these documents that
00:36:05
expose what they think and nobody actually connects the dots. >> Yeah. To steelman their position for a
00:36:10
second. I mean, I think probably the way they think about it is that they are creating something very powerful,
00:36:15
something godlike, and therefore it needs to be safe and that they care the most about that
00:36:23
out of everybody. Nobody else takes this seriously. Remember that Enthropic was basically a spin out of open AI and they
00:36:30
felt that Sam and the company leadership weren't taking their point of view seriously enough.
00:36:35
>> It was the most woke portion of Open AI. >> We're steel Manning. So the most for so
00:36:42
they they see the power of it. They're the ones who are concerned about safety
00:36:47
>> and they care the most and therefore they're in the best position to do that.
00:36:51
>> Now I think the issue is just you can see how this can lead to red capture,
00:36:57
right? Which is if you brand yourself as the safe AI company and then try to characterize everybody else as a
00:37:05
reckless player and reckless AI needs to be stopped. you can see how this would basically further your monopolistic
00:37:14
control over this industry. And if you see AI through the lens that you know that really frankly the pope and I see
00:37:21
it which is centralization versus decentralization I do think that is you know one of the key lenses we should
00:37:28
have on the technology is whether you want this to be a centralized or decentralized technology. This way of
00:37:34
viewing the world leads to more centralization and I think that's dangerous. I mean, if AI is this very
00:37:41
powerful technology, I think it needs to be decentralized so that all of us can protect ourselves to some degree, right?
00:37:48
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
00:37:56
beholden to a single company that might be in bed with a deep state. >> Let's say it very pointedly. If benefits
00:38:03
and compensation and economic support were all of a sudden tied to some algorithmic decision, this is a
00:38:11
dystopian episode of Black Mirror that we're dealing with. And to your point,
00:38:15
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
00:38:24
a singular answer. A singular answer to these kinds of questions, which is effectively what some folks would want,
00:38:30
is incredibly dangerous. >> And this is something that is in control, I think, of humanity. I've been
00:38:37
talking about AI sovereignty here for a bit just in terms of how much more cost effective it is and how you're not
00:38:45
training other people's AIs with your knowledge and your insights. This is why
00:38:49
it's super important that open- source, open- source agents and local hardware
00:38:53
be able to run these models and that consumers and companies learn how to roll their own language models, how to
00:39:00
make a small language model, an SML, a VSSML, a verticalized one and run it on your Apple hardware because Apple
00:39:08
actually has taken a principled approach historically to your sovereignty for your data. Data sovereignty now is
00:39:14
privacy. >> Yes. And now it's intelligence sovereignty. the the intelligent
00:39:18
sovereignty is different than privacy. Privacy is, oh, you can't see my photos.
00:39:22
You can't, you know, peek into my notes app and what I wrote there in my journal. Now, intelligent sovereignty is
00:39:29
you can't tell me what to think. You can't use your AI to analyze my photos,
00:39:34
to analyze my emails, to analyze my messages, and tell me how to interpret the world. That's actually going to be
00:39:39
the next key piece here. This is why I think Apple is just the dark horse in this entire race. there is an
00:39:45
open-source product that can run on this hardware, the M5s, the, you know, 48 gigs, 128 gigs, the stu new Mac Studio
00:39:53
coming out with supposedly a terabyte. That changes the whole game. And this is so paradoxical, Bill, that our
00:40:00
adversary, the Chinese of all people, the Communist Party is leading the open-source movement and the United
00:40:08
States is centralizing. >> They're leading the openweight movement. It's not open source. Just the
00:40:14
distinction is important. >> Yeah. Yeah. >> Look, I Jacob, I agree with you about
00:40:18
the importance of open source because open source means software freedom. You can run the program yourself on your own
00:40:24
hardware. You don't have to share. You don't have to give up your data sovereignty. You don't have to give up
00:40:28
your privacy to again to some monopolist who's going to be, you know, in bed with
00:40:33
the government or the deep state, right? So that's the thing we're all afraid of.
00:40:36
And if that's the only AI that's available is from the, you know, monopoly or duopoly,
00:40:42
then your choices are to live off the grid and not participate in the modern economy or give up control, right, to
00:40:49
some social credit system. So I think the open source is really important. And by the way, that was Elon's instinct in
00:40:54
creating open AI. He was afraid that Google was going to monopolize AI. So he's like, let's create open AI so that
00:41:03
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
00:41:10
think their instinct to the idea of powerful AI is to clamp down and just control it. But actually you have to
00:41:17
have multiple players. That's the only way you're going to be protected is is
00:41:20
to have multiple players. >> This next wave of the market evolution I think is going to be extremely high
00:41:27
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
00:41:33
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
00:41:41
analyst essentially and tested all of the frontier models. And it was so interesting because they summarized I
00:41:48
read their paper that they published and I quoted the most interesting part because I see it everywhere now across
00:41:54
all EVALs which is this one phrase there is no single best model anymore. at the
00:41:59
top of the leaderboard. Opus 47, GPT55, Sonnet 46 appear almost indistinguishable,
00:42:07
separated by less than, in this case, you know, 3/10en of a percentage point overall. Read superficially, the results
00:42:12
suggest convergence. Three frontier systems reaching roughly the same level of capability. Okay, why is that
00:42:18
interesting? Well, you got trillions of dollars going into each of these guys to
00:42:22
trying to create these next superb brain, but increasingly our existing set of evals and our existing capabilities
00:42:31
when applied on these models roughly produce the same thing which theoretically says that these things are
00:42:36
getting commoditized way too quickly. And then you'd say, well, what's the ROI
00:42:39
on all this incremental spend, which is a very interesting economic and investment question. So I don't know
00:42:44
like gurley what do you think happens if these evals continue to asmtote and we need more and more and more money for
00:42:52
training >> some of the smarter people in the open source community have suggested to me
00:42:59
that we need more open-source connectors of types so MCP uh is actually run by the Linux Foundation and if you think
00:43:08
about any surface area where a model might interact with other software the more of those connectors that can be
00:43:16
open sourced and commoditized, it would lower. This is what Google did with Kubernetes uh to to try and commoditize
00:43:24
where workflows live off of AWS and to make it easy to migrate. And so the more you can create systems that make that
00:43:33
type of exchange you just described super easy so that you can plug and play the model and you have to worry about
00:43:39
things like context and how does context come in and and data and you know stuff
00:43:44
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
00:43:51
that then the models become swappable and certainly with the both the model companies trying to move up the stack
00:43:58
you have massive desire from the app layer players to try and figure this out and we already you
00:44:04
know watched what cursor is doing and playing with their own model and being forced to kind of reckon with the fact
00:44:10
that they're coming up the stack fast. So I think that's a really good insight
00:44:14
that this gentleman shared with me and I think we the founders and developers that are out there should work on more
00:44:21
of these interfaces and throw them into the open source world just to make it more exchangeable, swappable. Is there
00:44:27
an issue right now with we don't have a good harness for open source? I mean the
00:44:32
way that like claude is a harness for >> Yeah. There's people making open-source
00:44:37
versions of this or building companies around harnessing and building the integrations into it. But open source is
00:44:44
always like the last to build the fit and finish around the product. They focus on the core of the product, right?
