Speaker 1: A media.
Speaker 2: Your scientists have yet to discover how neural networks create
Speaker 2: self consciousness, let alone how the human brain processes two
Speaker 2: dimensional retinal images into three dimensional phenomenon known as perception.
Speaker 2: Yet you, somehow brazen lye declare seeing is believing.
Speaker 3: Yes, I do.
Speaker 2: I'm at Zitron. This is better offline. I'm your host,
Speaker 2: by our merchandise. Go to my newsletter. Where's your ed
Speaker 2: dot app?
Speaker 3: Anyway? Fuck all that.
Speaker 2: Brian Kopperman is joining us here in the studio. He's
Speaker 2: the incredible writer, producer, and he's in the Bear a Bear.
Speaker 2: He's a real deal actor. He's also the co creator,
Speaker 2: showrunner and executive producer of Showtimes, Billions and super pumped
Speaker 2: the battle for Uber. Brian, thank you so much for
Speaker 2: joining us.
Speaker 1: Thrilled to be here with you.
Speaker 2: Man. We've of course got Mike drug At, the wonderful comedian.
Speaker 2: And of course you have a book, don't you.
Speaker 4: Mike, Yes, sir, it's called Good Game, No Rematch. Get
Speaker 4: out embarrassing myself with video games throughout my entire.
Speaker 2: Life, wonderful, I'll be embarrassing myself with tech on this show.
Speaker 2: Sherlyn Lowe as well, joining us from mang gotcha hate
Speaker 2: doing shell.
Speaker 5: I am about it down a protein shake hopefully.
Speaker 2: Yes, Yeah, we're just talking about the Ninja Creamy and
Speaker 2: all the various slops.
Speaker 1: They're great Ninja Creamy. I'll tell you there's no endorsement
Speaker 1: out there for any of us. They don't need it
Speaker 1: because people just get these things and they immediately go
Speaker 1: to tiktokh because they want to share how good they are. Yeah,
Speaker 1: they're honestly, they're so good. That's why I have full
Speaker 1: indorse full endorsement.
Speaker 3: This is the Ninja Creamy show.
Speaker 2: Now I'm going to get what's great about this is
Speaker 2: literally any time I mention any product, I will get
Speaker 2: an email from someone being like, here's a post from
Speaker 2: two thousand and three from the CEO in which case
Speaker 2: they shot the door.
Speaker 3: It's like some insane ed how dare you bring up?
Speaker 3: I'm like, I don't know everything. Please tell me.
Speaker 5: Well, Fair Lives bottles have a lot of Dalley's in them,
Speaker 5: so you know that's our that's our thing today.
Speaker 2: Yeah, I just eat like too much yoga. So I
Speaker 2: want to actually start with a really good thing. So, Mike,
Speaker 2: you wrote a really great piece of the Gamer I
Speaker 2: think they went out, Yeah, yeah, very recently is called
Speaker 2: I'm starting to worry this industry has no respect for
Speaker 2: the people who work in it.
Speaker 3: Well, you walk us through.
Speaker 2: The article, because I think it's a good subject.
Speaker 3: Matsa sure well.
Speaker 4: As listeners may or may not know, Microsoft recently laid
Speaker 4: off about nine thousand people, most of which were in
Speaker 4: their gaming department. Simultaneously, they were claiming that their gaming
Speaker 4: department's quite profitable and they're making a ton of money
Speaker 4: and everything's going well.
Speaker 3: I don't know if that's actually.
Speaker 4: True, but they are saying that, And they've kind of
Speaker 4: also said that a lot of the money that they
Speaker 4: were paying these employees isn't isn't about losses, it's that
Speaker 4: they want to move this money into AI development.
Speaker 2: Did they say that, Yeah, yeah, that's horrifying.
Speaker 4: Yeah, it's kind of im I mean they didn't say
Speaker 4: that word for word, but it was very implied that
Speaker 4: the budget was you know, they're more focused. That was
Speaker 4: kind of the language. The language was like, you know,
Speaker 4: as we restructure, we're more focused on AI going forwards.
Speaker 2: It's just so ironic, is like video games is one
Speaker 2: of the first real exposures to AI for most people, yeah,
Speaker 2: I remember when Fear came out.
Speaker 3: He won't remember fit. Yeah, it was one of the first,
Speaker 3: one of the first.
Speaker 2: It was the first time a guy would like shove
Speaker 2: his head over and look around before just jumping up
Speaker 2: and getting shot.
Speaker 1: Yeah.
Speaker 2: It's just the reason this really spoke to me, other
Speaker 2: than in fact it's very well written, is the I
Speaker 2: feel like this is the central problem with a lot
Speaker 2: of tech, entertainment everything right now, where it's like the
Speaker 2: people at talk and you make this.
Speaker 3: Point well in the article.
Speaker 2: Yeah, the industry is the problem because the industry is
Speaker 2: not being piloted by the people creating right exactly.
Speaker 4: I mean, you know, and it's a problem that also
Speaker 4: extends to the you know, Hollywood, which I also work in.
Speaker 3: Because I'm famous. No, that's not true at all.
Speaker 4: But it's this problem that, like, you know, a lot
Speaker 4: of the decision makers are not as close to the
Speaker 4: product as they used to be. Yeah, I mean, I
Speaker 4: mean you could even say the same same for things
Speaker 4: like Boeing, where you know, you don't have engineers running
Speaker 4: the department anymore. You have business people who've been brought
Speaker 4: in because they're good at checking well track alliance exactly exactly,
Speaker 4: and you know, these people are far away from the product,
Speaker 4: they're far away from the development of it, so they
Speaker 4: see these you know, workers as numbers on a spreadsheet.
Speaker 4: And for better or worse, video game development is a
Speaker 4: very long process. It takes a lot of time, it
Speaker 4: takes a lot of money.
Speaker 2: It's getting longer. It's getting longer, yeah, horizon as well.
Speaker 4: And so it's you know, very easy for these companies
Speaker 4: that are looking for a short term you know, next
Speaker 4: financial quarter.
Speaker 3: Boost to go.
Speaker 4: We fired all these people and this product wasn't going
Speaker 4: to come out for two years, so it really doesn't matter.
Speaker 2: And that's the thing with Microsofts well they've that's that
Speaker 2: they've laid fifteen thousand people this year as well. Nuts
Speaker 2: and it is the money really even going an It's
Speaker 2: just so confusing. But you're seeing everyone with Hollywood. There
Speaker 2: was the Acme versus Coyote thing. Yeah, sorry, Coyote vusus
Speaker 2: Acme thing where they just like multhbuled it releasing it
Speaker 2: happily mouth bolded movie. Yeah, to save on taxes. I
Speaker 2: feel like that shouldn't be a loophole.
Speaker 3: I hate that loophole.
Speaker 4: I hate the idea of that loophole. I mean, it
Speaker 4: almost reminds me of that loophole from and Brian. You
Speaker 4: could maybe correct me on this, but remember like in
Speaker 4: the nineties they made a Fantastic Four film they weren't
Speaker 4: going to release just so they could maintain rights for it,
Speaker 4: because the rights for it were you have to make
Speaker 4: a movie to keep the rights, you don't have to
Speaker 4: release it.
Speaker 1: I don't remember that exactly though, now that you say it,
Speaker 1: it rings a bell, but I don't have particulars on it.
Speaker 1: But I think what you're talking about really the answer.
Speaker 1: I agree completely as you diagnose it with how depressing
Speaker 1: it is. But to me, these things feel like a
Speaker 1: system's response, like complexity theory and system well, they're like
Speaker 1: systems responses to what's happening in the world, as opposed
Speaker 1: to feeling like because I think it's easier for us
Speaker 1: to look at the human being and go that motherfucker,
Speaker 1: and that may be a motherfucker. But another possible answer
Speaker 1: is that from a far remove, like something's happening right,
Speaker 1: and when this thing is happening, it gets into quantum theory.
Speaker 1: But it is a complexity system's response to this giant
Speaker 1: change of artificial intelligence, having certain capabilities and all of this.
Speaker 1: You can look at all of it, and I mean,
Speaker 1: we've seen people who had one set of beliefs for
Speaker 1: so long and on the record in your industry, completely
Speaker 1: switch and they may think that's an autonomous decision they're making.
Speaker 1: But I found a little bit of solace by reading
Speaker 1: about complexity theory because that for me, offers a potentially
Speaker 1: more not hopeful, but sort of a more complete understand.
Speaker 2: You're saying, like a systemic response to conditions. Because I
Speaker 2: don't know about the AI capability side, but the existence
Speaker 2: of capabilities potentially being there makes sense. In the they're
Speaker 2: all trying to reconfigure for a future they don't know
Speaker 2: if it's actually there. The general AI doesn't seem to
Speaker 2: do it, but the potential of that, the idea of it,
Speaker 2: is motivating them so much. Microsoft of all people as well,
Speaker 2: should know how little money's actually being made from this,
Speaker 2: considering out the thirty.
Speaker 1: So that's it, Yes, But executives, honestly, because I've studied
Speaker 1: these people so much and written about them much, and
Speaker 1: I understand how venal they are and how short term
Speaker 1: they think at times. But they're also I think looking
Speaker 1: at data that we don't have very often, and they're
Speaker 1: trying to forecast out a long time.
Speaker 2: Why do you think they have that we don't have though,
Speaker 2: because like with Microsoft for example, and I have probably
Speaker 2: studied such in the DELLA too much at this point.
Speaker 2: I really I learned too much about the growth mindset
Speaker 2: and Karlyn Dweck and all of that nonsense. But the data,
Speaker 2: if the data is there, they're acting very peculiar about
Speaker 2: the data because they're only making thirteen billion dollars this
Speaker 2: year from AI. Ten billion is a ur ur I
Speaker 2: was from open Ai, burning giraffes and whatever they put
Speaker 2: into the machine for chat GPT. But it's it feels
Speaker 2: almost like they are reacting to what they hope will
Speaker 2: happen or what may happen. I'm just trying to lad
Speaker 2: it might just.
Speaker 1: Be when when everyone reacts to quarterly like the problem
Speaker 1: our business, the entertainment. The thing is that these people
Speaker 1: are responding to quarterly earnings calls that they have to make,
Speaker 1: and maybe the data isn't about the long term possible,
Speaker 1: maybe the data is literally that we don't know that
Speaker 1: they're looking at is their little cohort of people and
Speaker 1: the exact moment they can exercise which kinds of options,
Speaker 1: some of which they have to declare and maybe some
Speaker 1: of which they are somehow able to flip on a
Speaker 1: different market.
Speaker 2: What Anthropic basically Amazon did with Anthropic, they flip their
Speaker 2: investment into a certain kind of thing they could tax
Speaker 2: the dug.
Speaker 1: I mean, there's no doubt that there's heartlessness, But I
Speaker 1: just because Druckers here, I just want to say, you know,
Speaker 1: even in the most depressing times or in moments where
Speaker 1: the technology the platform seems brutal, people's humanity can transcend it.
Speaker 1: And I remember in some dark days of Twitter, Drucker
Speaker 1: was and it was really amazing man. And I remember,
Speaker 1: you know, you know, I don't know each other well,
Speaker 1: but we've known each other a long wi time, like
Speaker 1: twenty years, and yeah, it's true. And I remember that
Speaker 1: they're where many nights you were like not sleeping that well,
Speaker 1: sleeping at the wrong time, yeah, and like sleeping during
Speaker 1: the day up at night. But keep I remember him
Speaker 1: really like very vulnerably talking about sadness and depression and
Speaker 1: getting people to entrust sharing, and him actively trying to
Speaker 1: like save people in a place where like where people
Speaker 1: were so callous almost by profession on there by like
Speaker 1: everything they wanted to do that right, Well, all everyone
Speaker 1: was at home playing grand theft Auto, which could you
Speaker 1: guys fix that and get the next one out? But
Speaker 1: everyone's at home playing grand theft Auto, uh, and being callous.
