Cal Newport on Mythos and Anthropomorphization

In this week’s Better Offline, Ed is joined by computer science professor and writer Cal Newport to talk about the Claude Mythos marketing scam, the lies around AI job loss, and why LLMs shouldn’t talk like they’re people. Please support me by subscribing to my premium newsletter - here’s $10 off your first year of annual https://edzitronswheresyouredatghostio.outpost.pub/public/promo-subscription/84rt762qen Podcast & Videos: https://www.youtube.com/@CalNewportMedia/ Newsletter: https://calnewport.com New Yorker archive: https://www.newyorker.com/contributors/cal-newport YOU CAN NOW BUY BETTER OFFLINE MERCH! Go to https://cottonbureau.com/people/better-offline and use code FREE99 for free shipping on orders of $99 or more. Buy our new “FUCK DATA CENTERS” shirts today! --- LINKS: https://www.tinyurl.com/betterofflinelinks Newsletter: https://www.wheresyoured.at/ Reddit: https://www.reddit.com/r/BetterOffline/ Discord: chat.wheresyoured.at https://discord.com/invite/QUUQUP9szv Ed's Socials: https://twitter.com/edzitron https://www.instagram.com/edzitron https://bsky.app/profile/edzitron.com https://www.threads.net/@edzitron Email Me: [email protected] mailto:[email protected] See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  This is an iHeart Podcast. Guaranteed Human.

• 0:04Speaker 01

  Cash Flow Crunch? OnDeck's small business line of credit gives your business immediate access to funds, up to $200,000, right when you need it. Cover seasonal dips, manage payroll, restock inventory, or tackle unexpected expenses without missing a beat. With flexible draws, transparent pricing, and control over repayment, get funded quickly and confidently. Apply today at ondeck.com. Funds could be available as soon as tomorrow. Depending on certain loan attributes, your business loan may be issued by OnDeck or Celtic Bank. OnDeck does not lend in North Dakota. All loans and amounts subject to lender approval.

• 0:34Speaker 02

  Empower is all about helping you invest well, so you can go out and live a little. And their Free Empower Personal Dashboard shows you your full financial life in one place. You'll be able to see your net worth, monitor budgets, analyze your portfolio, set retirement goals, and more. Whether you're saving for something big, want to treat yourself, friends, or family, or meet long-term goals, Empower helps you see where you stand. You've worked hard for your money, and Empower can help you make the most of it. Download the Empower Personal Dashboard or visit empower.com. Not an Empower client paid or sponsored.

• 1:08Speaker 03

  With LPL Financial, we provide the services to help push you forward. When it comes to your finances, your business, your future, the only question should be, what if you could?

• 1:16Speaker 04

  Paid advertisement. Anika Hendrick is not a client of LPL Financial LLC and receives compensation to promote LPL. Investing involves risk, including potential loss to principal. LPL Financial LLC member FINRA, SIPC.

• 1:24Speaker 00

  We believe in starting with your financial goals, not a formula. At Oppenheimer, we put the full strength of our longstanding expertise to work, understanding your life and your ambitions, and designing the precise strategies that build and protect your wealth with confidence across this generation and the next. Put the power of Oppenheimer thinking to work for you. Wealth management, capital markets, investment banking.

• 1:55Speaker 05

  Call Zone Media.

• 1:58Ed Zitron?

  Hello and welcome to Better Offline. I'm, of course, your host at Zitron.

• 2:14Ed Zitron?

  As ever, support your neighborhood Zitron by subscribing to the premium newsletter. Discount link in the episode notes, of course. Buy a t-shirt, download a blog, whatever it is you want to do, okay? It's not up to me what you do. But today, I'm joined by the incredible comms side professor and commentator Cal Newport. Cal, thank you for joining me.

• 2:31Speaker 07

  Always a pleasure, Ed.

• 2:32Ed Zitron?

  So I kind of wanted to start with, I asked you for a quote a few, like a week ago, maybe two weeks ago, I can't remember how time works anymore. But it was around the way the reporters cover AI and how it seems that a lot of the reporting is kind of directionally true rather than actually true.

• 2:50Speaker 07

  Yes, and I want to add something to it since. So I've been thinking about that quote. Yeah, I've been thinking about it since. So what I said, if I remember that quote properly, what I was saying is I was picking up a lot in the reporting on AI that you would lean into a story without having necessarily verified that the details are true and that this is what's actually going on. Say with the new AI model, you would lean into it anyways because it was what I called directionally correct. It makes the general point that you see it as your job as reporter to make, which is, hey, you need to be worried about this or this is a big deal, right? And so I think that is a problem. There's another issue I'm seeing, though. I've sort of been refining my thinking on this.

• 3:31Speaker 07

  I'm also wondering if some of what I'm seeing in some of the reporting on this is just the embrace of the form of, I'm going to give you a stress wave with no relief. Just like we're all going to take turns, just I will choose an area you haven't thought about. How about mathematics are going to go away? Mathematicians are going to be, okay, I'll take that one. Yeah, let's go.

• 3:54Ed Zitron?

  So it's like negative clickbait.

• 3:57Speaker 07

  Yeah, but there's this weird sort of passivity to it where it's like, I'm just going to sort of, I call it like head shaking doomerism. You're just like, it's us, this field's just going away. What can we do? Like this, this sort of like passive head shaking. It's a very specific style. You don't see a lot of other reporting historically, I think, that takes on this resignation of, I'm just going to make the case that like, you're screwed and then kind of give you a shoulder shrug and then we're going to drop the mic and walk off. And I'm kind of getting tired of this. Like, I think there is a cost. Too stressing the hell out of people. I mean, I'm getting letters all the time now from people. They'll say things like, I feel like I'm trapped in a cage, just being hit with a wave after wave of stress.