00:44:50
So like Linux for your desktop never really took off because the interface was never polished. The UI was never
00:44:56
like perfect, but there are companies building that and I'll just I'll show
00:44:59
you one company that we invested in. This is a company called Abacus and they had a very simple idea. They came up
00:45:06
with their own hardware stack. They came up with their own uh platform and now they are sold out of these boxes that
00:45:13
they're building for insurance, healthcare and everybody wants to run AI inside their organization and then start
00:45:20
building their own models. We actually incubated this in our incubator and you can check it out goabacus.co.
00:45:28
They're just basically saying and organizations cannot get enough of this product. It is crazy how
00:45:36
savvy these organizations are getting and Chamat you're doing it with 8090 as
00:45:39
well I think where they're just like we have to build headless products so that
00:45:44
we don't get locked into any one provider. Whenever we go into the Fortune 1000, we never compete with
00:45:51
OpenAI or Anthropic, they'll have a preference sometimes of what they want to see under the hood. So, our control
00:45:57
plane can basically hot swap, as Bill said, between one or the other. We've also started to lay the seeds for open
00:46:04
source and open weights. But the reason is because they don't want to be tied into one of these
00:46:10
critical frontier labs. They want to be able to ride the wave of innovation, but
00:46:14
they're afraid of two things. They're afraid that one technology leaprogs the
00:46:18
other too quickly for them to participate and they pick the wrong one. And the second thing that they're
00:46:22
increasingly afraid of is terms of service and being at the sake of a frontier lab in a political philosophy
00:46:30
that they may be in the crosshairs of accidentally. Right? So you're a hospital system in Canada. You support
00:46:36
the euthanasia laws in Canada, but this frontier model in America says, "No,
00:46:40
can't do it. So now we shut you off." Right? That's an an example. I'm not
00:46:44
saying one is right or wrong. It's just to illustrate the case. So a lot of the
00:46:48
folks that we see now in the fortune 1000 and increasingly the global 1000. They want as Gurley said abstraction
00:46:55
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
00:47:01
flexibility because they don't know how it's going to shake out. They see all
00:47:04
the money being invested at the model layers but they see the model quality asmtote. So they're like, "Wait a
00:47:09
minute, what are we supposed to do just from a risk perspective?" >> And and regula regulated industries are
00:47:15
particularly sensitive to these kind of issues you're bringing up. >> Hugely hugely sensitive and regul.
00:47:20
>> So if you just follow what finance, healthcare, you know, and and those kind
00:47:24
of folks are doing, they're just like this has to be onrem and they're very
00:47:28
concerned about a data leak and they're very concerned about HIPPA compliance.
00:47:31
They're very concerned about training a model. Like what if you know all of a
00:47:36
sudden somebody does you know a query or or writes a prompt and it pulls some information from that Canadian
00:47:43
healthcare system and all of a sudden somebody gets a result and that sounds farical. Remember stable diffusion
00:47:51
built themselves on Getty on Getty images >> and they all of a sudden the Getty image
00:47:56
watermark was in the output like system you see anthropic and open AI in all of these Fortune 1000s at the developer
00:48:04
layer cuz most of the developers have their own credit cards they're allowed
00:48:07
to sign up for them you eventually wrap them in an enterprise license so it's a
00:48:12
typical PLG-led market motion like we saw in Slack we've seen it everywhere the interesting thing is not that but
00:48:18
it's the unwind that happens then when you have these huge licenses you have
00:48:22
these huge buckets of spend you can't really tick and tie it together the CEOs
00:48:27
then wake up and are told by the CFO hey FYI here's where we are Uber was one
00:48:32
example a second I don't know Nick if you have this tweet but from Vivecarpali
00:48:37
the founder of Clover yeah this was just yesterday overheard from a fortune 20 company CEO asked for a billion in AI
00:48:44
generated OPEX savings at the beginning of the year so we're 6 months in the
00:48:48
team has spent $200 million on tokens and with minimal results. And so now they're in this weird motion
00:48:57
now where the CEO is pulling the budget back and now you're having to cut the
00:49:00
licenses. You just saw Microsoft announce that they're killing the claude licenses.
00:49:05
It's a super dynamic market right now and I don't think we know what the
00:49:09
terminal solution looks like. And by the way, I would I would add Claude is really good at product. Like Claude for
00:49:15
Excel is better than Copilot by not by a little, by a lot. >> And so, you know, anyone that's going to
00:49:23
run against them, they're they are a a worthy foe, I should say. >> Yeah. I think I think Claude is
00:49:29
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
00:49:35
credit card, spent another couple thousand bucks, and I'm like, I was so angry, but I did it because it's so
00:49:40
good. >> Yeah. >> Yeah. Go ahead, Sax. Wrap us up here. Yeah. >> Yeah. So, well, just to wrap up, let me
00:49:46
just connect a couple ideas. So, one is that in terms of the the red capture agenda that you're seeing in Washington,
00:49:55
I think where it's all leading to is an effort to ban open source models or open
00:50:00
weight models. >> There's a lot of breadcrumbs leading here. I think people who want this are
00:50:04
being a little bit circumspect. They don't feel like they're quite there in
00:50:07
terms of being able to justify it yet. >> Can you explain it? >> Sure. You look at you look at a lot of
00:50:11
the rhetoric around how models need to have guard rails and that with open source models, the guardrails can be
00:50:18
removed and therefore they're dangerous. You see this rhetoric already in anthropics blog posts. So, you know, any
00:50:24
threat that they describe, they kind of go out of their way to take that shot at
00:50:30
open source models. you saw it with respect to cyber for example or with respect to bio threats things like that
00:50:36
I mean I've seen that type of language repeatedly that open models lack guard
00:50:41
rails or the guardrails can be taken off and therefore it's a problem and I think
00:50:46
again they're trying to create ideas or put predicate facts in the public record
00:50:53
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
00:51:01
where maybe they can push for that type of ban directly. They're not quite there
00:51:07
yet. >> But what does that do then to the rest of the market? Like let's just say
00:51:10
America bans open source and open weight. Okay. Well, what about the rest of the world? I mean,
00:51:16
>> it sure it'll put >> they're going to leap frog us. >> Sure. You'll put the US on an island.
00:51:20
Well, first of all, as we all know, what does it mean to ban a openweight model?
