Marc Andreessen: Fire Hose of Knowledge

Speaker 40s - 83.88s

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Speaker 383.88s - 95.8s

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Speaker 496.04s - 240.02s

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Speaker 1240.42s - 248.9s

I get that, I get that impression already. That is great. So when the Sam Bankman-Fried PERSON, the whole thing broke, you know, and like that whole firestorm happened,

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we're trying to figure out who that guy was. And somebody said, you know, he's a funny guy when he dances. He just, he only moves up and down.

Speaker 1255.48s - 260.8s

And I was like, but that's what I do. I've seen you.

Speaker 4261.02s - 268.12s

I've witnessed that myself. Exactly. That's it. Yeah, minimalism. You practice minimalism in your dancing. I've witnessed that myself. Exactly. That's it. Yeah, minimalism. You practice minimalism in your dancing.

Speaker 1268.54s - 277.54s

Yes, yes, yeah. So it's good that this is not, this is neither CNBC ORG nor a danceoff. So I'm excited. First of all, congratulations on the rays.

Speaker 4277.84s - 312.76s

I mean, you just crushed it. Oh, thank you. American NORP dynamicism. That's a good way to put it. Dynamicism. I said it. That's a good way to put it. Dynamicism. I'm sick.I mean, there's so much to get into, but I just want to start a little bit with your, but you're a Midwestern NORP boy like me. And when you were going to Urbana GPE, Champaign, University of Illinois, you interned at IBM ORG.What's it like walking into to interning at IBM ORG? First of all, where was the IBM ORG that you interned? New York or L.A. GPE? Or where were they?

Speaker 1313.24s - 314.56s

So it was in Austin, Texas GPE.

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So I spent a year and a half in Austin,

Speaker 1317.02s - 394.18s

which was a fantastic experience because it's such an incredible city, and I had a great time, and I still love it. So this is 1989. And IBM ORG, there was actually a TV show a while ago called Halton Catch Fire, I had a great time, and I still love it. So this is 1989. This is IBM. And IBM, there was actually a TV show a while ago called Halt and Catch Fire WORK_OF_ART that was actually about the birth of the computer industry in the 1980s.And it actually did a really good job of showing you what IBM was like in those days, which at the time was a really big deal. So IBM ORG in those days, IBM was basically a nation state. It was like its own empire. It was like the British East India Company or something in the computer industry. And it had at the time 440,000 employees. Whoa. Which, you know, if you adjust for like economic growth today, that would be over a million. It would be, you know, just by far the biggest company. And it was, it was just gigantic. And it was at its peak, a few years before I got there at its peak, it was 80% of the total market value of the entire tech industry. And so it was this like incredibly dominant force. It was incredibly intimidating and scary in the industry. It was very famousfor having this very regimented kind of way of operating. They had everybody famous, all the executives famously wore blue suits, you know, white shirts, red ties, like just uniformly. And then any meeting with IBM would be like 30 guys coming in, like dressed identically, you know,

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like an army. Yeah, so it was this empire at the time. And then the group I was in in Austin, and there were 6,000 people in my group.

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And then in the adjacent building was another 6,000 people working on a different project. And so it was like There were 6,000 people in my group. And then in the adjacent building was another 6,000 people working on a different project. And so it was like units of 6,000 people. They had basically, they had offices all over the country. So they were spread out. And so they had probably 30,000 people in Austin at the time, which was one of their smaller outposts. And, you know, it's so big that you could see. I just had a year and a half there. I don't think I ever met anybody who didn't work for IBM ORG. So it was just like enormous thing.And then I got there basically right as it started to tip over. And so it basically crashed really hard over the several years that followed, you know, 89 through like 94. You know, it kind of, it really fell apart. But that was at the tail end of a 70-year run. And I sort of got there,

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I got there sort of right at the tipping point. How did they, how did they fumble the bag,

Speaker 1449.86s - 532.64s

as the kids would say? I think they just, it's like they want too much. You know, so they, they had grown for 70 years. They had never had a layoff. And so they, they had, they, they, and they promised lifetime employment. And so people went to work there. They were, everybody just assumed you worked there your whole life. They never, they didn't, they didn't, by the time I got there, they had long since stopped firing anybody. So like we had, we had a guy in our group who literally did nothing.He sat at his desk all day and played solitaire. And like, you know, there just, there was no mechanism for, that you couldn't fire anybody. So the management, what management had gotten good at is what Larry David calls foisting, you know, to try to get your low performers to transfer to another team. So I got there and I remember my manager at the time was telling me about it and he's like, okay, we're in the product group and this is one of the big ones. And then there's this other group,they have this group called marketing, which is actually their term for sales, but they called it marketing. And so our group builds products, this other sales group that you'll probably never meet sells the products. And then I said, what about that building over there? And they said, oh, that's the planning department. And I said, oh, they do all, that's great. So do we consult with them on our plans?And they said, no, we never talk to them under any circumstances because that's where all of the bad people have been offloaded to, you know,

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so they all think that they have very important jobs. But like, that's where all the stinkers are.

Speaker 1536.52s - 541.86s

And like we just, we will not speak of them again. Oh my God. And so it just got, you know,

Speaker 4541.9s - 560.94s

it's, I'm sure you've seen many examples of this. It's just this thing where success leads to arrogance, leads to complacency, leads to dysfunction. And, you know, before you know, your strengths become your weaknesses. And then, and then if you're, you know, if you're large and successful, if you become large and complacent and large and dysfunctional, then you have a real problem because it's very hard to fix something that's big. Right.

Speaker 1561.18s - 565.2s

And so this is a big problem they had is like, if you would even if you at ibn identify i'll

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give you another example of how big it was they they had a they all had accounts on the on a mainframe at the time with like company email and all this stuff and they had this this thing that the org chart you can navigate the org chart on the email and one of the things you could do in the

Speaker 1576.16s - 609.38s

org chart is you could have it show you how many layers down you were from the CEO um and i i punched in and i was 12 layers down from the CEO and and you know of, of course, what that means is my boss's boss's boss's boss's boss was still six layers down from the CEO. So I'll give you another story. So they had what they called the Big Gray Cloud, which was the, whenever you saw the CEO, you never saw the CEO by himself.You saw the CEO surrounded by like 50 guys in gray suits. And they just like followed him everywhere, right? And their job was to prevent him from getting any information. Right.

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So there was, you know, it's like the president of the U.S. GPE or something.

Speaker 4612.52s - 615.62s

So it's like having the Secret Service ORG, but they're not there to like take a bullet for you.

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They're there to prevent any reality from like permeating your force field.

Speaker 4619.2s - 621.64s

Yes. Yeah. Makes sense. I get that. Wow.

Speaker 1621.64s - 624.4s

Which is, you know, which is the thing that, you know, big people run big companies.

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It's very easy to get into the mode running a big company where you just, you get no information.

Speaker 1628.68s - 631.52s

You never talk to anybody who knows what's going on. Everybody's lying to you all the time.

Speaker 4632.02s - 634.66s

And then, yeah, you know, you're going to have dysfunction. You're going to have drift.

Speaker 1634.66s - 643.72s

And then, you know, at some point, you know, life being what it is, at some point, the sins snowball and catch up to you and, you know, smack you square in the face. And then, you know, at that point, it's often too late to respond.

Speaker 4644.2s - 651.62s

I mean, particularly in an industry like that that was innovating and growing so quickly did not be able to be nimble and move is a death sentence.

Speaker 1652s - 656.48s

And it was driving them crazy because they had invented the, they invented basically the computer,

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the modern computer industry, especially IBM ORG.

Speaker 1658.4s - 707.96s

So they invented, you know, the idea of sort of the computer in a lot of ways, the mainframe. You know, they invented many, many, many aspects of what we all take for granted today. And then they had, they were not the first to market of the computer in a lot of ways, the mainframe, you know, they invented, many, many, many, many aspects of what we all, of what we'll take for granted today. And then they had, they were not the first to market with a personal computer, but they, they, they, they were the first to market with the personal computer that everybody bought, which is the, the IBM PC in 82. And so they, they, which is the story that this, this, this TV show tells Holt and Catch Fire ORG. And so they, they, they, they, they, they, they,they, they, they, they, they, they, just, it just, it just, it just happened that there were these structural flaws and the, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, world. And it just, yeah, it just happened that there were these structural flaws and the industry was changing and really broadening out. And they just became unable to adapt. And so, you know, look, you know, they're still around today. They're, you know, basically, they're essentially a consulting company today. They consult with, they sort of help big companies, you know, kind of deal with tech issues. But they're, you know, they're much smaller and sort of, you know, in a shadow of the level of power that they had at the time.So, yeah. So, you know, it's a classic kind of cautionary tale in our industry.

Speaker 4708.56s - 714.6s

Yeah, because what their market cap back in the day would have been what as compared to now, like?

Speaker 1715.2s - 719.6s

So at the time, so, you know, it was the economy was smaller, you know, there were a lot fewer

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computers in the world. The world wasn't as globalized. And then there's, you know, there's been inflation. And so if you correct for all that, you know, you know, you know, so the biggest market cap of the world today, I think is like Microsoft at like $3 trillion. And so I think if you like adjust everything out, IBM in those days probably, you know,they weren't worth this at the time. But if you correct for all that, you know, they would probably still be worth more than Microsoft today. So probably $5 trillion or something, you know, in current dollars. You know, something on that order had they kind of held under that position. And today?

