Speaker 1: Corruption. We're living in the greatest hyptocracy. You're in my lifetimes.
Speaker 1: Someone gets you a billion dollars in crypto, you'r bot period.
Speaker 1: So the question is where do they go as they
Speaker 1: get more power than The answer is Elon became a narcissist.
Speaker 1: This is Gavin Newsom and this is read Offman. Well, welcome,
Speaker 1: my pleasure to be here the first time in the
Speaker 1: Governor's match.
Speaker 2: It is not bad, right, yes, bad, and it's you know,
Speaker 2: it's you know now, I don't know, it's not, but
Speaker 2: it's you know, we're blessed to be here, but I'm
Speaker 2: blessed to be here.
Speaker 1: Look how many books you written? Six?
Speaker 2: Six best selling books? Two podcasts one's not enough.
Speaker 1: Yes, you know everyone it was getting to the point
Speaker 1: where everyone had a podcast, so I had it too.
Speaker 2: To the most you know, I mean you've been You've
Speaker 2: been around sort of og started a few companies. You're
Speaker 2: part of this mafia, this mob called PayPal.
Speaker 1: Yes, although I try, you know, everyone likes the mafia
Speaker 1: kind of thing of it. We didn't do anything criminal.
Speaker 1: It's PayPal network.
Speaker 2: Well, I'll get to I want to get to you know,
Speaker 2: do you guys obviously embrace that a little bit. Yes,
Speaker 2: and you know, we'll also talk about you know, it's
Speaker 2: kind of broken apart a little bit, the old the
Speaker 2: pal version of the mafia started this company LinkedIn. Yeah,
Speaker 2: and you're currently though not maybe for long. We'll talk
Speaker 2: about that on the Microsoft board. And you've got a
Speaker 2: number of AI companies that you've started up, and you
Speaker 2: also have invested seems like everywhere in the AI space,
Speaker 2: and you're doing.
Speaker 1: A lot of angel investing.
Speaker 2: So all of that and you haven't even turned sixty
Speaker 2: years old coming up, but not quite.
Speaker 1: It's not quite.
Speaker 2: But I really wanted to get you read to talk
Speaker 2: about the AI in the broadest sense because we've looked
Speaker 2: we're just everybody's ringing their hands, the doomers, the gloomers,
Speaker 2: it's going to take our jobs.
Speaker 1: The anxiety is boiling.
Speaker 2: You're seating and representing polls and just anecdotal feelings. People
Speaker 2: are angry about data centers. People are furious that their
Speaker 2: kid who went to Stanford and got this unbelievable degree
Speaker 2: is not getting as many interviews as mom and dad
Speaker 2: expected their perfect child to get.
Speaker 1: But you have a different take on all this.
Speaker 2: You're a little bit more optimistic about this.
Speaker 1: So, I mean, first you've got to acknowledge people are
Speaker 1: in pain having difficulties, right, I mean, and yes, there's
Speaker 1: difficulties with entry level jobs. And if you listen to
Speaker 1: the press, including by the way, a bunch of the
Speaker 1: AI people who make, you know, foolish statements like white
Speaker 1: collar blood bath and other kinds of things, they go, well,
Speaker 1: it's AI's fault. And it's like, actually, if you actually
Speaker 1: look at it thus far, it's not AI's fault. Doesn't
Speaker 1: mean there won't be an impact from AI and all
Speaker 1: this stuff and entry level jobs, but the pain that's
Speaker 1: being felt right now is overhiring from covid is tariffs,
Speaker 1: you know, screwing our economy and business planning, and when
Speaker 1: and when all of that kind of stuff happens, businesses go,
Speaker 1: I'm gonna do no hiring until I figure out what's
Speaker 1: going on. Right.
Speaker 2: So you're saying some of those big headlines that we
Speaker 2: saw box and others that somehow suggested or at least
Speaker 2: added in the press release maybe a number of factors,
Speaker 2: including AI, and then the mainstream press runs with AI overhyped.
Speaker 1: Yeah, well overhyped, but it's a natural reason for a
Speaker 1: CEO to say that, because if I was like, oh
Speaker 1: I overhired and I mismanaged, it's my fault. No, No,
Speaker 1: I'm strong. I'm taking advantage of AI. AI is replacing jobs.
Speaker 1: I am just being a really good CEO and and
Speaker 1: and manager of my shareholder capital, which like like CEOs
Speaker 1: are smart people. Pick reach you one you want dorowy
Speaker 1: or Dori B. It's like, oh, take door B, thank
Speaker 1: you very much.
Speaker 2: So what do you make then, of the college graduate
Speaker 2: and the unemployment rates that legitimately, at least numerically statistically,
Speaker 2: what's the causation of that? What would you what's the
Speaker 2: factor that how would you factor AI in that respect? Well,
Speaker 2: what do you think, more broadly is the reason that
Speaker 2: those numbers are higher?
Speaker 1: Well, I think what is factually case is that a
Speaker 1: wide range of businesses are like, we don't know if
Speaker 1: we should be hiring new entry level people right now.
Speaker 1: Some of it's like, well, we're doing layoffs because we
Speaker 1: hired too many people during the pandemic and and and
Speaker 1: then did this whole remote work thing which is not
Speaker 1: really working out and refactoring it, and da da da,
Speaker 1: and then there is oh and uh, and now we've
Speaker 1: got trade war going on with global tariffs, which are
Speaker 1: increasing cost to consumers, cost to businesses, costa and so
Speaker 1: like like, and we got volatility central like, hey, it's July.
Speaker 1: We're starting a new war, right like you know da.
Speaker 1: So it's like like in all those cases, what businesses do.
Speaker 1: The very first thing I do is let's not encour
Speaker 1: any new expenses. It's let's not hire any new people
Speaker 1: except the very clear people we need entry levels are
Speaker 1: usually like, oh, these are people we need five years
Speaker 1: from now. Well, we don't know we need five years now,
Speaker 1: so let's not do that. It's also let's not do
Speaker 1: a new lease. Let's not like it's like, let's let's
Speaker 1: just chill. So that's the primary driving actual factor. Now
Speaker 1: that being said, And by the way, there are a
Speaker 1: few places which are AI related, like for example, the
Speaker 1: metal layoffs are we need to free up costs for
Speaker 1: spending on compute and so we're gonna do So it's
Speaker 1: not that there's zero, it's just that the broad brush
Speaker 1: you know kind of college grad is not actually in
Speaker 1: fact yet, Like if it's a percentage from AI, it's
Speaker 1: like five, it's not you know, it's not thirty or fifty.
Speaker 2: So you talk about I mean some that have used
Speaker 2: some pretty aggressive language about a white color blood bath,
Speaker 2: but I mean you And I don't know if Dario
Speaker 2: said that or not, but I mean it was specifically
Speaker 2: not surprising on the basis of the question I'll ask,
Speaker 2: which is obviously he's because of his emphasis and he
Speaker 2: put on numeric about fifty percent of why collar jobs
Speaker 2: be eliminated. At least knew why collar jobs in the
Speaker 2: next well five years, less than five years by twenty thirty. Again,
Speaker 2: hyperbole from your personspective and your guys. You know you're
Speaker 2: a fan of Dariayes. I'm a huge fan of Darios.
Speaker 1: And look, Daria frugally gets criticized that he's doing it
Speaker 1: for like kind of promoting his own technology, and this
Speaker 1: is how important my technology is. There. No, Daria is
Speaker 1: very principled, right, He's like, look, I think that there's
Speaker 1: a real worry here and it's not on like society
Speaker 1: should be ready. I'm trying to help society figure out
Speaker 1: getting ready. So I appreciate Dario's principle, his motivation, et cetera. Now,
Speaker 1: after he said that, I called Daria and I said,
Speaker 1: look what you said is not heard the way you
Speaker 1: think it's heard, right, because what people here is, well,
Speaker 1: if that's going to create a huge blood bath and
Speaker 1: that's the outcome, why are you building AI so fast?
Speaker 1: Why are you doing all the stuff? Right? Is it
Speaker 1: just to make yourself rich? Right? Because what they hear
Speaker 1: is they hear the Hey, everyone, I have this really
Speaker 1: great technology that's going to like ruin half of your
Speaker 1: lives and good for me and sucks to be you. Right,
Speaker 1: that's what they hear. That's not what you meant to say,
Speaker 1: but that's what they hear. And so and so I
Speaker 1: was like, look, I think the I said, Daria, the
Speaker 1: better thing to say is we're going to have a
Speaker 1: lot of job transition, and there's a lot of uncertainty
Speaker 1: of what's going on, and it could have a really quick,
Speaker 1: massive impact and we should be figuring out what to
Speaker 1: do on it, right, right? And is that so?
Speaker 2: I mean, you've talked about it in the terms of
Speaker 2: a cognitive industrial revolution, and you talked about not being
Speaker 2: poland rather be England take advantage of this, and and
Speaker 2: that's and you've done that in the context of making
Speaker 2: the case that we, you know, we should be accelerists,
Speaker 2: though probably with the notion of a steer.
Speaker 1: Yes, so you're not naive sometimes you slow down on
Speaker 1: the curve and.
Speaker 2: Slow down on the curve. But vehemently opposed to this
Speaker 2: sort of precautionary principle framework. This notion of this is
Speaker 2: you know, we've just got to put a damn pause
Speaker 2: on this.
Speaker 1: Yes, So so let's start with the pause because it's simple,
Speaker 1: which is, say you issue a call for a pause,
Speaker 1: and you have two groups of people, the group of
Speaker 1: people who pause and the group of people who don't pause.
Speaker 1: The group people pause and go, oh, I hear you.
Speaker 1: The humanist stuff really matters and I care, so all pause,
Speaker 1: and then the people go I don't give a shit
Speaker 1: and they keep going. So then what kind of AI
Speaker 1: is built? Right? Not good? It actually has a negative impact. Right.
Speaker 1: That's the reason why I'm vehemently opposed to like this
Speaker 1: kind of like pause and kind of things, and say, well,
Speaker 1: what if we can get everyone to pause, Like, well,
Speaker 1: what's your plan to get everyone to pause? Including China?
Speaker 1: And everyone? Look like, is this that all realistic? So
Speaker 1: my strategy tends to be, how do we keep like
Speaker 1: you want the good guys to win? E g. The
Speaker 1: things that are pro like humanist human you know, like
Speaker 1: you know, the Pope's awesome and cyclical, like you know,
Speaker 1: kind of like like keeping human beings at the center,
Speaker 1: keeping a notion of what is a positive to society.
Speaker 1: By the way positive societies over years. That doesn't mean
Speaker 1: that there won't be massive transformation, things that will be
Speaker 1: painful and difficult to get through, but like having a
Speaker 1: this is how society is better with this as where
Speaker 1: we're going.
Speaker 2: So when people hear that, I mean the good guys,
Speaker 2: I mean tech is getting slaughtered in the context of
Speaker 2: public opinion. People just don't trust anybody. The whole issue
Speaker 2: of truth and trust, obviously it has been accelerated social media,
Speaker 2: but now obviously with AI deep fake this deep fake
Speaker 2: that voice and we can get to even your own
Speaker 2: interesting avatar in that space. But this notion of trust
Speaker 2: and you know, someone may be listening to go okay, yeah,
Speaker 2: read this is easy for you to say, you know,
Speaker 2: sitting on the Microsoft board and obviously investing in all
Speaker 2: these places. You got two of your own AI companies,
Speaker 2: you know, come on, man, So.
Speaker 1: I am not of the view that like frequently what
Speaker 1: it is is like just trust us, right, like like
Speaker 1: like you know, it's like, look, we're in a very
Speaker 1: low trust environment overall, right, low trust of almost every institution,
Speaker 1: even mixed trust of historically great trust institution doctors and
Speaker 1: so on. So it's like, so there's an overall thing,
Speaker 1: so they just trust us. But then you have to
Speaker 1: say is like, okay, well you have to prove my
Speaker 1: trust before you do anything. Well, that doesn't really work,
Speaker 1: and it doesn't work in any of these places, right,
Speaker 1: So the notion is to say, well, do the things
Speaker 1: that ultimately are building trust over time, and then when
Speaker 1: people really investigate, like, ah, you're doing something that's fairly trustworthy. So,
Speaker 1: like we're talking about Dario, one of the things that
Speaker 1: Dario did is it said, Okay, we're going to build
Speaker 1: AI with a kind of a constitution. I actually don't
Speaker 1: think they should have used that word, but like you know,
Speaker 1: it could be a it could be a set of
Speaker 1: principles like you know whatever, you know.
Speaker 2: What if fends you have a constitution, sir.
Speaker 1: Well, I, for one, I am a huge believer in
Speaker 1: the American constitution, right it is our I'm.
Speaker 2: A little old school like you. I appreciate that we'll
Speaker 2: get to that a little bit later.
Speaker 1: Look that that is our religion is the constitution, right,
Speaker 1: so like we stay with that. And it's a little
Speaker 1: bit of saying, oh, implying that this is a constitution
Speaker 1: is not really like a constitution is a sacred document
Speaker 1: for me, so and so and so. The but here's
Speaker 1: here's how we're gonna build trust is here is the
Speaker 1: document that is central to all of our training of
Speaker 1: our eyes. So you can read it, you can come
Speaker 1: and on to us, you can suggest changes, you can
Speaker 1: understand where we're going, what we're trying to do. That's
Speaker 1: the kind of thing that I think you know needs
Speaker 1: to be there. Transparency. Yes, that's that's the beginning, and.
Speaker 2: That's along the lines. I mean, you and I've had
Speaker 2: these conversations over the years. In California's regular tour, a
Speaker 2: framework SP fifty three which we advanced was around this
Speaker 2: issue of transparency exactly for frontier models, these large language models.
Speaker 1: What about this?
Speaker 2: You know, I think from your perspective, it'd be interesting
Speaker 2: to hear your perspective about some of those contours. I Mean,
Speaker 2: we talk about Dario as the you know, the good
Speaker 2: guy and is in for a lot of folks that's
Speaker 2: through purely political lens because of some of the issues
Speaker 2: he had with p Hexic and the Department of War
Speaker 2: issues around Mythos, which I'm interested in your take on
Speaker 2: Mythos and the fact that he pulled that back what
Speaker 2: that means or what that suggests. But it also has
Speaker 2: the origin story that played out very publicly with Sam Altman,
Speaker 2: with Elon Musk. All those origin stories of which you
Speaker 2: had a front seat, sir, front.
Speaker 1: Seat, front seat, and participation on someone.
Speaker 2: An actual board seat is relasd to open AI exactly.
Speaker 1: So look, most of the people creating AI, you know,
Speaker 1: are like kind of unique human beings. Yes, so you know,
Speaker 1: and part of it because by the way, geniuses frequently
Speaker 1: are right and so and usually you know, with folks
Speaker 1: who like it's pretty easy to attack anybody. I mean,
Speaker 1: you've had the experience. I've had the experience of it's
Speaker 1: like an attack by a negative person who is willing
Speaker 1: to invent shit or build on what is a small
Speaker 1: thing to make it into a huge thing. Is one
Speaker 1: of the things that kind of flows its Now I
Speaker 1: have the you know, the fortune of knowing all of
Speaker 1: the head like every head of all these labs and
Speaker 1: so I have a pretty good sense of what their
Speaker 1: actual moral characters are and what the things are. And
Speaker 1: many of them are good human beings. That doesn't mean
Speaker 1: they're perfect, right, but they're good.