00:51:24
It's a file. It's a bunch of numbers, you know, that you can run on your your
00:51:28
laptop. >> Yeah. But what it will do is you think about like all the cloud service
00:51:34
providers who run open models like they will stop doing that because they got to
00:51:38
comply with the law and so all this infrastructure that's been built up it will get much harder to use open models
00:51:45
in the United States now the rest of the world will continue to benefit from them
00:51:49
because there's a tremendous benefit in terms of cost and customization and control that you get with an open model
00:51:56
>> and we're on a completely different price curve. And we haven't talked about
00:52:00
this yet. There was an economic and capital mode to training that is going away. It's going away in two ways. One
00:52:07
is because we're getting these domain specific architectures at the silicon layer. And then second, we're rebuilding
00:52:12
all of the core components. I don't know if you guys saw yesterday, but Elon was
00:52:16
like, we've rewritten the entire training complex in C and it's an order
00:52:20
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
00:52:27
innovations are going to make the cost of model training so much cheaper that it's like, why would we stick to the $10
00:52:35
billion training runs when we can have the $10 million training runs? >> Well, if it got 1% better, just as a
00:52:41
thought experiment, Nick, could you find Elon? If okay, if it got 1% better, that's the
00:52:48
equivalent of 2,000 GPUs, which is the equivalent of hundreds of millions of dollars in compute. So every 1% equals
00:52:56
hundreds of millions in compute. If he gets 10% 20% more efficient every quarter, every
00:53:02
>> look at this speed improvement, the speed improvement versus jacks for for
00:53:08
training runs is now an order of magnitude. When you think about then the capex buildout, the opex, the power,
00:53:16
the cabling, the copper, all of it. And now this is a closed source model, but I'm pretty sure that just that tweet
00:53:26
is going to get read by enough people where there's going to be five or six open- source stacks for training that
00:53:32
are rebuilt closest to the bare metal as possible. >> Yeah. >> Why wouldn't you do that now? And so to
00:53:38
your point, Sax, cutting that off so that we lose that kind of innovation makes no sense to me.
00:53:43
>> I agree. And and like I said, I don't know that the forces who want to ban
00:53:46
open source are strong enough or have made the case or created the predicate facts necessary yet to ban open source,
00:53:55
but I do think it is on the agenda and it's where all the breadcrumb trails are
00:53:59
leading. So just watch out for that. I I agree totally with with what David just
00:54:04
said and I wrote a blog post recently on open source and and made the exact same
00:54:09
point. >> I read that too. That was a good one too on above the crowd. >> No, it's not.
00:54:17
It was on the Santa Fe Institute. >> Oh, no, it's it's the P3 Institute which
00:54:23
is my new my new institute. Anyway, um I same same exact conclusion which is rest
00:54:29
of the world ends up running on Chinese models if if if they're able to succeed
00:54:35
at what you just said. >> And if you want to know the canary in the coal mine sacks obviously the place
00:54:40
they love regulation most is the EU. So EU has already done volley after volley of proposed regulation for AI and open
00:54:50
uh and open source is particularly in the crosshairs there because nobody's in
00:54:54
charge of it. So are you going to get a bunch of open source contributors having
00:54:58
to vet their model with the EU regulators like that's obviously not going to happen. Nobody's in charge of
00:55:03
it. There just a bunch of contributors. But open source is the solution I think to
00:55:09
>> Yes, I agree. >> It is the back stop. It is the backs stop. I mean, unless you want to live
00:55:13
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
00:55:18
other final point. It kind of maybe leads into our next topic is I do think that there is the potential for the
00:55:24
monopolization of this market to a greater degree than people may be pricing in right now. First of all,
00:55:30
we've seen that every other major tech category has led to a monopoly or duopoly situation. Seems to be the the
00:55:36
way that these things work out. But also if you look at the growth rates right now, Enthropic does seem to be pulling
00:55:43
away. There's a article in the information showing the latest numbers where I think Anthropic's now at they
00:55:49
seem to have pulled away from open AI, which is not surprising and something I I predicted. Look, if you have one
00:55:54
company that's growing at 10x year-over-year and another company that's growing at 3x year-over-year,
00:56:00
within 2 years, the first company will have 90% market share. This is the power of compounding, right? is just do the
00:56:07
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
00:56:15
2 years, you will achieve monopoly market share. Now there are reasons to believe that anthropic cannot continue
00:56:22
that growth rate for 2 years. There's going to be a competitive response. It's
00:56:26
already happened. Also, there may not be enough compute to support that kind of growth. There may be physical
00:56:31
constraints, but you'd always rather be the company that has that inertia that's
00:56:36
on that totally trajectory than the one that has to do something different to then knock that leader off its current
00:56:43
trajectory. >> Did you guys see what just hit the wire? Nick, can you throw it up from Poly
00:56:47
Market? This is insanity. Poly Market puts out there that an AI consultant revealed that one of their clients
00:56:54
accidentally spent half a billion dollars in a single month after failing to set employee limits on clock usage.
00:57:03
>> What? >> Oh my god, look at this. Look, the 16.6 million per day, almost 700,000 per
00:57:11
hour. Oh my god. Well, there seems to be there seems to be a new like meme taking
00:57:17
shape that somehow like all this token spend is is wasteful and basically useless. And you know, we're constantly
00:57:23
oscillating between narratives like AI is going to put everyone out of work to like AI is useless and it's a bubble.
00:57:29
The doomers can't seem to make up their minds whether AI is going to be our new
00:57:32
god or whether it's basically a total waste of money and it's going to lead to
00:57:36
a bust. But in any event, yeah, I think you know the there there's no question
00:57:40
that token efficiency is going to be a big theme over the next year because the spend has been ramping up way faster
00:57:46
than enterprise customers thought and there's going to be a drive for efficiency. Does that fundamentally
00:57:51
change the dynamics? I don't think so. But it it might, you know, it might temper the growth to some degree. Well,
00:57:58
and they've done a tremendous job making people believe that tokens are free by
00:58:04
giving them these crazy deals like $20 a month, you can do whatever you want. $200 a month, you can do whatever you
00:58:08
want. And it's like everybody's leaving the hose on, everybody's watering, and
00:58:13
then >> you get a photo that says you've hit your usage and it's like, "Come back at
00:58:16
230." I'm like, "230? It's 10:30. I can't do anything between 10:30 and
00:58:20
2:30." And then it says, "Well, you can put in your credit card." And so I did.
00:58:24
>> Yeah. But I mean it's it's literally like the first the first 10,000 gallons
00:58:30
of water are free basically and then all of a sudden it's like okay it's a penny
00:58:34
a gallon and then everybody in the organization and this has literally happened in our organization. One person
00:58:40
built like an interface for the founder university program. Another person built
00:58:44
one. Then another person was like, "Well, those two people got credit at the management team meeting, so I'm
00:58:48
going to build an interface." And the next person builds an interface. And then everybody shipping like interfaces
00:58:53
and I literally had three different people on the team make three different versions of like a founder university
00:58:58
portal and I'm like, "We don't need three. Can we get coordinated here?" And
00:59:02
it didn't get to the point of like spending thousands of dollars, but it certainly got to the point of spending
00:59:07
hundreds of dollars and it would have gotten to tens of thousands. >> Are we still on the first topic? What
00:59:11
are we doing? Well, no, we kind of merged like two or three of them together. >> Oh, we did? Okay.