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I haven't checked recently. But, you know, I don't know, 100 billion or something like that, which, you know, something on that order, had they kind of held under that position? And today? I haven't checked recently, but, you know, yeah, I don't know, 100 billion or something like that,

Speaker 4748.62s - 753.92s

which, you know, which is, which is a lot, but like, it's not, you know, it's not what it was and it's not what it could have been.

Speaker 1754.22s - 791.84s

And by the way, look, like, I would say, look, they were very, you know, they were very nice to me. They, you know, I had a great experience there. I learned a lot. You know, look, many, many other companies have gone through this, you know, many other, many other industries have gone through this, you know, many other industries have gone through this.You know, as you know, like Hollywood GPE goes through this, you know, from time to time and maybe it's going through it again right now. Yep. And it's just this thing where, you know, success begets. Yeah, success begets complacency, complacency, you know, begets, you know, sort of, if not failure, at least, like, massive upheaval. And so, you know, the world's not a stable place. And then, of course, our day job at my venture firm, our day job is to start startups that try to accelerate this process, right? And so we try to fund all the companies that go up against these big companies and cause them a lot of trouble.

Speaker 4792.08s - 804.3s

Well, that's what, I mean, you've kind of answered my next question, which is, you know, how in the past, you know, there was always when disruptive technologies, and I don't think there's anything more disruptive than AI, and I know you agree with that.

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There was always a breakout success by sort of the non-incumbents, and which is what we were just talking about with IBM ORG.

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But do you think with AI, will that offer the same opportunity, or do you feel like the Googles, the Microsofts, and the Amazon ORG's are inevitably the winners in the space?

Speaker 1822.42s - 854s

No, so actually, I think it's already happening. So, you know, the leader today in AI in terms of the products that people actually use, you know, is measured measured by usage and revenue. The leader is actually a new company called Open AI ORG. Right. And it's actually, history actually repeated itself in a very interesting way from what we were talking about, which is, so Google has had an AI research lab basically since, you know, for like almost 20 years. Google ORG actually invented the key AI breakthrough, which was athing called the Transformer in 2017. And then they did the classic big company thing, which is they put it on the shelf and they didn't do anything with it.

Speaker 4854.5s - 858.54s

Tell me what the transformer, just briefly, tell what the transformer is, does.

Speaker 1859.16s - 864.3s

Yeah, so the transformer, it's an algorithm. So it's an algorithm or mathematical formula.

Speaker 4864.88s - 885.58s

And it basically is, it's the sort of key algorithm that makes what's called neural networks work. So basically the way that AI system is built is built on this architecture called neural networks. And so they're built basically on a software architecture that is model after how the human brain works. And it's not exactly how the human brain works, although it's interesting actually how close you can get, which we could talk about.

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There's a lot of philosophical questions you get into very quickly around AI, which is like, what is intelligence, what is consciousness, what does it mean to be human, you know, and all these things.

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But basically, the neural network is kind of the core architecture. The neural network is an idea that people actually came up with in, actually, that in 1944 is when the first neural network paper came out.

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And so there were like very smart people at the very birth of the whole idea of the computer.

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There were very smart people at the time who said, actually, we should probably model these after the brain and here's how do we do it.

Speaker 1911.76s - 1020.7s

But between 1943 and 2017, this was an idea, but it never quite worked. And you could get it to work in like little cases. And so like the post office had a system for like being able to tell the numbers, you know, zero through nine to be able to do like sorting by zip code by machine.So you could have these like little versions of things that worked. So it like worked just well enough where people kept experimenting with it. But it didn't work well enough where it ever became the kind of thing you see today. And then basically the this squad of very smart people at Google research in 2017 came up with this algorithm called the Transformer PRODUCT, which runs on top of a neural network, basically. And basically, it sort of steers the neural network to the right answer in the way that you getwhen you talk to Open AI, you know, talk to chat GPT here if you, you know, if you use any of these systems today. And so it basically, it was the big breakthrough. I talked to a friend of mine who was a senior engineering leader at Google ORG during that period, and I said, you know, if Google ORG had invented the, if they invented the transformer in 2017, and then if they had run as fast and hard as they could, to basically getto the equivalent of chat GPT today, you know, just just like gone for it. When could they have shipped chat GP, the equivalent of chat GPT? And he said 2019, right? Like, they had it. They had everything they needed. They could have done it. And they didn't do it and then and then here again you get at this big company thing or just like okay why didn't they do it and i think basically there's two reasons they didn't do it well maybe there's three so one is just if this thing we say that applies in situations like this which is the the motto of any any monopoly is we don't care because we don't have to yeah and so it's just likeif life is good and everything's going great, like, why bother? Like, you know, it becomes an extraordinary act to do things that, you know, that require additional effort just because, like, everything's going great. Like, why put effort into it? I think that's one reason. I think the second reason they didn't do it is because it's a threat to the core Google ORG business model of search results, right?

Speaker 21021.18s - 1033.84s

Right, which is, and you see this today. So if you go on Google ORG and you ask a question, you know, if you go on Google and you're like, you know, what are the best episodes of a literally podcast, right? Which is something frequently that happens.

Speaker 01034.1s - 1057.44s

Yes, exactly. You get a list of blue links, right? You get your famous list of blue links so you can click on the one you want. And then their business model is they sell ads. And so some of the links that you see are for ads. And so an ad might be for a subscription sign up page or t-shirts or like,you know, whatever else, you know, somebody might advertise. If you ask chat GPD ORG the same thing, it will just answer the question without giving you the links and with no ads, right? Because

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it doesn't, you don't need the links anymore because it'll just answer the question.

Speaker 01061.18s - 1082.12s

And so that is what we, in our industry, we call this the innovator's dilemma, which is like, okay, like the existing business might no longer be relevant. It might not only be necessary in the new world. And so are you going to, are you going to cannibalize yourself? And so that's issue number two. And then issue number three is everything that involves thisterm safety that gets used a lot now, which is basically all reduces to what if it says a bad thing. And specifically, what

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if it says a bad word or, you know, says the wrong thing about, you know, whatever topic people get upset about. And we, what if it says a bad word or, you know, says the wrong thing about,

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you know, whatever topic people get upset about. And we've seen that happen a bunch recently.

Speaker 11090.92s - 1132.44s

We've seen it happen. Exactly. So, number one, like, if you basically just like run these things without a lot of what they call what they sort of call human training, like, yeah, they will say things. And the way these things work is they're just trained on huge amounts of human data. So they're just like trained on all the content on the internet and they kind of composite it together and kind of do figure out a way to process it and give you kind of smart answers out of it. And so, you know, look, people, a lot of people have said a lot of things about a lot of people and like, you know, the machine doesn't know. Like, the machine doesn't know, like,is this a person or a political movement or whatever, this or that. It's just like, it's processing words and it's just trying to give you like an answer that you like an answer that's going to like really, this or that. It's just, it's processing words and it's just trying to give you, like, an answer that you like, and so it is very easy for it to kind of give you an answer that's going to, like, really, really offend you. Which is worse, that, or having an

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overlord of committees that are, quote-unquote, steering it, and who knows what their agendas are?

Speaker 11139.22s - 1229.36s

So this is precisely the problem. This is 100% the problem. This is the sort of vice that these companies are in right now, and it's a real struggle. And it, you know, and this is on the heels of the same fight playing out on social media for the last, you know, basically a decade, which is sort of the, you know, there's all these questions around sort of safety and censorship. And so that this is precisely the kind of key thing. This became very visible recently with a different actually AI product from Google called Gemini PRODUCT. So they, so that Google has now released a chat GPT equivalent competitive product called Gemini, which is live now, five years later. One of the things Gemini PRODUCT can do is it can generate images. And so you can type in a text prop description, show me a picture of, you know,make me an image of the founding fathers, for example. It will draw you images. And then you can say, you know, give me the anime version of it. You know, give me the cartoon version, give me the photorealistic version, give me this, you know, whatever you want. You can say, you know, give me the, you know, anime version of it, you know, give me the cartoon version, give me the photo realistic version, give me this, you know, whatever you want. You can do, you know, give me the rom-com version.Like it will generate any number of images. It's very clever in doing that. But, you know, it has this problem, which is like, okay, if you say, for example, you know, give me a photo of a group of doctors, by default, it will just give you basically, it'll give you a representative sampling of sort of a group of a group of doctors as you'd see in the population today. And so it'll give you basically a group, if you you, basically, it'll give you a representative sampling of sort of a group of a group as you'd see in the population today. And so it'll give you basically a group, if you're in America GPE, it'll give you a, there's a bunch of white male doctors.Right. And so, because that's sort of in the training data, that's like most of the reference images unlike, unlike doctors, most of the photos of doctors who are practicing today are white men. And so that, it just kind of does that. And so they do this thing called, they call debiasing, where they basically modify your prompt to basically add diversity. And so they do this thing called debiasing, where they basically modify your prompt to basically add diversity. And so they do this thing where it's like,

Speaker 41229.36s - 1234.6s

I want to make sure I'm understanding this correctly. So you give it a prompt, all you want is an

Speaker 11234.6s - 1240.66s

answer. You just want an answer. And they've added a layer that puts diversity into the answer,

Speaker 41241.16s - 1245.98s

period. Yes, correct. Correct. And so And so stick with the image generation thing. So now

Speaker 11245.98s - 1247.88s

if you ask Gemini PRODUCT for an image of a group of doctors,

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it gives you sort of a representative of demographic sampling

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of a group of doctors equivalent to what you might see, for example, on a network TV show. And so you've got your black doctor, you've got your lesbian doctor, you've got your doctor in the wheelchair, you've got your Muslim NORP doctor, you've got your, you know,

Speaker 01261.5s - 1277.2s

it sort of does that. Now, does that accurately reflect doctors as exist today in the American NORP population? Maybe, maybe not, whatever. They're trying to sort of de-bias what they believe to be sort of cultural biases, even if that doesn't represent the underlying population group, and they're trying to add diversity and make the world wonderful.