Speaker 2: But it's a nice I mean, I want to pause
Speaker 2: on that because I mean, objectively from your perspective, many
Speaker 2: are good human beings. Yes, because they've been I mean,
Speaker 2: these guys really have been vilified across the spectrum. Yes,
Speaker 2: and you know, and perhaps more so even today with
Speaker 2: the first trillion air being minted, et cetera, and all
Speaker 2: that issue which.
Speaker 1: I wanted on that I didn't say, all we're good
Speaker 1: human We'll get to specifically to that human being.
Speaker 2: But this notion that most are good human beings, but
Speaker 2: they're also trapped by incentives, right, I mean, we're all
Speaker 2: creatures of incentives. In this notion of the incentive, as
Speaker 2: you suggest to accelerate at peril. If it's not us,
Speaker 2: it will be someone else once you rather the American
Speaker 2: stack in the context of what Jensen talks about in Nvidia,
Speaker 2: this notion of the American stack with the American values
Speaker 2: to the extent possible. But what I mean those incentives
Speaker 2: aren't necessarily even good people for good behavior.
Speaker 1: Yeah, so in any incentive system, you will get some
Speaker 1: good effects on it and some bad effects. No incentive
Speaker 1: system is only good effects, right right. So so you know,
Speaker 1: for example, you have an incentive system to try to
Speaker 1: make more money, Well you try it, like it creates
Speaker 1: jobs and par activity, but you also do a whole
Speaker 1: bunch of other things. Like so it's a blend, right,
Speaker 1: and you get people, you know, uh, selling cigarettes and
Speaker 1: other kinds of things. So and so I think the
Speaker 1: incentive system. What you have to do is say, how
Speaker 1: do we tune the incentive system so that the major
Speaker 1: incentives mostly align with good outcomes. Now, part of the
Speaker 1: reason why is you already noted the England versus Poland
Speaker 1: and the industrial revolution. If we are the society that
Speaker 1: kind of has called it the primary pole position, and
Speaker 1: how AI does this next industrial revolution which I think
Speaker 1: is going to be bigger than the previous industrial revolution?
Speaker 1: And where this then we can sort out how the
Speaker 1: economics society works. Like if you say, well we have
Speaker 1: the massive economic benefit it careers to our society, and like,
Speaker 1: well it's only these seven companies, Well we're in a society.
Speaker 1: We can broaden that out. Something you say, well, any
Speaker 1: any you know company that has you know, profitability above
Speaker 1: per employee now has an extra tax that's used to
Speaker 1: pay for all the rest society. And if you own
Speaker 1: that industry, you can do that. If you don't own
Speaker 1: that industry, It's a little bit like when people you know, say, hey,
Speaker 1: I hate these social networks. And by the way, there's
Speaker 1: some real social network issues. Although I always, to my
Speaker 1: own defense, you're LinkedIn one.
Speaker 2: Of the few, if not the only, yes, social network
Speaker 2: that actually had no better I mean right, yeah, I
Speaker 2: mean kids are doing fine on LinkedIn.
Speaker 1: Yes they're on that, Yes, exactly, like LinkedIn works just fine.
Speaker 1: So it's doable. But if you said, hey, we ban
Speaker 1: social works, even ignoring a LinkedIn, questions like, what would
Speaker 1: you want it to be only Chinese social networks? No, no,
Speaker 1: you'd rather have the social networks here and have our
Speaker 1: ability to shape them. Now, of course we need to,
Speaker 1: there's the political melee around it and all the rest,
Speaker 1: but you want it to be a US property that
Speaker 1: you're shaping. And the same thing with AI, And that's
Speaker 1: part of the reason I'm an accelerationist. It's like one
Speaker 1: of the things I was saying a couple of years ago,
Speaker 1: is we want AI to be American intelligence. Right, So
Speaker 1: it's like like it matters, right, And and that doesn't
Speaker 1: mean at any cost. Nothing is at any cost, right,
Speaker 1: Like if you said, well, like it would it would
Speaker 1: destroy an entire generation of children. That's a horrific Like
Speaker 1: can we avoid that and still be acceleration at ansorus?
Speaker 1: I think yes, But it's like, Okay, what are the
Speaker 1: things we do in order to do that? Now? I
Speaker 1: do want to wrap back to one of the things before,
Speaker 1: because I think this is very important given you know,
Speaker 1: we've seen you know, uh, you know, American college students going,
Speaker 1: I've I hate AI, right booing, Ye have you given
Speaker 1: a did you do a commencement? You know, probably smart
Speaker 1: enough not to do it this year? It needs that, yes, well,
Speaker 1: because you're showing up to try to offer something to
Speaker 1: help them, right, Like the usual protest and commandment speech
Speaker 1: is sleeping you asleep? But what do you mean when
Speaker 1: do you make it? But it reinforces the anxiety?
Speaker 2: Yes, no, no, and I get it highly educated people
Speaker 2: that are played by the rule.
Speaker 1: Yes, and I feel I look, I understand, I feel
Speaker 1: the pain. Right. So, but the question is, and this
Speaker 1: is why I think it's so important is Look, it
Speaker 1: is completely legitimate for college graduates to be going, you know, hey,
Speaker 1: the older generations, the boomers, ceter you really fucked it
Speaker 1: over for us. We got all this shit going on
Speaker 1: and this is on your watch and you suck. I
Speaker 1: get it, and I think it's a legitimate gripe, right, Like,
Speaker 1: but in crisis, this is the thing I really want
Speaker 1: the kids to hear, you know, the college kids. Crisis
Speaker 1: is opportunity. And by the way, you can be the
Speaker 1: AI generation. You should be using it. You should be going, hey,
Speaker 1: company X, you need people to help you, like AI
Speaker 1: aify your company. I can be the person doing it.
Speaker 1: You shouldn't be trying n opt out. It's a disaster
Speaker 1: for you, right, And I'm saying it for them. Look,
Speaker 1: I don't have any steak in. Like the entire current
Speaker 1: graduating class could all say we refuse to use AI.
Speaker 1: It makes no difference to me, but it will be
Speaker 1: terrible for their lives. Right. And so it's like, look,
Speaker 1: embrace and figure out how to make it useful to
Speaker 1: you and then have that help amplify your career and
Speaker 1: life path.
Speaker 2: And you continue to make that point it's about amplification,
Speaker 2: it's about having a copilot. But this notion back to turbulence,
Speaker 2: this idea that the transition, So talk about the transition
Speaker 2: the context. Look, if Dario's over stating the short term,
Speaker 2: are we understating the long term or is it just
Speaker 2: you know, modest fits and starts, a scale, scope speed?
Speaker 1: Where are you and all that?
Speaker 2: How do you calibrate all that if you're policy maker
Speaker 2: sitting in this seat, how do you begin to anticipate
Speaker 2: where that stress, where that friction, where the real turbulence
Speaker 2: is going to come.
Speaker 1: Well, some of what I thought you guys did that
Speaker 1: was really smart with SB fifty three was get data,
Speaker 1: start monitoring, start asking questions, like because it's like, Okay,
Speaker 1: what's really happening here? Not Oh I watched her like
Speaker 1: like some journalist wrote a story about one case, you know,
Speaker 1: blah blah blah blah. Yeah, that's not the way to
Speaker 1: do it. That's that's like like the dumbling olk. Oh
Speaker 1: my god, we should restrict airplane travel because it's unsafe.
Speaker 1: It's like no, no, no, it's the drive to the airport
Speaker 1: that's unsafe. The plane is actually so much safer, right
Speaker 1: per mile per minute. Everything else is like no, the
Speaker 1: plane is much better. So it's like making policy decisions
Speaker 1: based on data, and we should be getting the actual data,
Speaker 1: not the hysteric kind of responses and start there is
Speaker 1: actually in fact with important. Now that being said, you know,
Speaker 1: as a rough template, we want to be thinking of,
Speaker 1: okay AI is this transformative tsunami that's coming and within
Speaker 1: a small number of years jobs there will be a
Speaker 1: large number of jobs that will be completely transformed. Some
Speaker 1: of those jobs will be they're just all done by AI.
Speaker 1: Some of them will now be clerical jobs. What kind
Speaker 1: of jobs?
Speaker 2: See, people have their theories of this, and of course anthropic,
Speaker 2: but it's out literally the pie chart, yes, of what
Speaker 2: kind of jobs are most likely to be impacted?
Speaker 1: What's your theory of that case? So those pie charts
Speaker 1: are usually limited in that they say, if the tasks
Speaker 1: of doing the jobs are only the ones today and
Speaker 1: that there aren't new tasks, this is what looks like
Speaker 1: there will be new tasks. Now that being said, For example,
Speaker 1: I think that there's a relatively small n number of
Speaker 1: years before a customer service person, a customer calling customer
Speaker 1: service says please put the A on. It's a lot
Speaker 1: more helpful, right, because you have a human being trying
Speaker 1: to follow a robotic script by looking at the screens
Speaker 1: or yeah, it's going to do that so much better,
Speaker 1: just like there's rules for human beings, but they're like
Speaker 1: looking at what's going on with the pattern of AIS
Speaker 1: and trying to reimagine that's not the bulk customer service jobs.
Speaker 1: So like that's one. I think there's a lot of
Speaker 1: like there's a whole classes of sales jobs that I
Speaker 1: think will be much more AI. And you begin to
Speaker 1: get to this weird sci fi story where the AI salesperson,
Speaker 1: the sales agent calls the company AI agent to listen
Speaker 1: to the AI sales agent, and there's a whole thing
Speaker 1: that kind of navigates through. It's a whole weird, weird
Speaker 1: universe that will happen. That will happen, Yeah, en years
Speaker 1: and not three, maybe ten, like not twenty, right, right,
Speaker 1: and so and so those will be like kind of
Speaker 1: swaths of jobs. But here's the thing, and it's that
Speaker 1: new task thing that was mentioning earlier, which is basically
Speaker 1: there will no longer be there were very few human
Speaker 1: jobs that are just humans by themselves. We will all
Speaker 1: have teams of agents that are working with us and
Speaker 1: doing But actually, in fact, what you can see from
Speaker 1: the pattern of already looking at it is you actually
Speaker 1: get to some pretty incredible increases in performance where the
Speaker 1: human brings in the things that the AI don't have.
Speaker 1: And look, one of the questions is will the ais
Speaker 1: not have those for a long time? Will they get
Speaker 1: them quickly? We don't know it's all coming right. My
Speaker 1: bet would be we're very adaptive like this whole like
Speaker 1: human beings will be replaced and we'll have our cognitive faculties.
Speaker 1: Goes all the way back to the printing press and writing.
Speaker 1: Like I actually think there's areas of where we make
Speaker 1: good judgment, Like people say, oh my god, look at
Speaker 1: look at cloud code, like there's no need for engineers anymore.
Speaker 1: We'll actually talk to a whole bunch of people who
Speaker 1: use cloud code. And I've used it myself intensively, and
Speaker 1: I've I've used codex and open ai, and I've used
Speaker 1: Microsoft Copilot. And by the way, some of it is
Speaker 1: just amazing, like amazing, Like if you had told me,
Speaker 1: like you would asked me even like say five eight
Speaker 1: years ago, would I be seeing this? I said, no, no, no, no,
Speaker 1: that's not like yet They're like, yes, here it is.
Speaker 1: That's amazing. On the other hand, it breaks on weird shit, right,
Speaker 1: And so part of the human thing is like orchestration.
Speaker 1: It's like, okay, like, for example, how how does coding
Speaker 1: work at open AI. Well, they have a big screen
Speaker 1: and they have multiple agents working, and they're like, oh,
Speaker 1: oh that one's stuck. We got to get that one unstuck, right,
Speaker 1: da okay this, and and it makes them hugely more productive.
Speaker 1: Now if you thought, well, it makes them huge alial productive.
Speaker 1: They're just doing all the work. We don't need anyone
Speaker 1: else doing all the work. It's like, look, there's infinite work.
Speaker 1: It's like, now maybe there will be say, for example,
Speaker 1: tech companies may more naturally be at you know, call
Speaker 1: it fifty percent of the current engineering crew. That doesn't
Speaker 1: mean that those engineers. It's like other engineering firms start
Speaker 1: more competitors, etcetera, etcetera. It's just the producttivity of how
Speaker 1: you operate. It's like the humans aren't replaced in all
Speaker 1: cases by AI. They're replaced by humans using AI, and
Speaker 1: so you want to be the humans using AI. And
Speaker 1: then this gets back to I think this is a
Speaker 1: central point, is like, well, what's the thing you should
Speaker 1: be thinking about? Is one is monitoring, and then the
Speaker 1: other one is how do we help AI be part
Speaker 1: of the solution. Because the thing that's driving it at
Speaker 1: scale and speed is AI. We need solutions that work
Speaker 1: on the same capability set. So, for example, okay, how
Speaker 1: do I help AI? How do I have AI helping
Speaker 1: people make job transitions? I want to be seeing that, right,
Speaker 1: So you're like, one of the things you could do
Speaker 1: right here at the mansion is you could say, hey, great,
Speaker 1: you know, California is the center of the AI revolution
Speaker 1: in the world. It's part of the reason why fifty
Speaker 1: three mattered. Hey, I want you guys to all come
Speaker 1: by and tell me about how AI could be useful
Speaker 1: in helping people all ranges. I want to hear about
Speaker 1: blue collar, white collar, multiple industries. How does that help
Speaker 1: those people you know, find the right work, do the
Speaker 1: right work, you know, have pride in their work. I
Speaker 1: just we're going to have a we're gonna have a
Speaker 1: day here in the mansion. You're going to come talk
Speaker 1: to us about it because I want to hear you
Speaker 1: thinking about it, right Because by the way, ultimately if
Speaker 1: you're not delivering on this, then I have to apply
Speaker 1: more pressure because, like, my responsibility is to the citizens
Speaker 1: of the state. And look, I'm very happy that we
Speaker 1: have the AI revolution and the economics flowing in from
Speaker 1: that and all the rest. But I care about all
Speaker 1: my citizens, So tell me what you can do for them. Yeah.
Speaker 2: Interesting, I mean there's notion of using AI the thing
Speaker 2: that has displaced that worker, to help find and place
Speaker 2: that worker in a new opportunity, a new career that's
Speaker 2: not quote unquote just training per se and the old
Speaker 2: sort of Black and White movie community college construct.
Speaker 1: Yes, but I want to if I could, I want to.
Speaker 1: I want to get back.
Speaker 2: There's so many areas on computing issues, limited limiting issues
Speaker 2: in that space, and what's going on with data centers,
Speaker 2: et cetera, and where we are in terms of the
Speaker 2: competitive landscape.