Speaker 1: And he was like literally going, let me explain depression
Speaker 1: to you and what you can do and what the
Speaker 1: resources are and why you shouldn't kill yourself, and which
Speaker 1: I think is great. Of course you would lead the
Speaker 1: empathy on this too and look at these assholes and
Speaker 1: think about all the engineers, and it's the right way
Speaker 1: to process it. I just think often it's not a binary.
Speaker 2: No, and that makes sense. And that's the thing I've
Speaker 2: been saying like a lot about the show is I'm
Speaker 2: talking about the pigs in the arsholes and the skumbags
Speaker 2: and all the different names and the voices I.
Speaker 1: Do for them.
Speaker 2: But it's also about the fact that there is like
Speaker 2: I'm pissed off case of Kagawa.
Speaker 3: Friend of the show's said this to him a lot.
Speaker 2: It's I'm broken hearted dramatic because things like what Mike did.
Speaker 3: Actually one of the reasons every day and.
Speaker 2: Gadget as well, is it's like Yeah, there are a
Speaker 2: lot of these financial horrors in there, but there's fun,
Speaker 2: dorky shit online. Still, there's still one Like most of
Speaker 2: my friends are from the internet, you know. It's like
Speaker 2: I'm like the drill quiet crying. It's like being on
Speaker 2: Like it's like like everything I got is through emails.
Speaker 3: But I still think there is a lot.
Speaker 2: Of joy in this And I think the central thing
Speaker 2: about your article now is just like beneath this capitalism
Speaker 2: crush is actually some really like wonderful things being built.
Speaker 2: There are still wonderful games being built. Yeah, there's like
Speaker 2: an entire economy on Minecraft, for better or for worse
Speaker 2: about selling mods and stuff. There are people on roadblocks
Speaker 2: other problems with roadblocks obviously, who are like building games
Speaker 2: in there and selling them. There's still some cool shit
Speaker 2: happening in tech, just being in with because every three
Speaker 2: months someone gets upset at them.
Speaker 4: Or finds a new way to make money off it,
Speaker 4: which you have to you know, shove into a new category,
Speaker 4: but the new thing.
Speaker 5: To chase, right that's where it is right now. I
Speaker 5: think that what you were talking about, the like macro
Speaker 5: picture of everyone sort of having that reaction, and I
Speaker 5: think we will course correct in time. I think we're
Speaker 5: right now at that stage in history where it's not
Speaker 5: as Cotton dried to me as the NFT crypto sort
Speaker 5: of bubble, where like it was clearly about criminals.
Speaker 1: Yeah, it was walking people.
Speaker 5: Over, knowing right, And I'd argue that on some level
Speaker 5: these are criminals. There are criminals that play in this
Speaker 5: scenario right now. I will say that with what Mike
Speaker 5: was writing about in your article, the Microsoft thing was
Speaker 5: all the more like I think when my team saw
Speaker 5: the news last week, my instant reaction was, didn't they
Speaker 5: just ratify a union contract? Was like their first ever
Speaker 5: in the US? Too like to be saying that on
Speaker 5: one hand, we really care about workers rights and really
Speaker 5: want to protect workers, and the other you're like, and
Speaker 5: those are their quality people, right And now we're like, oh,
Speaker 5: game developers, man, nine thousand of you can go because
Speaker 5: AI n PC's are all the rage right now and
Speaker 5: they really make a lot of sense. A m PCs
Speaker 5: never said a bad thing, never said anything.
Speaker 2: That was demo last year?
Speaker 4: Was it this year?
Speaker 5: I can't remember.
Speaker 2: They've done too and video wheels out at demo would
Speaker 2: be like the generative AI NPC's here and within one
Speaker 2: day someone has made it says layah or like it's
Speaker 2: just said something in spane. Microsoft tay was the twenty
Speaker 2: sixteen AI bought that learned from the Internet to be racist,
Speaker 2: like one of a proto Mecha Hitler situation.
Speaker 4: Oh that was Grock Yeah taal that the Microsoft bathroom
Speaker 4: Yeah from twelve or something.
Speaker 3: I forgot about that.
Speaker 5: But the thing is, back to Brand's point is that
Speaker 5: this keeps happening and then we keep course correcting back
Speaker 5: like it feels like there is a system's response and
Speaker 5: Ed I think you're looking for the joy. I wouldn't
Speaker 5: use the word intervening or interfering. I would say it's noise.
Speaker 5: And the way for companies and people existing in this
Speaker 5: industry to deal with that is to focus on what
Speaker 5: you think is good. I find the irony in saying that,
Speaker 5: which I think these tech bros that you're referring to, Brian,
Speaker 5: they're also trying to focus on what they think it's good,
Speaker 5: so they're cutting out noise from their perspective. And I
Speaker 5: don't know it's that movie that was just released featuring
Speaker 5: those four dudes in the Mountain Lodge.
Speaker 1: Oh not out Head Mountain.
Speaker 5: Mountain Head, mountain Head. Yes, so it feels like that.
Speaker 5: It feels like everyone's got their little bubble, which is
Speaker 5: also at the same time created maybe and supported by tech.
Speaker 5: And if we continue to operate in silos, I don't know.
Speaker 5: I feel like if we.
Speaker 1: Only if we only think of those and often they
Speaker 1: are men in those roles. They're not all, but often
Speaker 1: they are. If you think of some of those you said, bros.
Speaker 1: But if we only reduce them to those guys running
Speaker 1: around trying to kill someone in a song where I
Speaker 1: think in a way it allows in a way, it
Speaker 1: allows us to like not worry about them because we
Speaker 1: can do them.
Speaker 3: Moll right, that's fair.
Speaker 1: Some of them are smarter, like just raw synthesizing power.
Speaker 1: Some of those people, not all of them, they're smarter
Speaker 1: than everyone in this building combined, couple of them. And
Speaker 1: I'm not saying that that makes them good or anything
Speaker 1: in any way good or in any way good for now,
Speaker 1: because even if you say, like I agree with you
Speaker 1: that some of them may believe that they're doing this,
Speaker 1: that they're doing good, right, But if they're thinking in
Speaker 1: a thousand year chunks, that's really bad for You've all
Speaker 1: said this and you've all I think is amazing. And
Speaker 1: he said, well, the problem is historians like me. He goes,
Speaker 1: you may look at it now. He was on a podcast.
Speaker 1: He said, you may look at it now and say,
Speaker 1: but those things worked out. Okay, look where we are.
Speaker 1: But as a historian, I have to look at the
Speaker 1: cost of human life. Yes, that happened for all the intervals,
Speaker 1: all the little intervals to get from there to here.
Speaker 1: And that's really what you guys are just talking about. Rightly,
Speaker 1: so is all the you know, the devastation in the way.
Speaker 1: But but can I just because you might might be
Speaker 1: so jaded, but do you not think AI is like
Speaker 1: mind bogglingly great?
Speaker 3: It's nice.
Speaker 5: I can see the valance. I think it's like far
Speaker 5: off you.
Speaker 1: Don't wait, you really I think it's like the single
Speaker 1: I think it's why the single greatest invention in my life.
Speaker 5: What is what is your favorite thing that has done?
Speaker 1: I think the ability to have super high level conversations
Speaker 1: about really esoteric about systems theory, right, you know it's
Speaker 1: correct in them? Well you can, well, you have to
Speaker 1: do a bit of work.
Speaker 2: I don't want to talk to something that I have
Speaker 2: to verify constantly I talk to people.
Speaker 5: Well, you have to do that with people to some extent.
Speaker 5: You can't trust everything you feel about.
Speaker 1: The automobile or is the horse drawn carriage still your thing?
Speaker 2: No, I'm just saying, no, I'm wondering what the point is.
Speaker 5: It looks very uneasy, right, I mean the point?
Speaker 1: No, I just have jokes in my head.
Speaker 3: No, I'm well, because I.
Speaker 1: Think you can decry the industry and the way people
Speaker 1: are using it. And I guarante I'm pretty sure I
Speaker 1: was reading Alazer you had Kowski before anyone in this room.
Speaker 1: I mean, how to actually change your mind as a
Speaker 1: book that I was obsessed to give it Christmas gifts.
Speaker 3: I can't take your ds.
Speaker 1: I just it's you gotta take him serious, isn't. I
Speaker 1: mean you have to take one to take that guy's
Speaker 1: brain seriously. He think everything you guys are worried about
Speaker 1: he called out fifteen years ago in detail.
Speaker 2: Okay, I mean, like, here's the thing. The automobile is
Speaker 2: not a comparison because we knew who had to go forward,
Speaker 2: side side and everything like that, Like we had an
Speaker 2: actual use case for that with generative AI. The way
Speaker 2: that these conversations happen and large language models can be
Speaker 2: conversing with documents. It's one of the only use cases
Speaker 2: that is actually remotely useful because you can actually verify
Speaker 2: based on the parts of the document. Having a conversation
Speaker 2: with one of these. Fine, it's a thing. I'm not
Speaker 2: amazed by it because there have been chatbots doing this
Speaker 2: with KMS since like what thirteen, twenty fourteen.
Speaker 4: And the Eliza effect goes back to the sixties.
Speaker 2: Yeah, and Eliza even then, there's a Karen Howe's Empire
Speaker 2: of Ai is a great thing about Eliza.
Speaker 3: What the creator was just like, why is everyone so
Speaker 3: fucking impressed? But it's just like, really, just like, what
Speaker 3: the fuck is this?
Speaker 2: I think what it is is. I am just not
Speaker 2: that impressed by it. Based on the larger discussion. Everyone
Speaker 2: acts like this as the fucking future, and it just
Speaker 2: feels like a growth of the past. Chat GPT has
Speaker 2: become for better or for worst is what Google could
Speaker 2: have potentially been. It's insane the attention.
Speaker 1: I agree with you, but like, okay, I got a
Speaker 1: tick bite. Okay, and you can literally the second you
Speaker 1: get a tick bite, everybody says antibiotics you gotta go.
Speaker 1: If you can't find the thing. I got a picture.
Speaker 1: I put it on there. The AI was immediately able
Speaker 1: to say, yes, I could verify it after because I called,
Speaker 1: I was able to say, this is the kind of
Speaker 1: ticket is, this is the area you're in, this kind
Speaker 1: of tick. You don't need antibiotics. You're not gonna get
Speaker 1: lyme disease. Here's why sent it to my doctor who
Speaker 1: that it's feedback and they agreed they'll be harder to
Speaker 1: do it.
Speaker 2: Why didn't you send it to your doctor before you, Austin, Well.
Speaker 1: He doesn't. His job isn't too like identify what ticket is.
Speaker 3: Oh, oh, sorry, I misunderstood what you said.
Speaker 5: Yeah, I want more clarity on the doctor thing. I
Speaker 5: raised my hand as you were talking because I'm like,
Speaker 5: did you trust the chat GPT answer and leave it
Speaker 5: at that?
Speaker 2: Right?
Speaker 1: Then? I took when it said that, then I searched
Speaker 1: for what it said and compared and it was right.
Speaker 1: But it was.
Speaker 4: Out of curiosity and ed you might be able to
Speaker 4: answer this question. Is that And I don't actually know
Speaker 4: the answer. Is that iterative AI or is that generative AI?
Speaker 2: So we're using chat GPT so that it's a mix,
Speaker 2: so that would be generative okay, and so that would
Speaker 2: still be that And by the way, sounds like a
Speaker 2: use case.
Speaker 3: It is the growth of so what you.
Speaker 5: Say, you know, I was going to say, I think
Speaker 5: I think a version of Google could have done that
Speaker 5: for you in the past two before chat chept. What
Speaker 5: chat gupt, the generative side of it is providing is
Speaker 5: the l M, the natural language interface about pulling a
Speaker 5: lot of different sources of data and putting that together
Speaker 5: for you. That is chat jept. You could have done
Speaker 5: that with Google or I think there were apps right
Speaker 5: that you could do a photo uh sort.