00:59:15
>> And it's super interesting. Trust me, >> it's super interesting. I think what
00:59:17
Gurley said is one of the most interesting things I have heard >> in a long time.
00:59:23
>> Take people by their word. And if you read their words, >> if you just read their words and you can
00:59:30
understand what they're saying, you don't have to guess about why they want
00:59:34
to have a digital guide. Well, now I'm not the sharpest I'm not the sharpest
00:59:39
arrow in the quiver, but I can take down a buck. And I can tell you that this don't make a lot of sense to me. Even
00:59:46
the dullest arrow can take a buck down. >> All right, let's get back to
00:59:52
It's so great having you here, Bill. We missed you. >> I got you. I got you.
00:59:55
>> We missed you, brother. >> We're going to transition to the next
00:59:58
topic. There is some evidence that Daario is mitigating his dumer rhetoric. Did you see this?
01:00:04
>> Let me get to it. Yeah. Yeah, I got to it here. All right, we we're going to
01:00:07
have to talk for the 16th time in the last 18 months about AI's impact on labor because again this chaotic
01:00:15
schizophrenic interpretation of the data continues. Cloudfare as we talked about last week,
01:00:21
shout out Matt Prince Shimath's favorite CEO of the year. Letter of the year
01:00:28
>> letter of the year. He cut 20% >> award for the letter of the year
01:00:32
>> making friends every week. here on the program. So they both blamed AI spec explicitly and specifically and
01:00:40
Zuck then paired his 8,000 cuts at meta with the fact that he has put uh spyw wear on everybody's laptop
01:00:51
to study every employee to make their training data better. That got leaked and people thought, hey, that's a Black
01:00:58
Mirror episode. We're we're working at Meta in order to, you know, get our
01:01:02
two-year severance package. But on the other side of the table, Goldman Sachs's
01:01:07
uh CEO, David Solomon, wrote an op-ed in the New York Times. I'm the CEO of Goldman Sachs. Period. The AI job
01:01:16
apocalypse is overblown. Period. Obviously, he might be fighting for that anthropic or open AI IPO in the coming
01:01:24
months, or maybe is doing it right now. He made three points. AI won't eliminate
01:01:29
25% of jobs. It's going to automate 25% of work hours and workers will fill that
01:01:34
time with higher level tasks. Obviously, that didn't happen in the case of Zuckerberg's layoffs. Just because a job
01:01:40
can be replaced doesn't mean it will be. Bank tellers increased after ATMs. Live
01:01:45
entertainment became more popular after TV. And the US labor market creates and destroys 25 to 35 million jobs annually.
01:01:52
And the gross churn dwarfs net losses. New categories like agentic AI management are already hiring yada yada
01:02:00
yada. Uh a publication called Fortune is apparently still publishing AI slop and
01:02:04
they say both Sam Wman and Daario have walked back their AI job apocalypse predictions as they gear up for an IPO
01:02:13
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
01:02:20
create more jobs. There was a a recent one of the job boards put out some stats that the number of software jobs is
01:02:27
going up, the number of listings of other jobs going down. So, I guess you're probably in the camp of creative
01:02:33
destruction and churn at this point, Sax. >> Well, I mean, I think you should be
01:02:38
giving me more credit than that cuz my most contrarian take back in January on our prediction show is that AI would
01:02:46
lead to job gains, not job loss. And over the past week, you've now seen the
01:02:52
narrative shift, I would say, almost completely towards that position. So, you have the CEO of Goldman Sachs right
01:02:57
in this in the New York Times. You know, I don't think he'd be doing that if he
01:03:01
felt like he was completely stepping out on a limb. Maybe even more importantly,
01:03:05
you had Sam and even Daario now walking back their claims of massive job loss. And they explained why Daario said, it's
01:03:15
kind of like the 25% of work hours thing. He said that AI might automate away 90% of someone's task, but the
01:03:22
other 10% will expand to do a whole bunch of new new tasks and new things, which is very similar to the the types
01:03:30
of of arguments that people like me have been saying and actually that Jensen's
01:03:35
been saying that just because you automate away some task doesn't mean that you automate away the purpose of a
01:03:40
job. But now the worker is freed up to do new things, to do the higher complexity tasks that David Solomon, the
01:03:47
Goldman CEO, is talking about. So the fact that Daario is now walking this back and coming around to my position,
01:03:57
I think that that's kind of amazing. And uh where do I go to get my apology? You
01:04:02
know, >> well, we're going to have an ap we're going to have an official apology form
01:04:06
that you can fill out. It's got check boxes. I was wrong. I mean, some mornings I woke up thinking, why am I
01:04:13
going out defending these guys? You know, these idiots. I mean, they're scaring the public with all these dire
01:04:20
predictions about an apocalyptic future. There was no data to support that. I mean, we can all debate what's going to
01:04:26
happen in the future, and we probably should be humble about what is going to happen in the future because we don't
01:04:30
completely know, and this industry is very dynamic. But you have to look at what is the data that we have so far in
01:04:36
the current situation. And we do not see data that supports massive job loss. You
01:04:41
can cite this layoff or that layoff Jcal those are anecdotes and the plural of anecdotes is not data. If you look at
01:04:48
the actual data like Yale Budget Lab did they said no discernable disruption in the labor market in the last 3 years due
01:04:55
to AI they've done a comprehensive study. You look at job postings for software engineers. It's up 15%
01:05:02
year-over-year. Their job postings for software developers have hit a new three-year high despite the fact that
01:05:10
coding is the single breakout use case of AI this year. So if AI has not caused job elimination for software developers,
01:05:18
what category has it caused? I mean code is now the number one use case I think of AI in the enterprise.
01:05:26
>> Okay, >> let's be honest. Over the last five or 10 years, a lot of companies overhired.
01:05:31
They mishhired. These CEOs did not have a good handle on it. Their opex budgets completely got bloated, inflated,
01:05:41
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
01:05:49
>> never waste a crisis. >> Never let a good crisis go to waste. Exactly. And so they point to this
01:05:53
thing. It's very simple to say. It's AI. It's two letters. And say we're going to
01:05:57
fire people. But underneath that is not AI because we know this. It hasn't done
01:06:02
anything measurable yet at the end consumption of these tokens. Nobody is standing there and saying look at my
01:06:09
filing here is the lift that I have gotten. Nobody has said that yet. That's very
01:06:14
important to observe. And so instead what people are doing is realizing okay I have this cover now to go and clean up
01:06:20
what was very poor management and mismanagement over the last 5 and 10 years where I overhired and I mishhired.
01:06:28
That's what's happening today. >> Okay, Bill Gurley, I'm going to let you
01:06:31
chime in here. You've got two besties saying, "Hey, this is all hogwash. It's
01:06:36
AI washing. These jobs were just, you know, the strategy obviously in Silicon Valley was
01:06:41
>> they need a scapegoat. They need a scapegoat. >> They're hired two years ahead of time.