Speaker 1: But you, I was I didn't know this.
Speaker 2: You you were at Stanford back in the talk about
Speaker 2: Black and White movie. Wasn't that It wasn't just a
Speaker 2: couple of years ago, but way back when, and you
Speaker 2: were studying what was simplistic solutions?
Speaker 1: What the hell is this symbolic system? Yeah, what the
Speaker 1: hell is this? Well, it's artificial intelligence.
Speaker 2: So so I was part of you as an undergraduate
Speaker 2: and an AI degree. You had an AI degree, Yes,
Speaker 2: when no one had ever heard of this nonsense, Well
Speaker 2: not no one, when most of folks ever.
Speaker 1: Heard of it.
Speaker 2: Yes, even though we started realizing we all had it
Speaker 2: and we've all been using it for decades. But there's
Speaker 2: notion of jen ai the thing that we kind of conflained.
Speaker 1: That was what was new.
Speaker 2: Yes, and so you so it was it just a
Speaker 2: natural inkland? I mean, did you see the future then?
Speaker 2: I mean, was it just a major that started to
Speaker 2: present itself? No one else was in the class, and
Speaker 2: you figure.
Speaker 1: It out, get in, get an a in this one.
Speaker 1: The No, it was so what people assume people in
Speaker 1: my kind of role, and many many people in my
Speaker 1: kind of role are fascinated by technology. I'm not. I'm
Speaker 1: fascinated by human beings, okay, right, And so what I
Speaker 1: was interested in was human thought and human language, and
Speaker 1: so how do we understand ourselves, how do we insenter
Speaker 1: each other, how do we communicate? How do we get
Speaker 1: to a better understanding talking to each other? Etcetera, etcetera.
Speaker 1: And that was what most interested me, And so like
Speaker 1: I looked at you know, do I do anthropology or psychology?
Speaker 1: Like I was looking at the whole range. But I
Speaker 1: was like, what's the thing that in doing this I
Speaker 1: could actually make the most interesting things. I've always had
Speaker 1: a belief that we evolve ourselves through technology, like this
Speaker 1: is a you know, these glasses, these are a piece
Speaker 1: of technology, this podcast, and that's actually how we evolve
Speaker 1: our state as human beings and who we are and
Speaker 1: so on. Right, And so I was like, Okay, this
Speaker 1: AI thing, that's interesting, right, so I'll go do that,
Speaker 1: and I did it some Olcays is a multidisciplinary major,
Speaker 1: so it included psychology, included linguistics, included philosophy, so you know,
Speaker 1: did all of that as a part of it. And
Speaker 1: he went to Oxford and got it. Philosophies, yes, because
Speaker 1: well what I concluded at Stanford was none of us
Speaker 1: understood what thinking I'm speaking was, right, So here we
Speaker 1: are trying to build AI and we have no sense
Speaker 1: of what that is. Maybe philosophers did. Went to Oxford
Speaker 1: included philosophers didn't.
Speaker 2: Either, And so give me, I mean, this is what
Speaker 2: year where you're studying this stuff?
Speaker 1: Roughly nineteen eighty five, to nineteen ninety three ninety three
Speaker 1: in that both Oxford and the and so AI as
Speaker 1: we know it today.
Speaker 2: In the context of the vernacular of this sort of
Speaker 2: notion of gen ai et cetera, I mean, the origin story,
Speaker 2: they tend to lazily go back. It's sort of like
Speaker 2: the beginning of biotech maybe seventy nine with genen tech
Speaker 2: or something. There's a lazy punitrard that. But is that
Speaker 2: punitry accurate to suggest somehow in the mind's deep minds
Speaker 2: of Google that sort of the origin stories started to
Speaker 2: take shape early twenty thirteen fourteen, range, How would you
Speaker 2: describe what we are addressing or dealing with today in
Speaker 2: the context of that origin story? Where did it really
Speaker 2: begin at a scale that we're now more accustomed to.
Speaker 1: Well, so, by the way, like many technological revolutions, including
Speaker 1: modern ones, there have been multiple like oh, in five
Speaker 1: years we'll be having AI and invent new science, and
Speaker 1: that goes all the way back to the eighties, goes
Speaker 1: back to the eightiesies. Yeah, so here we are. We're
Speaker 1: there because what happens is some achievement happens and then
Speaker 1: people go aha, So like we beat human grand master
Speaker 1: at chess. Yeah, that was the hard problem. And now
Speaker 1: it'll be inventing physics and you're like not so much
Speaker 1: and so like cycling through it. And that was actually
Speaker 1: part of my conclusion in Stanford was like, no, none
Speaker 1: of these technologies, none of these current technolical approaches will work.
Speaker 1: So what's the thing that got me back in AI
Speaker 1: was a three hour meeting with demsisabas Uh, the CEO
Speaker 1: and co founder of deep Mind. And what I realized
Speaker 1: that he had that he had like he is the
Speaker 1: I think the the he and his co founder is
Speaker 1: the original kickoff.
Speaker 2: Of the deep And it's not I mean again, it's
Speaker 2: not Microsoft, it's not Anthropical AI, it's not SpaceX as well.
Speaker 2: I mean it's that's the I mean, if you really
Speaker 2: want to start to understand in luck and understanding.
Speaker 1: And what Demis realized was we have scale compute, and
Speaker 1: with scale compute we can create scale intelligence. Now, his
Speaker 1: original idea has been less of the important thing, which
Speaker 1: is self play. So it had pong and go and
Speaker 1: it plays against each other. But the answer was we
Speaker 1: can apply a lot of compute to evolve a competent machine,
Speaker 1: a with cognitive capabilities and I was like, you're right.
Speaker 1: We now have scale compute and what's more, we have
Speaker 1: scale data and we have scale engagement, you know, through
Speaker 1: internet and mobile. The revolution, a revolution, a massive revolution
Speaker 1: is here now. Did I know when I walked out
Speaker 1: of that meeting, you know, and at you know, King's
Speaker 1: Cross that I was like, Oh, actually it won't be
Speaker 1: the self play. It will actually be these these things
Speaker 1: called transformers, these large language models that read the trillion
Speaker 1: and a half words on the Internet and use that
Speaker 1: as a learning basis to create something. No, I didn't
Speaker 1: know that well, I didn't know is this is now
Speaker 1: a revolution? And so I was like, okay, how do
Speaker 1: I help? And you know, for me, I'm not adverse
Speaker 1: to doing stuff commercially. Obviously I've done a whole bunch
Speaker 1: of stuff commercially. But for me, I look across the
Speaker 1: whole spectrum. I go, Okay, what's the stuff that I
Speaker 1: should do as a founder, as investor, What's the stuff
Speaker 1: that I should do as a content provider and author?
Speaker 1: What's the stuff that I should do talking to you know,
Speaker 1: people who care about society like you and others? And
Speaker 1: what to do? Like, how do I go from you know,
Speaker 1: humanity society, industry. And that's the order of which I
Speaker 1: care about them, right, Humanity first, society second industry third
Speaker 1: industry can be very useful for society and humanity. But
Speaker 1: you like part of the like when we were talking
Speaker 1: about that earlier steering and shaping, well, we want to
Speaker 1: steer and shape industry to go. It should be on
Speaker 1: average massively positive for society over time, right. And if
Speaker 1: that's not, the director in it needs to be fixed
Speaker 1: right now over time, not this year necessarily right, right,
Speaker 1: there's always costs of transformation and all the rest now
Speaker 1: and so I went, that's the revolution we're in. And
Speaker 1: so for me, I think that's twenty thirteen or twenty fourteen, right,
Speaker 1: And it's and that's why when like Sam called me
Speaker 1: and said, hey, I'm thinking of pulling this thing together
Speaker 1: with you know, for AI for humanity, will you help,
Speaker 1: the answer is yes. It was one of the things
Speaker 1: where I had just gotten my partners at Greylock really
Speaker 1: focused on crypto, and I was like, oh, I'm gonna
Speaker 1: stop doing this crypto thing because this AI thing is coming.
Speaker 1: And they're like, what AI thing. I'm like, Oh, it's coming.
Speaker 1: And and actually, you know, I think you know, I
Speaker 1: think my partner is at Greylock were the first venture
Speaker 1: partnership that saw GBT four because I got Sam's permission,
Speaker 1: I was on the board of open AI to say, hey,
Speaker 1: come in and demo this and and and show this
Speaker 1: because there was there was a six month period where
Speaker 1: GBD four was not public because we're like, oh is
Speaker 1: it safe enough and all the rest, and you know, they
Speaker 1: were doing it. I was like, okay, look, I think
Speaker 1: it's safe enough. Is it okay to show the partnership?
Speaker 1: And Sam's like, yeah, yeah, this this since you're serving
Speaker 1: on a five one C three board of open AI
Speaker 1: trying to do this, this is the least we could do. Yes,
Speaker 1: you could go show them you know what's coming.
Speaker 2: Goal there's or there's some interesting I I and I
Speaker 2: don't you know, I don't want to get in a gossip,
Speaker 2: but I think it's interesting because it's instructive to a
Speaker 2: lot of people, and it's also I think connects a
Speaker 2: lot of your own personal relationships and dots. So you
Speaker 2: you know, you were notoriously, as we were alluding to earlier,
Speaker 2: part of the Payfoul mafia, and those are the brand
Speaker 2: names today and Elon Musk obviously, Peter Thiele, David Sachs,
Speaker 2: less of a brand name, but increasingly trying to be
Speaker 2: one in terms of association with the Trump administration. Musk
Speaker 2: allegedly and Larry Page, co founder of Google, had a
Speaker 2: conversation that, as at least Musk's telling goes, Musk was
Speaker 2: concerned that Larry wasn't taking this jen Ai seriously enough
Speaker 2: in terms of its downside risks, and decided to go
Speaker 2: off on his own, made the same contacts you made
Speaker 2: with Sam Altman and others, uh, and went down this
Speaker 2: path of a five oh one c three and tried
Speaker 2: to birth open ai.
Speaker 1: Is that reasonably accurate? That is reasonably accurate. I think
Speaker 1: it was a conversation. I think it was. You know,
Speaker 1: Larry was kind of saying, was you know, you know
Speaker 1: it's probably too simplistic, but you know, kind of articularly
Speaker 1: a transhumanist perspective to Elon that you know naturally freaks
Speaker 1: someone out because the rational response to that is that
Speaker 1: it's almost strange, right and so and so it got
Speaker 1: very concerned about it. Now, you know, in Elon's case
Speaker 1: in particular, it's the you know, Elon has the definition
Speaker 1: of a Messiah complex. So it's like, no, no, I have
Speaker 1: to be the one building AI, not anyone else. So yeah,
Speaker 1: there's the there's a little bit of the I'm worried
Speaker 1: about it generally, but it's also the I'm worried it's
Speaker 1: you not me. Uh.
Speaker 2: I think that's sort of proven itself a little bit,
Speaker 2: this turn of notion of going back. Even when you
Speaker 2: said the glasses, which is interesting technology I can see
Speaker 2: better if you've been aiding and a better and as
Speaker 2: a human that technology it's not just you know ones
Speaker 2: and zeros, yes, though you know now the now they're
Speaker 2: becoming one zero asth meta uh and others I think,
Speaker 2: and now Apple's coming out with their own version. But
Speaker 2: what this this notion of technology trends? I mean you
Speaker 2: reminded when what what what allegedly Larry said to Elon
Speaker 2: that freaked Elon out is what guys like Peter Teal
Speaker 2: couldn't even answer. You know, I think it was a
Speaker 2: seventeen second pause in an interview about you know, human
Speaker 2: beings and technology. But when you yeah, you sort of
Speaker 2: invited that in with the glasses, I mean, what what
Speaker 2: is all that?
Speaker 1: I mean for folks that may not be.
Speaker 2: Familiar with some of this, but maybe familiar with the
Speaker 2: anxiety that some of these conversations have induced. More broadly,
Speaker 2: what is the suggestion is this? Are we just all
Speaker 2: in a simulation or something?
Speaker 1: Is that the point?
Speaker 2: There's that kind of there's a cast of few of
Speaker 2: those conversations of them. Yes, It's like it's like like, actually,
Speaker 2: I was sitting with two of my friends at the time.
Speaker 2: Elon was one of them. Yes, right, I won't like
Speaker 2: and they're like, oh, yeah, everyone smart I know is
Speaker 2: living in a simulation. And I was like, am I smart?
Speaker 2: And they're like yes.
Speaker 1: I'm like, well, then not everyone.
Speaker 2: And it wasn't I remember the origin that we had
Speaker 2: second life, we had some of these virtual realities. Maybe
Speaker 2: they were alluding to a version of playing around with that,
Speaker 2: but they mean quite literally, we're in a simulation.
Speaker 1: Yes, And so I think simulation is the kind of
Speaker 1: classic theory that gets people to like the kind of
Speaker 1: Christian theory of intelligent design about how we get created
Speaker 1: or the Firman s parad I was like, we have
Speaker 1: questions we don't know the answers to therefore, right simulation
Speaker 1: and you're like, no, no, we have questions we don't
Speaker 1: answers to stop, like, we will try to figure out
Speaker 1: the answers of those questions. Like the simulation theory stuff
Speaker 1: is like, sure, there's unknowns, like, for example, the classic
Speaker 1: one that you usually used to argue with this is
Speaker 1: we don't have signals that there's other intelligent universe in life,
Speaker 1: in the universe and so you know, like with radio
Speaker 1: waves and statistics and all the rest, we should have that. Well, okay,
Speaker 1: that's an interesting puzzle. That's an interesting question. Why do
Speaker 1: we not have that? And but like and therefore we're
Speaker 1: in a simulation is like, that's a lot of cognitive
Speaker 1: theoretical infrastructure to explain this in a similar like like
Speaker 1: the hey, we have an unknown about the complexity about
Speaker 1: how human brains evolved and what the intermediate steps looked like, Well,
Speaker 1: therefore there must be a creator. Well there's a lot
Speaker 1: of it's an unknown and by the way, therefore them
Speaker 1: must be a creator. And therefore, by the way, the
Speaker 1: creator must be my religion, not any of the other twenties.
Speaker 1: Like it's like what like it's like, no, no pause
Speaker 1: on the mystery, right, and then go, okay, we have
Speaker 1: an unknown answer, So there's a whole bunch of craziness.
Speaker 1: But I think coming back to the first part of
Speaker 1: your question, I think is very important because I think this.