Speaker 2: Of recognition for a while.
Speaker 5: Yeah, and I to my knowledge that parts of Google
Speaker 5: and Google Health researchers with their AI divisions were working
Speaker 5: on apps that could identify different things like skin things,
Speaker 5: so like is that a bug bite or is that
Speaker 5: exemon kind of thing through the pixel phones. I don't
Speaker 5: think they've ever broadly released it, but they were experimenting
Speaker 5: way before chat GPT was even a thing. I would
Speaker 5: argue that I think the LM portion of this is
Speaker 5: more about how it converses with you and how it
Speaker 5: like understands what you're actually concerned about. So if you
Speaker 5: didn't give it the exact words of look up this
Speaker 5: thing and should I see a doctor? Even if you
Speaker 5: didn't input this your doctor request, it might you know
Speaker 5: divine that that's what you realize.
Speaker 3: This is the thing like chat GPT.
Speaker 2: I don't think would have been a big deal if
Speaker 2: Google had actually innovated and search at all, if they
Speaker 2: have something adds to it. Google search has been the
Speaker 2: same for like fifteen twenty years, except worse what you
Speaker 2: were describing their valid its inference. Basically, it's infers the
Speaker 2: understanding from the image and all this and then spits
Speaker 2: out an answer.
Speaker 3: It's the use case.
Speaker 2: I think that in the way you use it that
Speaker 2: was responsible. The problem is at scale that is not
Speaker 2: going to work out so great because.
Speaker 1: I believe you know way more about this than I.
Speaker 2: No. I'm genuinely glad you brought this up because it's like,
Speaker 2: but what about that is extrapolating out to the greater
Speaker 2: AI replacing jobs? Think, because that's where my principal problem is.
Speaker 2: People are taking what is what Google should have been
Speaker 2: in twenty seventeen and turned it into this is going
Speaker 2: to replace half of workers. A quote from Dario Amit
Speaker 2: Day that was fucking made up.
Speaker 3: Which he set off the top of his head. It's
Speaker 3: not a bird.
Speaker 2: Sorry, just getting Wario himself. Oh harrio amitay.
Speaker 5: I think what you're also bringing up, Brian, is that
Speaker 5: there is this marketing I guess problem with AI, which
Speaker 5: is that like AI has existed for a very long time,
Speaker 5: and the current version that everyone's really obsessed with is
Speaker 5: jen AI and generative AI is all about like what
Speaker 5: it can generate for you, using large language models, using art,
Speaker 5: like creating art, creating videos, all of that stuff. Is
Speaker 5: this current iteration of AI we're all talking about, But
Speaker 5: the previous stuff has existed before, and this is all
Speaker 5: like just more of the same. I think that's why
Speaker 5: so many of us in the industry are so frustrated
Speaker 5: with it, because there's a misconception. There's also this idea
Speaker 5: that the jobs that it's trying to replace are in
Speaker 5: that field of coming up with art, music and words
Speaker 5: that are not jobs at APay wall to begin with,
Speaker 5: but be like our parts of our life that we
Speaker 5: want it replaced, right, we want it.
Speaker 1: When I talk about Yodkowski, the reason I do is
Speaker 1: that it is that he was somebody who he's right
Speaker 1: on your side way and his thing always was this
Speaker 1: is not going to be a net good. First, that's
Speaker 1: not even he and I mean I remember, I'm sure
Speaker 1: you remember when astro Teller wrote Ex Jesus. I remember
Speaker 1: reading that book like the day it came out, and
Speaker 1: it really did freak me out about what was possible.
Speaker 1: Now we're not even there yet, right, it even isn't
Speaker 1: where that but that version of Ai.
Speaker 2: And Butowski's he's Awskidkowski.
Speaker 3: Sorry, he's so find him quite distasteful.
Speaker 2: But on top of that, he's a fucking agi dom
Speaker 2: and he's saying he's just yeah, sure if a frog
Speaker 2: had but a frog had wings that could fly, It's like, yeah,
Speaker 2: if the computer wakes up and does this, this could
Speaker 2: be scary. He's one of the few people that seems
Speaker 2: to what you think about what a g I could do.
Speaker 2: But also we're so far more off from it that
Speaker 2: I can't see him as anything but a grift of
Speaker 2: because all he is doing is grift.
Speaker 1: It's just he's been on it long before there was grift.
Speaker 1: He was on it as a nonprofit. No he no,
Speaker 1: I mean, think about what I've written. You think I
Speaker 1: know nonprofit's the matter with your one? Yeah, but he's
Speaker 1: I have a different view. Now, I'm not saying all
Speaker 1: his opinions are sure are correct. What I'm saying is
Speaker 1: that that's somebody who flagged a bunch of these potential
Speaker 1: issues a long time ago, and of course it shouldn't
Speaker 1: and it's horrible that these people in charge are so
Speaker 1: willing to slough off being the moment they think there's
Speaker 1: this much of an edge. But also because of what
Speaker 1: I study in life, I can't be so we've all
Speaker 1: of us who write about this stuff in fiction, right,
Speaker 1: you do it because okay, and you guys have to
Speaker 1: report on something you have to. I can take sort
Speaker 1: of like my partner, I could take what's in there
Speaker 1: and try to dramatize what might happen, and always would
Speaker 1: try to point out exactly that these motherfuckers do all
Speaker 1: this shit. It's not surprising to me. It's horrific, but
Speaker 1: not surprising.
Speaker 3: What bothers me as well with it?
Speaker 2: And I think you're completely right, And also like I'm
Speaker 2: not completely saying everything you're saying is wrong, Like you
Speaker 2: actually have well read on this, which is nice because
Speaker 2: a lot of people who mentioned the AGI stuff don't
Speaker 2: read anything.
Speaker 3: But I think the thing is as well.
Speaker 2: Is so much about this aiag I think is not
Speaker 2: about what it can actually do. Yeah, the best fiction
Speaker 2: about AGI, girlfriend Sarah showed me the kill Switch X
Speaker 2: Files episode. Fantastic AGI episode. It's scary because it's not
Speaker 2: about the people making it. It's about the computer itself
Speaker 2: and the intentions spilling into it. A lot of what
Speaker 2: the AGI discussion now is and it will auto make jobs.
Speaker 2: And that's the last time I'm going to think about
Speaker 2: it before I say, here's anthropic and it's and I
Speaker 2: think what it is is there are discussions to be
Speaker 2: had around what this stuff could do. If AI could
Speaker 2: do the things that they're saying it could do, if
Speaker 2: it could replace jobs, it would be doing it. But
Speaker 2: also it would actually require a change in society. It's
Speaker 2: almost as if they're like they want all of the
Speaker 2: profits from all of the exposure and the ability to
Speaker 2: lay people off without actually doing anything to earn it.
Speaker 2: And it comes back to what you said about the
Speaker 2: people running this shit aren't even trying to build AI.
Speaker 2: They're not Mark Zuckerberg's building a Manhattan size get data
Speaker 2: center to build superintelligence.
Speaker 1: I wonder though, when you say, and you guys ask
Speaker 1: you to this. I wonder when you when when you
Speaker 1: talk about the Google could have done this or should
Speaker 1: have done this, And then it's a great point that
Speaker 1: you made about that it is the way that it communicates,
Speaker 1: because what I wonder is, you're all expert, you're all
Speaker 1: native early adopters, native to not only the Internet, but
Speaker 1: native to tech, and so sure you could you have
Speaker 1: used Alda Vista to do oh yeah, ge for fox sake, baby,
Speaker 1: But I'm saying you could have used all that, but
Speaker 1: for generations of people who aren't literate, in a million,
Speaker 1: billions of people exactly, even if that was possible through
Speaker 1: Google image search. But you ever try Google image watch
Speaker 1: people try to do a Google image searching.
Speaker 3: I agree.
Speaker 1: I'm thinking this is all making it for people friendly
Speaker 1: to them, as you said, it easy for them, and
Speaker 1: I wonder if that's.
Speaker 3: That's exactly what I'm saying.
Speaker 2: That's why people like chat GPT. It's not because it's
Speaker 2: this amazing product, it's because it does what people go
Speaker 2: to Google that's hard.
Speaker 1: But communicating well in an inviting, seductive way is very challenging. Yes,
Speaker 1: So for text people to do that to regular people
Speaker 1: is the amazing thing it's almost when you're saying Google
Speaker 1: invented this tech.
Speaker 2: The attention the twenty seventeen Attention is All you Need
Speaker 2: paper was eight Google scientists.
Speaker 3: I just look this up.
Speaker 2: I thought it was several, but it's like, no, shousea.
Speaker 2: They ended up paying like two billion dollars of character
Speaker 2: just to bring him back. Google had this technology and
Speaker 2: had this movement just been we're going to make inference
Speaker 2: of meaning better exactly what you're talking about, it would
Speaker 2: not be this big story. The thing is they need
Speaker 2: it to be what you were describing our use cases good, bad, whatever.
Speaker 2: They are things that people use it for the actual
Speaker 2: things they're describing on as a PhD level intelligence, it's
Speaker 2: going to solve physics. And it's like, no, it's not.
Speaker 2: But if they say, what if Google Search worked, they
Speaker 2: can't make a trazillion dollar They can't be like this
Speaker 2: is going to be everything we need. We're going to
Speaker 2: build data centers. It's just because what you're describing, Brian
Speaker 2: is the most evil thing.
Speaker 1: In going back to Mike Er, yeah, because I think
Speaker 1: what I think in all these things, what I've learned
Speaker 1: just being curious is to look at the incentives.
Speaker 3: Yes, that's what I mean.
Speaker 1: And Google was de incentivized to disincentivized to make search
Speaker 1: work a bit for the user. Yeah, because of the
Speaker 1: profit agenda, right you should, Oh, they think should make
Speaker 1: a fucking profit. But here's the thing, in a weird way,
Speaker 1: them not making a profit is better for the users. Yes,
Speaker 1: and the Google wasn't. But I'm sure it's all on
Speaker 1: the Google paper that nobody's fucking reading except I'm talking
Speaker 1: about for the user. I'm trying to You're raising these
Speaker 1: amazing questions, but if I try to think about how
Speaker 1: to answer them, it's that these companies are like in
Speaker 1: the early days of social media and all this stuff.
Speaker 1: In the beginning, they try to super serve the user
Speaker 1: to get you addicted to it so that then they
Speaker 1: could But the incentive structure is what you got to
Speaker 1: look at. And obviously Microsoft's incentive structure has been locked
Speaker 1: in for a very long time, and that is for
Speaker 1: the people who have the most stock in Microsoft to
Speaker 1: make the most money one. That's the incentive.
Speaker 5: Struct Google too, to an extent, and that's why they
Speaker 5: had that stuff for that long, but they never because
Speaker 5: they never found a way to integrate it into all
Speaker 5: the different parts of his businesses that matter. That ads part,
Speaker 5: the search.
Speaker 3: Parts do still so they monopoly.
Speaker 5: They just they have a monopoly. They have no reason
Speaker 5: to be. But I don't know if you remember this
Speaker 5: Google Io twenty seventeen, twenty eighteen, even twenty nineteen when
Speaker 5: first show kitchen Sink, which was their version of chat GPT,
Speaker 5: but it wasn't as conversational. It was you can ask
Speaker 5: this app to come up with ways to learn about
Speaker 5: a new hobby or to plan a thing for you.