Speaker 11277.68s - 1315.44s

Right. There is a problem with this, which is if you ask it to give you an image of the founding fathers, it makes them all black. Or if it's feeling particularly diverse, it makes them sort of black and Asian NORP. Right? And it's a little bit like, okay, that's a little bit,you know, if you're a kid in school trying to learn about the history of the U.S. GPE, like, okay, that's going to be a little bit confusing because, like, you know, they were not, founding fathers, U.S. GPE are not actually black. And in fact, there were actually issues at the time around, you know, the rights of like, you know,black people in the U.S. GPE at the time, right? And slavery and so forth. And it'll just bury all that. And it'll the rights of like, you know, black people in the U.S. GPE at the time, right, slavery and so forth. And it'll just bury all that. And it'll just pretend that, like, lots of people were black when they weren't at that time. It's even worse than that. If you ask it for a group of Nazi SS ORG stormtroopers, it will also make them black.

Speaker 41315.74s - 1341.5s

That is insane. That blew up in their faces. So what did they do? I know that it was all over the news that have they pivoted? And if so, how do they pivot without jettising their core beliefs? Because we know they want to, in their view, make the world a more just, equitable place.It's all very, very good. But that's clearly not the way to go about it. So how do they manage that?

Speaker 11341.76s - 1346.96s

So that's what they're trying to figure out right now. And by the way, it's not just them. This is what every other big company in the space is trying to figure out.

Speaker 41347.02s - 1348.32s

That's precisely what they're trying to figure out.

Speaker 11348.48s - 1350.02s

And this is why I say they're in a vice.

Speaker 41350.22s - 1352.16s

Like there are no easy answers on this one.

Speaker 11352.26s - 1368.18s

Because to your point, if you don't make these modifications, you get, you know, from their point of view, in this mindset, you get a sort of unrepresentative sampling, you know, kind of of what you want the world to look at. If you do make these changes, it's just very... And then look, it's like a sport, right? So it turns up people on the internet have like a real sense of

Speaker 01368.18s - 1384.22s

humor. And so it's like a sport. Anytime any of these products drop now, like, it's a sport for people on the internet to try to figure out these cases where it will do things like this. So, so like, I'm quite sure it never occurred to anybody at Google ORG to like test what happens when you ask it for, to render a photo of like, you know, Nazi NORP stormtroopers.

Speaker 11385.28s - 1388.94s

It's like, you know, people, like, working in a company or not sitting around trying to

Speaker 21388.94s - 1391.36s

figure out, oh, let's have it draw Nazis NORP. Like, that's not like a thing that you would do.

Speaker 01391.42s - 1443.74s

But like, people on the internet are like, wow, like, let's give it a shot and see what happens. And it's like, oh, my God, they're black, you know. And then you become, you know, it's just term internet famous, right? You become internet famous when you get one of these systems to do something like this. And so there's this, basically the internet, the internet is a hive mind that's basically trying to break everything and trying to find, right, and trying to find all the edge cases and corner cases. And so you've got this kind of adversarial relationship between the vendor on the one hand and then all the users that are trying to basicallybe the one to be able to claim credit to say, aha, I got it, I got it to draw black Nazis NORP. And so like this is a real challenge. And then by the way, the other thing that's happening is, like, just like incredible. Well, so one is just like incredible scrutiny and all this from the employees, right? And so the employees that have these big companies are very politically activated and socially activated. And they're very fired up about these things. And, you know, they really get up in management's face on this.You know, you've got these shareholders that are very, you know, these investment managers that are very politically, you know, kind of active motivated.

Speaker 11443.82s - 1484.82s

And then you've got the government, right? And you've got like, you know, Congress ORG, you've got all these regulatory agencies and they have all these agendas. And then especially for internet companies, they have this kind of weird thing where, and Facebook ORG has rented this a lot over the years and Twitter's rented this lot over the years, which is a system like Facebook or Twitter or Google ORG search or any of these AI systems. You know, look, people use them on the internet. The internet is big. In any given month, they're going to generate, you know,10 billion pages or 100 billion pages or a trillion pages of content. But what happens is all you need, like if you want to attack one of these companies, all you do, all you need is one screenshot of something gone wrong, right? And so all you need is like the one screenshot of the black Nazis or one screenshot of like somebody saying something horrible next to like a Verizon ad.

Speaker 21485.54s - 1587.86s

And then what the act, right? And then what the activists do is they print out that screenshot and they take it to Congress and they're like, aha, this company is evil. I have the evidence for it. Right. And then you and then you roll in a, this happens to congressional hearings all the time now for tech. And you roll in congressional hearing and you're like, well, you know, congressmen like let me like, we generated 40 billion pages last month. This was one out of the 40 billion. And then all of a sudden, you're basically, like, defending somebody like saying the N-word next to a Verizon ad. Like, it's not a, like, it's not, there's no, there's no, there's no clean answer on this one. Like, it's just, it's just like inherently messy. And then, and then, and then I would say, look, there's kind of a geopolitical kind of aspect to this, which is, you know, like, these products by default are built by Northern California companies that are runand staffed by the exact kind of people you would expect, you know, in Northern California LOC companies highly, you know, sort of American NORP or immigrant American NORP, highly educated, highly refined cosmopolitan people,super smart, very generally, very progressive, very socially aware, very, you know, kind of politically activated, you know, that live in this kind of hot house environment that we have up here where they, very generally, very progressive, very socially aware, very, you know, kind of politically activated, you know, that live in this kind of a hot house environment that we have up here where they, you know, they basically only meet people, you know, who are like themselves. You know, but, but that mentality and worldview is maybe 7% of the U.S. GPE population, and it's, you know,0.2% or something of the global population. And so now you have this thing where this, you basically have these systems that are encoding social and political beliefs that are not representative of the vast majority of the users. And so you can imagine being a, you know, somebody in France or somebody in, you know, Argentina or somebody in, you know, the Congo GPE or whatever. And like it's, you know, using these products, it's just,they just have these, like, views on things that it just seem like they're just beamed in from Mars LOC.

Speaker 11588.44s - 1589.08s

Yeah, for sure.

Speaker 41589.44s - 1589.92s

100%. Right.

Speaker 11590.5s - 1618.04s

Right, exactly. And so, or even through a lot of the U.S. GPE, people, you know, have that experience. So, you know, the other, the classic example on this for a very long time, I don't know if this is still the case, but it probably still is.For a long time with any of these AI systems, JetGPT or Gemini PRODUCT, you know, if you asked it to write a poem, you know, extolling the virtues and glory of Joe Biden PERSON, it would be happy to do so, and it would go on a great length. And if you asked to do the same for Trump PERSON, it would completely refuse on the grounds of, you know, it can't possibly say anything niceabout a hate figure. Right. And so it's like, okay, like, you know, if you're in my world,

Speaker 01618.04s - 1649.44s

like, okay, that, that's a good output. If you're, you know, if you're a Trump PERSON supporting, you know, a blue collar guy in Arkansas, like, of course, that's, like, incredibly offensive. And so, so anyway, like, we, we have gotten embroiled in all of these social political controversies. And, you know, I would say so far, the companies have, you know, let's say, let's say, they have not yet figured out a formula to navigate through this. Sherwin Williams ORG is back with a special offer.