Speaker 1: I've been giving some speeches in Italy, like I gave
Speaker 1: one a Bologna and Perusia because I wanted Silicon Valley
Speaker 1: to remember some of the important humanist nature of the Renaissance,
Speaker 1: which is, what is it to really be a humanist
Speaker 1: when you're thinking about this technology? And it's not just
Speaker 1: self declaration I am humanist? Like no, that that that's nice,
Speaker 1: it's better than I'm not right, But it's like, well,
Speaker 1: what is it to be humanist to say, Look, I
Speaker 1: have a theory about why the work I'm doing will
Speaker 1: cause a much better result for call it at least
Speaker 1: eighty percent of humanity. Then the next thing is, and
Speaker 1: I'm transparent about it, I'm talking about it. I'm giving
Speaker 1: you a chance to critique me, dialogue with me, et cetera,
Speaker 1: et cetera. And then this is a super important thing
Speaker 1: is I'm not like a narcissist about it. I don't
Speaker 1: come to my theory of humanity because I go, well,
Speaker 1: this's good for me, right, or or I'm the most
Speaker 1: genius person in the world. Everyone else's theory of humanity
Speaker 1: is bad. Mine is the good one. But you know,
Speaker 1: engage in dialogue, get critique, understand kind of what's going
Speaker 1: on for this. That's what being a humanist for technology
Speaker 1: is right, and we have some right great. Doesn't mean
Speaker 1: that they don't make mistakes Dario sam et cetera. But
Speaker 1: they're they're actually, in fact, they are committed. And you
Speaker 1: can tell they're committed because they do things that are
Speaker 1: not in their own economic self interest and they invest
Speaker 1: in it in order to try to make it work.
Speaker 1: Doesn't mean they're perfect, doesn't. I mean it's not worth
Speaker 1: speaking up and say, hey, do X do also more
Speaker 1: of X or less of why? Perfectly good thing to do.
Speaker 1: It's part of the reason why we have the dialogue
Speaker 1: about it, to say, hey, the way that we try
Speaker 1: to make decisions about because because your answers, these technologies
Speaker 1: will build by small groups of people right and will
Speaker 1: have humanity level impact. And you're like, okay, you can't
Speaker 1: then say hey, we're gonna have a un global voting day.
Speaker 1: That's not the way it's gonna work. So the dialogue
Speaker 1: and bringing up the concerns about what it is is
Speaker 1: that iteration is the way that we get to being
Speaker 1: more broadly humanist.
Speaker 2: What are the great anxieties? And you triggered it this
Speaker 2: notion that it's a handful of people. Yeah, and you know,
Speaker 2: we talked about the American version and least having a
Speaker 2: chance at regulating something within our quote unquote jurisdiction. But
Speaker 2: regulatory capture is real. Yeah, just massive obscene off the charts.
Speaker 2: Wealth comes with massive obscene influence to write the rules
Speaker 2: of regulations to and the incumbency protection racket, So lock
Speaker 2: everything out and lock everybody out to buy politicians. Yes,
Speaker 2: I mean, so how does that play in? I mean,
Speaker 2: that certainly plays it. That is playing into people's anxiety
Speaker 2: in a profound and outsized way.
Speaker 1: How do we address both? And so when you have
Speaker 1: a kind of a tsunami like this, and this is
Speaker 1: to some degree talking to you, talking to the Dems
Speaker 1: on this, who tend to be the oh fight all
Speaker 1: the wealthy power, and you're like, you need capital on
Speaker 1: your side too, right, politically right, So have that as
Speaker 1: a good theory of the game. So the issue is say,
Speaker 1: and like for example, and I'll come back to AI,
Speaker 1: but this is like the mistake the dems made with crypto,
Speaker 1: which is like, there's a huge amount crypto wealth. If
Speaker 1: we just go attack it and go, hey, we're just
Speaker 1: going to try to kill all of you. The go
Speaker 1: you're trying to kill us. Okay, we're going to vote
Speaker 1: the other way with not just our votes but our
Speaker 1: dollars and all the rest. And it's like, okay, that's
Speaker 1: really painful and causes a whole bunch of bad outcomes
Speaker 1: for society. So again you go, well, how do we
Speaker 1: shape it. It's like, look, we're not trying to like
Speaker 1: extinguish all of you. We're trying to make sure that
Speaker 1: crypto has the right positive function in society. And they say, well,
Speaker 1: I can't envision anything. It's like, well, I come call me.
Speaker 1: I can envision things. Right, there's payments, there's much cheaper
Speaker 1: banking systems, there's all kinds of things. Let's just shape
Speaker 1: it that direction. Yeah, I get it. You don't like
Speaker 1: because who does like terrorist ransom coin? Right, like like
Speaker 1: you know, like there's a bunch of bad shit we
Speaker 1: should do bad shit about that, Or the question of
Speaker 1: well it's this random speculation. It's like, well, look, we
Speaker 1: do allow betting in various ways, let's try to contain
Speaker 1: it and make sure it's not too bad. You know,
Speaker 1: same reason why we go. You know, alcohol has a
Speaker 1: bunch of bad outcomes, but it's better for society if
Speaker 1: we go. Sure, it's okay if when you get to
Speaker 1: age you drink, don't drive. But it's like that kind
Speaker 1: of stuff. You get to shape it right, because there's
Speaker 1: certain ways. Now you get to AI and you say,
Speaker 1: all right, an AI wealth generation, and it's like shit,
Speaker 1: this is creating a massive amount of economics that will
Speaker 1: have massive impact politically. And by the way, what shared
Speaker 1: across all this economics is a interest in not having
Speaker 1: the economics of the AI industry like trimmed, right. And
Speaker 1: by the way, some of that trimming is a terrible idea,
Speaker 1: which is let's just reduce our own American wealth. Some
Speaker 1: of it, like taxation for helping the rest of society,
Speaker 1: can be a good idea. Right. So it's and you know,
Speaker 1: getting it right is hard, but I think it's doable.
Speaker 1: And it's like, well, then you go to, well, who
Speaker 1: are the people who would be with me on, hey,
Speaker 1: we should tax AI in some good ways, robot tax
Speaker 1: whatever else, and I'll make it happen. What are the
Speaker 1: ways we do that? So we take off some of
Speaker 1: the AI wealth that fights on our side for helping society,
Speaker 1: and we fight against the other AI wealth that's like no, no, no,
Speaker 1: I should take my trillion dollars and be able to
Speaker 1: do whatever the hell I want. So easier said than done.
Speaker 2: I mean, this gets too And we talk about that turbulence,
Speaker 2: and we talk about the transition and using your vernacular,
Speaker 2: and there's a lot of conversations about all right, if
Speaker 2: this does have a more pronounced impact sooner than we anticipated,
Speaker 2: and we don't have the answer to what to do
Speaker 2: about that, and we don't have the AI solution to
Speaker 2: address the AI problem in terms of that transition, this
Speaker 2: notion of universic basic income versus universic basic capital, this
Speaker 2: notion of equity, this notion of ownership broadly shared so
Speaker 2: that we can address some of that anxiety. We all
Speaker 2: have a mistake in the game. You tend to be
Speaker 2: on the UBC yes side of this equation. But the
Speaker 2: question I have for you is not where you are
Speaker 2: on that simple question the binary, at least in that context,
Speaker 2: which is hardly the binary. But the question I posed
Speaker 2: is how the hell you do it.
Speaker 1: Who's going to do it?
Speaker 2: You think Sam's gonna he says two and a half percent.
Speaker 2: You know what, they're about to go public. We've we've
Speaker 2: called fort in California. Why doesn't he do it here
Speaker 2: in California. Let's well, happily take two and a half
Speaker 2: percent a year in this his home state that helped
Speaker 2: birth this damn industry. I think he's going to pick
Speaker 2: up the phone after hearing this.
Speaker 1: Uh he might. I'm like, Sam cares about the stuff.
Speaker 2: To his credit, he put out exactly and to his credit,
Speaker 2: yes he put that out.
Speaker 1: Yes, he put that out. He's been running universal basic
Speaker 1: income experiments, funding it himself in Oakland. Like like like
Speaker 1: he's here's the moment. Yeah, so this is the moment.
Speaker 2: Yeah, all these I pos coming, Dario, here's the moment.
Speaker 1: Yes. No, So like I think he do a great
Speaker 1: called ass right now. I actually believe of all of
Speaker 1: the open Ai folks and all of the Tropic folks,
Speaker 1: they're very philanthropically minded.
Speaker 2: So I think like the foundation, I mean, objectively, you
Speaker 2: can you can dismiss these I get the populist these guys,
Speaker 2: but they did put a foundation with the largest in
Speaker 2: the world yes, exactly. That they set up exists, yes,
Speaker 2: and has tens a bit over one hundred billion dollars.
Speaker 1: Today, Yes, exactly, and so and what I think is unlike,
Speaker 1: for example, take the Open AI Foundation. I don't think
Speaker 1: they're going to be sitting on their hands, right. And
Speaker 1: I actually think one of the things that you know
Speaker 1: you should do, and I think California should do, you know,
Speaker 1: uh it should be, is hey, you guys, uh, you know,
Speaker 1: we're only possible because of California, right, Like we provided
Speaker 1: the platform by which you guys could do this, could
Speaker 1: you guys, you know, disproportionately focused on helping our state
Speaker 1: and doing stuff we'd love to talk?
Speaker 2: You supposed to take your capital gaze to Texas, Yes, Texas, Florida,
Speaker 2: et cetera.
Speaker 1: It's like, yeah, like you couldn't have made this without us, correct,
Speaker 1: so in fact, so please contribute back, right or contribute
Speaker 1: back without the police. Yes, we're grateful for the job
Speaker 1: creation of the innovation. We're grateful for all the energy
Speaker 1: and daring.
Speaker 2: We're very very proud of your success and and please
Speaker 2: yes and time, yes, yes, right, because like for example,
Speaker 2: you know, space had forward impossible without this state, yea
Speaker 2: Tesla exists without the regulations.
Speaker 1: Impossible period without this state. Thank you, right, So it's like.
Speaker 2: You're welcome, Elan, and thank you for your innovation and
Speaker 2: daring as well.
Speaker 1: Yes, extremely importantly, I'm pretty sure you're gonna ask me
Speaker 1: a question where I'm about to dump on you lot,
Speaker 1: but for a good reason. But this is amazing for
Speaker 1: me to have to ask. Yes. But why isn't I mean,
Speaker 1: so let's you open that door. Why doesn't he feel
Speaker 1: this way? I mean, honestly, well, because me, what what? What?
Speaker 1: What is it?
Speaker 2: You know? I remember there was a different guy though
Speaker 2: I was with someone the other day. I said, no,
Speaker 2: he was always this guy and I said, well, you
Speaker 2: didn't or that way in the fifteen interactions I had,
Speaker 2: you know him better than anybody.
Speaker 1: So the people are a dynamic. So the question is
Speaker 1: where do they go as they get more power, more
Speaker 1: sycophants around them, and so forth. And the answer is
Speaker 1: Elon became a narcissist to who he wasn't a narcissist.
Speaker 1: I think he was a small narcissist and now he's
Speaker 1: a big narcissist, right, and like he lies through his
Speaker 1: teeth constantly. I don't know if he if he tells
Speaker 1: him self stories about it, like and it basically like
Speaker 1: the like like the whole pitiful open AI lawsuit, it
Speaker 1: was pathetic and courts agreed. Yes, well, and it's pathetic
Speaker 1: written out large for everyone to see. Yeah, that too,
Speaker 1: right now, It's like it's a court of law with
Speaker 1: with truth in like documents, depositions, et cetera. It's just pathetic.
Speaker 1: It's like the no, no, no, Like I'm trying to
Speaker 1: do anything possible to argue that you guys are wrong
Speaker 1: and I was right, and it's like, no, they were
Speaker 1: right and you were wrong.
Speaker 2: But it's just I mean, so it just I mean,
Speaker 2: I guess, I mean, it's just a classic clinical definition
Speaker 2: of narcissism.
Speaker 1: Yeah. Well, and like, for example, he goes I like,
Speaker 1: for example, he helps found open ai as like we
Speaker 1: need to have AI for the benefit of humanity, not
Speaker 1: just Google, okay, and he goes, oh, should I should
Speaker 1: have my own? So he gets XAI started, and in
Speaker 1: a desperate bid for market share, he's like, oh, yeah,
Speaker 1: that's fine. If we create a whole bunch of like
Speaker 1: pornographic images, some of which your children, your journalists have
Speaker 1: been reporting on this et cetera. And that's because it's
Speaker 1: more important that I have this AI thing than this
Speaker 1: damage that we're doing to children and all the rest
Speaker 1: of stuff. It's like, it's crazy.
Speaker 2: So do I mean, by the way, just I mean
Speaker 2: accelerating and fast forward. I mean space space X is
Speaker 2: a pretty remarkable company on the basis of the facts
Speaker 2: and evidence starlink in particular from a sort of cash
Speaker 2: flow perspective, an ROI perspective.
Speaker 1: And a goodness for society.
Speaker 2: Yeah, and by the way, I've seen that firsthand in
Speaker 2: the middle of the Amazon, which actually really inspired and
Speaker 2: surprised me to be that, in fact universally awkwardly connected
Speaker 2: in the middle of the rainforest, even more so than
Speaker 2: frankly out here in the Silicon Valley. But I'm curious,
Speaker 2: just you know, with regardless SpaceX in the IPO, I mean,
Speaker 2: there's other component parts of that that are a little
Speaker 2: more dubious and questionable. There are folks out there, deeply
Speaker 2: more cynical than I am that just call it a
Speaker 2: dam Ponzi scheme period full stop.
Speaker 1: Where you are on then, for example, yes, look, so
Speaker 1: I'm a small investor, but I think it's nuts, right,
Speaker 1: It's I mean, it's like look, for example, you look
Speaker 1: at the they just look at the pspectus. And the
Speaker 1: biggest part of it is payments from Anthropic for these
Speaker 1: data centers that are horrific for the environment, are badly
Speaker 1: set up in their networking equipment. That nominally, he's trying
Speaker 1: to restart XAI for the third time by Cursor to
Speaker 1: go somewhere.
Speaker 2: By sixty billion dollars sanan Scho based company that five
Speaker 2: years ago didn't exist.
Speaker 1: Yes, and it's like okay, and I'm glad he's buying Cursor,
Speaker 1: you know, great, hopefully something will come of it.
Speaker 2: What are they vibe? What is vibe coding? Sorry to
Speaker 2: go down that rabbitries, but it's a vibe coding company.
Speaker 1: Well, it's one of the early revolutionis of how do
Speaker 1: you have AI accelerate your coding? And Vibe coding is
Speaker 1: a part of that. It's not the whole thing. It's like,
Speaker 1: you know, like basically, anyone who is coding who's not
Speaker 1: using AI right now or not. Everyone called it ninety
Speaker 1: plus percent. If you're coding and not using AI, you're
Speaker 1: making mistake, right, so and and it's only getting better,
Speaker 1: right and both Claude codex. Uh sorry, claud code open
Speaker 1: a codex. I think Microsoft Copilot. I think we'll have
Speaker 1: a good entry here are all, you know, I think
Speaker 1: the fundamental way has changed the entire world in terms
Speaker 1: of how we operate. So and dropics willing to buy
Speaker 1: the revenue, but like that is your primary revenue thing
Speaker 1: in the thing that you're going public on, like this
Speaker 1: is in the government. Yes, well, and then you're like, oh,
Speaker 1: the dj is saying they've got to drop the lawsuit
Speaker 1: because this is part of our national scurity defense, Like well,
Speaker 1: that's none of that's in their perspectives. And by the way,
Speaker 1: the entire XAI thing, Elon himself said it's a complete
Speaker 1: train wreck. We're rebuilding it. I was like, well, you know,
Speaker 1: if you had like honor integrity, you'd say, well, we'll
Speaker 1: hand back those government contracts because we just said our
Speaker 1: product was a complete train wreck. Right. It's like, you know,
Speaker 1: so just it's all corruption, I.