Speaker 5: Before chat GPC even was known widely to everyone, I
Speaker 5: think it was a I wasn't really even a thing,
Speaker 5: and it just wasn't a chat interface. And I think
Speaker 5: to Brian's point, the incentive that chat GPT has brought
Speaker 5: to people and to my parents, who by the way,
Speaker 5: discovered chat GPT last year, very annoying to me. But
Speaker 5: it's like it's so much easier. It brings them into
Speaker 5: technology in a way that technology used to be kind
Speaker 5: of looking down on people for not knowing things, and
Speaker 5: you deal you do away with that with the chat bot.
Speaker 5: My parents not only like feel so hip now, which
Speaker 5: sorry Mom and dad, you're not, but but also like
Speaker 5: there's people who seek comfort in the companionship brought on
Speaker 5: by AI chatbots like chests differently, they are amazing. They
Speaker 5: dance at their age and I love that. But the
Speaker 5: thing is, if you look at the use of jen
Speaker 5: a I from the last and I think I talked
Speaker 5: about this on that Kevin Ruse episode you're on, but
Speaker 5: the use of chat aih services has to change, right.
Speaker 5: Used to be like very interest based on very search basements.
Speaker 5: Now companionship base as the top few uses. And that's
Speaker 5: why people are drawn to it. And I think that
Speaker 5: my last point that came up really when I was
Speaker 5: like listening to you talk ed, is that like the
Speaker 5: incentive for them to push towards like, yes, let's go
Speaker 5: towards a GI. It's not just like laying off people.
Speaker 5: It's also who can get there first. It's the race
Speaker 5: of like it's like it's the tech AI ego thing,
Speaker 5: that tech the text ceo ego thing, and then from
Speaker 5: the ego standpoint, then they pushed down to profits.
Speaker 1: So many businesses are like so many businesses are already
Speaker 1: sort of the industries are already acting in bad faith.
Speaker 1: Oh yes, yeah, like okay, look at them. Here's here's
Speaker 1: I'll give you, not a youth, like a real industry
Speaker 1: that I think will be transformed by it. And I
Speaker 1: think that's not a bad thing. Is like money management.
Speaker 1: Money management, which is a billions of AI AI already
Speaker 1: can replace delineate between Yeah, though, but well you can,
Speaker 1: you can do that. But I'm saying, I know that
Speaker 1: whole business, That whole business is about a front money management.
Speaker 1: I'm not talking about the high net worth I'm saying
Speaker 1: in general, people who use for their retirement accounts money
Speaker 1: managers well front all that stuff. But within those companies
Speaker 1: they're they're they're front facing language of humans who are
Speaker 1: just trying to keep you invested. They don't know that stuff.
Speaker 1: They are not offering value really, and they're taking his
Speaker 1: big percentage from regular people trying to say it for
Speaker 1: their retirement, and they're bleeding off my and in the
Speaker 1: end they're going I was listening to.
Speaker 2: Like, No, I'm smiling because you were right already this
Speaker 2: was the twenty fifteen through twenty twenty wealth.
Speaker 1: No, I know that all that stuff, but I'm talking
Speaker 1: about even now like big banks, like the big banks,
Speaker 1: I'm not talking about their their AI front. I'm saying
Speaker 1: that I was listening to a talk given by Josh
Speaker 1: Brown is uh and I one of his partners, I think, okay,
Speaker 1: And he was talking about how essentially all of the
Speaker 1: back end of all that stuff, meaning you might still
Speaker 1: have a person talking to the user to but everything
Speaker 1: else is going to be done by I just just
Speaker 1: it is Michael Batnik from his company.
Speaker 2: He was talking because here's the thing with that is
Speaker 2: from my knowledge of basically financial regulation, they don't want
Speaker 2: LLM touching much of this. They there's a lot of
Speaker 2: stuff within financial research happening now with jener I, a
Speaker 2: ton of companies doing like insanely high compute burn to
Speaker 2: do these massive kind of like evaluations of stuff. I
Speaker 2: don't know if anyone wants to touch the money with llms.
Speaker 2: And they've actually been quite resistant to it, partly because
Speaker 2: they don't know how they work, Like they truly don't know,
Speaker 2: I know, the black box thing, yeah, yea yeah, And
Speaker 2: so it's like a lot of these things. Also, when
Speaker 2: are they gonna happen though, because they've been saying this
Speaker 2: for two years.
Speaker 1: But do you think there's a scenario, But do you
Speaker 1: think there's a scenario where this this goes this goes away.
Speaker 3: I don't think it goes I.
Speaker 1: Don't think it's gonna do you think it's going to
Speaker 1: reveal itself as as being fraudulent for what.
Speaker 2: I'll explain, I think you're going to see what call
Speaker 2: him my shot. So I believe that open ai will
Speaker 2: is an ongoing concern eventually go into nothingness.
Speaker 3: Matt Hughes, my editor, believes they'll become a patent. Sal
Speaker 3: I actually think it's an amazing thing.
Speaker 2: I think that what we experience of large language models
Speaker 2: will vastly pull back. I think there will be rate
Speaker 2: limits that, as there will be rate limits on GPT,
Speaker 2: people are going to be horrifyingly sad because those.
Speaker 1: Comparive companions are going to go away, And they're not
Speaker 1: going to go.
Speaker 2: Away, they're just going to be much, much, much more limited.
Speaker 2: And I think that everything we see today the kind
Speaker 2: of and you look in any of the reds behind
Speaker 2: any of the serious like GPT's, they're all kind of
Speaker 2: saying like, yeah, we know that the abundance the free
Speaker 2: ride is over. So no, it's not going away, but
Speaker 2: you're not going to hear about it constantly, And everything
Speaker 2: you use today is going to be so severely rate limited,
Speaker 2: or those companies that are charging for generative AI things
Speaker 2: beneath the surface. All of the API rates behind these companies.
Speaker 2: So the things that you plug in to run the
Speaker 2: models are vastly subsidized by big tech and by the companies.
Speaker 1: Alda Vista goes away and but Google takes over.
Speaker 2: Well, Google Gemini exists, but the Gemini request perhaps don't
Speaker 2: hit the Lelem as much they.
Speaker 1: Have using it as a parallel.
Speaker 2: Yeah, but it won't be this big thing you hear
Speaker 2: about all the time.
Speaker 3: I think you were going to.
Speaker 1: Of course, it'll just be the back end of lots
Speaker 1: of stuff.
Speaker 5: No, it would just be something that sits large skills.
Speaker 2: It's also not.
Speaker 3: Good as a back end. Large language models are not
Speaker 3: good back.
Speaker 1: At they're good at talking to you.
Speaker 2: Can they can divine stuff as well.
Speaker 4: One thing we're kind of circling on the consumer level
Speaker 4: that we're not talking about is it's still a novelty now.
Speaker 3: I think it's going to.
Speaker 4: Be continued to be used. I do think that people
Speaker 4: are going to continue to make lists and scheduling and
Speaker 4: summarize summari like you know, what's a good vacation.
Speaker 2: And they are on device models that we are able
Speaker 2: to do that.
Speaker 4: I just think that right now it's such a big
Speaker 4: deal that everyone's using it because it's cool, because they
Speaker 4: you know, your parents hear about it, because you're told
Speaker 4: you should use it for work. And I do think
Speaker 4: that it'll stick around. I do think there'll be a
Speaker 4: contraction in the sense that you know, it'll be a
Speaker 4: cool thing. But I think in fifteen years it's no
Speaker 4: longer gonna be as funny to produce, like a picture
Speaker 4: of a pig with like Mickey Mouse's head and three boobs.
Speaker 4: And I feel like, now.
Speaker 2: That's a big, big Some comedy is timeless, like, but
Speaker 2: I just.
Speaker 4: Don't imagine that in like fifteen years having the same
Speaker 4: novelty as it does, or five years, ten years.
Speaker 2: If you take away all the headlines, if you take
Speaker 2: away all of the money and you actually look at
Speaker 2: what's there, it is everything. What you're describing is probably
Speaker 2: the most useful thing. It's like, do I know this, Okay,
Speaker 2: this seems plausible. I'm gonna double check it. It's kind
Speaker 2: of like what in Karta could have been. I don't
Speaker 2: even mean that sarcastically. I as a very cool child,
Speaker 2: I was very cool. Would sit them then caught for
Speaker 2: hours reading stuff.
Speaker 3: Because it was kind of good. Why you have access
Speaker 3: to everything?
Speaker 2: And I think human beings a curious so of course
Speaker 2: they're gonna talk to it if it talks back. I
Speaker 2: just think right now, there is no business model. That's
Speaker 2: the biggest one. The biggest one is there really is
Speaker 2: no business model. Ads do not work, ads are not going.
Speaker 2: How do you put you inject ads.
Speaker 3: Within an L and M. Look at what happened with
Speaker 3: grog grok.
Speaker 2: Happened because they tried to make us let's make it
Speaker 2: just how we crank up this racism dial and like,
Speaker 2: how do we mess with this system prompt. But the
Speaker 2: thing is those subtle changes for even advertising will be bad.
Speaker 2: Perplexity's been talking about there and ads for a fucking year.
Speaker 2: Not heard much of that aravant, and it's like, on
Speaker 2: some level, regardless of how useful it is, the economics
Speaker 2: do not make sense. They're nothing like an uber. Uber Yes,
Speaker 2: you well know Uber was a complete fucking and it
Speaker 2: still barely makes sense. They're raising another one point two
Speaker 2: billion dollars, but you can at least tell someone exactly
Speaker 2: what uber is and why you'd use it and it's
Speaker 2: just kind of chugging along through necessity. I don't know
Speaker 2: how necessary. Chat GPT is a've large language model, a
Speaker 2: Google Gemini, and Google is claiming that doing efficiency stuff
Speaker 2: that could lost. I think it will be heavily right limited.
Speaker 1: I'm certain you are all right about the business models
Speaker 1: and the viability of this from a business standpoint. You
Speaker 1: know so much more than I do. I'm learning and
Speaker 1: it's fascinating as a user of it who is not
Speaker 1: on the inside of the business. I my prediction is
Speaker 1: you're dead wrong.
Speaker 4: No, Brent.
Speaker 1: I it's going to become the dominant thing in most
Speaker 1: of society in lots of ways. I think here's people
Speaker 1: are going to use it and it's going to be
Speaker 1: part of them, like William Gibson predicted a really long
Speaker 1: time ago. Like I think that it's fine that. I
Speaker 1: think it's bad at creative things, the thing people think
Speaker 1: it's good at. I don't. It's bad at that. I
Speaker 1: don't think you can write a story. Yet none of
Speaker 1: them can convincingly write a story like drugs are good,
Speaker 1: Like there are lots of that stuff that's not there yet.
Speaker 1: I have no idea. Again, you all know way better
Speaker 1: than I did the science behind it, but you're asking
Speaker 1: about working out before you could. There are ninety five
Speaker 1: percent of people who are trainers can't do as good
Speaker 1: a job of programming, and you could play different aias
Speaker 1: against each other and asking questions.
Speaker 5: That's also ninety percent of them are influencers with no
Speaker 5: serious backgrounds.
Speaker 1: But I'm saying, even if you talk to sign but
Speaker 1: because you can show programming, it can track for it
Speaker 1: can just now you may, you may, And I'm sure
Speaker 1: you're correct. That's not the AI doing it. It's other
Speaker 1: people could have done. But the way I I can
Speaker 1: program and interact with you and allow you to catch up.
Speaker 1: If someone asked me all day long, people are asking me,
Speaker 1: wait the question about programming. Well, I can't program for you.
Speaker 1: I don't know you well enough. But if we talk
Speaker 1: generally about what your goals are, I could definitely talk
Speaker 1: to chat, GBT or Claude and build something that you
Speaker 1: could then iterates.
Speaker 2: Such engine were describing the iterations of such.
Speaker 1: Yeah, but it's packaged in this way. Now go ahead.