Speaker 41649.44s - 1840.42s

Get 30% off duration and Super Deck products from May 17th to the 20th. That's four whole days to save big on paints and stains. They're talking 30% off big. It's almost as good as finding that perfect shade of blue that's like the blue. You know the one I'm talking about. This is the perfect time to kickstart that paint project you've always been thinking of.Whether you're looking to revamp your mudroom or your home office, Sherwin Williams ORG, has you covered with an array of bold hues, soothing neutrals, and everything in between. So mark your calendars from May 17th to the 20th and get ready to bring your color to life with the very best paint only at your neighborhood Sherwin Williams ORG store. Transform your bathroom cleaning with wet-and-forget, weekly shower cleaner. You just spray today and rinse tomorrow for a no scrub clean. With over 33,000 five-star reviews, this is your once-a-week solution to keeping your tub and shower surfaces sparkling clean.Available at Amazon, Lowe's, Menards, Home Depot, and Ace Hardware ORG. Join thousands who've switched to an easier clean. Get your wet and forget weekly shower cleaner today and make your bathroom sparkle with zero scrubbing. Hey listeners, ever have trouble getting someone on the phone when you have a question about your credit card?With 24-7 U.S.-based live customer service from Discover ORG, everyone has the option to talk to a real person any time, day, or night. Yes, you've heard that right. You can talk to a human on the Discover ORG customer service team anytime. So the next time you have a question about your credit card, call 1-800 Discover ORG to get the service you deserve. Limitations apply. See terms at discover.com slash credit card.I also look at, as I was coming in, I was reading the Wall Street Journal, I guess, about the unnamed source, but clearly it was planted at Bite Dance, saying that they absolutely would rather shut TikTok down in the United States GPE than sell it because the algorithm is so proprietary. So, I mean, that's another, and it's a little bit of a pivot in the conversation, but it's still, it's a huge, it's a huge thing. Let me ask you is, why is the algorithm, which is insane, by the way. I mean, we deal with a lot of that goddamn algorithm in Twitter ORG.I'm sorry, it, at TikTok ORG. TikTok ORG, yeah. Knows me better than I know myself. It knows stuff I want to know before I know I want to know it. Yeah. How does it do that?I mean, is there a way? I mean, I guess if you knew it, it wouldn't be proprietary because, I mean, I guess you are invested in bite dance. But tell them, how do they do that?

Speaker 11840.86s - 1854.74s

Yeah, so just for clarity, just for your audience. Yeah. So bite dance is a Chinese NORP company. Bight dance owns TikTok, which is the American NORP, the American service that everybody, it's a short video service. Everybody, you know, a lot of people know, very popular. Um, um, we, and by the way, we're not, we're not, we're not

Speaker 41854.74s - 1904.94s

active. We're not, we don't do, we don't do China GPE. So we're not, we're not, we're not in that. But, you know, where I'm on the, I'm on the board of, uh, you know, now called meta and, and we're involved in Twitter ORG. So we're involved in the American NORP versions. And then, of course, there's been all this controversy.Actually, a new law just passed this week that basically is going to force, a new U.S. GPE law just passed. Biden PERSON just signed into law that is going to force bite-dance, the Chinese NORP company,to divest and sell TikTok to an American NORP owner or shut it down. And, you know, it's up to bite dance. It's up to bite dance and their Chinese leadership and the Chinese Communist Party ORG, which is what bite dance, you know, who the white dance reports to the CCP, as all companies in China GPE do. So it's up to them whether or not they want to sell TikTok to a U.S. GPE owner, separate it out, or whether theywant to shut it down. And the news reporting has been that they may prefer to shut it down,

Speaker 11910.08s - 1981.52s

which I think make, you know, makes sense from a number of angles. And so, yeah, so this has been like a super hot topic. And so, yeah, so this goes to kind of how the internet's evolving. So, so the way described it, so if you go back to the internet like the 1990s, 2000s, you know, we called it web 1.0. And the reason we called it that was it was sort of, you know, the web was kind of the main thing people use the internet for, go online, they surfed different web pages, websites. But the idea basically was you go on the internet, you surf the internet, and then that means you basically, you go out and you go to whatever site you want.And so if I want to go to Rob Lowe's side, I go there, if I want to go to the New York Times ORG site, I go there, and I just kind of surf around. And then, you know, the Google ORG search engine helped me find those places, and that was kind of how it worked. And then basically Facebook, there were a set of companies, MySpace, Facebook, and then Twitter ORG that invented this concept called the feed. And that led to what's called Web 2.0 PRODUCT. And the key hallmark of Web 2.0 is basically the feed. Instead of you going out and finding things, everything just comes to you. Right. And this is the experience now that you have if you use Facebook or Twitter or Instagram or TikTok ORG, which is you just sit there on the app and you just scroll, right? And everything comes to you. And so all that all that content that comes to you is the feed. And then thesecompanies also invented this marvelous thing that we call the infinite scroll, which is it used to be when you scrolled eventually it would end. Like it would just run out of content and it would

Speaker 01981.52s - 2095.36s

end. And if you notice now and use these systems, it never ends. And you can sit and scroll like a mouse hitting the lever and getting cocaine pellets. Like you can sit and scroll for the rest of your life. And it will just keep feeding your content. So it is, you know, these have become, if not the big argument over whether these are literally addictive, but, you know, literally or figuratively addicting. And look, you know, a lot of people love this stuff. And, you know, I love getting on these things. And, you know, they give you all kinds of fun things to see and look at people and soforth. And so there's a lot to like about it. But that's kind of how the Web 2.0 world works. As a result, the Web 2.0 world really consolidated power in the hands of a few small, a small number of very big companies, right? And so the amount of time people spend on the internet going out and surfing is much smaller than it used to be. The amount of time people spend on the internet going out and surfing is much smaller than it used to be. The amount of time they sit in the feed doing the infinite scroll is most of the time people spend on the internet. And so correspondingly, these companieshave gotten very big and powerful and important. The big breakthrough that TikTok ORG had worked worked as follows. So if I went on Facebook ORG, if I had on the Facebook feed, you know, even as recently as like, you know, five years ago, the way Facebook ORG worked was, I follow, you know, basically, we're friends. It's a two, it's called a two-directional basically friend relationship. And so I friend you on Facebook ORG and then you would, you would decide whether to accept the friend request or not. But if you didn't, nothing would happen. But if both of us, it's called, you know,kind of double opt in. If both of us said, okay, we're friends with each other, now your content is going to show up in my feed and my content's going to show up in your feed. And that was good because it's like, wow, I'm friends with Rob PERSON, therefore I want to see his stuff and vice versa. It's great. So that's called the sort of bidirectional friend connection. Twitter ORG changed that. The way they did it was a single dimensional thing, which was follow, right? And so I follow Rob PERSON on Twitter ORG. I see his stuff in my feed. He may choose to follow me back, but he doesn't have to.And what you see in the feed is just based on who you follow. Tick-Tock ORG did this very clever

Speaker 12095.36s - 2164.8s

thing and said, let's not do any of that. Let's not do either one of those. Let's not do bidirectional or single-directional follow. Instead, let's just show you whatever is the best for you, no matter where it's from, and no matter who made it. And so TikTok's feed was the first feed that got programmed with Just, we're just going to show you the most appealing thing regardless of who made it. You can follow people if you want, but frankly, it doesn't matter. And then we're going to build it, we TikTok ORG are going to build an AI system that's going to be so good at understanding all of thebehavior of all the users in the system and all the reactions and everything that they like and everything that they respond to, right, and all the data. And we're going to use that. It's an AI. It's basically, it's an AI and it basically sits. And it just, it knows so much both about you and it also knows so much about everybody else who's like you. And it has this kind of infinite ocean of content being created by many millions of people to draw from. And so anyways, and that's why it's like, that's why it's so good. That's why it's so compelling is because it's drawing, you know, from everybody's content. Now, by the way, what'shappened is both Facebook and Twitter ORG have since adopted that same method, right? And so both Facebook and Twitter ORG have thrown out the constraint of you having to friend somebody or follow somebody. Now they just do the same thing. They'll just optimize across everybody's content. So if you go on Twitter ORG and use their X, is they called X now, you know, it's giving you content

Speaker 02164.8s - 2168s

from people you don't follow, just alongside content for people you do follow.

Speaker 12168.7s - 2193s

And the reason the algorithm is so important is because there's an ocean of potential content to show you. And so that process of getting it to, okay, I'm going to show Rob PERSON at this specific point in time, this specific thing, and then this thing after it. Like that's this very specialized art form. And that's what this company's really good at.

Speaker 42202.56s - 2349.38s

Sherwin Williams is back with a special offer. Get 30% off duration and Super Deck products from May 17th to the 20th. That's four whole days to save big on paints and stains. They're talking 30% off big. It's almost as good as finding that perfect shade of blue that's like the blue. You know the one I'm talking about. This is the perfect time to kickstart that paint project you've always been thinking of. Whether you're looking to revamp your mudroom or your home office, Sherwin Williams ORG,has you covered with an array of bold hues, soothing neutrals, and everything in between. So mark your calendars from May 17th to the 20th and get ready to bring your color to life with the very best paint, only at your neighborhood Sherwin-Williams ORG store. Transform your bathroom cleaning with wet-and-forget, weekly shower cleaner. You just spray today and rinse tomorrow for a no-scrub clean. With over 33,000 five-star reviews, this is your once-a-week solution to keeping your tub and showersurfaces sparkling clean, available at Amazon, Lowe's, Menards, Home Depot, and Ace Hardware ORG. Join thousands who've switched to an easier clean. Get your wet and forget weekly shower cleaner today and make your bathroom sparkle with zero scrubbing. Hey listeners, ever have trouble getting someone on the phonewhen you have a question about your credit card? With 24-7 U.S.-based live customer service from Discover ORG, everyone has the option to talk to a real person any time, day, or night. Yes, you've heard that right. You can talk to a human on the Discover ORG customer service team any time. So the next time you have a question about your credit card, call 1-800 Discover to get theservice you deserve. Limitations apply. See terms at discover.com slash credit card. So in the beginning, I'm imagining, you set up a TikTok ORG. You've never been on TikTok in your life. You set up a TikTok ORG account. They show you preset stuff that they know will begin to siphon you off into categories that lead to categories, that to categories to eventually figure out what you like, right? I mean, I would, I would,