Speaker 2: Mean corruption, Yeah, I mean you just call it.
Speaker 1: Yeah, call what it is. Call it what it is. Yeah,
Speaker 1: we're living in the in the in the greatest kleptocracy
Speaker 1: of your.
Speaker 2: In my lifetimes, and it's I want to circle back
Speaker 2: on that stay tuned for those that are tuning in
Speaker 2: on that, because.
Speaker 1: That deserves some attention.
Speaker 2: But as we sort of bounce back and forth the
Speaker 2: anthropic data center point you made in this notion of compute,
Speaker 2: and you made the point the biggest limiting factor in
Speaker 2: terms of the acceleration is less. The chips is important
Speaker 2: and profound as they are, it's really about the compute.
Speaker 2: And so it gets to the question of data centers
Speaker 2: and all the anxiety and data centers which has actually
Speaker 2: been sort of a leading indicator of one of the
Speaker 2: reasons people have such animis towards AI because they connect
Speaker 2: the dots. And there's been a few studies DC Maryland
Speaker 2: that's sixty percent of the growth of those retail or
Speaker 2: rather residential utility bills have been attached to the issue
Speaker 2: of data or growth.
Speaker 1: So where are you and all that?
Speaker 2: I know you've said we blamed AI for everything. So
Speaker 2: the issue of utility costs which have been growing yep,
Speaker 2: separate from AI, certainly haven't been benefited.
Speaker 1: Yeah, they're not benefiting centers. Look, I think that the
Speaker 1: clear thing for you and other folks to do is say, look,
Speaker 1: we want to enable data centers that are very positive
Speaker 1: contributors to communities. So, for example, very easy one is
Speaker 1: to say, hey, if you're building a massive data center,
Speaker 1: you have to provision power at like one hundred and
Speaker 1: thirty percent, right, and that thirty percent is that's amongst
Speaker 1: the things that you're contributing back, right and so so.
Speaker 1: And by the way, who should benefit from that, Well,
Speaker 1: the local residents who should have a choice whether they
Speaker 1: want that or not. Their powerbells go down right as
Speaker 1: part of that.
Speaker 2: I mean the irony is the data centers are getting
Speaker 2: subsidies on their bills and we're socializing an increase on
Speaker 2: everybody else's.
Speaker 1: No, and so what it should be is that you
Speaker 1: should contribute. Look, we will help you because, by the way,
Speaker 1: knowing from the inside Microsoft board and other things they
Speaker 1: care about, here, you are walking conflict. Yeah I don't know,
Speaker 1: but that's a conflict, but information informed. Look what do
Speaker 1: these hyperscalers care about. They care about reliability, ability to
Speaker 1: construct the thing, ability to deploy it, ability to manage
Speaker 1: it the right way, et cetera. Look, if you said
Speaker 1: you have to have like your cost structural increase because
Speaker 1: you have to have a one hundred and thirty percent
Speaker 1: contribution for the power stuff. They would sign that deal
Speaker 1: in a heartbeat if you gave the like if you
Speaker 1: you said hey, and and by the way, they do more.
Speaker 1: It's like, well, what are you going to do for
Speaker 1: local community in terms of jobs? Right, we want we
Speaker 1: want to see something serious here. Look, it's a simple
Speaker 1: kind of like like simple set of asks.
Speaker 2: And in the absence of that, they'll take what you're
Speaker 2: giving because it's of course tasting for these things.
Speaker 1: I think it's twenty five percent of all their base load.
Speaker 2: Now, yes, it's data centers, which is off the charts insane.
Speaker 1: Yeah, and so you should it should be an ask
Speaker 1: for we will help you do this stuff. These are
Speaker 1: the things you need to do. And by the way,
Speaker 1: if someone else give you a better deal, fine, go
Speaker 1: with this someone else.
Speaker 2: This notion of jobs though, I mean, the construction jobs
Speaker 2: are legit and we should celebrate that. And these are
Speaker 2: good high paying jobs and and and careers, and people
Speaker 2: bounce around even they're temporary and get the benefit of that.
Speaker 2: But there are not a lot of jobs on the
Speaker 2: permanent side of this.
Speaker 1: No, although, for example, when you're going to hyperscalers, let's
Speaker 1: take Microsoft. The thing I would ask if I was
Speaker 1: a local areas, I'd say, I want you to open
Speaker 1: up a Microsoft office here. Now you're talking, just open
Speaker 1: up a Microsoft office.
Speaker 2: We need to be better Dan negotiators, yes, whereas I
Speaker 2: mean we just yeah, okay, I mean I'm having a
Speaker 2: hard time arguing with these these deeper points. What about
Speaker 2: this notion of these things being what is it's the
Speaker 2: g don't last very long, right, just a few years?
Speaker 1: Well, because the next ones are so much better.
Speaker 2: Right, So is this I mean back to froth even
Speaker 2: KKR big promoter in the future, I mean saying a
Speaker 2: little froth here, Sam said, bubble Mark, you know all
Speaker 2: these guys, I mean, you know, the.
Speaker 1: Zucker Birds of the world.
Speaker 2: You're like, ah, yeah, I mean so this knows where
Speaker 2: are you in the bubble on the sort of frothy bubble,
Speaker 2: so of this and the capex in this.
Speaker 1: Space and that the ROI is you.
Speaker 2: Know or is it? It's electricity to you?
Speaker 1: So I think it's ultimately electricity where we're getting intelligence
Speaker 1: at the cost and scale of electricity, and that's just great.
Speaker 1: And so for example, it's one of the reasons why
Speaker 1: a lot of the challenges are just wrong. Like they said,
Speaker 1: well you know, uh, you know, climate impact, and you're like, well, actually,
Speaker 1: let's just make sure that AI is applying something to
Speaker 1: grid analysis and power running. And so then as you say, hey,
Speaker 1: if all of a sudden, all of the h facts
Speaker 1: and laundry machines and all the rest were intelligent devices
Speaker 1: that ran when it was cheap on the grid and
Speaker 1: all the rest and was doing power management net very
Speaker 1: positive benefit. And we've already seen Google do that with
Speaker 1: their own data centers and all the rest. Like, it's
Speaker 1: a whole bunch of stuff there, And I think the
Speaker 1: same thing in terms of ultimately that doesn't mean that
Speaker 1: there won't be some things that are Ponzi schemes and
Speaker 1: some things that are major economic losses. But a bubble
Speaker 1: is oh, this isn't sustainable. It all just kind of
Speaker 1: falls down and it has domino effects other things. The
Speaker 1: short answer is, like nthropics revenue is limited by its compute.
Speaker 1: It has more demand that it can provide right now,
Speaker 1: and so that like this isn't like oh, no one
Speaker 1: wants this. It's no, no, This intelligence at the scale
Speaker 1: and cost of electricity is massively useful, massively wanted. So
Speaker 1: doesn't mean you say well, maybe we built that data
Speaker 1: center for fifty billion and action ends up being worth
Speaker 1: forty billion, and we've got some operating losses, but by
Speaker 1: the way in operating it, it operates profitably and all
Speaker 1: the rest, and we just have to take a charge down.
Speaker 1: That's not a bubble, that's volatility in a market.
Speaker 2: Yeah, what do you make of a market which is
Speaker 2: so fierce in the competition this notion, that of super intelligence,
Speaker 2: this race to this holy grail and then a nanosecond
Speaker 2: I shut every competitor down.
Speaker 1: I quite literally talk about the Messiah complex. I own
Speaker 1: the world in my palm of my hand, maybe literally.
Speaker 2: That a company like Google and Gemini are uniquely positioned
Speaker 2: against an anthropic, against open ai and others just on
Speaker 2: the token question that they can sort of do what
Speaker 2: companies Amazon infamously many other companies do, and that's just
Speaker 2: gut their competition and price them out by lowering the
Speaker 2: cost below their actual cost and have tokens as lost
Speaker 2: leaders until they bleed out their competition.
Speaker 1: Well, they definitely are the cheapest price tokens of the
Speaker 1: major stuff today and it's not having that much of
Speaker 1: an impact. Interesting, right, so right, So it isn't that
Speaker 1: to say it's an it's a not an issue to
Speaker 1: pay attention to. But like for example, when people kind
Speaker 1: of check token costs across call it. You know, you
Speaker 1: know open Ai and Thropic and Google. Google's by far
Speaker 1: and away the cheapest, but the heat and usage is
Speaker 1: still an open eye and and and Anthropic and by
Speaker 1: the way, within the enterprise context Microsoft, right and so,
Speaker 1: so yes, that's a worry, but it's not really playing
Speaker 1: out that way now. Some of it is you know,
Speaker 1: for example, you know Google missed the curve on the
Speaker 1: code agent thing, right.
Speaker 2: Uh.
Speaker 1: Some of it's you know, kind of other things Google.
Speaker 1: And look, I'll just so it just doesn't look like
Speaker 1: I'm Microsoft, you know, dumping on Google. Like Google missed
Speaker 1: a bunch of different productization things, so did Microsoft. Right. So,
Speaker 1: so it's like, you know, there's a bunch of stuff there,
Speaker 1: and so did open Ai. I mean, is there investing
Speaker 1: in Sora? Yes? First, you know, and I what is it?
Speaker 1: What was it? Banana something? I like it? No banana? Google? Uh?
Speaker 2: Meanwhile Anthropic sort of plug it along?
Speaker 1: Yeah no, No, last year and this year you're of entropic, right, right?
Speaker 1: What happened with mythos what did it mean to you? It?
Speaker 2: Was it overhyped? Was it a Dario once again? Doomskall?
Speaker 1: Yeah? Here I was? I mean, is it you know?
Speaker 2: Was it just the friction of just anyone's sort of
Speaker 2: pushing back against Petex's and Trump and so they need
Speaker 2: to be banished? Is it Elon making the calls in
Speaker 2: this competition in sex saying we want these sont bitch
Speaker 2: shut down?
Speaker 1: What is what does mythos represent to you? So mythos
Speaker 1: is I think both real and overhyped. Right, it's a weird.
Speaker 1: I don't think I've ever said that sentence before. And
Speaker 1: it's real because they tuned they had a coating sharp lead,
Speaker 1: they tuned it to cyber. That was a genius and
Speaker 1: genius for both. And they did the responsible thing of saying, hey,
Speaker 1: let's try to allow a bunch of different places, which
Speaker 1: your critical infrastructure, which are both within the kind of
Speaker 1: public sphere and also private shere banking, et cetera. Let's
Speaker 1: make sure that all of that is hardened early before
Speaker 1: this stuff is and we're doing a very responsible role
Speaker 1: out for all that. And that's the real And then
Speaker 1: the overhyped is you know, like you know it would
Speaker 1: be the end of the you know, it would just
Speaker 1: be catastrophe if it came out. And you're like, yeah,
Speaker 1: I don't think it's quite that. I just think it's
Speaker 1: like more train wrecks, right, Like, there would be some
Speaker 1: real costs, but I don't think it would be the
Speaker 1: you know, end of civilization or anything else. Now, what
Speaker 1: I think that happened is because you know, in thropics
Speaker 1: trying to be responsible, uh we as far as I
Speaker 1: understand from the outside looking at the administration, there's a
Speaker 1: lot of different people jockeying for control and the AI sphere,
Speaker 1: there's there's there's people who are like, oh, we hate
Speaker 1: all tech, we hate big tech. Let's just close all
Speaker 1: this AI stuff down. That's like banning, et cetera. There's
Speaker 1: people who are like, oh, this is a commercial thing,
Speaker 1: I should own it. It's like best end, et cetera.
Speaker 1: There's you know, sacks going there should be no controls here.
Speaker 1: The only way that AI becomes American intelligence is there's
Speaker 1: zero control, you know. And so like there's a melee
Speaker 1: within the UH, within the White House to which tends
Speaker 1: to really only the factions that tend to ultimately win
Speaker 1: is you know, is there a big payoff for someone
Speaker 1: in the clyptocracy, right, so, I think. And they don't
Speaker 1: like anthropic because they also like to be that we
Speaker 1: are the big you know, swinging you know, things right
Speaker 1: in and we don't like that they're not rolling over
Speaker 1: and going, you know, yes, sir, you're my master. And
Speaker 1: they're like, they're principled. And by the way, we live
Speaker 1: in a country by which uh, you know kind of uh,
Speaker 1: individuals are citizens, organizations, companies must follow the law. But
Speaker 1: the law is not I do whatever the fuck you
Speaker 1: tell me to do, right, it's we follow the law, yes, right,
Speaker 1: both and yes yes, and so.
Speaker 2: The law, well, we'll get to the role of God later, yes, exactly.
Speaker 1: And so so their principle about that, and that's what
Speaker 1: they were trying to hold up to and what they
Speaker 1: were doing, and it was like, no, no, you must
Speaker 1: do what we tell you to do. It's like, no,
Speaker 1: not necessarily, right, you know. And so so it's like, ah,
Speaker 1: we have an option to show them whose boss, right, right,
Speaker 1: You're like, ah, I don't think that's that, by the way, Frankly,
Speaker 1: I think that's an American We should be celebrating achievements
Speaker 1: of Americans. Of things that we do and so worth
Speaker 1: and it's like to say, no, no, you must be
Speaker 1: following hair leader's commands. Whoever hair leader is, whether it's
Speaker 1: a you know, uh, you know, uh, left wing version,
Speaker 1: right wing version, whatever it is, Yes, it's like no, no, no,
Speaker 1: it's like we follow a rule of law together. There
Speaker 1: you go.
Speaker 2: So Sam took advantage of this from a competitive perspective
Speaker 2: at open AI and said, we're good.
Speaker 1: Yeah, what did you make of that? I wish you'd
Speaker 1: called me beforehand. Yes, it was a mistake. It didn't
Speaker 1: didn't go over well.
Speaker 2: Yeah, well so maybe Trump folks did.
Speaker 1: I haven't talked to Sam about this yet, partially because
Speaker 1: it all happened very quickly, and then I was like,
Speaker 1: and then it happened at that point showing up and
Speaker 1: saying I wouldn't have done this. It's like not very
Speaker 1: constructive and helpful, you know. I undoubtedly part of what
Speaker 1: Sam's trying to say. Look, if the if the good
Speaker 1: principled people like you know, anthropic and open ay bowed,
Speaker 1: then it's only left to the unprincipled people like XAI.