Speaker 5: The thing that three of us are going to tell
Speaker 5: you are at different levels. I think it's coming to
Speaker 5: you at the business model. The very like micro right
Speaker 5: and sure, and yeah, that's the way kind of how
Speaker 5: it's got to play out financially, and druggers come in
Speaker 5: with the medium level of the use case and everything,
Speaker 5: and I'm going to tell you that at the top level,
Speaker 5: I draw another parallel for you, which is two things
Speaker 5: come to mind. One is how bitcoin and crypto very
Speaker 5: exciting everyone found in novels y factor and it ran
Speaker 5: for everyone wanted to make NFTs and crypto a thing.
Speaker 5: And then now is kind of dialed back down to
Speaker 5: a less fever pitch and more of a regular body
Speaker 5: temperature pitch. The macro metaphorical level is what I'm going
Speaker 5: to say. I think AI will dial back down to
Speaker 5: that Norman normal regulatory sort of body temperature. And then
Speaker 5: to draw another parallel tinder was everyone was making their app.
Speaker 5: The tinder of this tinder of real estate and we
Speaker 5: were describing is like an interface that works really well
Speaker 5: for something like a use case. The Chad GBT model
Speaker 5: is an interface that works really well for question and
Speaker 5: answer is seeking help assisting you with things that might
Speaker 5: never go away, that might just get built into every app.
Speaker 5: As access to LLMS becomes easier for developers, they'll build
Speaker 5: it in to the Bank of America, Chat Bottle build
Speaker 5: it into everything, and so I think that's where it
Speaker 5: balances out eventually over time, maybe through rate limits. I
Speaker 5: don't know that that's going to be the way. I
Speaker 5: think some consolidation might happen.
Speaker 3: You have right limits own actually accessing your pa R.
Speaker 5: The question back and forth for the people who are
Speaker 5: using chat gubt right or yeah. I think that will
Speaker 5: come too, But I think eventually we're talking like five
Speaker 5: years with Druggers. I think with the rate limits, maybe
Speaker 5: in the short term, but I think even longer term
Speaker 5: than that, we're seeing that might eventually go away. Those
Speaker 5: apps may not even exist stand alone.
Speaker 2: Yeah, and I think I actually don't know if I
Speaker 2: fully disagree with you about everything you're saying. It's just
Speaker 2: the scale of what we're talking about might be different.
Speaker 2: Everyone having a large language model to access. Just saying
Speaker 2: that this is the future we're talking about doesn't really
Speaker 2: change that much. I don't like the economics effect. I
Speaker 2: know I'm going to do the business bullshit thing I do,
Speaker 2: but it's the economic effects are quite limited right now.
Speaker 3: Now.
Speaker 2: If you're saying everyone will have a large language model
Speaker 2: will be hamstrung in some way or what have you. Fine,
Speaker 2: I can buy that for good or for bad. I
Speaker 2: could see that happening. I just don't think that it
Speaker 2: goes much further than what we see today. And I
Speaker 2: think what you're describing is what Google Search should have become.
Speaker 2: And like that was what I remember when Bard came out.
Speaker 3: I wrote about this and was kind of.
Speaker 2: Like, surely what chat GPT is is what search was
Speaker 2: meant to.
Speaker 1: Be, right as the com Brothers said, you know, sure
Speaker 1: if if if a frog you know, had had wings,
Speaker 1: had wings, it wouldn't bump its ass hopping, you know
Speaker 1: what I mean?
Speaker 4: And so and I'll say that, you know, I think
Speaker 4: that even as it's completely absorbed into our culture, we're
Speaker 4: still going to be on the phone listening to an
Speaker 4: AI list medical options, yeah, human, human operator, human, Like
Speaker 4: I don't think that's.
Speaker 2: Going away green seven seven one right, yeah, Like I
Speaker 2: don't think.
Speaker 4: I do think that people are going to be like, yeah, okay,
Speaker 4: I'll talk you through my problems until I hit this
Speaker 4: part with my insurance. And I just want a human
Speaker 4: right right right now. And I don't think that's going.
Speaker 3: Away, No, not at all.
Speaker 2: I actually think we're really more on the same page. Yah,
Speaker 2: it seem because it's like, my whole thing is what
Speaker 2: you're describing is the use case. I think there are
Speaker 2: real harms, but I think we kind of agree where
Speaker 2: the dangers would be. My thing is is that people
Speaker 2: are extrapolating from that to this insane level, like this
Speaker 2: whole they keep talking about agents everywhere. You've got Matthew McConaughey.
Speaker 5: And a But agent is kind of what I'm describing,
Speaker 5: which is like every every service has its own chat
Speaker 5: bot more or less. They're just using different.
Speaker 2: They're just using a different Yeah, And I mean that's
Speaker 2: kind of what like Bank of America already has a
Speaker 2: chat bot and it does it.
Speaker 3: Does not work.
Speaker 2: It's the bottom is when you're trying to search for
Speaker 2: a transaction.
Speaker 1: He's talking about for sure, the human of course we
Speaker 1: all do that. I guess I think it'll fool us.
Speaker 4: That's fair, that's fair.
Speaker 1: I don't think right, I've already fooled a lot of people.
Speaker 4: Very well, people into up killing themselves.
Speaker 1: Oh god, well that's tell your car that old character AI.
Speaker 3: Of course Google paid two billion dollars for them.
Speaker 1: I'm not making an argument that it's this is a
Speaker 1: beneficent as in any way, shape or form. Like Like
Speaker 1: I said, I've been reading about this for so long,
Speaker 1: but I do think that to just sort of That's
Speaker 1: why I brought up the horse and buggy because no,
Speaker 1: the people who wanted the horses right, they were right
Speaker 1: about a lot of stuff about the harms that would do,
Speaker 1: the pollution, the pollution, the noise, the way would take
Speaker 1: us away from our communities, like they were right about
Speaker 1: so much. What they were wrong about was the inevitable
Speaker 1: march of the future in time.
Speaker 5: That's I think the same. Before coming to this podcast,
Speaker 5: I was reading Mike your piece and I was like, oh, yeah,
Speaker 5: are we like in the Industrial Revolution forgetting about the
Speaker 5: agricultural revolution? For getting all the revolutions.
Speaker 1: That came there. Because I've seen it all from when
Speaker 1: I was I remember when AOL showed up and coffee served,
Speaker 1: and I remember mess I was invited on a message
Speaker 1: board where I was fourteen. I'm fifty nine, like this
Speaker 1: guy I knew had a message board in New York
Speaker 1: and had to dial up. And I mean, so I've
Speaker 1: seen this, So I'm an early adapter of stuff, even
Speaker 1: though I'm an old dude, I'm but not from a
Speaker 1: tech side, from.
Speaker 3: A user side.
Speaker 1: Single. This is this single as a just as a
Speaker 1: user meaning I don't know how it works why, but
Speaker 1: I can explain to you why people are so fascinating
Speaker 1: and NFTs I was on. You could find the old
Speaker 1: tweets going calling people buy one? Are you fucking I
Speaker 1: don't know. Studying people is like literally like why I
Speaker 1: started doing what I do. But like, no, of course
Speaker 1: I recognize that as a con from the moment one.
Speaker 5: But this doesn't mean like a con.
Speaker 1: But even when you say the bitcoin things today, yeah,
Speaker 1: I know, so Bitcoin one, NFTs were always huckster devices
Speaker 1: to separate suckers from their money. And look, Theodore Eblin said,
Speaker 1: and David Mammock quotes it all the time. Every profession
Speaker 1: is a conspiracy against the laity, every profession fox over
Speaker 1: the regular. Yes, that's the and there's no doubt about Yeah,
Speaker 1: Mamott was ahead of that by twenty years. But you
Speaker 1: gotta you gotta look at it and not me Mammott
Speaker 1: and then me, but but so uh, you got to
Speaker 1: just understand that it is very active. Sure, people, I'm just.
Speaker 2: Trying to bridge from what you're describing to the automobile,
Speaker 2: which changed everything. I don't think large language models. I
Speaker 2: think they're going to create harms. I think they are
Speaker 2: going to be things that change. But it's like what
Speaker 2: happens now, because what we have right now is basically
Speaker 2: what we've had for two years. If you want to
Speaker 2: email me about reasoning, please do our all email as
Speaker 2: much as you want. But the thing is you look
Speaker 2: at this and people are going, okay, and then this
Speaker 2: will happen. It's like that thing that with an LLM
Speaker 2: that goes and does something really basic. Thing an LLLM
Speaker 2: that you tell to go and do a thing online.
Speaker 2: They are bad, bad at it. There was a Salesforce
Speaker 2: study that sayds like thirty five percent they like it
Speaker 2: was like thirty something percent they fail or that that
Speaker 2: was only the only ones they complete it.
Speaker 1: I don't think I've never asked an AI to do
Speaker 1: a task for it. That's I'm saying. I've never asked
Speaker 1: it to do it. Do one of those agent kind
Speaker 1: of functions. I wouldn't agree with you. I wouldn't well,
Speaker 1: I don't think it's there yet. I mean, for again,
Speaker 1: as a user. But research, I've had good research.
Speaker 5: Done, really well, I mean the AI and jen AI
Speaker 5: has done a lot of good stuff in the medical
Speaker 5: fields too, right, Chrisper and all of that stuff. There's
Speaker 5: been a lot of discoveries about what sort of mutations
Speaker 5: you find in certain types of cancer that like, I
Speaker 5: don't think that done.
Speaker 1: I want to study an industry to consider writing about it,
Speaker 1: I can ask you have to ask good question. I mean,
Speaker 1: it's like in anything else, right, I can ask really
Speaker 1: good questions of an AI and send it, you know,
Speaker 1: for the two hundred dollars a month model one where
Speaker 1: they'll do that research thing. And if I ask it
Speaker 1: to do research and then you can, it'll like it
Speaker 1: will come back and maybe you have to send it
Speaker 1: back three times, but you have the speed and accurate. Yeah,
Speaker 1: but you can very quickly a lot of it because
Speaker 1: you can. Like the booklist thing that I can't fathom
Speaker 1: being that irresponsible, like those idiots who in the paper,
Speaker 1: but you literally all you have to say to them
Speaker 1: is when it presents any kind of list, all you
Speaker 1: say to it is go verify that list. Please.
Speaker 3: How do you know what right is?
Speaker 5: Or myself? I mean I would at some point, but you.
Speaker 1: Go verify the list. It immediately goes, You're right, I
Speaker 1: was hallucinating these three books don't exist. That happens. Then
Speaker 1: you go do it one more time and make sure
Speaker 1: that these titles are available in these stores. Then they'll
Speaker 1: give you links and then you can go look at
Speaker 1: something that you're doing.
Speaker 4: And I think sometimes we're splitting here though, is you're
Speaker 4: both of you are extraordinarily intelligent people who have done
Speaker 4: a lot of research in your life, so you know
Speaker 4: how to do those states. You know how to be like,
Speaker 4: I need to call this up, I need to search
Speaker 4: this make sure. I do think that one of the problems,
Speaker 4: again coming from like the low level consumer level, is
Speaker 4: it's often being marketed as an impartial refer impart.
Speaker 1: You're totally right, You're totally right. It's not that you
Speaker 1: cannot you'll be fucked so bad.
Speaker 2: But most people don't interact with it like you do,
Speaker 2: is what I'm saying.
Speaker 1: Well, but but they can.
Speaker 4: They can, and I agree with you, they can. I
Speaker 4: think it's almost but it's it's.
Speaker 2: They don't lead them to do that. It's not like
Speaker 2: they have things that guide them.
Speaker 3: Right.
Speaker 1: This is really interesting here what you're saying about this.
Speaker 4: Yeah, well, I mean I think that you know, when
Speaker 4: you see people and we all saw the Rock Nazi thing,
Speaker 4: but if you see people on Twitter, they don't use
Speaker 4: they I would say, fewer use it to do not
Speaker 4: see ship as much as they go, hey rock, is
Speaker 4: this true?
Speaker 3: Is this true? Is this true?