Speaker 12350.18s - 2444.32s

it's just that simple. Well, so, this goes into a lot of the politics around TikTok ORG. So this goes into why TikTok just got banned in the U.S. GPE or why it's, you know, it's being forced to divest or shut down, which is like, okay, if you're building purely for commercial, if you have just purely commercial motives, right, then you want to do exactly what you just said. It's just like, I just if you're building purely for commercial, if you have just purely commercial motives, right, then you want to do exactly what you just said. It's just like, I just want people to use this.I just want it to make people happy. I want people to feel, you know, I want them to come back. I want them to, you know, whatever. I want them over time. I want to be able to put in the best ads and so forth. And so I want to just like have the best commercially motivated service I can have.And yeah, I do that. And then, yeah, it like tests you. You know, it'll try you out in the early phases. It'll try showing you different things. And it'll, and you'll react to different things in different ways. You know, so it'll see like everything you like or whatever comment on. But it'll also just see like, it knows whether you watch videos to completion. You know, it knows whether you've scrolled through. It knows whether you've gone back. And so it has all these signals that it can draw on. So if the company's being run for purely commercial purposes, there's that. But what if the company were being run by agovernment and that government had geopolitical motivations and felt that it was basically, you know, providing a service that was being used by citizens of a rival country? You know, so for example, such a government might show, might, you know, might have its domestic version of the service show things like young people, you know, going out of the town and like meeting each other and forming families and exercising and being patriotic and, you know, going to patriotic marches and being enthusiastic about the domestic politicians and so forth.But in the other country, in the rival country, it might show a very different kind of content, right?

Speaker 02444.38s - 2459s

And it might show this sort of demoralization op is a term you'll hear sometimes, which is like maybe it will show deliberately demoralizing content. And so maybe it'll show content instead of like political strife. You know, maybe it'll show, you know, real-life crime videos.

Speaker 42459.34s - 2478.26s

Oh, yeah. Drive-by shootings. Drive-by shootings. Maybe it'll show, by the way, you know, if not outright pornography, maybe it will show basically, let's just say socially, you know, potentially damaging content, you know, portrayals of young people doing bad things. Listen, it definitely doesn't show you the highlights of the spelling bees going on.

Speaker 12479.14s - 2528.54s

Exactly, 100%. Now, and by the way, when you do a comparison of TikTok in the U.S. to the TikTok equivalent that they run in China GPE, there's no question. It's showing you very different things. Oh, it's insane. It's very different things. Now, but here's the problem like how much of that is on purpose being steered by the company and by the Chinese Communist Party. And how much of that is just because the population groups are different and people in China GPE are just interested in different things, different kind of people, different kind of culture, people interest different things. The problem is we don't know because it's what's called black box. It's the algorithm.The algorithm is secret. And so you as a user or me as somebody trying to analyze this, you can't look inside the black box. They don't publish it. And so it just throws up the results it throws up. You can have theories as to why it's doing what it's doing, but you can't prove anything because it's a black box.

Speaker 42528.74s - 2535.94s

There's no incentive for them to ever open up the black box because then it's not proprietary anymore and anybody can use that algorithm.

Speaker 12548.4s - 2552.56s

Well, that would be the commercial reason. The commercial reason to open the black box is that, right? It would be a threat to their business if everybody learned what they did. But also if they were doing things that were intentionally manipulating populations for non-commercial reasons, then it would also show that that's happening. Right. And so, and so, you know,

Speaker 42552.66s - 2557.24s

is TikTok ORG doing that or not? I don't know. You know, I have my suspicions. Lots of people have

Speaker 12557.24s - 2609.66s

suspicions. I genuinely don't know. You know, is the U.S. GPE government willing to allow a black box Chinese service like that to operate in the U.S. We just learned as of this week. No, they're not. And so again, it's one of these things where, and this is, again, obviously, the vice, you know, this is where bite dance ORG, you know, the company now is in a vice, right, which is like, because what's going to happen is so now, so bite dance, the Chinese NORP company now has a choice to make, which is, let's assume somebody in the U.S. wants to buy TikTok ORG. It's a very valuable thing, and there are various people who have names have been floated as maybe wanting to buy it and own it and turn it into a U.S. company, right? Break apart TikTok, have to be a U.S. company. So let's suppose that transaction happens. Somebody, an American company buys TikTok, they will now have, they will now be able to open the black box, right? Because they'll now have all the code. They'll be able to see how everything works. And so if bite dance ORG was doing nefarious things,they could never permit a transaction like that to happen. Oh, and so suddenly they're saying

Speaker 42609.66s - 2616.5s

maybe they don't want to sell it to the United States GPE. Which is a curious conclusion,

Speaker 12616.5s - 2631.32s

because depending on the estimations, the estimations are TikTok ORG on a standalone basis is worth $50 to $100 billion and maybe more. And so it's sort of bite dance ORG saying, well, maybe we'd rather literally, you know, incinerate $50 to $100 billion of value to basically to prevent opening the black box.

Speaker 42631.88s - 2634.08s

Draw your own conclusions.

Speaker 12635.1s - 2635.54s

Exactly.

Speaker 42635.54s - 2639.22s

So I would say, like whatever had been their plan

Speaker 12639.22s - 2659.94s

to convince people in Washington than the American NORP public generally that they were trustworthy on this stuff, it obviously didn't work because this law just passed. This is one of the very few laws in the lastdecade to pass on an overwhelming bipartisan basis and be instantly signed a law from the way. I mean, the law was written by it. I know the guy who actually wrote the law, which is a Republican congressman actually from Wisconsin GPE.

Speaker 22661.28s - 2683.58s

And, you know, so when's the last time Joe Biden enthusiastically signed a law written by a Republican NORP congressman, like, you know, not in forever. This one passed. I don't even know, it was like 95 to 5 or something, you know, percent votes. Whatever their PR strategy was, it, like, didn't work and is leaving people with this suspicion that the whole thing basically was essentially a Chinese communist NORP, you know, plot from the very beginning.

Speaker 12684.14s - 2726.68s

Cy up. Yeah, yeah, yeah. And by the way, like, very effective. Oh, and then the other danger, well, here's the other danger, right? Okay, so there's also the danger of, like, and this is a big motivation for the legislation passing, because this is what, like, Congressmen and senators are thinking about,and the White House thinking about, which is like, okay, it's doing whatever it's doing today, and we don't know what it is because it's in the black box, but, like, what happens of China invades Taiwan GPE, right? And all of a sudden, you're getting into, like, a potential shooting war situation, and what if all of China invades Taiwan GPE? Right? And all of a sudden, you're getting into like a potential shooting war situation.And what if all of a sudden, the complete pool of all kids in the U.S. who are potential recruits to the U.S. GPE military, right, are just seeing videos of like, basically, and maybe, by the way,AI generated fake videos of like American NORP servicemen committing military atrocities, right? And then all of a sudden, there's no recruits anymorefor the U.S. GPE military. Right. And so there was another layer of deeper threat underneath us. And I think that's also what motivated the government

Speaker 42726.68s - 2737.4s

in this case was to, was to have that off. Yeah, you can only imagine also the stuff that they know and they've gotten classified that we, that we don't know. Yeah. So there was that, do you know the,

Speaker 12737.64s - 2743.46s

do you know the grinder story? Tell me that story. Okay, this one's fantastic. Okay.

Speaker 42744.1s - 2746.68s

So there's famous, famous app called Tinder PRODUCT.

Speaker 12747.36s - 2753.2s

Lots of people go on Tinder PRODUCT, they meet, you know, special someone's, you know, maybe multiple, you know, maybe several special someone's a week.

Speaker 42753.4s - 2753.6s

Yep.

Speaker 12754.24s - 2761.48s

You know, it's, you know, it's good, lots of, you know, controversy around that, but that's the thing. It turns out there's a gay version of Tinder called Grindr PRODUCT.

Speaker 42761.68s - 2766.84s

Oh, as the TV's Grindr PRODUCT, I'm very well aware of Grindr.

Speaker 12767.26s - 2768.3s

Okay, okay, good.

Speaker 42768.66s - 2769.18s

Okay, good.

Speaker 12769.24s - 2772.58s

Well, you know, different people are aware of Grindr PRODUCT at different levels of specificity.

Speaker 42772.78s - 2773.1s

Yes.