01:06:45
Build for the future and it was a vanity metric and you were blocking talent from
01:06:49
working on other startups or competitors. The Google strategy." >> Hold on. Wait, wait, wait. You just said
01:06:54
the critical thing. That is exactly why they did it. >> Yes. That was the explicit strategy from
01:06:58
>> the actual strategy. These guys were a wash in cash. And so part of it is you
01:07:02
were just hoarding talent or what you thought was talent. >> Yes. And just keeping them off the
01:07:07
market. >> And now you're jettisoning it because the reality is as companies get bigger,
01:07:11
their growth rates monotonically decrease and you get to like a GDP plus some number and your valuation
01:07:16
frameworks change and there's nothing you can do to fight that law of gravity
01:07:20
in the public markets. And so as each of these CEOs who at some point thought they were different and the rules didn't
01:07:26
apply to them are now realizing you're just like everybody else. Okay, we have
01:07:31
to stay humble as Sax said, but Bill Gurley, would you like to apologize for Sachs andor give him credit for his
01:07:36
incredible non-conensus? >> He wasn't the Hold on. He wasn't the one
01:07:40
promoting the jobs apocalypse. >> It was you. I will give my thoughts in a
01:07:46
moment. You're the for the mainream media. >> I'll give mine. >> You always represent the legacy media on
01:07:55
our show. Jay Cal, you have been in the fourth. >> I represent the legacy media represent.
01:08:00
You're the New York bluehaired. >> I'm just giving you the statistics,
01:08:05
guys. I'm just presenting the numbers. Now, let's remember anecdotes. >> Let's remember.
01:08:09
>> Actually, let me give you an important statistic. Let me give you a very No,
01:08:12
no. This is really important. >> We have to let Bill Girly comment. Then you can really important. Do you use
01:08:18
ketamine? I don't use ketamine. That's the terrible drug. Do not use ketamine,
01:08:22
folks. >> Bill Gurley, you have the floor. >> I would just touch on two things that I
01:08:28
already said earlier. One, you know, historically innovation has led to more prosperity for humans. And I gave those
01:08:36
numbers from 1891 to today. I see no reason why that won't happen here. In the short run, from a bottomup
01:08:43
perspective, every human that wants to protect themselves needs to be the most AI enabled version of themselves they
01:08:50
can be. And the people that might be a threat of job loss are someone who like stands hard, fast, and refuses to use
01:08:58
AI. And I would just say that's simply like saying, "I'm not going to use
01:09:03
email. I'm not going to use a spreadsheet. I'm not going to use a computer." And and you know, you
01:09:09
probably are at risk. >> Yeah. Yeah. The paradigm will shift to give you actually my position which is
01:09:15
>> Would you like me to give my position or just want to jump? >> Yeah, I do but I I never got to finish
01:09:18
that point. So, but I can do it after you. >> Yeah. Yeah. So, I I will give my
01:09:22
position on this which is there and it's always been the same which is there's
01:09:26
going to be a massive job displacement that occurs and that massive job displacement is going to come because
01:09:33
CEOs in many cases believe that this technology is going to make people more efficient. they can do more with less
01:09:40
and they will be rewarded by the public market by just having higher earnings and we see that for every single
01:09:46
company. Now I fully concur it was because of bloating and I gave my position there. I know specifically that
01:09:52
Sergey and Larry took that strategy of taking talent off the market so there wasn't a Google competitor that was
01:09:58
literally explained to me by those individuals. We hire people and then we figure out what to do with them later.
01:10:04
That strategy permit just became the standard in Silicon Valley and now it's
01:10:09
being reversed. Now there will be wholesale jobs that will be retired. If you look at
01:10:16
self-driving that's obviously happening with Whimo with 3,000 vehicles and and
01:10:20
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
01:10:26
idea of somebody driving a taxi is going to seem silly and dangerous. We will see
01:10:32
the same exact thing happen with Optimist. You may have seen the figure robot sorting packages. All those
01:10:37
sorting jobs at Amazon factories are going away. Amazon themselves, these are the savviest people in the world said,
01:10:44
"We are going to eliminate 600,000 future positions and we are going to cut
01:10:49
positions." And Andy Jasse said, "This is going to be a reoccurring theme. As
01:10:53
we deploy AI, we will do more with less." You will see the headcount at all
01:10:57
these big companies dramatically decrease or stay the same as earnings massively increase. And you can take the
01:11:03
position, Saxs, that oh my god, the numbers are in my favor. They're not. The numbers are in my favor. The job
01:11:09
loss is tremendous. And there are numbers associated with that. 8,000 people at Meta after 20,000 before that.
01:11:16
And if you look at the steady state of these companies, they has nothing to do with AI. Let me finish.
01:11:21
>> They overhired. >> No, no, no. We are beyond that. We are beyond that. They are now getting rid of
01:11:25
people. When they say they're getting rid of measurers, you can take them at
01:11:29
their word. When they say they're getting rid of middle managers, you can take them on their way and
01:11:33
>> scapegoating. That is you've given your position already. I'm giving mine. My
01:11:36
position is they are obsessed with this technology, they're obsessed with earnings and they will continue that.
01:11:41
Now on the other side of the ledger, I believe we'll have a Cambrian explosion
01:11:45
in startups and all these this talent if they embrace the tools to Bill Gurley's
01:11:49
point are going to be able to solve more problems and create small companies of five or 10 people who are laid off from
01:11:55
Amazon or Meta and make double their salary or have a better job that they control. I believe that is going to be
01:12:02
the ultimate solution. But that transition is going to be extremely painful and we should have some humility
01:12:07
on this [ __ ] podcast for the people impacted. Every cab driver is losing their job. Every truck driver is losing
01:12:13
their job in the next 10 years. Anybody sorting packages losing a job. Now you can say all you want. You can say all
01:12:19
No, let me finish my thought. You can say all you want, Chimov, that those people don't want those jobs. But they
01:12:25
may need those jobs >> and you are an elitist by definition. We are all elitists on this program. We are
01:12:31
elite performers. >> And these people are gonna lose their jobs and they may not get a job very
01:12:36
quickly. By being able to call something what we think it is is not being elitist. It's actually
01:12:43
telling the truth. Meta over hired. Okay? You could have stopped the company at 3,000 people when I left and it would
01:12:51
not have changed the outcome of that company. There was no need to go to 90,000 people and burn $50 billion on
01:12:56
VR. They did it because they had the freedom to do it. That's allowed. It's
01:13:00
capitalism. Okay? They're coming back to realize that there's a more efficient
01:13:05
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
01:13:11
to do is just say that. >> I think you're wrong. And let me explain to you why you're wrong. I believe
01:13:16
you're wrong. I believe Zuckerberg is putting that software on people's computers in order to to find more jobs
01:13:24
to eliminate to increase it. And the surface area of problems in the world is not decreasing, but what is uh
01:13:31
decreasing is the number of humans to take on the next opportunity. And that's
01:13:36
going to continue. And I think the companies that will be rewarded and their stock prices will be rewarded are
01:13:40
the ones who do much more with much less. And they're going to keep eliminating these jobs. And I take them
01:13:47
at their word. >> You don't have to explain everything with conspiracy. Maybe they just
01:13:51
mismanaged for a period and they could agreed on that. I I think that explains the postcoid two or three years. I think
01:13:59
what we're seeing this year is actually the tools working. the tools are working
01:14:04
and there are jobs that are no longer needed. The measurers as Matthew Prince pointed out or product managers or
01:14:10
designers, those have all been consolidated into one job. Somebody who ships a product and it doesn't require
01:14:17
12 people. It requires two people now. I know >> I don't think that's been consolidated.