Speaker 4: And depending on what fingers, on which scale, the answer
Speaker 4: is different each time.
Speaker 1: But I think I understand why. I mean I did.
Speaker 1: I haven't been on Twitter since Yer whatever that date is,
Speaker 1: so I don't know, but I would never. Of course,
Speaker 1: you can't just say let's go to the ay as
Speaker 1: though that's a final arbiter and it's certainly not today.
Speaker 3: But it's being pransitioned.
Speaker 4: I think that's my problem is it's being positioned that way.
Speaker 4: And I think you're absolutely right. I think you're absolutely
Speaker 4: right how useful it is, especially if you have the
Speaker 4: skill to use it. I think the problem is it
Speaker 4: is being marketed as this is a catch all solution,
Speaker 4: this is a panacea to your knowledge problems, and oh.
Speaker 1: Yeah, you know what I mean.
Speaker 3: Well, it is like.
Speaker 1: Believing rock Star games that that they're going to get
Speaker 1: fucking grant the motto out right. I mean, it's no doubt, no,
Speaker 1: I mean I literally look at the actuarial table. If
Speaker 1: you have to build one on my life expectancy verse
Speaker 1: when the next popperation of GTA, I might lose.
Speaker 3: But here's the thing. Here's the thing.
Speaker 2: Though you're describing the research, it isn't an invalid use case.
Speaker 2: What you're describing is how people use Google Search to
Speaker 2: do research. They pull up a bunch of stuff, they
Speaker 2: go through them, they look at it and they go,
Speaker 2: is this right?
Speaker 1: That's a slog?
Speaker 3: It is a slog? Why that is a slog?
Speaker 1: No, it is not. It's a pleasure. It's not. No,
Speaker 1: you're gonna be honest about it. It is a total pace.
Speaker 2: I should be clear. I'm also I have actually used
Speaker 2: these things. I've genuinely tried because I'm I love my
Speaker 2: dud Dad's Mcgizmo's and I've really I've sat down and
Speaker 2: been like, what I'm I missing?
Speaker 1: You just became Paul McCartney And that was Paul McCartney moment.
Speaker 2: He has not my invite for the show though. No,
Speaker 2: I'm not invited Mecca. My mom would be so happy.
Speaker 3: No, it's just.
Speaker 2: I really feel like this keeps coming back to the
Speaker 2: you were using it in a totally fine way. I'm
Speaker 2: mad at the fact that everyone's like, and this is
Speaker 2: the only thing you'll need. You can fully trust this,
Speaker 2: this is the best thing. The information's the best. You're
Speaker 2: looking at it and going this is a way of
Speaker 2: digging through information and passing stuff and having a conversation
Speaker 2: with the information.
Speaker 1: Always common and in the broad society, yes, the lowest,
Speaker 1: that's the lowest common. But unfortunately, yes, you're right, our
Speaker 1: educational systems really fucked up. Disadvantaged people have no chance
Speaker 1: that Mike went to a school that allowed people from
Speaker 1: disparate areas to get We gotta, yeah, we gotta reform
Speaker 1: the education system, and we don't trust it. Everyone has
Speaker 1: a fair shot, I agree.
Speaker 2: But there's a very base so let's do it. Yeah,
Speaker 2: but there's actually a very basic thing we don't have
Speaker 2: to with that. There should be regulation that says that
Speaker 2: these things need big fucking disclaimers that say, hey, check everything.
Speaker 2: They won't do it because the incentives we discussed, but
Speaker 2: that would actually be I think called the stealing is
Speaker 2: also bad. I think the environmental damage is bad. But
Speaker 2: I think we agree on that.
Speaker 1: It's just Safeguards are always great, But then you gotta
Speaker 1: figure out who decides what those safeguards are and who's
Speaker 1: Like you talk to Bill Girly, he'll talk about regulatory creep.
Speaker 1: So where do you want to I'm just saying, no, no, no,
Speaker 1: I agree with you. He's a smart person and he's
Speaker 1: you know, thoughtful about this stuff. And so how who
Speaker 1: do you want? Do you want to go? I mean this,
Speaker 1: you want the current government? I think the guardrails. Who
Speaker 1: who's to do?
Speaker 3: But here's a very basic god roil.
Speaker 2: It's just a disclaiming that says everything with the general
Speaker 2: if I is blah blah blah, let you.
Speaker 5: Kind of some of them have it now, but they're
Speaker 5: all in preview right, and that's probably what they're coaching.
Speaker 1: Again, they do say right on every single time, every
Speaker 1: single time, every single time I've got today actually for sure.
Speaker 5: Yeah, because they they have been criticized. But to Brand's
Speaker 5: larger point, there are guardrails put in place into a
Speaker 5: lot of these. I'm most familiar with the Geminis and
Speaker 5: the Apple intelligences and the Amazon ones of the world,
Speaker 5: and they their guardrails are around like see Sam Right
Speaker 5: child sexual abuse material, or like not presenting people's faces
Speaker 5: or like trying to avoid photo realism because then you
Speaker 5: get very deceptive, very quickly. You don't see any of
Speaker 5: that in rock. Maybe it depends.
Speaker 3: I just look, I just used the which one does.
Speaker 1: Really it does. But I'm not gonna turn on my phone.
Speaker 2: But I'm like, I'm just like, here's the thing. If
Speaker 2: they're there sometimes and not others, that's also bad. Like
Speaker 2: it's like it's it's because when you've got people who
Speaker 2: are killing themselves, people are having it was miles clear.
Speaker 2: I think it was a rolling stone wrot, this piece
Speaker 2: about people having psychotic reactions. Yeah, I agree this This
Speaker 2: administration I've probably done won't regulating this. But the answer
Speaker 2: being let's regulate nothing is terrifying.
Speaker 1: Well, it's really, but it is confusing because if you
Speaker 1: think about, let's say Facebook, right, there's no doubt that
Speaker 1: Facebook was used in me and mar to uh foment
Speaker 1: a genocide. People were warned inside. Who knows where it
Speaker 1: got to? It is very well documented. How could one
Speaker 1: after the fact it's okay, we know it's really hard
Speaker 1: to sort of figure out these use cases, and then
Speaker 1: she's all social media you have gone away like some
Speaker 1: people think it should be. I would social media feel.
Speaker 3: Better about that.
Speaker 2: If Andrew Bosworth the CTO, Yeah, yeah, yeah, I mostly
Speaker 2: say it for the this, yeah, because also the yellow.
Speaker 1: But if I know I'm a well, that's good. If
Speaker 1: I know he did. He did an.
Speaker 2: Internal letter in twenty sixteen twenty seventeen where he said
Speaker 2: that all things were justified for growth, including a terror attack,
Speaker 2: and that's kind of how they approach everything.
Speaker 1: No, it was monstrous, Like when I saw that Me
Speaker 1: and Mark thing, it made me say, like I should
Speaker 1: never use Facebook. I mean, I think that is as
Speaker 1: bad a thing as I've ever seen.
Speaker 2: I mean literally, this is still an example that and
Speaker 2: Meta's l M allows children and Jeff Horwitz report this
Speaker 2: in the journal allowed children to like have sexual conversations
Speaker 2: with John Cena very peculiar, Like there was like super clear.
Speaker 1: You say with John That's what I say.
Speaker 2: One, it was just John c He's gone to jail
Speaker 2: for one hundred years.
Speaker 1: On the Bear. I was in a scene with John
Speaker 1: lovely guy, and he definitely wasn't doing that.
Speaker 2: No, No, he seems like I'm saying it was the
Speaker 2: voice of John c You're gloud to have pedo conversations with.
Speaker 2: But again it's this lack of restriction because no particular
Speaker 2: technology is evil.
Speaker 3: At it's it's.
Speaker 5: I think what Brian was saying. And I don't know
Speaker 5: if I misinterpreting you, but like it's there is some
Speaker 5: fatigue at seeing these things throughout all the pharmaceutical warnings
Speaker 5: you get the end of every commercial, every warning you're
Speaker 5: gonna get from Gemini from now on, every Apple intelligence warning.
Speaker 5: That's like notification summaries can be wrong sometimes, like sometimes
Speaker 5: you see that I see them on my phone.
Speaker 2: Are no, no, no, I believe you.
Speaker 1: It's I guess what I'm saying. Is that why I
Speaker 1: brought up me and Mara is No, we as a society, unfortunately,
Speaker 1: we default to the convenient, fun.
Speaker 4: Easy way.
Speaker 1: Yeah, that'sactly what we all should have done when face
Speaker 1: And I'm not even blaming exactly like you can blame bos.
Speaker 1: I don't know enough to blame anybody there. We know
Speaker 1: that the technology that Facebook itself was used by these
Speaker 1: generals in me and mar right, yes, and nobody took pause,
Speaker 1: Like I think very few people left Facebook as a
Speaker 1: result of that. I think. So I just don't know
Speaker 1: what the fix is for these problems because we gravitate
Speaker 1: like bees to honey.
Speaker 5: But they're also like tools that can be used as weapons,
Speaker 5: and it depends on the perpetrator and the person using
Speaker 5: these right. And this is an age old question again
Speaker 5: coming back to the industrial and agricultural revolution. This can
Speaker 5: be just a tool for hacking a plant off of
Speaker 5: its huscal. It can be used as a murder weapon.
Speaker 5: Back to AI, can be very informative, very helpful for
Speaker 5: people who need companionship. It can be used like people
Speaker 5: will send me scam texts all the time. The technologies
Speaker 5: keeps keeping up with them and filtering them out, so
Speaker 5: they keep changing their spam. Bad actors are going to
Speaker 5: bad act That's just the way it's going to be.
Speaker 5: What can we do? We can I stop using Facebook.
Speaker 5: I try to educate my parents every single time they
Speaker 5: use a GBT answer with me. I'm like, Mom and Dad,
Speaker 5: stop using that. But then they just keep using it
Speaker 5: because they're the sort of person that's accessible to this.
Speaker 5: They will just use it convenience and they don't want
Speaker 5: to do the extra work of maybe the Google search
Speaker 5: method which you were saying at, or they just want
Speaker 5: something that's easy and they don't care if they get
Speaker 5: it wrong.
Speaker 1: Me. Yeah, I guess I love the idea of you
Speaker 1: using your brains to figure out how to make these
Speaker 1: things safer and more useful as you agitate within the industry.
Speaker 1: I think trying to trying to find a way for
Speaker 1: them to disappear seems all possible. And again, like NFTs
Speaker 1: were obviously going to disappear, but the underlying bigcoin thing
Speaker 1: wasn't because there's too much the moment this election happened,
Speaker 1: the moment this election happened, bitcoin is going to two
Speaker 1: hunch of bitcoin was going because.
Speaker 2: Once about that is we could have stopped crypto. I
Speaker 2: was writing about it at the time. I was, and
Speaker 2: the only one are you going to starve crypto by
Speaker 2: informing people about the inherently criminal aspect that underlies everything,
Speaker 2: the fact that tether is more than likely in the
Speaker 2: hands of multiple different I tried, and I failed, and
Speaker 2: you know what, it sucks, But you try. You can
Speaker 2: put ideas out there, you can see if people pick
Speaker 2: them up. And I mean that's kind of what you
Speaker 2: do there. In the case of crypto, it's such a
Speaker 2: weird thing as well, because it's there, but it isn't.
Speaker 2: It doesn't really do anything other than fun things. Or
Speaker 2: be funded, and it just kind of exists where it's
Speaker 2: just like they kind of they don't even I kind
Speaker 2: of respect the fact they don't even try and.
Speaker 1: Be literally you're talking to Charlie Monger and Warren Buffet's book.
Speaker 1: That's what they always say. I know, but that's what
Speaker 1: they always said. Because of that. That's their whole point,
Speaker 1: that to forget the blockchain. It doesn't really do it,
Speaker 1: you know yet really oh yeah, do anything.