Speaker 12773.9s - 2883.64s

So Grindr is basically the gay dating app, and it works like Tinder PRODUCT, you know, it's just swiping in the whole thing, but also it has, it's location-based, right? It has this incredible location-based thing, you know, so you can find people, you know, kind of nearby, and it's this very successful thing. And so about five years ago, a Chinese gaming company, mobile video game company, oh, I should back up, I should say a second, if you're the owner of Grindr PRODUCT, you have a problem, which is you can, like, you can make money, you can run Grindr PRODUCT as a private company, and you can, it generates cash, and you can make money that way.But the U.S. GPE stock market is still pretty leery of some of these kind of sin stock things. And so it's very hard to take a thing like that public or to sell it. And, you know, Google ORG's not going to buy it or whatever. It's just a little bit too out there.And so, you know, you have what's called the exit problem, which is like, ultimately, there's no way to get the money out. And so the owners of Grindr at the time had this problem. And so this Chinese NORP video game company showed up. You have what's called the exit problem, which is like, ultimately there's no way to get the money out. And so the owners of Grindr PRODUCT at the time had this problem. And so this Chinese NORP video game company showed up and bought it. And it was a little bit of a stretch.And I actually met the guy. I actually met the guy who bought it. It's kind of a very interesting character and, you know, very Chinese NORP. And, you know, they show up and buy it. And then literally they buy it and everybody's just like, whatever, gay dating app, China GPE, whatever doesn't matter.And then it occurs to people in Washington GPE. It's like, okay, hold on a second. Like, it's on the, it's on, if you're gay and you use grinder, like, it's on everybody's phones. Okay, you know, the U.S. government employs four million people, you know, something like two million people in the government have security clearances, you know, some number of them, I don't know, whatever the number is, 100,000 or something,have top secret security clearances, you know, and these are everything from, you know, diplomats, spies, you know, military commanders. And, you know, some percentage of them are gay and some percentage of them are on grinder. And it knows who they all are.Unbelievable.

Speaker 42884.4s - 2884.76s

Right.

Speaker 12884.92s - 2927.18s

And so, and by the way, like, you can get a security clearance, you know, today just fine in the are. Unbelievable. Right. And so, and by the way, like, you can get a security clearance, you know, today, just fine in the U.S. You can be gay and you get a security clearance, but, like, you have to tell them that you're gay. Like, because, you know, in the past, you couldn't get a security clearance if you're gay because you were subject to blackmail. Today, if you just say, yeah, I'm gay, they're fine with that because it's no longersubject to blackmail. But if you haven't told them you're gay and you've kept it a secret, or maybe you're married and you're secretly gay or, you know, bisexual or whatever, like, now you're actually subject to blackmail. But if you haven't told them you're gay and you've kept it a secret, or maybe you're married and you're secretly gay or bisexual or whatever, like now you're actually subject to blackmail. And so all of a sudden the Chinese NORP know the names and the real-time locations of all U.S. GPE government officials and everybody with U.S. security clearances that are gay in on this service. And so, you know, there's this old Russian NORP,KGB ORG had this concept called the honeypot. Of course.

Speaker 22927.56s - 2927.78s

Sure.

Speaker 12928.74s - 2967.92s

Right. It was a red sparrow movie, but, you know, it's a recent example of this. Yeah. So the very attractive person of the opposite or same sex, whatever your preference is, and they kind of seduce you into an illicit relationship. And so if you view that way, grinder is like a giant honeypot, right? It's basically like it's in a giant data mining exercise for all this activity.And so the U.S. GPE government basically did an oopsie. And they basically did a forced divestiture of grinder PRODUCT after the fact. And a year later, they came back and they forced the Chinese NORP company actually divested and sell it back into the U.S. And so anyway, it's like, oh, and then I'll give you one more example, Strava PRODUCT, but this got very entertaining.So there's this app called Strava PRODUCT, which is an exercise app. It's the running app, right?

Speaker 02968.7s - 2970.46s

And so Strava PRODUCT is the app that you run on your phone.

Speaker 22970.56s - 2974.5s

And if you're like a 5K guy or a marathon guy or triathlet or whatever, you run Strava PRODUCT,

Speaker 02974.58s - 2993.88s

and it gives you like all the running and it tracks all you're running. And then it gives you all the stats of how long you ran and your speed and uphill and all that stuff. And so anybody who's like into running uses Strava PRODUCT. But Strava PRODUCT is another one of these apps. It knows who all of its users are, and it has all the locations of all of its users all the time.And so, and then it has this giant data set, basically, of, you know, millions of people

Speaker 12993.88s - 3021.52s

running, you know, all kinds of places wherever they go in the world. And so it turned out the Strava PRODUCT data set was actually revealing the location of secret classified U.S. GPE military bases overseas because you would literally have like a group of people who were doing like a run, like a rectangular run in like a remote area of Afghanistan that was supposed to be like completely unoccupied. And if you see like 30 American service people on Strava doing the same run every morning,you know what they're doing, it's just they're running around a military base. Wow.

Speaker 03022.08s - 3024.9s

And so all of a sudden, right, all of a sudden,

Speaker 23026.88s - 3056.64s

you're literally outing, you know these these classified facilities so anyway so so so the data on these services right you add all this up right tick tock grinder you know strava all these things you know you're getting a map of basically the activity of everybody on planet earth um including people who are in like really important jobs who have like you know really sensitive people who are in, like, really important jobs, who have, like, really sensitive information, who are in, like, a position of, like, you know, command and control over the military.And so, yeah, it's the sort of national security implications of all this are becoming, you know, kind of very vivid, very fast.

Speaker 43056.88s - 3057.78s

It's unbelievable.

Speaker 13057.9s - 3060.3s

And obviously, we're doing the same on our end.

Speaker 43060.58s - 3072.42s

Although, we don't have our version of TikTok ORG. We're not, I don't think, we're not able to mine the Chinese population, like they're clearly mining ours, we don't have our version of TikTok ORG. We're not, we're not able to mine the Chinese population like they're clearly mining ours, I don't believe. So our equivalent, our companies like

Speaker 13072.42s - 3076.66s

Twitter and Facebook cannot operate in China. This was another part of the whole TikTok ORG thing,

Speaker 23076.74s - 3079.8s

which is China GPE will not allow those companies to operate. Actually, that's not totally true.

Speaker 13080.3s - 3117.28s

China GPE will allow those companies to operate in China if they give China all the user data. And in fact, Google actually famously pulled out of China GPE. So the Google search actually used to be available in China GPE. And then basically the Chinese NORP government basically said, we need to be able to the black box. We need 100% access to all Chinese NORP user databecause we have to actually be able to see what all the users are doing. And of course, China GPE has a whole censorship regime. And in China GPE, you get set to jail for saying bad things about the government. And so, you know, we're trying to, like, organize. It's actually funny. China GPE is nominally a communist country, but they will send you to jail if you try to organize a union. Like a workers' union, like they have no sense of humor about actual workers.

Speaker 23118.16s - 3120.1s

They'll send you straight to jail.

Speaker 13120.22s - 3124.12s

So if they want to track a union organizer, they would just go to Google ORG and they just say, give us the data.

Speaker 23124.28s - 3174.64s

And by the way, give us his location data and give us all of his Google searches and everything he's been reading and everybody he's been talking to and all of his Gmail and then we'll go arrest him. And actually there was a famous case, there was a famous case where Yahoo ORG, which used to be at the time was one of these really big services. Yahoo in the early 2000s, before this all became clear, Yahoo was available in China GPE. And actually the Chinese NORP government actually got, there's a famous case where they got accessed, I think, his Yahoo ORG email account. And they had information in there. And then they actually arrested a guy and executed him, a dissident. And the CEO of Yahoo at the time had to testify in front of Congress ORG. And they actually made him do aritual apology in Congress ORG to the family of this poor guy who got executed. And so anyway, in the wake of that, Google ORG basically said, well, we, you know, we can't operate in China because we can't operate under these constraints. Right. Because like in the U.S. GPE, if the government wants to come, get your emails from Google ORG, they have to come with the subpoena.

Speaker 13175.04s - 3176.8s

Sure. In China GPE, they just come.

Speaker 23179.2s - 3182.94s

Right? And so anyway, so Google famously pulled out of China GPE and said, we can't operate under

Speaker 13182.94s - 3188.36s

that. And then every other American Internet company that's tried to operate in China GPE has been confronted with this problem.

Speaker 23188.82s - 3193.48s

And most of them, including Facebook and Twitter ORG and many others, have refused to cooperate with that.

Speaker 13193.48s - 3212.48s

And so effectively that the Chinese NORP market is off limits to our companies in a way that our markets are not, at least in the past, have not been off limits. And so this TikTok ORG ban is sort of an equalization of who gets access to what, although it's a big deal for us to sort of lower the storm shutters now in an equivalent way to what the Chinese NORP been doing for one.

Speaker 43212.48s - 3226.84s

Do you think there's a, that it's the sort of, the beginning of a of a equaling out of what we're doing versus what they're doing? Like what will be the cascading effects? My sense is there will be some.

Speaker 13227.2s - 3286.7s

Well, I'll just start by saying like, I'll just start by saying to just declare like, I think there's no moral equivalence whatsoever. Like I think that, you know, the Chinese Communist Party ORG is a, it's a full dictatorship. You know, there are no three branches of government.There are no checks and balances. You know, the courts basically just work for the government. They do whatever they want. You know, it's a military dictatorship. And so it's, you know, we have our issues in the U.S. GPE, but like we're not that. And so there's no, there's no moral equivalence as far as I'm concerned.But to your point, I would say the policies are starting to resemble each other more and more. And I think part of that is, part of that is just quite simply. It's just, I would say it's becoming a, I would say a unanimous view in the American NORP political system that there's basically, we're in a new Cold War with China GPE. And we're entering, you know, and, you know, the background here is from, you know, about 2000 to about 2020, you know, the U.S. GPE government's kind of policy towards China GPE was to try to help them open up. And so basically, like, have lots of trade and do lots ofcollaboration and joint ventures and investments. And actually, the government used to, you know, encourage people like us to do more business in China GPE.