01:14:21
I see it in Fortune 1000 companies all the time. I don't think what you're
01:14:24
saying adopters. You're talking about the slowest adopters. I'm on the front
01:14:27
line with >> startup. These are where all the jobs are. But I'm sorry, but a startup is not
01:14:31
going to go and enter a regulated market and put JP Morgan out of business. Not gonna happen.
01:14:36
>> They will eventually uh displace those companies. It happens all the time.
01:14:41
>> Not going to happen. >> We're going to agree to disagree. >> Good luck to the startup trying to
01:14:44
disrupt Boeing. Good luck. I'm going to take Boeing. >> Okay. Well, some people might take
01:14:49
SpaceX. So, >> good luck making drugs out of an Excel spreadsheet. I'll take the regulated
01:14:54
pharma company. Good luck. >> Sure. Listen, there are some industries that are so much to one and you're going
01:15:00
to show up at the FDA and like, okay, where's your team? Oh, it's just me. I
01:15:03
do it all. >> Me and my model. Look at this. >> You joke. Somebody just did that in
01:15:08
>> It's not a joke. It's not a joke. And it's not going to happen because that's
01:15:11
not the way society wants safety, predictability, governance, auditability to work.
01:15:16
>> Yeah, I there's a distinct difference between, you know, drugs and software
01:15:21
and services in the world. I think we can agree on that. And listen, a regula with truck driving is one of the most
01:15:27
regulated industries out there. So is cab driving and taxis as Bill and I well know and those jobs are being
01:15:33
eliminated. Bill, I'm gonna give you the final word, then Sax, I'll give you the
01:15:35
final word. >> A chance to respond. >> Let's do Sax. >> Okay, Sax, then Bill, go.
01:15:39
>> Well, first of all, Jake, you remind me of the Troskyite who when confronted
01:15:44
with the fact that none of Trosky's predictions had come true that simply proved how far-sighted Trosky was.
01:15:50
>> I didn't go to graduate school. You're going to need another reference.
01:15:53
>> In other words, none of your predictions about job loss have come true. In fact,
01:15:56
the data >> none zero data >> except for what M just did last week. But go ahead.
01:16:01
>> That's an anecdote. That is not >> It's not an You're calling 8,000 people
01:16:06
losing their jobs an anecdote. >> You don't hear yourself? >> Hold on.
01:16:10
>> Do you hear yourself? It's not an anecdote. 8,000 people lost their jobs.
01:16:13
>> Can I make my case? I heard you about the the meta data point. First of all,
01:16:18
those jobs that job loss was not directly attributable to AI. It just wasn't. That's something you've invented
01:16:24
and put in the data. >> Something Zuckerberg said. No, they they clarified that. Okay. Okay. Sure.
01:16:29
>> He said it was related to they were trying to balance additional spending
01:16:33
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,
01:16:40
you're not netting those jobs against all the other jobs that are being created because of AI and all the new
01:16:46
companies that are being created right now because of AI. So, you're just cherrypicking one statistic. You're
01:16:53
attributing 100% of that to AI and then you're not basically netting it and pre
01:16:57
presenting a balance. You've got >> I'm not cherrypicking it. I am reading
01:17:01
the news and I'm describing what the CEO said. Jack at Block said he's doing this
01:17:07
because of AI. Matthew Prince said it's AI. Zuckerberg said it's AI. >> I'm just taking them on their word.
01:17:14
>> Yes. Exactly. So Jack Dorsey came out and said that he was going to do a 50%
01:17:18
elimination because of AI. Okay. And within 24 hours, all the financial analysts on X said that Jack was AI
01:17:26
washing and that block had horribly overstaffed during COVID. It was running much more inefficiently than all of its
01:17:32
other peers in this category. And they've needed to do a 50% job cut for a long time. So pretty much everyone
01:17:39
thought that was pure AI washing. In fact, you've just proven my point. And what exactly are the efficiencies that
01:17:46
Jack is getting? I mean, this is the most handwavy thing ever that, oh, we're
01:17:49
just magically going to be able to eliminate half our cost structure right now. >> Okay. So, Jack, Matthew Prince,
01:17:55
Zuckerberg, and Andy Jasse are all lying and doing awashing. This was due to AI. He just did it.
01:18:03
>> That's that's your reading of it. But like I said, even if you attribute those
01:18:07
specific job losses to AI, which is questionable, you're not netting it against all the job creation that's
01:18:13
happening and also the new company creation. Furthermore, let me just give you some I specifically attributed that
01:18:22
the future and the new jobs will come from startups. So don't misrepresent my
01:18:24
point. Thank you. >> Okay, we currently have a 4.3% unemployment rate in the economy.
01:18:30
Economists consider 5% to be full employment. So basically unemployment is at or near record lows right now despite
01:18:38
the of our lifetime despite the fact that we're over three years into this AI
01:18:42
wave. Second and again this is the point I wanted to make earlier with respect to
01:18:47
coding. Coding is the single job category most impacted by AI right now. We are at the point where AI is writing
01:18:54
most of the code. We have almost complete automation of codew writing. You would think that if you could look
01:19:02
at this in a simple Malthusian way, all the software developers would be getting
01:19:06
laid off right now. Is that happening? No. No. Software developers are not being laid off on net. In fact, job
01:19:13
postings, job wrecks for software developers are at a three-year high, growing 15% year-over-year. Now, why is
01:19:21
this? I think the explanation is really, really important. Okay, you look at code
01:19:26
commits on GitHub, which is the leading code repository. There were 1 billion code commits last year. In the past
01:19:33
month, there's been 1.1 billion. So, in other words, >> make something easier, more people do
01:19:39
it, >> right? We have basically a 14x year-over-year increase in code generation. That code has to be managed
01:19:45
by somebody. You still need humans to look under the hood. And when the amount of code explodes and you get 10x or 100x
01:19:53
more code, the complexity also rises as well. So look, we're not hiring 10 times
01:19:58
more engineers, but you do need more engineers now to manage all of that code. The other thing that's happening
01:20:05
is that there's been an explosion of the use of code across the economy by different businesses, different
01:20:11
applications, and different use cases. I'm hearing from people who are now hiring software engineers who never
01:20:17
would have hired them before. I was talking to a fund manager, and he said that his next two hires were not going
01:20:22
to be data analysts. they were going to be software developers because they're
01:20:25
now deploying code for the first time in ways that they were not before. This goes back to my point about claude
01:20:32
proficiency being the most marketable skill right now in the economy. People are using these tools in entirely new
01:20:39
ways. I think that we're at the outset of a boom right now caused by bespoke
01:20:45
software proliferating throughout the economy and being used by firms that never thought of themselves as tech
01:20:51
firms before. All of which is leading to more productivity and that leads to a healthier economy and that leads to more
01:20:57
job creation. And you're seeing that again in the aggregate numbers and that
01:21:01
doesn't even include the bluecollar boom that's happening right now with the
01:21:06
development of all this infrastructure, the data centers and the new energy and power generation. We are seeing hundreds
01:21:11
of thousands of new construction jobs being created among bluecollars. Jan, I'm sure you don't want them losing
01:21:17
their jobs by turning this boom off. So again, >> no I I never advocated you misconrue you
01:21:24
like to misconrue my position. I am very clear there's job displacement going on
01:21:29
and the job displacement is related to AI but net I do think the economy will grow. Bill Gurley
01:21:34
>> maybe at some point in the future you'll be right like the Trosky eye communism
01:21:38
has never been tried. Maybe it'll work. >> Nobody knows your Trosky references.