Speaker 1: I get it. It's a challenge issue. It's not straightforward, okay,
Speaker 1: but this would be a would have been a very
Speaker 1: good chance to say no, no, all of us principled
Speaker 1: companies should stand together and we should sort this of
Speaker 1: it all together, right, And so we're like, we're not
Speaker 1: going to jump in. We also think these principles. And
Speaker 1: what happened is he quickly deluded himself as like, oh,
Speaker 1: this is solvable technically. It's like, no, the Anthropic people
Speaker 1: are good technically too. There's from Open AI, and he
Speaker 1: was oh, shit, that doesn't work. Yeah. Yeah, that's the
Speaker 1: reason why Anthropic was going, We're not going to do
Speaker 1: it this way, right, And so it's like and you know,
Speaker 1: the part of what happens is the competition gets so
Speaker 1: ferocious that it's like the ah, I'm just communien. It's like, no, no,
Speaker 1: there are some places you put the competition aside, and
Speaker 1: when it's humanity and society, you put the competition aside.
Speaker 2: What they're not putting aside at Open AI is this
Speaker 2: notion of AI.
Speaker 1: Into the physical space.
Speaker 2: They're actually trying to lean into that partnerships with Johnny
Speaker 2: and others, and that gets even to what Elon's doing
Speaker 2: and Dexterity robots. The robots are coming physical AI we're
Speaker 2: seeing it manifest and you know, driverless cars, driverless planes,
Speaker 2: or flightless planes or pilotless planes shortly or at least
Speaker 2: flying cars in the vernacular of the Jetsons, which is interesting.
Speaker 1: They're doing a reboot of the Jetsons. Seems to make
Speaker 1: some sense in this world they were living. But what
Speaker 1: is that? I suspect it'll be a little bit more
Speaker 1: mixed than the Jetsons, just in the current cultural context.
Speaker 2: I suggest you're right, or believe you're right. So what
Speaker 2: is the physical AI? I mean, we could talk about
Speaker 2: robots as a separate thing, but what do you think
Speaker 2: what I mean?
Speaker 1: I don't know.
Speaker 2: What do you think where Sam's going with with open
Speaker 2: AI and the partners.
Speaker 1: With Johnny Ivy and others.
Speaker 2: In terms of designing some reedy revolutionary there's sort of
Speaker 2: an Apple esque, you know, Steve Jobs, Johnny sort of.
Speaker 2: This is, you know, imagining the future without the constraints
Speaker 2: of what you already know a race or mania, forget
Speaker 2: what you already know, design a project, a product for
Speaker 2: the for the AI agent. It's not constrained by the
Speaker 2: thinking of the past.
Speaker 1: So just like within a small number of years, none
Speaker 1: of us will be doing anything that's like knowledge or
Speaker 1: information work without having multiple AI agents that we are
Speaker 1: managing a workflow and so doing and that's small and
Speaker 1: five maybe right, Like you know, there's no longer such
Speaker 1: a thing as a human individual contributor. There's a human
Speaker 1: manager of agents maybe working on a team with other
Speaker 1: humans managing agents and all the rest and all the
Speaker 1: you know, and there's what's happening. That's an amazing transformation.
Speaker 1: There will be within a small number of years some
Speaker 1: amazing AI bringing into the work into a workplace. Will
Speaker 1: it be the kind of Johnny you know, reimagination of
Speaker 1: the phone, et cetera kind of thing. Will it be
Speaker 1: the rebirth of manufacturing in America through robotics and all
Speaker 1: the rest. Will it be autonomous vehicles which you know
Speaker 1: we'll call will bring enormous like health savings, you know, deaths,
Speaker 1: other kinds of things enormous. And by the way, there's
Speaker 1: obviously job transitions. Although by the way, like we're short
Speaker 1: a lot of truck drivers.
Speaker 2: Yeah, which is remarkably because it hasn't come yet.
Speaker 1: It's scale. It's coming, right, yes, yeah, But by the way,
Speaker 1: even if all truck manufacturers started manufacturing only autonomous trucks today,
Speaker 1: it's at least ten years before there is over half
Speaker 1: of the trucks in the road, or autonomous drugs. Right.
Speaker 1: So it's like, so there's even there's an adjustment, right,
Speaker 1: and so so all the stuff and we want it, right,
Speaker 1: I get. It's like people say, well, I don't want disruption,
Speaker 1: I want disruption of what I.
Speaker 2: Want robots, I want my humanoid Robut I do, yes, actually.
Speaker 1: You do, right. It doesn't mean you want every different
Speaker 1: version of them, right, but like, for example, like take
Speaker 1: autonomous vehicles, like like, we have over forty thousand deaths
Speaker 1: per year. That doesn't count injuries, maiming, et cetera, et cetera, Right,
Speaker 1: Like that's a cost in human lives. What's more, you go, well,
Speaker 1: you care about environment? Well, if you can actually in
Speaker 1: fact have the grid manage all the more efficiently massive
Speaker 1: environmental impact, right, so you want all that And it's
Speaker 1: like yes, And by the way, you say, well, what
Speaker 1: happens the truck driver jobs? Like, well, one, not a
Speaker 1: lot of people doing them. They hate the fucking jobs.
Speaker 1: And then two, yes, the central thing we should be
Speaker 1: doing and this age of AI revolution is how do
Speaker 1: we help figure out large swath of people, like get
Speaker 1: new kinds of jobs, whether it's entrepreneurial new starts, whether
Speaker 1: it's things that we're doing with society, whether it's like
Speaker 1: all of that stuff. We need to lean in heavily too,
Speaker 1: because the jobs will be changing. And most people say, legitimately,
Speaker 1: I like my job. I don't want it to change,
Speaker 1: and you're like, yeah, it happens, right, and we'll help, right.
Speaker 1: But that's that's I think how it so much of
Speaker 1: the focus.
Speaker 2: And you, as you're speaking, got me thinking about in
Speaker 2: your two AI companies that you've that you've founded, co
Speaker 2: founded yea, not all those others. I think everyone we've named,
Speaker 2: you've you've invested in U. We can get to that
Speaker 2: in a minute, but this so much of our time
Speaker 2: and energy. I was talking to Ezra Klein about this
Speaker 2: and back east a week or two ago, and he said,
Speaker 2: be good to mix in I'm paraphrasing him, and I
Speaker 2: want to talk out of school some of the good
Speaker 2: stuff along the lines of what you now are sprinkling
Speaker 2: in and you're you're investing very directly just in the
Speaker 2: area that we you know, you talked about twenty thirty
Speaker 2: years ago. People were focused on the issue of breakthroughs
Speaker 2: in medicine. Yes, breakthroughs. I mean I can live longer,
Speaker 2: healthier life. So I mean, where are we Let's talk.
Speaker 2: Let's now paint a more positive picture of what AI
Speaker 2: can do for good for society, not just for Elon.
Speaker 1: So he's worth six trillion.
Speaker 2: Dollars by the time my daughter graduates college.
Speaker 1: Exactly, So Manasi. So director Muker ge Ujol Singh and
Speaker 1: I have co founded and the idea is to create
Speaker 1: a drug discovery factory with AI. And it's the best
Speaker 1: shot I think we have seen ever in human history
Speaker 1: for doing a lot of cancer curing and a bunch
Speaker 1: of other things too. Because AI, it's like a search problem.
Speaker 1: Biology is more complicated than all of his other shit. Right,
Speaker 1: It's like he said, well, you know, there's there's more
Speaker 1: moves and go than there's atoms in the universe, And yeah,
Speaker 1: goes a child's simplicity tool relative biology. But now that
Speaker 1: we've got scale compute, it's like, Okay, what's the thing
Speaker 1: that is going wrong with leukemia? Can we something that
Speaker 1: allows us to monitor stuff early, allows us to figure
Speaker 1: out what might be going wrong and something that might
Speaker 1: be an easy therapeutic that might be as simple as
Speaker 1: an injection or a pill. Because you create a small molecule,
Speaker 1: an antibody, a protein, et cetera, that combined with the
Speaker 1: you know, kind of the thing that's going wrong and
Speaker 1: disable the bad thing and not have serious toxic side effects.
Speaker 1: That's a difficult charch problem. And right now what we
Speaker 1: have is we have And by the way, I think
Speaker 1: we'll continue to have genius clinician PhDs researchers doing stuff.
Speaker 1: I don't think it takes away their job, but we
Speaker 1: have them like it's like they're doing all the computation
Speaker 1: by hand and they're trying to be brilliant and figure
Speaker 1: out something. So like figuring this out takes them a
Speaker 1: decade to have a maybe I've got I started a
Speaker 1: decade and I got one maybe right, Well, I can
Speaker 1: now go all right, here are like I did today's compute,
Speaker 1: I generated one hundred maybees. Let's sort through which of
Speaker 1: these things might be worth looking at more, Which are
Speaker 1: I should earn it more, et cetera, And and and
Speaker 1: and how do we run that through the entire process
Speaker 1: by which we do, of course we want to do
Speaker 1: safety checking and so forth, and is our theory that
Speaker 1: it is is non toxic. Okay, we've we've included in
Speaker 1: our in our search and how the air works. But
Speaker 1: let's test it, right, and let's run through it. Like
Speaker 1: we should have that because that's part of what makes
Speaker 1: our medicine system. Like we have the envy of the
Speaker 1: world in the pre RFK junior FDA, you know, kind
Speaker 1: of like of of like gold plated medicine. Right, So
Speaker 1: when the reasons like if you're if if it's accepted here,
Speaker 1: it's accepted everywhere, right, and and let's let's let's keep
Speaker 1: our rigorous standards. Maybe we could figure out how to
Speaker 1: make it more efficient in various ways. I think that's
Speaker 1: a good thing to do. But and then deliver more medicines.
Speaker 1: And by the way, this is part of like the
Speaker 1: AI for humanity. Is if you said, like and you know,
Speaker 1: I don't know, like what I will categorically assert is
Speaker 1: AI has the best shot in human history of curing
Speaker 1: all cancer. Right, Like if we if we can deliver
Speaker 1: even our percentage of that, right, that's huge.
Speaker 2: Have we though, I mean, we've been saying this for
Speaker 2: a few years and there's exponent I mean, I feel
Speaker 2: like AI's exponent. I mean, I know, we're always just
Speaker 2: right around the corner here, we are just fusions.
Speaker 1: Just a few weeks.
Speaker 2: It's it's like, you know, it's like the Iranians are
Speaker 2: just you know, they're right there with fusion, fusion a
Speaker 2: couple of weeks away.
Speaker 1: Yeah, whatever, So where are we? So so at at
Speaker 1: Mansi we have we have some of the world's brightest
Speaker 1: computational chemists and some of the chemistry that the AI
Speaker 1: has been saying, how about this. They're like, that's really interesting,
Speaker 1: that might work. I've never seen that before, and that
Speaker 1: gets exciting. Yeah, and we're calling this to move thirty
Speaker 1: seven off alpha go of we're getting maybe move thirty
Speaker 1: seven chemistry. Right, So it's a very interesting like it's like,
Speaker 1: that's interesting, and how do.
Speaker 2: We socialize it? I mean, that was the point Ezrah
Speaker 2: was making to me. It's one thing again just in
Speaker 2: the hands of you, sir, God bless you, rather you
Speaker 2: than these others. But the point being, how does you
Speaker 2: know it's it's a compute for you know, the UC
Speaker 2: system and the CSUS and for forty million Americans in California,
Speaker 2: for three hundred and fifty million Americans for society written
Speaker 2: large so so it's not about modernization. It's not just
Speaker 2: about the commercialization in the context of an ROI that
Speaker 2: is in numeric and I know there's the sort of
Speaker 2: free enterprise case that that is. You know, we don't
Speaker 2: even get it at the larger philosophical point.
Speaker 1: Well, one of the things I think it's important for
Speaker 1: everyone to think about is we don't have the AI
Speaker 1: revolution except through the commercial sector. The capabilities of doing
Speaker 1: it in any other sector than the commercial sector do
Speaker 1: not exist. Because what you need is you need to
Speaker 1: be able to apply scale teams with scale resources, and
Speaker 1: like scale teams I mean thousands of people, tens of
Speaker 1: thousands of people, scale resources billions, two hundreds of billions
Speaker 1: in risk environment where a lot of this will fail
Speaker 1: as you're going, no other sector other than the commercial
Speaker 1: sector can do it. And that's because people go, well, sure,
Speaker 1: I'll build a billion dollars here that I might lose, right,
Speaker 1: because I'm not going to then be castigated for it
Speaker 1: or else because it's like, look it's my billion dollars,
Speaker 1: I'm trying to do it, etc. And that's part of
Speaker 1: what gets to the scale compute, scale data centers and
Speaker 1: all the rest now, So we when we think about
Speaker 1: this is we say, well, how do we shape it?
Speaker 1: Back to some of your earlier questions about like, well,
Speaker 1: what should you know, folks in your chair be doing?
Speaker 1: Like what we want in your conversation with ISRA, what
Speaker 1: we want in short order is at minimum three assistants
Speaker 1: given to every citizen, state, country, et cetera. One medical,
Speaker 1: one legal, one educational. And we want them to be
Speaker 1: very competent, and we want them to be essentially equivalently free,
Speaker 1: no matter if it's like a low cost does a matter,
Speaker 1: if it's like ad subsidized, a matter of like whatever,
Speaker 1: And it can be done without the state paying anything.
Speaker 1: Because if you go to say Google, Microsoft, Open AI
Speaker 1: and thropic and you say, look, if you're willing to
Speaker 1: build this on what you're doing, what would you want
Speaker 1: from us that would make it worth your while to
Speaker 1: do it? Because, by the way, the money you'd get
Speaker 1: from us, you don't care about relatively all the omeerning
Speaker 1: you're getting like just being paid. We don't have to
Speaker 1: spend public money on this. What do you want from us?
Speaker 1: They might say, well, you know, we got like we've
Speaker 1: got some permitting problems and these three data centers and say, well,
Speaker 1: as long as you clear with the local community jobs
Speaker 1: electricity sort will help you with your permitting problems if
Speaker 1: you do this right, like or oh well, look, we
Speaker 1: would love to be in the healthcare business, but like,
Speaker 1: the medical liability stuff is so intense. Could you give
Speaker 1: us a channel of safe harbor that could be by
Speaker 1: an independent review committee that you set up from the
Speaker 1: amazing hospital system in California and say, hey, give us
Speaker 1: a parameters of safe harbor to operate. And if you
Speaker 1: give that, then we'll be learning and we'll be building
Speaker 1: an industry off this great and then we will provide
Speaker 1: a medical assistant that's twenty four to seven available to
Speaker 1: every citizen of California. May I prefer the US, but
Speaker 1: we're just sitting here in californ Are you fine anything
Speaker 1: of that, because then, by the way, I have access
Speaker 1: to this kind of medical thing of twenty four to seven,
Speaker 1: I can call a doctor and get an answer for
Speaker 1: something I need. Very few people have that, right right,
Speaker 1: I would love it if every single person had it
Speaker 1: for their kids, for their partners, for their grandparents, for
Speaker 1: their family members, for their friends, et cetera. And by
Speaker 1: the way, these things can give really good medical advice.