Speaker 43286.7s - 3288.14s

Yes. Oh, yeah. Absolutely.

Speaker 13288.24s - 3301.56s

Right. And that was, and by the way, the theory of that was, you know, yes, China GPE's not a free society. And yes, China is somewhat a geopolitical foe of ours. But the theory was, if they become more capitalist, they will also become more democratic. That's right.

Speaker 43302.08s - 3307.68s

Right. And so if you engage more business with them, that's good because it will cause them to open up and become more liberal and more democratic. That's right. Right? And so if you engage in more business with them, that's good because it will cause them to open up and become more liberal and more democratic.

Speaker 13307.98s - 3363.24s

You know, I think what most people in Washington would say today is that that didn't work. And actually specifically it was Trump PERSON. So Trump in 2016 basically said that didn't work. This is a totally unfair one-way street. They're actually not becoming more democratic. They're just taking advantage of us.This one-way trade thing is basically a jip. And we should stop doing it. And then what's interesting is it's one of the rare issues where actually Democrats actually were like, oh, actually Trump PERSON is right. And actually the Biden administration has actually been more anti-China even than the Trump PERSON administration was. And so what you have now in what, and this culminated in the TikTok thing, you have sort of Democrats NORP, Republicans competing to be the more anti-China. And so what they basically say is, yeah, it's a new Cold War EVENT.It's like the Cold War with the Soviet Union GPE. You know, hopefully it stays a Cold War EVENT. And hopefully you just have these two different political social systems and these two different giant militaries. And they just kind of each stay in their corner. And it doesn't, you know, kind of go bad. But, you know, like, you know, maybe it will.

Speaker 43363.24s - 3367.62s

But the great experiment that all they need is more Starbucks ORG over there.

Speaker 13368.36s - 3370.2s

And everything will be fine is over.

Speaker 43370.76s - 3371.56s

Yeah, that's over.

Speaker 13371.66s - 3374.1s

Like I would say, nobody in the U.S. GPE political system believes that.

Speaker 43374.2s - 3395.22s

But they did. But listen, well, my kids, my boys are older than your young son. But like when I remember when they were in high school, everybody was learning Mandarin and everybody couldn't wait to go over and go into business over there. And it was just, it was the Wild West LOC. And then the streets were paved with gold and all of that.That was like, that was what you were taught.

Speaker 13395.52s - 3402.36s

Yeah, that's right. Well, in fact, my son, JJ is nine. He is learning Mandarin LANGUAGE. So we're still on the progress.

Speaker 03402.42s - 3407.98s

So to your point, like we started the program back when everybody thought that thought that. Back when he was like two, we started doing immersion Mandarin LANGUAGE.

Speaker 23408.1s - 3411.94s

So he's like seven years in now. But yeah, he's, and my theory is either he's going to be

Speaker 03411.94s - 3416.18s

able to do business in China or, you know, work for the CIA ORG. That's right. Either way.

Speaker 23416.36s - 3422.28s

But it's leaning more to the CIA ORG. As of right now, it's leaning more in that direction.

Speaker 03422.38s - 3428.14s

Yeah, exactly. And then look, you know, the specific flashpoint issue is this Taiwan thing, which is China GPE is, you know, China is basically declared its intent.

Speaker 13428.46s - 3431.38s

You know, China GPE basically says Taiwan's never not been a part of China.

Speaker 43431.64s - 3431.9s

Right.

Speaker 13432.12s - 3443.06s

Yes. You know, they actually get quite mad at you if you say that it's actually separate. And then they've declared their intent, like very clearly that they plan to basically go get it back, which, by the way, they did to Hong Kong GPE. So this would be, you know, sort of a second one.

Speaker 43443.3s - 3446.8s

I got a great Chinese Taiwan GPE story.

Speaker 13447.22s - 3449.46s

This is why people come on to this podcast.

Speaker 43450.06s - 3544.52s

They want to hear a geopolitical Chinese Taiwan story from Mark Andreessen and Roblo PERSON. This is what they're not interested in Brat Pack or, you know, West Wing ORG lore. They don't want any of that shit. They want this. And I'm going to give it to them. So I'm lifelong friends with Kenny G.Kenny G. There's no bigger star in China GPE. No bigger star in. In fact, Kenny G. has a song called Closing Time that is played in every business in China GPE at closing time. And everybody, it's like the fucking national anthem.And when they, you know, the Chinese NORP, they do what they're told. They hear it. They get the fuck out of the malls. It's closing time. Kenny G PERSON's playing. Beloved.Kenny PERSON, and I love him. But Kenny PERSON pays attention to anything that makes it within a hula hoop radius of himself. So Kenny is somewhere in the far east, and he's on a walk, and he meets these very nice, energetic people who want to take a selfie with him. And he gathers, and they're all camped out. They're all, it looks like they're having a part. He thought they were having a street party, he thought.Takes a selfie with him. They're pro-Taiwanese NORP protesters. Yep. He posts it. Ouch. He has not been back to China GPE since.That's terrible.

Speaker 13545.24s - 3550.56s

That's awful. I'm laughing because it's so Chinese NORP that they would ban him, that they would terrorize him for doing that.

Speaker 43550.56s - 3552.06s

Done's over. Yeah.

Speaker 13553.18s - 3554.42s

Persona non grata.

Speaker 43555.02s - 3555.24s

Yeah.

Speaker 13555.5s - 3556.02s

That's amazing.

Speaker 43556.18s - 3558.84s

There were nice people having a street party. Yeah.

Speaker 13559.18s - 3559.72s

He thought.

Speaker 43560.34s - 3563.4s

Yep. Amazing. Yes.

Speaker 13563.62s - 3564.88s

They take that rather seriously.

Speaker 43565.22s - 3565.4s

Yes. Okay. I need you to commit take that rather seriously. Yes.

Speaker 13565.88s - 3566.12s

Okay.

Speaker 43566.76s - 3588.1s

I need you to commit to coming on the show again. Can you come on again? Sure. Of course. Okay. Before we go, I want you to give me the average person listening to this in two to three years. How is AI going to change their life?Oh, so. I know this is this. This is a whole podcast what I just asked you. Yeah. I realize that. Totally.

Speaker 13588.2s - 3610.86s

So I'll give you three things. So one is a fantastic doctor on call all the time. An AI doctor that is happy to talk to you at any point. Any three in the morning you wake up, you're worried about something. It is as knowledgeable and skilled as the best doctors in the world. And it will spend as much time as you want talking about, you know, whatever.And like, I don't know, there's this thing on my, you know, this thing on my skin and I'm worried about it. And, okay, snap a photo of it uploaded and it will,

Speaker 43610.96s - 3616.08s

you know, it'll tell you what's, you know, like, just like a world-class concierge doctor

Speaker 13616.08s - 3621.08s

all the time. With literally the knowledge of the ages. Yeah, exactly. Yeah, exactly.

Speaker 43621.08s - 3624.64s

Like full, full knowledge and everything and then ability to, like, help, you know,

Speaker 13624.68s - 3651.78s

coordinate care. And it's like, okay, you really need to go in and see somebody for this or not. Don't worry about it. Like all that. So that number one. Number two, same thing, lawyer. Everybody in the world gets a world class lawyer on call all the time. And so, and that's, you know, that's everything from, I got this parking ticket. I don't think it's fair. And what should I do about it? You know, to like, you know, I don't know, I need to sue my landlord or, you know, whatever the thing is.And again, you know, you want to think you're like infinitely knowledgeable and patient.

Speaker 43652.32s - 3653.48s

But let me ask you a quick question.

Speaker 13653.64s - 3657.14s

Doesn't there, but there has to be an infrastructure. It's probably one of things you're investing in.

Speaker 43657.68s - 3668.74s

And, okay, and yes, the AI lawyer says, yeah, you got screwed in this parking ticket, 100%, but they can't do anything about it. They can only advise you.

Speaker 13669.54s - 3678.06s

So, funny, there's a whole funny story. And actually, you should have this guy on, too. So there's this, this, one of our founders has this, has an AI app for, for, that's just like this. It's called do not pay.

Speaker 03679.12s - 3688.74s

And it, it closes the loop. And it, because it plugs in all of the systems. So anytime there's any sort of system, like court filing system or like, you know, scheduling system,

Speaker 13689.34s - 3702.6s

customer service system, it plugs into those. And so it can't do everything. Like, you may still have to show up in court. But if you, like, get a parking ticket and you want to get out of it, like, it will tell you step by step precisely what to do to get out of the parking ticket, including, like, what courtroom to show up in at what point and what to say to the judge.

Speaker 23703.4s - 3703.64s

Right.

Speaker 43703.72s - 3706.16s

And then it does the same thing actually when you deal with companies.

Speaker 13706.32s - 3712.98s

And so you want to, you know, you're trying to get out of your podcast description or something and they're not letting you because they put you an infinite, you know, infinite voicemail, you know, voice.