Speaker 2: And the thing is, though there was real money in that,
Speaker 2: which there isn't a generative payer. And I think that
Speaker 2: what's funny is this convenience thing you're talking about may
Speaker 2: actually be their downfa because those five hundred million weekly
Speaker 2: active chat deepert users, the cost of them billions of dollars,
Speaker 2: it's probably all gonna fascinate it.
Speaker 1: It's not as fascinating interesting that they mean their popularity
Speaker 1: is going to destroy. Yeah, those companies, not underlying tech,
Speaker 1: but that the companies themselves, that's fascinating. I'm really like,
Speaker 1: I'm saying, you're teaching me something I had no idea
Speaker 1: about that.
Speaker 2: I'll explain it very simply, which is open Ai last
Speaker 2: year spent nine billion dollars to lose five billion dollars.
Speaker 2: Anthropics spent five point three billion dollars. No, sorry, they
Speaker 2: look they spent like nine seven eight. They spent billions
Speaker 2: to lose five point three billion dollars, of which a
Speaker 2: chunk of that was just given to Amazon for servers.
Speaker 2: It's very fucking weird. They lose money. Their conversion rate
Speaker 2: on chet GPT is awful. So five hundred million, I
Speaker 2: think they have fifteen point five to sixty million paying subscribers.
Speaker 2: They don't publish monthly active users because if they did,
Speaker 2: you could do the math and see it's trash. And
Speaker 2: on top of that, they just can't find a way
Speaker 2: to make money. They so much money. So what's more
Speaker 2: than likely is, yeah, these companies might die. Llllms will
Speaker 2: hang around because there are use cases and Google has that,
Speaker 2: Like Jeff Dino for at, Google is one of the
Speaker 2: least evil tech people. There are actually people there who
Speaker 2: like the tech and give a shit about it, and
Speaker 2: there's more efficiency stuff coming out of Google's models. The
Speaker 2: thing is what we see today I do not believe
Speaker 2: is I think the most annoying scenario is going to
Speaker 2: be the longest life large language model with unlimited access
Speaker 2: is going to be on fucking Meta because of their
Speaker 2: unrestricted tripe that's on every fucking app. But I think
Speaker 2: things like chet gupt are just going to be limited.
Speaker 2: You may still have people who use them in the
Speaker 2: way with the gym.
Speaker 1: But it's interesting what you were saying about. Maybe an
Speaker 1: answer and you think about the industrial revolution is eventually
Speaker 1: is that people are going to have to be trained
Speaker 1: on instead of firing nine thousand, people train nine thousand,
Speaker 1: become prompt engineers, and yeah, become prompt engineers. And the
Speaker 1: fact that they didn't, I mean, look, no one is
Speaker 1: less surprised than me by incentive structures making these motherfuckers
Speaker 1: act like evil. It's completely non caring, you know, monsters.
Speaker 1: But if they can be convinced that there's a profit
Speaker 1: motive in training people.
Speaker 3: It's no profits.
Speaker 1: No, that they can be convinced of it. No, But
Speaker 1: I must be clear though, but event but in all
Speaker 1: these businesses there was no profit until nothing even as
Speaker 1: long did take Amazon to become profitable.
Speaker 2: Amazon took about eleven years with a WS but AWS
Speaker 2: was a concern that reduced costs for Amazon itself to
Speaker 2: run there.
Speaker 1: But in two thousand and a lot of people thought
Speaker 1: it was never going to become.
Speaker 3: Profitable, right, Yeah, but that's not the same.
Speaker 2: Yeah, but the economics computer is, it's completely different economics.
Speaker 5: Ask so, Brian, how much would you pay to keep
Speaker 5: using GBT a month?
Speaker 1: I'm a bad I'm older, and I've done well and
Speaker 1: I've do you know what I'm saying?
Speaker 5: Do you pay anything right now?
Speaker 1: I pay two hundred dollars a month.
Speaker 5: Two hundred a month. Okay, so Google one's like two fifty.
Speaker 3: Do you pay two hundred for.
Speaker 1: The research because for the supercharged researching research on the
Speaker 1: twenty bucks a month one though not the same level.
Speaker 4: That's an interesting thing to point out, too, is that
Speaker 4: you're getting better quality by paying for a higher I'm.
Speaker 1: Aware of it. Seriously, is there a quality difference if
Speaker 1: you look at it? We could yet, oh my god,
Speaker 1: they would tell you there isn't any amount of What
Speaker 1: is the rate?
Speaker 5: So they sell your ship product to make you buy
Speaker 5: them less?
Speaker 1: Well, I don't know if they sell product, but you're
Speaker 1: saying the US rate. I someone told me someone I
Speaker 1: trust a lot, a person who's tech savvy, was like,
Speaker 1: this is when that happened. They used it for a
Speaker 1: while and a couple of months ago, I was in
Speaker 1: a meeting with someone and they were like, if I
Speaker 1: was going to tell you to spend money on anything,
Speaker 1: spend two hundred bucks.
Speaker 3: Want do you want to something crazy?
Speaker 2: Though?
Speaker 3: Yes, they lose money on every two hundred buck a
Speaker 3: month customer.
Speaker 1: I believe you because because I'm using, Because when they
Speaker 1: do that search, you're saying it's burning so much.
Speaker 3: But that's the thing.
Speaker 2: How likely do you think that that will continue because
Speaker 2: the deep research that.
Speaker 1: Well, of course there's a number very soon. I'm already
Speaker 1: at that.
Speaker 5: Yeah, you're very high end of it.
Speaker 1: Yeah, yeah, for sure, double this I would I would
Speaker 1: not pay double that.
Speaker 2: I would not pay And I will be honest. And
Speaker 2: this is not even me being like hate or anything.
Speaker 2: It may not be that cheap because right now.
Speaker 3: It's the big store of my news. Let please head it.
Speaker 2: Look for a two hundred a month power user who's
Speaker 2: already using the losing the money. They lose so much
Speaker 2: money on them that it's like four hundred, five hundred,
Speaker 2: one thousand dollars a month clawed code right now, which
Speaker 2: is slightly different because the way they do context stuff. Nevertheless,
Speaker 2: on the two hundred dollars max user on Claude they
Speaker 2: could be losing. They had someone on ia on Twitter
Speaker 2: they spent ten thousand dollars in compute on a two
Speaker 2: hundred month subscription. These are the majority of power users.
Speaker 2: Power users go nuts, as you well know. This is
Speaker 2: why I'm so pushy on the economics, because what we
Speaker 2: are seeing today, it's like if every uber weighed forty
Speaker 2: thousand pounds and the fuel was giraffe blood. It was
Speaker 2: just like this insane economic And I sound like I'm kidding,
Speaker 2: but the economics are completely bonkers. So as much use
Speaker 2: as you're getting today, I just don't know how practically
Speaker 2: they'll provide that. And they might be cheaper models, but
Speaker 2: the cheaper models and I might not be able to
Speaker 2: do I see me use three Yeah, I've got.
Speaker 1: Yeah, yeah, So which takes a lot. Yeah, sometimes it
Speaker 1: still takes such a long time.
Speaker 3: That's the thing.
Speaker 1: You can have a conversation and that's long.
Speaker 2: How much of this is sustainable long term? And I
Speaker 2: know the business stuff is annoying because you still have
Speaker 2: your experience, which you like.
Speaker 1: No, it's not annoying, it's fascinating. I'm fascinated about the
Speaker 1: whole thing. This is just great.
Speaker 2: It's just the long term here, and I'm talking long
Speaker 2: terms in eighteen months is I don't know if we
Speaker 2: will have deep research at any price point approaching the
Speaker 2: one we'll have in that period.
Speaker 1: Well, the deep research is the only reason anyone should
Speaker 1: pay the money.
Speaker 2: And that's the thing, though, the only reason that people
Speaker 2: should pay is the thing that is not sustainable and
Speaker 2: has no problems. So when you talk about how we
Speaker 2: bring this towards like an AWS situation, AWS is lack
Speaker 2: of profitability was built on infrastructure expansion. It was because
Speaker 2: they were building the rails of cloud rip large. It
Speaker 2: was never in the billions and billions a year with
Speaker 2: no There is no path the profitability here. There was
Speaker 2: one model of open aies that they we can deliver
Speaker 2: to open Microsoft in twenty twenty three, called a.
Speaker 3: Racus, and.
Speaker 2: They failed to do it. They have yet to discover
Speaker 2: a or make because it may not be mathematically possible
Speaker 2: a really good large language model that can do the
Speaker 2: kind of reasoning like that that would be reliable and
Speaker 2: have the web search too.
Speaker 1: And I want to say you do have to when
Speaker 1: you talk about prompt Sorry, I was thinking about this
Speaker 1: when I was learning about complexity theory. I read this
Speaker 1: book by a gun named Neil Tiste that I loved.
Speaker 1: He's professor at at NYU. And I'm not good at physics,
Speaker 1: and I really want to understand quantum physics, and so
Speaker 1: I would ask questions, Right, do research on this and
Speaker 1: then find a way to be able to explain it.
Speaker 1: So go read these books, go find documentaries. And then
Speaker 1: I just quickly realized at some point that that that
Speaker 1: the AI hadn't It was clear to me it hadn't
Speaker 1: read something and it doesn't have access. But I could
Speaker 1: figure it out it hadn't, And I just said, like,
Speaker 1: did you look at that video? Like it was a video?
Speaker 1: I go, did you really look at that video that speech?
Speaker 1: And then it immediately went no, you got me there.
Speaker 1: I didn't look at the speech, but I'm gonna go
Speaker 1: now find it a different way. So you do. You
Speaker 1: do have to be vigilant acculturated to having those kinds
Speaker 1: of crazy too, like you have to maybe have advanced
Speaker 1: degrees or have trained yourself. So I'm not this is fascinating,
Speaker 1: right because I take for granted the steps I take
Speaker 1: for granted to and make my way through the world.
Speaker 3: Yes, and.
Speaker 1: Like the way that I would interrogate something like that
Speaker 1: to get to an answer that's useful.
Speaker 5: Yeah, as opposed to maybe my parents would be like, oh, okay,
Speaker 5: you watched that video.
Speaker 1: Okay, okay, and they might get wrong information from this.
Speaker 1: I can't argue with that. You're right about it.
Speaker 2: And I think that a lot of this grand theory
Speaker 2: of this comes down to I think people have a
Speaker 2: lot of questions and not a lot of people to
Speaker 2: ask them to questions about their life, how they're feeling.
Speaker 2: Then I think it's answer with the medical side, where
Speaker 2: it's it's quite hard to ask a doctor a question
Speaker 2: in any country, it's hard to know whether they and
Speaker 2: also doctors regularly make you feel annoying. I'm not talking
Speaker 2: about my doctor.
Speaker 3: He loves me.
Speaker 2: But you can't go to a doctor regularly with little questions.
Speaker 2: They don't have the time because they must maximize profits
Speaker 2: or they are busy one of the two. Yeah, And
Speaker 2: ultimately we are sitting there going I've got this weird
Speaker 2: rash or like I might leg itched in this place
Speaker 2: in the same day three days running.
Speaker 3: What could that mean? And you can't really google that.
Speaker 2: It's just you're dying but you can't really google that,
Speaker 2: but chat, GPT whatever can do an impressive impression of it,
Speaker 2: or in your case, Brian and I think this is
Speaker 2: reasonable lead you in a direction towards like a male
Speaker 2: clinic article about a particular things, something you could raise
Speaker 2: to your doctor. That makes sense. People are lonely, people
Speaker 2: just have weird questions. And I think that there is
Speaker 2: partially a bad cybe where it's like everyone wants everything immediately,
Speaker 2: we must have everything we want immediately. But also people
Speaker 2: are curious, and we are more connected as people. We
Speaker 2: are more decentralized as people. We don't meet people we
Speaker 2: don't have We are by at scale, overworked, underpaid, so
Speaker 2: we don't have the time to be generous with our time.