01:21:42
Okay you lose you lost 95% of the audience. Just speak like a normal person. >> Chimath laughed. Chimath understood it.
01:21:47
>> Okay great. I know the artist is smarter smarter than you give them credit for.
01:21:51
>> Okay. No, I just think you're just making these deep polls to try to sound
01:21:55
smarter than you actually are. Uh the reality is the reality. These people are being laid off because of AI. Bill
01:22:00
Gurley, of 20 million people in the United States driving cabs and trucks and doing that as a job right now, how
01:22:07
many of those do you think will lose their jobs to self-driving in the next decade or two based on just being in
01:22:12
there? And I'm not trying to lead the witness here in any way. Obviously, some
01:22:15
people prefer a human driver, but what what's your take on on that specific part of the economy?
01:22:20
>> I think it's impossible to go with a 100% automated uh solution because the the economics don't work
01:22:28
well. And so, I think like some of the other examples that were given, ATMs and whatnot, I I think the the use of
01:22:36
nonownership cars is going to go way up. So, it's going to keep growing through this and
01:22:43
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
01:22:50
actually stays the same or grows. And let's remember these jobs didn't exist
01:22:56
before because regulation had limited what the taxi market was capable of and and getting around that actually led to
01:23:05
job creation. And so I I'm not a big fan of the doomerism because around jobs,
01:23:11
you know, there's a word lite that that kind of is used to to talk about it. And
01:23:17
I don't have high confidence in any government program for skills retraining. So it's not clear to me what
01:23:25
okay yes it's happened. What do we do now? It's not clear to me. I think the
01:23:29
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
01:23:35
get out there. And then two, if your job is going to go away and maybe it's a job
01:23:39
you don't care about, start thinking about where there are opportunities. Everyone's talking about it. The skilled
01:23:46
trades are like we're we're short of people. >> Shortage for plumbing, electricians,
01:23:52
HVAC, all that. Yeah. >> It's amazing how Jay uses facts that haven't happened yet as like support for
01:23:57
his argument. Like you just state that, oh, all the truck drivers are losing their jobs. All the drivers are losing
01:24:03
their jobs. And then you say that this proves my take. Yeah, I know it's your
01:24:07
belief, but that is not proof. Do you understand? >> The proof I gave was Amazon and Andy
01:24:11
Jasse, Shopify, they were doing that before Mark Benny off automated Amazon. Let me ask Bill
01:24:20
everybody knows our Amazon car being delivered so you cherry pick anecdotes and then misattribute them to AI.
01:24:27
>> They literally have a self-driving division. It's called Zuks. >> You're the biggest AI washer there is.
01:24:31
They are the largest user of robotics in the world. So yes, Chimath, they are pursuing robotics
01:24:39
massively more than anybody and they are pursuing self-driving. >> You just you just like all these words
01:24:44
together. At one point it's a warehouse worker, then it's a driver, then it's
01:24:47
Amazon. It's just >> it's not it's not you can you can personally attack me all you want. The
01:24:53
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
01:25:02
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
01:25:07
I will take people I will take people at their word. I'm curious, Bill, your take
01:25:12
on >> these large enterprises. You've heard two positions here. >> I have a question for you.
01:25:17
>> I have a legit question for you. >> Can I just let the guest be involved,
01:25:20
please? Sax your monopoly. actually engaging with your with your perspective. Explain to me. No, no. This
01:25:25
let me let me truly ask you. >> Okay. >> Explain to me why job postings for
01:25:30
software engineers are up 15% year-over-year despite the fact that code has now been fully automated.
01:25:35
>> Oh, I think there's a Cambrian explosion in uh software. You're absolutely
01:25:40
correct. And I believe people who know how to vibe code or to like who are non-developers are making bespoke
01:25:46
software. I've said that a hundred times on this podcast over the last few years
01:25:49
and I predicted it. So absolutely I believe that will be an area of job growth. I believe the positions that are
01:25:55
being removed or I just I know based on what we're hearing is product managers,
01:26:00
middle managers, what Matthew Prince call measurers, what other people call mid management. Everybody believes that
01:26:06
the recording and this daily standups and the uh zoom calls all of that is turning into people management is being
01:26:15
done better by AI and people are more self-directed and then the stack of people to build products is being
01:26:21
consolidated right it's like the the typical designer can now vibe code the developer can do front-end design and UX
01:26:29
and they can project manage themselves so I there there are a series of jobs that will increase and a series of jobs
01:26:35
that will be eliminated just like the mail room got eliminated and mess bike messengers got eliminated
01:26:42
that >> got on net on net do you think there'll be mass >> do you think there'll be on well your
01:26:47
position is shifting a little bit do you think on net do you think on net there'll be mass job loss
01:26:54
>> uh I think there is a chance that we're going to see uh job loss increase in the
01:26:59
short to midterm and then eventually the displaced people are going to have to learn or leave the workforce, which
01:27:05
is what happened during other revolutions like this. Some people went with the paradigm and adapted and some
01:27:11
people didn't and just retired. That I I saw that firsthand in the PC revolution
01:27:15
as but one example. Some lawyers just would never use these tools and they just retired at 55 65 and they moved on.
01:27:22
And then other attorneys were PC first and they just took that. >> By the way, did you guys see the news
01:27:26
that Kirkland Ellis is going to spend half a billion dollars to roll their own Frontier model?
01:27:32
>> Makes total sense. That was like to our earlier point today is that people are
01:27:34
doing on prem and going to make their own models. Bill, I have one specific question for you and thank you for the
01:27:39
good engagement there, Sax. It was it lacked the ad homonym that usually uh starts every conversation we have.