Speaker 1: No medical advice is perfect, but they can give really
Speaker 1: good medical advice. So there's medical advice. And so it's
Speaker 1: like take them the kind of medical thing that only
Speaker 1: the ultra wealthy have access to and make it democratically
Speaker 1: available like every citizen. Legal assistant, right, Okay, currently, like
Speaker 1: like law law is expensive, right, and so currently like
Speaker 1: when a guy, when a person's kind of going into
Speaker 1: like signing a rental contract or an employment contractor anything else,
Speaker 1: most people can't afford lawyers, right, and I'm like, I
Speaker 1: trust that it probably works out. It's okay, et cetera. Right, Well,
Speaker 1: legal assistant, like it will help you with your rights,
Speaker 1: with what goes on with with how to interface this,
Speaker 1: Like that's why we have these laws to help protect you.
Speaker 1: Now we have an agent that can help navigate that
Speaker 1: and say we want to make sure that's provided to
Speaker 1: every citizen. Nice, right. And then education, same thing, and
Speaker 1: they say they're with the education.
Speaker 2: So we talk about democratization and and you know, I've
Speaker 2: had a strong theory that it's the same fight that
Speaker 2: if order to save democracy, which I've been particularly passionate
Speaker 2: about Prop fifty redistricting and pushing back against what's happening
Speaker 2: in Washington, DC, that we have to democratize the economy,
Speaker 2: that this notion again of just concentrated wealth. I'm joking
Speaker 2: about the six billion trillion dollars. I mean, I think
Speaker 2: it's realistic. Yeah, uh, you know, maybe you know my
Speaker 2: oldest daughter graduation, but certainly my youngest son. That we'll
Speaker 2: see that you already have ten percent of people on
Speaker 2: two thirds of wealth. You have a thirty year old's
Speaker 2: not doing better than his or her parents for the
Speaker 2: first time in American history. There's just growing anxiety between
Speaker 2: the imbalance between the rich and the poor. You've got
Speaker 2: twenty states, it's still seven dollars twenty five cent minimum wage,
Speaker 2: people working full times at ending up on welfare. I
Speaker 2: talk about corporate subsidies, so those corporations are getting benefit
Speaker 2: of that. You talked in terms you use the word
Speaker 2: coletocracy that a lot of people are using right now.
Speaker 2: And I talked about regulatory capture, and I talked about
Speaker 2: that concentration of wealth ultimately becomes concentration of political power,
Speaker 2: et cetera. What do you make of the world we're
Speaker 2: living in today? What do you make of the state
Speaker 2: of our union in relationship to all of this.
Speaker 1: Well, you know, I always when a new administration kind
Speaker 1: of comes in the power, even when I disagree intensely
Speaker 1: campaign and I'm quiet initially because I want them to
Speaker 1: be successful. We want I agree, right, it's like we
Speaker 1: want for society for citizens. And it's just like like
Speaker 1: the level of like call it Chernobyl squared catastrophe is
Speaker 1: just huge. It's like, no one has a theory that
Speaker 1: tariffs lead to better economics for your average citizen. Well, yeah,
Speaker 1: maybe he doesn't buy eggs and gasoline, you know, and
Speaker 1: so uh, you know, no one who understands how economics
Speaker 1: and economies work, yes, right, and so, and it just
Speaker 1: it just goes down the list, and then you get
Speaker 1: to the like like the absurdity of like maybe that
Speaker 1: like the iconic one is uh, you know, when Trump's
Speaker 1: being given the plane, even Laura or leaves the leaves
Speaker 1: the plane, leaves the boat. No, no, don't accept that.
Speaker 2: By the way, we are a huge investor in that plane.
Speaker 2: Not just the four a million dollars the Gutari government
Speaker 2: gave to Trump, but the nine hundred almost one billion
Speaker 2: dollars in the Pentagon budget.
Speaker 1: To retrofit.
Speaker 2: It was also appropriated, and that is a plane he
Speaker 2: will take with him.
Speaker 1: Yes, Yes, to the foundation he will take with him. Yes, yes, exactly.
Speaker 1: So like it just like it's just it's it's it's
Speaker 1: not just I think, frankly illegal, but it's gross and
Speaker 1: non American, right, I mean, it's not It's like, what
Speaker 1: we stand for is not the rip off everything that
Speaker 1: you can out of the public offers to benefit yourself.
Speaker 1: But that's happening. And these are your old friends. Some
Speaker 1: of these were my old friends.
Speaker 2: Yeah, I mean I knew some of these guys. When
Speaker 2: they seem to be completely indulgent in us, it's not
Speaker 2: just showing up. It's it's they're the beneficiaries all.
Speaker 1: This, Like it is. The thing I mentioned earlier is like,
Speaker 1: you know, Elon acknowledges that the XAI stoff is a
Speaker 1: complete train wreck catastrophe, and you're like, okay, well hand
Speaker 1: back your government contracts. That would be the honorable thing
Speaker 1: to do. And by the way, I'm you know, that's
Speaker 1: against my own you know, very small shareholder and small with.
Speaker 2: Large is not small to the rest of us. But
Speaker 2: I appreciate your point, yes, but why the hell are
Speaker 2: they doing. I mean, seriously, it's not just Elon, It's
Speaker 2: it's all these I mean, I've got knee pads right
Speaker 2: there for sale on my Patriots sight.
Speaker 1: For a damn reason, I had to go.
Speaker 2: I dropped your note. I love this, God bless you, man.
Speaker 2: I mean not everyone does. But it wasn't just for
Speaker 2: the CEOs and the brand names. But it's for you know,
Speaker 2: law firms talking about law. It's about the universities that
Speaker 2: we're selling out. It's about you know, all these you
Speaker 2: know folks that you used to count on selling their
Speaker 2: soul to get the deal.
Speaker 1: I don't know how these people look at themselves in
Speaker 1: the mirror. I mean it's like, look, it's what's the
Speaker 1: price of your honor, your integrity? Yours is crazy? Right like?
Speaker 1: And and look, if you're a citizen that has any
Speaker 1: you know, power, which basically is all of these people,
Speaker 1: including myself, state of your principles, some of the most.
Speaker 2: Powerful people in the world, and they're falling prey to
Speaker 2: this bullshit and.
Speaker 1: They're rationalizing it. Oh, the the Dems would be worse.
Speaker 1: And you're like, in what planet right like like, like
Speaker 1: is the sky purple where you live? I mean what like,
Speaker 1: what's what what's going on? It's probably red the the
Speaker 1: you know, and so uh, you know, it's kind of
Speaker 1: the the question of like, how do you defend this stuff?
Speaker 1: I mean, it's it's it's it's like, for example, the
Speaker 1: Iranian war will have massive impact on your average American citizen.
Speaker 1: You know, even as Homos opens, the ships haven't been
Speaker 1: haven't been going for you know, months. We're not like
Speaker 1: I appreciate the fact that the market's like, oh, really
Speaker 1: hopeful it's back and we're gonna lower lower the price
Speaker 1: of oil futures. This will work through.
Speaker 2: Yeah, I mean, whether there's some estimates or where you
Speaker 2: look at the total costs over trillion dollars, not the
Speaker 2: fifty billion. Yes, it's the direct cost the costs that
Speaker 2: have been born, yes, globally, yes, all the.
Speaker 1: Rest of us. And that's to every American citizen, right,
Speaker 1: And then the notion of oh well, because like the
Speaker 1: classic one is a all apologies excepted because I know
Speaker 1: this is not true of you, you know, and and
Speaker 1: actually many politicians, but they got all politicians are crop
Speaker 1: Trump's just more and more straightforward, right, and you're like.
Speaker 2: No, he's gonna he does it openly.
Speaker 1: Yes, at least seeson Man.
Speaker 2: That's he's the most transparent.
Speaker 1: Everyone was getting plained. He's just the first one who's
Speaker 1: acknowledging it's no, that's not the case. Not the case, right,
Speaker 1: not the case and so and by the way, you
Speaker 1: know someone who says, hey, uh, you like whatever politician acts, Oh,
Speaker 1: you misreported that. You probably should have said, hey, this
Speaker 1: weekend was a gift. Okay, small dollars. What do you
Speaker 1: think that corruption like like like like people think about it.
Speaker 1: Would you have been bought off by that nick? No,
Speaker 1: it was a mistake. Okay, these things can happen. Someone
Speaker 1: gets you a billion dollars in crypto, Yeah, yes, you're
Speaker 1: bought period. Yeah.
Speaker 2: Yeah, well we get to the UAE and then the
Speaker 2: fact they got high valued chips in yes, turn things
Speaker 2: that were denied in the previous administration exactly after we're
Speaker 2: a liberty financial deal.
Speaker 1: Yes, and all that, and.
Speaker 2: How well I can go down to litany a list,
Speaker 2: including just the usc fight and how it was paid,
Speaker 2: bonuses were paid in the Trump back crypto exactly. Can't
Speaker 2: make this stuff up. Also, you can't make up the
Speaker 2: fact that you know you must have teld me the truth.
Speaker 2: Did you feel an inclination at first? You're like, all right,
Speaker 2: I'm going to turn the page. A lot of my
Speaker 2: friends are going to the inaugural, you know, even if
Speaker 2: I'm not invited. You know, you know, we wish this
Speaker 2: guy success. Maybe he's different this time. Maybe he learned
Speaker 2: his lesson after all, you know, being on the receiving
Speaker 2: end of you know, so much stress during the Biden years.
Speaker 2: You must have gotten calls from friends of yours that
Speaker 2: did go is like, read, brother, I'm just doing this
Speaker 2: because it's the right thing to do for my company.
Speaker 2: I'm a fiduciary. What I mean, what how did you
Speaker 2: You chose not to do any of that? You're paying
Speaker 2: a price for that. I want to talk about that briefing.
Speaker 2: But you chose not to. Most folks chose too.
Speaker 1: Yeah. Look, I think the important thing is to say look,
Speaker 1: and people may not realize. It's like people can see
Speaker 1: that you were you were. What's the price that you're
Speaker 1: putting on your own honesty? And frankly, the only kind
Speaker 1: of price side to accept from my honesty is is
Speaker 1: saving millions of children. If there was something where I
Speaker 1: were where you say, okay, this would save millions of children.
Speaker 1: You're not going to be dishonest, Okay, I would take
Speaker 1: that trade.
Speaker 2: Contrast that to doge in usaid.
Speaker 1: Yes, yeah, five hundred thousand children, Yeah, probably dead because
Speaker 1: of that. Yeah right, great job. Yeah, ip, Yeah, I'm
Speaker 1: the defender of children. I see lots of corpses, right,
Speaker 1: and so the I think that the look the exhortation
Speaker 1: is look at yourself in the mirror and see it.
Speaker 1: And by the way, if the person goes I look
Speaker 1: at myself in the mirror, I'm just fine because I
Speaker 1: don't care. Then we have to speak about it. And
Speaker 1: that's part of the reason I wouldn't go. That's part
Speaker 1: of the reason I don't like. You know, I got
Speaker 1: these funny phone calls from people saying, hey, you know,
Speaker 1: for twenty million dollar is the right thing I can
Speaker 1: make your your your Trump problems go away.
Speaker 2: And you literally got to call it like, don't donate
Speaker 2: to this, so that the equivalent of a ballroom at
Speaker 2: the time, Yes, exactly, And it's like.
Speaker 1: I can knock your things and it's just sick. This
Speaker 1: is happening, Yes, happens, Yes, it's it's it is It's
Speaker 1: like like that is Unamerican right, I stand for what
Speaker 1: the country like aspires to be and should be. This
Speaker 1: is corrupt, this is fucked no possibility.
Speaker 2: And you and I share something sadly in common, which
Speaker 2: is just the elephant in the room. So it would
Speaker 2: be either of it. We can act like it didn't exist.
Speaker 2: We can edit it and say, but the Department of Justice.
Speaker 1: Yes, which is being instrumented as as a personal and
Speaker 1: corruption corrupted to a personal attack vehicle for President Trump.
Speaker 1: In your case, it's political opponents, right, which is no.
Speaker 1: Our whole point from George Washington's you know, seating of
Speaker 1: and and the and what this country stands for is
Speaker 1: we do not allow the instrum the state to try
Speaker 1: to corrupt the political process for people running for office.
Speaker 1: Oh no, no, I'm gonna I'm gonna stand up, because
Speaker 1: what's the basis of your Department of Justice investigation? Like,
Speaker 1: do you have any evidence? Do you have anything?
Speaker 2: No?
Speaker 1: No, we're just harass them. We'll just we're gonna look
Speaker 1: for something. And and we're not gonna look for something
Speaker 1: in red states, We're not gonna look for something. We're
Speaker 1: gonna look for something. And oh, who are the people
Speaker 1: who might be running, you know, for probably let's look
Speaker 1: for them, right that are running against us, right right.
Speaker 2: Or those that donate yes to the other team.
Speaker 1: Yeah, well, this one is crazy. So look, I have
Speaker 1: the honor of being called out three times by you know,
Speaker 1: Trump for and Trump administration, actually twice by Trump and
Speaker 1: once most recently, uh, kind of indirectly for like investigation.
Speaker 1: The first one was in TIFA, which which is like
Speaker 1: like an organization that they can't name a member of,
Speaker 1: an activity of, a leader of, and a tributal action,
Speaker 1: et cetera. But whatever that is. Maybe I've been financing it,
Speaker 1: Like what are you talking about, So.
Speaker 2: You've been doing how many years you've been financing Antifa?
Speaker 1: Yeah? Well, like and can you point it out to me?
Speaker 1: I would love to see it. Oh well I will like, like,
Speaker 1: as far as I know, I have never financed anything
Speaker 1: even remotely in the same universe. Yes, right, but whatever.
Speaker 1: So now, most recently, you know, some lawyers for Egene
Speaker 1: Carroll came to me and said, we have a woman
Speaker 1: who is the victim of sexual assault, who is being
Speaker 1: slandered and attacked and wants to go to court and
Speaker 1: would you like make a five one seri? Your donation.
Speaker 1: By the way, totally legal to finance legal cases. By
Speaker 1: the way, it would even been financial little legal cases
Speaker 1: to say, hey I get a percentage of the proceeds.
Speaker 1: That's actually like no, no, no, I think what's important here
Speaker 1: is that a that that a VIC, a survivor of
Speaker 1: sexual assault, can have her day in court with an
Speaker 1: American jury who makes the decision. Yes, I will I
Speaker 1: that that is an important thing as being Americans. I
Speaker 1: will I will finance that, right versus financing a ballroom, yes,
Speaker 1: versus finance and wall room. And I have no economics.
Speaker 1: It was literally like like like if economics come back
Speaker 1: from it, she is the survivor, she should get that, right,
Speaker 1: I like, I am just helping her have her you
Speaker 1: know kind of ability to speak her truth in court.