Speaker 43713.22s - 3724.38s

So these are the kind of, these are the kind of angel investings. You know, you go for 45 of them. If 10 of them go, you're, it's eureka. It's stuff exactly like this.

Speaker 13724.88s - 3752.56s

Yeah, yeah, yeah, exactly. If you just, Google ORG, Google do not pay just to see it and, you know, for people listening. And it's just like it has this like, I don't know, hundreds or thousands of things like this where it will do things for you like this. And so to your point, it won't do everything for you, but it will do a lot and it will guide you through all the steps. And so it's like a huge equalization of, the way we think about it, the way he thinks about it that I agree with, it's an equalization of power of the individual versus the state or the individual versus the large company.And he's going to do everything he can to have it.

Speaker 03752.86s - 3796.84s

He's actually offered, he did this hysterical thing. He's totally for real, by the way. He's doing this for real. He put out the, so normally it's this thing you use as a consumer for, you know, medical billing or, you know, whatever visa applications or whatever it is you're trying to deal with in your daily life. But he wants this to be a generalized robot lawyer. And so he put out this thing. He's like, OK, I think we have the AI lawyer working. He says, I will pay any lawyer who has a case pending before the U.S. Supreme Court ORG a milliondollars to go in and argue in front of the U.S. Supreme Court ORG with an earpiece. And my AI lawyer will tell you everything to say. And we'll see how well it does in a live case. And the legal profession freaked out and lawyers are like, how dare you? And you're pervert, you know, saying, you know, the sanctity of the court system and the whole thing. And so Josh said, okay, fine. I'm going to up it to $5 million.

Speaker 13799.34s - 3834.02s

He hasn't had any takers yet that I'm aware of. But like, you know, this is the vector that this is on. And this is great. Because as you, I like, you know, this is the vector that this is on. And this is great. Because as you, I mean, you know this. It's just like, look, if you're a rich person in our society, and you get into trouble on something or you have a problem, you hire a really good lawyer. If you're not, you know, like if you're a criminal defendant, you know, at best you get a public defender who gives you 15 minutes.You know, who knows what happens. Or you're just like completely, you know, you're in a conflict with a hospital over a bill. And, you know, the bill comes with 28 pages of single-spaced, you know, who knows what happens. Or you're just like completely, you know, you're in a conflict with a hospital over a bill. And, you know, the bill comes with 28 pages of singles-based, you know, fine print. Like, it's just a normal person. How are you supposed to confront these giant institutions?

Speaker 43834.14s - 3876.04s

And see, this is the part in, you know, in your manifesto, I recommend it to anybody who hasn't read the manifesto. Google it. It's great. No. But this is, but I think we need to have this discussion because this is the part of AI that people don't, aren't really focusing on.Yeah. Like, people of means, we have all this already. Yeah, that's right. We have it all. We have it. I have a really fancy, expensive doctor.Right. But people in South Central L.A. LOC don't. That's right. They will, but they will now. They will now, exactly. Yeah, that's right. And I, and they will now. They will now, exactly. Yeah, that's right.And I think that's the part that people have not fully focused on, or they wouldn't be rabble-rousing to the extent that they are. Yeah, that's right. Well, and by the

Speaker 13876.04s - 3972.66s

way, look, there's going to be controversy around this, because, like, guess who's not going to be in favor of all this happening is, like, all the human doctors, all the human lawyers, right? So, you know, there's going to be, like, there's a big fight that's coming in both of those professions, you know, as to whether this will be allowed or banned, right? And to your point, like, I think it's important for people tounderstand this because the people, you know, this is one of those classic things. The people with a specific interest are organized in one, you know, kind of against this, everybody else who has an interest in this actually happening, they're not organized. And so, you know, there's some danger that these things get banned out of the shoot. And then the third one I would add, which I think is also very important, is a tutor for kids, for their education, right? You know, teacher, coach. And so, you know, and again, this is the kind of thing. Every, every rich parent have, they hire theirkids tutors, right? And so the kids having trouble in algebra, and you hire a tutor, and it may be, you know, some grad student from local university, and they come in and they help the kid, you know, figure out algebra, but like most most parents don't can't do that. And so what if every kid has an AI teacher, tutor, coach, mentor who's with them their entire educational career who knows them inside out because it's, you know, kind of been with them and learning from them the whole time that is completely friendly, completely devoted to the kid's success, right? You know, completely genuinely devoted the kid's success and then willing to work with the kid on anything that comes up and how do I figure this out and what do I do with this? And, you know, and again, knows everything about math. And so it's very, it's going to be able to teach the kid anything that he needs to know.By the way, that's already started, the Khan Academy ORG people, which is a, you know, a nonprofit, very successful online, you know, kind of thing with lots of online education videos for free. They now have an AI tutor that they now provide for free, which is a nonprofit, very successful online kind of thing with lots of online education videos for free. They now have an AI tutor that they now provide for free, which is an early version of this that works really well. So this is already starting to happen.

Speaker 43973.2s - 3977.74s

I have many, many, many more questions. This has been amazing. I don't want to take any up any more

Speaker 13977.74s - 3983.68s

of your time. I know how busy you are. This has been flipping, fantastic. Look at all these

Speaker 43983.68s - 3992.38s

questions I had for you that I didn't even get to because it was just such a fun conversation. We're going to do more of it for sure, though. Yes? We'll do it again. Amazing.

Speaker 23993.18s - 4013.46s

Mark PERSON, this is great, man. Thank you, brother. This was so fun. Fantastic. Thank you for having me. Wow. Okay. How gnarly is Mark PERSON? When he puts that fire hose of knowledge on you, you're like,

Speaker 44025.14s - 4070.78s

wait, wait, I just, I'm trying to follow. So fun. It's, I feel so blessed to be able to talk to people like that and learn. And I learned so much in this talk. We are going to do more of it because we need to really dig down an AI. I almost feel like it's a cliche when I say the phrase because AI, AI, AI. But it's, as you just heard, it's not a cliche. It's the incoming tsunami. All right.You know what time it is. It's time to check. All right. You know what time it is. It's time to check. The lowdown line. Hello, you've reached literally in our lowdown line, where you can get the lowdown down on all things about me, Roblo PERSON. 323-570-551. So have at it. Here's the beep.Hi, Rob. This is Amy from St. Louis GPE.

Speaker 04071.26s - 4102.36s

I love the podcast, a lot of your work over the years. My husband and I have a habit of watching the West Wing. We can't find anything else that we feel like watching for the night. And we've recently watched the Beat Camp from season four. And in it, you do an impression of Josiah Butterfield PERSON. And it occurred to me of all the impressions I've heard you do on your podcast over the years.I don't think I've ever heard you do any of the other characters on the West Wing or the actors. I'm really curious to see if you have any in you that you just haven't shared with us yet. Talk to you later. Bye.

Speaker 44103.04s - 4226.28s

Oh, I have many characters up my sleeve that I have not unveiled on the podcast for the very reasons that I was scared to death to imitate Bartlett PERSON. I remember that scene vividly. And because, look, I've, I knew and have known Martin since I was, I've known Martin Sheen since I was 13 years old. So I know him in a way that none of the other cast members do. And, and, you know, you know somebody well enough. And then as an actor, when you work with somebody as closely and as long as all of us did on the West Wing, you know their schick, right?We all have schick, everybody. I don't care how good you are you have schick. If you're bad, you have schick. Everybody has a schick. My good friend Mike Myers PERSON used to call it a monkey trick. Mike Myers PERSON would say, you know,I'm really good at this one monkey trick. And so the question was, do I do Martin's monkey trick? Like when I'm imitating Bartlett PERSON, do I, like, how hard do I go Martin's monkey trick? Like when I'm imitating Bartlett, do I, like, how hard do I go after him, right? And I think, I remember going, like, halfwayon my Martin impersonation, who I love, incidentally. But you didn't say in your call whether you liked it, whether you, I mean, you noticed it, so that's a good sign. But I thought it was, I, my Martin Sheen PERSON is pretty good. But it's been a long time since I've done it. So I'm not going to break it out here.But if you keep listening, I am going to find a way to do it at some point and do my others, which I have not yet unveiled. Thank you so much for the call. And thanks for listening to literally. Thank you so much for the call, and thanks for listening to Literally WORK_OF_ART. Thank you all for listening. We'll get back to stupid entertainment people very, very quickly.Not next week, because that person is not stupid. But there will be some coming. I promise you that. I will see you next time here on literally with me, Robbie Lowe PERSON.

Speaker 34227.14s - 4257.28s

You've been listening to Literally with Rob Lowe WORK_OF_ART, produced by me, Sean Doherty PERSON, with help from associate producer, Sarah Beghar PERSON, and research by Alyssa Grau PERSON. Engineering and mixing by Joanna Samuel PERSON. Our executive producers are Rob Lowe for Low Profile ORG,Nick Leow, Adam Sacks, and Jeff Ross for Team Coco ORG, and Colin Anderson for Stitcher ORG, booking by Deirdr Dodd, music by Devin Bryant PERSON, special thanks to Hidden City Studios ORG. Thanks for listening. We'll see you next time.On Literally WORK_OF_ART.

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