01:27:45
>> I don't usually call you an idiot. >> That's because it's in our minds. Okay,
01:27:48
we're thinking about it. We're just not saying it. >> Good. I like it better. I like it
01:27:52
better. Um Bill, specifically when Andy Jasse, you know, uh last spring said, "Hey, we're going to do more with less.
01:27:59
We're going to be AI first." and they said, "We're not going to hire these
01:28:01
600,000 jobs." When you see Tubby Lucky, he say, "You have to do AI first before
01:28:06
you ask for a headcount and prove to me that you tried AI first before hiring somebody." Do you think this is
01:28:13
a sign that these organizations are AI washing or do you think these recent ones are more, hey, we're going to do
01:28:20
more with less and and the size of these companies will be smaller uh because of
01:28:24
AI? One thing that that I think that last question misses and I think a lot of the the AI dumerism stuff misses is
01:28:34
that competition exists. And so if you I don't think there's any scenario where
01:28:40
you just do more for less and all of a sudden everyone has 70% operating margins. That's not going to happen.
01:28:48
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
01:28:55
could have a productivity boom from lowerpriced goods and services and the basket of goods that humans are able to
01:29:02
buy gets cheaper and cheaper and cheaper and that's been true in many categories.
01:29:06
Unfortunately, it's offset by what happens in healthcare and other regulated industries.
01:29:11
>> Yeah. Education. But but yeah, so I expect products to get cheaper and people to be able to create more with
01:29:19
less. But I don't think it leads to obscene profits >> because it'll be whittleled away in
01:29:26
competition. >> Okay. >> By the way, just just on this AI washing point, there's a a trial lawyer named
01:29:33
Donnie King. He's a securities litigation partner at a firm called Acriman. He and his colleagues have
01:29:40
started to warn that we could start seeing shareholder lawsuits against companies that engage in this type of AI
01:29:47
washing cuz he thinks it's a type of puffery, right? Because essentially what
01:29:51
the company is doing is attributing their own non-performance or their operational issues to AI when in fact
01:29:58
there are real problems in the business and therefore it could be a form of securities fraud.
01:30:03
>> Wait, securities fraud? Yeah. >> I want to double click on this. Did you
01:30:06
see the CEO of Whisk today on his note about layoffs? >> No. Who's Wisk?
01:30:11
>> Find me the AI washing in there. Wix. >> Oh, yeah. Those that's the website
01:30:14
builder. Yeah. I mean, you can build websites with Claude. Yeah. The whole website business is challenged. Yeah.
01:30:21
>> Interesting that he just he just talked about operational details. >> Did he? I I didn't read the note.
01:30:26
>> Of course, you didn't read the note. >> Well, I mean, you said it just happened.
01:30:31
>> I I will read it. Uh, this is I'm just this broke at 9:25 this morning.
01:30:37
>> I think it's really interesting that this lawyer thinks there's so much AI
01:30:41
washing going on that he thinks it could constitute securities fraud and he's
01:30:44
warning clients not to engage in it. But look, Jake Al, you're like the last
01:30:48
person who hasn't gotten the memo on this. There was a huge narrative shift this week. Sam is backing off this. Even
01:30:53
Daario's walking it back. You got the Goldman Sachs CEO. You got the explosion in job postings.
01:31:00
Everyone's coming around to the idea that the job apocalypse is massively overblown.
01:31:07
>> I mean, it could be overblown looking at the stats. >> Your apology, I'm happy to accept.
01:31:12
>> No need for an apology. I mean, my position has always been apologize. >> It's displacement. You're going to have
01:31:16
some displaced in the short to midterm and then eventually there'll be more problems to solve and people will have
01:31:21
to reallocate. I do think we're being uh uh, you know, I think the tech industry
01:31:26
itself doesn't have enough empathy or enough thoughtfulness when discussing this because these are real people
01:31:32
losing real jobs and you can point at statistics uh and you think they're spinning, but these are real people
01:31:39
losing real jobs who may not make the transition. >> Jason, I got I got >> Do you think it's more empathetic to be
01:31:45
scaring the be Jesus out of people that they're going to lose? >> I'm not in the scaring camp. I'm not in
01:31:49
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
01:31:54
start a company and you should embrace the tools. So, I I'm I'm all about
01:31:57
empowering people. I think they if they learn the tools, they'll have 10 job
01:32:00
offers. Uh and they'll start their own companies. So, I do think there's a
01:32:04
solution to it. I just think we're going to go through, you know, low millions of
01:32:08
jobs being lost or being retired and transitioned out over this next couple years.
01:32:14
>> I was just going to be empathetic and offer some solutions. So we talked about
01:32:18
the skills trade deficit of of people working in that. Micro has a foundation called Micro Works where they fund they
01:32:28
funded $16 million 2600 people get a free scholarship for to be become a plumber, welder or electrician. So go
01:32:37
check that out if you want to reskill. I think >> generation tool belt. Yeah.
01:32:40
>> I think it's better than you know having the government fix things. And then, you
01:32:44
know, as as we started and talked about, I've got a new uh grant program myself
01:32:48
to help people >> Yes. >> kind of tilt their career in a different direction. Go do something you love and
01:32:53
and apply and maybe I can help fund your you moving in that direction. >> And and as to your vibe shift, I think
01:33:00
it's because candidly people's houses have been Molotov cocktailed because
01:33:05
they're doomerism. And people specifically are citing that when they shoot at their houses and throw Molotov
01:33:10
cocktails at them twice in the same week. And if you're IPOing and you're
01:33:15
coming out saying, "Hey, jobs are going away. Jobs are going away." That's just
01:33:18
a really bad look. >> And or it's because we called it out and they got cut and so now they were
01:33:23
telling the truth. >> All right, everybody. This has been another amazing episode of the AllIn
01:33:28
podcast. Thanks for coming. >> No, no, no. Sorry. I need to do one thing >> just doing at the end of this.
01:33:35
>> Yes. >> She's a friend of ours. I just want to just give a huge shout out to Tulsy
01:33:39
Gabbard and specifically her husband Abraham. is tragic. >> Going through some really tough stuff
01:33:44
with cancer. He is going to kick its ass. I just wanted to say we love you. >> Yeah. Uh Tulsi is great.
01:33:52
>> Cheers everybody. Uh that's episode 275 in the can. We'll see you next time.
01:33:56
Bye-bye. Love you Blues. >> We'll let your winners ride. >> Rainman David.
01:34:06
>> We open sourced it to the fans and they've just gone crazy with it.
01:34:10
>> Love you. Queen of Kino. >> Besties are gone. >> That is my dog taking notice in your
01:34:23
driveways. >> Oh man, my appetiter will be. >> We should all just get a room and just
01:34:30
have one big huge orgy cuz they're all just useless. It's like this like sexual
01:34:34
tension that we just need to release somehow. >> Wet your feet. Wet your feet. her feet.
01:34:42
>> We need to get mer. I'm going all in.