Speaker 3: Yeah.
Speaker 1: I'll give you one other use case though, because and
Speaker 1: it goes to the question of training. Training, But you
Speaker 1: could use this for you said, your parents dance or whatever.
Speaker 1: So I'll tell you that if you are somebody who
Speaker 1: is all used like deadlifting or squatting with a bar bell.
Speaker 1: As an example, if I put a thirty second clip
Speaker 1: into chat GBT and I say please watch this, tell
Speaker 1: me is this form at risk of injury? How should
Speaker 1: I modify it. Is it good enough? What do you
Speaker 1: think about the load of this weight? The answer it
Speaker 1: will give is and I have checked it against like
Speaker 1: the world. The answer will give is outstandings. And that's
Speaker 1: how would you get that in another way? I don't
Speaker 1: think there is. And that's a small example. Well that's
Speaker 1: different than search. There's an export. No, that's I'm searching
Speaker 1: using a video. No, no, it's not.
Speaker 5: The matching is a bit less spe sophisticated in the
Speaker 5: regular Google search.
Speaker 3: Oh I'm saying that.
Speaker 1: No, it's I'm merely matching it against a perceived perfect form.
Speaker 1: It's looking at your female literally, it'll go with your
Speaker 1: femur size. This is the kind of squad that you
Speaker 1: could do if I low bar versus high bar. Here's why,
Speaker 1: here's what this looks like. You're over, I'm agreeing with you.
Speaker 2: I'm just saying that search as a term has grown
Speaker 2: to look at this image and compare it to these sources,
Speaker 2: which is theoretically we'll search.
Speaker 1: But then in the good language, right language, fix how
Speaker 1: to fix it?
Speaker 4: And I worry if you ask a bad question, like
Speaker 4: if you not ask a bad question, phrase a question incorrect?
Speaker 3: Sure, And.
Speaker 4: I'm not saying you if one phrases let's say they
Speaker 4: ask a fitness question, but they phrase it a little
Speaker 4: bit weird, and the answer they get is harmful. It
Speaker 4: almost I'm worried about situations like that. And also it
Speaker 4: feels like we're removing an element of human responsibility or accountability,
Speaker 4: where it's like, well, the machine answered weird, rather than
Speaker 4: like a doctor answered weird.
Speaker 3: And I think that lots of corporations love that. They
Speaker 3: love that because they're already doing it.
Speaker 4: If I if my AI accidentally denies your insurance, it.
Speaker 3: Was the AI, that wasn't us.
Speaker 2: It's the algorithm. It's it's the same algorithmic pass on thing.
Speaker 2: But I think you're right in the that is kind
Speaker 2: of cool. I also have used those three because I
Speaker 2: do pay for this. I'm not a baseless hater. I
Speaker 2: did ask what's the distance between this bottom of this
Speaker 2: photo frame and the floor, and it spent ten minutes
Speaker 2: to give me a completely insanely wrong answer. They're not
Speaker 2: good with numbers.
Speaker 1: Oh fascinating. The other day, in this example, I just
Speaker 1: gave you it said I can't. It just said like
Speaker 1: I can't see, which is good. That was great.
Speaker 3: That should do that.
Speaker 5: That was great, both of you using the same I
Speaker 5: was using three.
Speaker 2: On Chap GBT plus though, So now I don't know
Speaker 2: how I feel about giving Clammy Sammy two.
Speaker 1: Underprive for a month and see what it does.
Speaker 3: Yeah, you can write it off.
Speaker 2: I don't want to write gave two hundred bucks to
Speaker 2: Warriolama day hopes.
Speaker 1: I would love you to do that and then call
Speaker 1: me and say it's the same result.
Speaker 2: No, I would love you to tell me I actually
Speaker 2: really careous.
Speaker 1: I would love you to say to me, dude, that's
Speaker 1: just been twenty bucks the same.
Speaker 5: Then you can say you're one eighty a month.
Speaker 1: Yeah, great news. Please.
Speaker 5: I am what Mike was bringing up I thought was
Speaker 5: going to be similar to the point I had been
Speaker 5: mulling over when you were talking about the training stuff,
Speaker 5: which is that we already deal with due to like
Speaker 5: you know, capitalism or barriers to entry, an influx of
Speaker 5: individuals who may not actually be fully equipped for the
Speaker 5: jobs they purport to do. So, whether it be journalists
Speaker 5: like myself or like again Finnish influencers or trainers that
Speaker 5: say they have whatever types of physical health degrees that
Speaker 5: are just the result of a ten hour course online
Speaker 5: that sort of thing. We're already dealing with the like
Speaker 5: quality dilution of like information coming from sources like that,
Speaker 5: to throw AI into the mix piece like making it
Speaker 5: even worse, like harder than ever to tell what the
Speaker 5: truth is. And I don't know about you all, but
Speaker 5: I find myself gaslighting myself all the time now, regardless
Speaker 5: of like my own life, whether it's the truth in
Speaker 5: the world, whether I'm being too sympathetic to multiple different perspectives.
Speaker 5: I don't know what the truth is anymore. I can't
Speaker 5: tell you what the cold heart scientific truth of anything
Speaker 5: ever is. And that's where it's led me.
Speaker 1: You also have to be willing, I agree with. That's
Speaker 1: a brilliant point. I think one of the things I
Speaker 1: would say to people if someone asked me, how do
Speaker 1: you how should you communicate? Mm hmm, I would say,
Speaker 1: And it's really painful for people because I've seen them
Speaker 1: talk online about what they love about conversing with the eye.
Speaker 1: You gotta say, click every toggle that says be mean,
Speaker 1: tell me the truth, don't tell me I'm smart. Yeah,
Speaker 1: Like you got to suck me rocked it to really
Speaker 1: be withholding in that way if you want to actually
Speaker 1: engage so that so that you're you're not getting gas lit,
Speaker 1: because yes, I agree that this is dangerous. The default
Speaker 1: setting is to gaslight you. You got to actually go.
Speaker 1: I don't need to hear like that glaze you.
Speaker 3: I think the young people.
Speaker 4: Blaze you sure before we run And you didn't hear
Speaker 4: the producer just laugh out loud.
Speaker 1: We talk about just one I think they used to say,
Speaker 1: gle but can we just talk about one positive, purely
Speaker 1: positive tech thing that happened the last week July fourth?
Speaker 1: Who who's on TikTok and knows all about the antipasto party?
Speaker 5: And was it the one that one person went to?
Speaker 1: Yeah, okay, it's the greatest thing.
Speaker 3: Please.
Speaker 2: This is this?
Speaker 1: Okay this They're in Texas. These people have a July
Speaker 1: fourth party. There's a woman she's just moved there recently.
Speaker 1: Her kid becomes friends with someone else's kid. And this woman, Sarah,
Speaker 1: is the parent of one boy, says, come with me
Speaker 1: over to these people party, these people's party. Woman a
Speaker 1: makes the apotheosis of all antipastos out, the greatest salady
Speaker 1: you've ever seen in your life, goes to their house. Yeah,
Speaker 1: and these people are like who's this stranger in our house?
Speaker 1: And they kick her out even though she brought this
Speaker 1: incredible She goes home and gets on TikTok and she's
Speaker 1: crying and she's like, I brought this salad and they
Speaker 1: kicked me out of their hounds. And the entire internet
Speaker 1: that her, yeah, and loves her so much, and it's like,
Speaker 1: it's an incredible story. Everybody I know is like, like
Speaker 1: everybody of all ages, like nieces and nephews of mine
Speaker 1: and then older people older than me are all sending
Speaker 1: and it's an amazing thing. Is a huge community is
Speaker 1: rallied to hate these people and to love her and
Speaker 1: her homemade mazzarella and come grown tomatoes that she brought
Speaker 1: to their.
Speaker 5: House scaling Lo, you saw something else, but no, I
Speaker 5: saw something else. All together, it's really worth But like
Speaker 5: Reddit does things like that, and that's the thing.
Speaker 3: Reddit like this is I liked ending this in the
Speaker 3: post of notes. That's love it. Reddit does that.
Speaker 5: You can say something well, yeah, no, community and social
Speaker 5: forums like that, that's what the Internet is great for.
Speaker 5: And then not a lot of AI as president, a
Speaker 5: lot of that and.
Speaker 2: It's almost read it especially right now has got good
Speaker 2: because it isn't they The CEO keeps thinking of shoving
Speaker 2: it places, but even on the.
Speaker 3: Better offline read nine thousand.
Speaker 2: Now, hey guys, but it's great because I one of
Speaker 2: my biggest stories I wrote recently was on Cursor and
Speaker 2: them falling apart, and it was because someone on the
Speaker 2: Red the forum was just like looking through their stuff
Speaker 2: like a you and everyone had this full conversation about it.
Speaker 2: You've got these people out there in this morass of
Speaker 2: fake stuff or generated stuff or seo stuff, You've got
Speaker 2: genuine people. There is still a joy to all of
Speaker 2: this crap. I love Blue Sky as well, but read
Speaker 2: it has really just I'm shocked.
Speaker 1: Spend a lot of time I read it. I read it.
Speaker 2: I'm shocked.
Speaker 1: And a group someone ever goes on you got to
Speaker 1: pick your on. No, but I'm saying, you know, like,
Speaker 1: but but there where people have a hobby or a thing,
Speaker 1: like whether it's music. You know, you're like I take stuff. Yeah,
Speaker 1: it's great and you must love the like the Claude Reddit.
Speaker 1: Every day someone's like, why does claud you must I
Speaker 1: love our slash Google.
Speaker 2: Yes, I like our slash sas because it's all just
Speaker 2: people like running sass. Know you're thinking of a different
Speaker 2: SaaS one. I'm talking s A A S as a service.
Speaker 3: Yeah, I'm a loser.
Speaker 2: So no, you watch people being like my app has
Speaker 2: been up for six months since made seven dollars. A
Speaker 2: bunch of people are like yes.
Speaker 5: And there was subs.
Speaker 2: I kind of love them that you've got these niches.
Speaker 2: But I hate to say, I do need to call
Speaker 2: this episode.
Speaker 3: Brian. Where can people find you?
Speaker 1: Oh?
Speaker 3: Instagram, Yes, we'll have a link to you there as well.
Speaker 4: You can find me on Instagram at Mike Drucker is Dead,
Speaker 4: and on Blue Sky at Mike Drucker and by a
Speaker 4: good Game, No Rematch. It is a book that's available digital,
Speaker 4: hardcover or audio with the audio read by myself.
Speaker 5: Hell yeah, I'm at engadget dot com or on threads
Speaker 5: at Sherlin Instagram c h r O I N N
Speaker 5: S c h r M.
Speaker 3: Type in Google the man who destroyed Google Search. That's me.
Speaker 2: I'm ed Zitchohn. Thank you so much for listening as
Speaker 2: ever is recording the wonderful New York Studio and iHeartRadio.
Speaker 2: Danel Goodman of course as our producer. Thank you so much, Daniel,
Speaker 2: Thank you all for listening. Thank you for listening to
Speaker 2: Better Offline. The editor and composer of the Better Offline
Speaker 2: theme song is Matasowski. You can check out more of
Speaker 2: his music and audio projects at Matasowski dot com, M
Speaker 2: A T T O S O W s ki dot com.
Speaker 2: You can email me at easy at Better Offline dot
Speaker 2: com or visit Better Offline dot com to find more
Speaker 2: podcast links and of course, my newsletter. I also really
Speaker 2: recommend you go to chat dot where's youreaed dot at
Speaker 2: to visit the discord, and go to our slash Better
Speaker 2: Offline to check out our reddit. Thank you so much
Speaker 2: for listening. Better Offline is a production of cool Zone Media.
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