Speaker 1: Twelve jurors, probably at least three of them were Trump voters, right,
Speaker 1: you know, twice demonstrated is nope quick universal you know,
Speaker 1: like you like kind of you know, like the entire
Speaker 1: journey went yep, this is this is bad. And now
Speaker 1: because it's like wow, you know, so now the DOJ
Speaker 1: should be investigating this. They started with will and will
Speaker 1: will investigate Egene Carroll right, and you're like, so wait
Speaker 1: you're investigating the victor, the survivor and the victim of
Speaker 1: sexual assault, which uh, an American jury has found in
Speaker 1: favor of So you, as the DJ are investigating her
Speaker 1: and now no, we're investigating the thunder right, well for what? Right?
Speaker 1: Like you know, I was like, and by the way,
Speaker 1: would I do it again? Yes, like a h a
Speaker 1: woman who has been assaulted by a very powerful rich man,
Speaker 1: she should have her ability to speak her truth through
Speaker 1: a jury.
Speaker 2: And wait, so I love the clarity. I would even
Speaker 2: do it again. I mean, you've been defiant, you said,
Speaker 2: quote unquote, I will not bend the knee. Your lawyers
Speaker 2: may have said, hey, reed, uh, why don't we just uh,
Speaker 2: why don't we Why don't we similar it down a
Speaker 2: little bit here and see if we can work something out.
Speaker 2: Why do you feel like you need to be so
Speaker 2: clear and defiant?
Speaker 1: Look, my lawyers, who are extremely good, said you have
Speaker 1: the following risks. But one of the things I love
Speaker 1: about my lawyers is the head and we admire the
Speaker 1: fact that you're you're you're, that you're doing the right
Speaker 1: thing that period. And that's part of the reason that
Speaker 1: they like to damn right, goddamn right, yeah, and uh.
Speaker 1: And this thing is playing out in real time. This
Speaker 1: is just a few weeks ago there, yes, exactly, yeah
Speaker 1: and so and as you know, maybe it's still going,
Speaker 1: maybe it's not. Who knows, who knows.
Speaker 2: Uh read a hell of a hell of a journey.
Speaker 1: This conversation has been around.
Speaker 2: The globe, and I'd be remiss if I didn't just
Speaker 2: circle back on one final thing, and that is you're
Speaker 2: over under assessment. You've been a lifelong Democrat. You've been
Speaker 2: trying to sort of work with a party from within,
Speaker 2: trying to sort of strengthen our muscles, strengthen our you know,
Speaker 2: our our approach and tactically and substantively in policy, and
Speaker 2: also just in terms of you know, how we're successful
Speaker 2: and just building coalitions, et cetera.
Speaker 1: What's your make of the.
Speaker 2: Overview of this whole autopsy and where we are and
Speaker 2: the lessons we learned or didn't learn from the last election,
Speaker 2: and where we stand as a party the Democratic Party today.
Speaker 1: Well, one major mistake we made in the last election
Speaker 1: that the next election we simply won't, which is most
Speaker 1: American people think DC is broken and want to change.
Speaker 1: And the problem is, like you know, uh, you know,
Speaker 1: Kamala's chance was to say I'm different than Biden, right,
Speaker 1: and like, yes, he was a necessary stabilization for the
Speaker 1: catastrophe that was Trump won, and they'll be necessary stabilization
Speaker 1: for the infinite catastrophe that is Trump too. But like
Speaker 1: I'm hearing that people feel pain and feel that there
Speaker 1: needs to be a change in DC is broken. That's
Speaker 1: going to be important, yep. And it's you know, including like, hey,
Speaker 1: until we figured out what's going on for us, could
Speaker 1: we like really limits slow down what's going on with
Speaker 1: migration because like like I don't know how migration is
Speaker 1: better for me, right, so you know that kind of stuff.
Speaker 1: But I think probably the most central thing is there's
Speaker 1: a lot of Democrats who don't understand why business is
Speaker 1: so important. They don't understand it pays for everything. It
Speaker 1: pays for the Medicare, it pays for Social Security, it
Speaker 1: pays for jobs. It's like really important. You got to
Speaker 1: be the I'm pro business, right, it just got to
Speaker 1: be you can't be pro job and anti business, yes exactly.
Speaker 1: So it's like stop being like, stop doing anti business
Speaker 1: rhetoric because people go, wait, that's totally broken, right, then
Speaker 1: that's what part of what this like socialist means. Right,
Speaker 1: It's like, so like be pro business. Now you may say, well,
Speaker 1: I want business to contribute more. Okay, be more specific
Speaker 1: about what that is, and then go on that as
Speaker 1: part of what you're doing. It's like, look, I'm very
Speaker 1: pro business, and I think business can contribute more in
Speaker 1: the following ways. I want business to succeed, and I
Speaker 1: think we should get business like it's a I want
Speaker 1: business succeed. Of course you do. It's what gives us
Speaker 1: jobs and everything else. And so being pro business in
Speaker 1: that regard and I think that's that's part of the
Speaker 1: thing where there is like I just don't think it
Speaker 1: works to say the real problem is in earlier elections
Speaker 1: we weren't anti power enough, where anti power means anti business,
Speaker 1: and so it's like, no, look we do. Look, all
Speaker 1: societies have pillars of power. They have pillars of power
Speaker 1: in politics, they have pillars of power in business, they
Speaker 1: have pillars of power in celebrity. They have pillars of power.
Speaker 1: And what you really want is a distribution of power. Now,
Speaker 1: when you get to a trillionaire, you go, hey, he
Speaker 1: should be limited about how he can buy elections and
Speaker 1: do other kinds of shit, right, Like that's important because
Speaker 1: that's a corruption on that kind of power. But by
Speaker 1: the way, part of the reason why, like I have
Speaker 1: not been worried about the scaling tech companies is because
Speaker 1: if we were this is one thing has had like
Speaker 1: eight plus years ago, If we were five to seven
Speaker 1: scale tech companies heading the three, I'd have a concern.
Speaker 1: If we're five to seven heading the fifteen, they compete
Speaker 1: with each other and they're balancing out their power and
Speaker 1: all the rest. And by the way, I'm right right
Speaker 1: in Nvidia, Open Ai, and Thropic it's more and more
Speaker 1: and more competing with each other. And that competition is
Speaker 1: part of how we govern the system in terms of
Speaker 1: how we're doing it, so being more business intelligent and
Speaker 1: pro business generally, and the thought shouldn't be how do
Speaker 1: we limit business? The thought should be how do we
Speaker 1: shape business to help society?
Speaker 2: And so in this I mean so it's interesting at
Speaker 2: the core, and I think it goes to you know,
Speaker 2: you had some issues with Lena Kon at the FTC
Speaker 2: and the context and then the brand of Biden. Yeah,
Speaker 2: sort of took a shape in a completely different direction,
Speaker 2: including by the way, in the crypto space, as you
Speaker 2: were implying earlier that there was an opportunity there. Yes,
Speaker 2: and they just turned their back because of the excesses,
Speaker 2: but without looking at the sort of baseline benefits of
Speaker 2: blockchain or democratizing access to banking and not having the
Speaker 2: friction and the capture of the banking system and the
Speaker 2: fee structures and the rest.
Speaker 1: Yeah, exactly. So what we want is we want democrats
Speaker 1: to say we're business intelligent and we're proposing things that
Speaker 1: shape it to the better benefit of the working class. Great,
Speaker 1: all for it.
Speaker 2: And you are aware on the Billionaire's text or read
Speaker 2: where are you on the billionaires tax? You know my
Speaker 2: position as a state level, but what about that debate
Speaker 2: and how does that play in to your broader point?
Speaker 1: So I'm not at all opposed to increasing progressive taxation.
Speaker 1: You and I have talked about the income taxes here.
Speaker 2: Withore California is a perfect example right.
Speaker 1: Now. But the the way that it's proposed and implemented
Speaker 1: is a disaster, right. I mean, it's the you know,
Speaker 1: it's kind of like the hey, fuck you, we hate
Speaker 1: you guys, We're going to take money from you. Well,
Speaker 1: a lot of them respond to that very rationally say great,
Speaker 1: we're going on another state. Right, And by the way,
Speaker 1: not only do they take the they reduce the perspective
Speaker 1: billionaire's tax.
Speaker 2: The annual income tax that we were otherwise enjoying is
Speaker 2: no longer with us.
Speaker 1: Yes, it's a disaster.
Speaker 2: As this state has discovered. It's not anecdotal. I mean, yes,
Speaker 2: people say, oh, it's bullshit. No, it's not bullshit. And
Speaker 2: we have actual names, real people, and then we have
Speaker 2: dozens of people they don't know about because they don't.
Speaker 1: Want to make a big deal all about it. Exactly.
Speaker 1: I personally know fifteen people have moved.
Speaker 2: Yeah, I don't say that, yes, because I'm at twelve.
Speaker 2: So let's compare the list. Yes, so it's a disaster
Speaker 2: now part of By the way, and someone watching this
Speaker 2: may be like rolling their eyes of course read mister
Speaker 2: billionaires saying this Newsom's captured by these guys as well.
Speaker 2: You know, that's why this is a chummy conversation. But
Speaker 2: the notion of the California billionaires tax at a state level,
Speaker 2: this is a real thing. I mean, just by the way,
Speaker 2: it's where the teachers opposed it. Yes, that's why the
Speaker 2: firefighters opposed it. That's why vast majority of organized labor
Speaker 2: opposes the California Billionaire's Tax, which I think is an
Speaker 2: incredibly important point to make. It's not just you saying
Speaker 2: it to me, who's well known in my opposition that said,
Speaker 2: it's at a federal level. This notion of again you
Speaker 2: say progressive tax system, but this notion of a tax
Speaker 2: system that does but inheritance needs to be reformed. Does
Speaker 2: it stepped up basis need to be reformed.
Speaker 1: Look, I think it's good to do all of these
Speaker 1: things right. Look, it's good to say, Look, we are
Speaker 1: not in a place where, roughly speaking, progressive taxation eg
Speaker 1: as you make more money, you pay a higher percentage
Speaker 1: of tax. H'ch just a higher number, but a higher percentage,
Speaker 1: not to infinite. I actually think roughly when you get
Speaker 1: to fifty, you start getting weird perverse incentives, like you
Speaker 1: go to, I'm now charging with seventy percent tax. The
Speaker 1: answer is, oh, I'm now going to work more on
Speaker 1: how are I not pay the seventy percent tax than
Speaker 1: you're in the next dollar? Roughly at fifty to fifty,
Speaker 1: many not all, but many people go, I'll just earn
Speaker 1: the next dollar, right, I'll find now. But the problem
Speaker 1: is the net effective rate for wealthy people is wall below.
Speaker 2: Fifty because it's not on their income, it's on the corpus,
Speaker 2: it's on the capital. It's the benefits that accrue then
Speaker 2: to having a lower tax rate.
Speaker 1: Yeah, so capital game. So this we should be fixing.
Speaker 1: And by the way, we already have versions of wealth
Speaker 1: tax like property tax a good way. I actually like
Speaker 1: the whole Pieter terror tax. I think it's a small thing,
Speaker 1: but I think it's a good thing to do.
Speaker 2: And Mendami obviously popularized it, but it's happened in many
Speaker 2: other cities incluely San Francisco, and a version it's in
Speaker 2: litigation and other parts of the globe have been doing
Speaker 2: it for years.
Speaker 1: Yeah, but I think it's a good like. It's a
Speaker 1: small one, but an example of this is a good one. Right,
Speaker 1: And so what are the ones that we can do
Speaker 1: that are healthy in the system and also don't have
Speaker 1: you know, a weird kind of massive double tax you
Speaker 1: know kind of things and are coherent across it and sort.
Speaker 1: But progressive tax is good. And of course the incentive
Speaker 1: is to try to avoid tax, right, I mean the
Speaker 1: natural deetive everyone has that incentive, right, but let's try
Speaker 1: to make it so that it's that you're like, okay,
Speaker 1: because this is the thing I like when people call
Speaker 1: me and ask me about the the California wealth tax,
Speaker 1: I say, look, here is how I would try to
Speaker 1: introduce new taxes in California. Whether it's raising the income
Speaker 1: or house, I would say, hey, we're going to tax
Speaker 1: very much disproportionate from the wealthy. The wealthy have had
Speaker 1: a huge benefit of being in California because that's how
Speaker 1: they've made all their wealth and all the rest. So yes,
Speaker 1: we wish that they would just go along with it.
Speaker 1: But of course everyone wants to avoid tax, but like
Speaker 1: pitch it to them in terms where you're like, I'm
Speaker 1: fixing the problem, right, Like, hey, we're creating a sovereign
Speaker 1: wealth fund for being able to fund ongoing you know,
Speaker 1: kind of prosperity of California's Like Okay, then like okay,
Speaker 1: I like, I'm I still would rather not pay more tax, right,
Speaker 1: but it makes sense to me that it opens the door.
Speaker 2: And by the way, so many of the conversations we've
Speaker 2: had with many of the people, including a number of
Speaker 2: people that have left, are in laws lines where they
Speaker 2: would they have publicly stated, not just privately stated, they
Speaker 2: would support something along those guts.
Speaker 1: So because it's economic rationality, because because in addition to
Speaker 1: first thing, you know, uh f you you wealthy people,
Speaker 1: we're gonna just charge you for this. And it's like, well,
Speaker 1: are you charging me for what, oh, the huge shortfall
Speaker 1: from Trump's you know, a big beautiful betrayal betrayal HR one, Yes,
Speaker 1: big cuts to medicaid, which we have these huge costs
Speaker 1: because cutting medicaid, So we're going to charge you for that.
Speaker 1: It's like, well, that's not a one off issue. That's
Speaker 1: going to continue on going. And you're telling me this
Speaker 1: is one off. I don't believe you by that. Amen. Well,
Speaker 1: I appreciate that sentiment, and obviously I.
Speaker 2: Believe very strongly we're gonna have to address the tax
Speaker 2: code federally in a in a profound way.
Speaker 1: In California many.
Speaker 2: Ways has some clues, it has some models, and I
Speaker 2: mean compare California most progressive tax rate states like New
Speaker 2: York as well, but to the most regressive states like
Speaker 2: Texas and Florida that tax their low wage earners more
Speaker 2: than we tax our highway. So the question objectively, is
Speaker 2: who is the high tax state, the highest tax rate
Speaker 2: for the one percent. Ninety nine percent don't live in
Speaker 2: the one percent, and so this is but this notion
Speaker 2: that there's a tonality here, there's a sentiment around but
Speaker 2: grudging success. There's aspects of this that I think there's
Speaker 2: nuance on what you're saying that I think is important
Speaker 2: as a Democrat.
Speaker 1: I certainly share. Thanks for sharing all this time.
Speaker 2: It's been a lot of fun, and thanks for coming
Speaker 2: to you know, Governor Reagan's mansion, who I think had
Speaker 2: seventy percent tax right.
Speaker 1: Yes, well, And I think that's one of the reason
Speaker 1: I was online, is like it just creates a huge
Speaker 1: incentive to try to do something of it. But it's
Speaker 1: a pleasure and I look forward to nex