• 4:40Speaker 07

  And there's no outlet. There's no door or possibility of making things better. And I think the CEOs are doing it. And I think increasingly, we're seeing commentators doing it as well. This is not good in many different ways. So I don't, I'm adding that to my list. Some of it's directional true reporting, like they really are worried that people aren't worried enough. And I think it's just sport now. Can you find an area to come in and just write a head shaking article? That's only trying to undermine the existence of this like important human activity or this job or our lives or whatever. It's a, it's a very unusual style that quickly became a standard.

• 5:13Ed Zitron?

  And I, I see it a lot with anything to do with AI and job studies. Like I've been sent this Tufts report where it's like, oh yeah, AI affected or AI. They find these weird weasel words where it's like, jobs that could be at risk from AI at some point. And we put them in one bucket and then jobs that might one day be, we'll put that in another bucket. And there you go. Don't know what we're, like you said, don't know what we're meant to do with this. Don't know what anyone's meant to do with this information, but it's just like, well, there you have it. There you have it. We're all fucked. It's, it's the, it's the end, the job. Even though the data does not say that, like I've read, I think every AI jobs report now, every single one.

• 5:57Ed Zitron?

  And they're all the same. They are all, right now, AI can do this. And then you look at what it says, it's like, it can do law. Well, it can't really do law. It can do one sigma within law, kind of. And even then, isn't really obvious. And the people saying it can do that are partners at law firms that don't write motions or don't do like the grunt work. So it's, it's almost, it's, it feels like the reporters have either given up or are just looking for clicks. And it's hard to tell sometimes.

• 6:26Speaker 07

  This is what I'm trying to figure out because I'm, I'm realizing if it's entirely just, I think this is directionally true. And that's good enough, then they should be way more upset and in the streets and sparking a revolution, right? Like if you actually really believe 50% of the economy was going to be automated, that we're going to have to have government checks just so we can afford to buy the cat food to eat after all the jobs are gone. If you really thought. That our entire infrastructure is about to collapse, that superintelligence was going to emerge suddenly and be a threat to human existence. You want to just write a sort of too cool for school, head shaking resignation article. You would be like, we gotta, where are the John Connors, right?

• 7:09Speaker 07

  Like, we need to get on the cool trench coats and get out there and go against the Skynet revolution. Like, you would be on your feet, you'd be, you know, nothing would be more important to you. So this is the, this is my case about the tech CEOs. I think there, there's a moral hazard that I don't think that we're putting our finger on properly here, right? So you have the tech CEOs in the AI space that are just, they'll just come out and just drop these bombs, like.

• 7:32Ed Zitron?

  Yeah.

• 7:32Speaker 07

  White collar blood, you know, I never actually said that, that's Axios putting words in people's mouths.

• 7:36Ed Zitron?

  That was Axios, I thought that that was a, he definitely, Dario Amadeo, Wario, he did say 50%, but I thought.

• 7:43Speaker 07

  He said 50%, but not.

• 7:44Ed Zitron?

  I thought he said the bloodbath, that's my bad.

• 7:46Speaker 07

  Well, I trust, I, I, this New York fact checkers figured that out for me. But Axios does a lot of this, where they put like, these really quotable quotes in the headlines about articles on interviews or speeches given by AI people, and it turns out the thing in the headline wasn't what they said, it was directionally what they said. But anyways, so they're out there making these big statements, the jobs are going away, the internet as we know it is about to all fall apart because of Mythos is going to have this, this new capability, the superintelligence is coming, I'm, I don't even know what's going to happen. There's two possible things going on here, and both of them are morally bad. One is, which is the one I think is true, which is, this is largely marketing. I, this, this works, it gets reported, it keeps us seeming inevitable and important,

• 8:30Speaker 07

  in which case, that's a huge moral hazard because you are making many, many people, normal people, stressed the hell out.

• 8:36Ed Zitron?

  Actively scaring them.

• 8:38Speaker 07

  Actively scaring them. The other option is you actually believe it's true. Well, this is an even larger moral trap that you've just fallen into because you are now perpetuating something that's going to cause exponentially more harm. You should be the very first person shutting down your company and trying to get the other ones to do it as well. So it's this weird moral trap they've set up where whatever is actually going on here, if they're coming out here saying these things, it is bad. This, this can't possibly, normatively speaking, be the right ethical behavior to be out there saying these scary things all the time, because either you need to be building the barricade, or you're just scaring people for the marketing. Neither of these, I think, is something that's defensible.

• 9:15Ed Zitron?

  I have a third and worst option, which is I choose Axios. I think Axios, there are some good reporters there. I think the leadership over there is disgusting. I think that they are aligning themselves with the companies. I think that what like if you watch, there was a Jim, what's his name, interviewing Sam Altman, these, I think that there is a level of, and I, I would put this across people like Kevin Roos and Casey Newton, these are my words, not Cal's, that they're aligning them, that they're saying, we think this is going to happen and we're here to tell you, great news. This is good news for me, the writer, because I will be safe somehow. I will be fine. You will not. You should be scared, but it's also a good thing because economy, marketing, market, good. And it

• 10:00Ed Zitron?

  is, it's a very incoherent message because it's like to your point, yeah, if this was a virus, like a pandemic, you wouldn't be writing, hey, millions of people are going to die. Well, pretty good, right? Hey, it'll be good. We'll have less people. That'd be good, right? It would be seen as peculiar.

• 10:18Speaker 07

  Someone did write that. Someone did write that, by the way.

• 10:21Ed Zitron?

  Someone did write that?

• 10:22Speaker 07

  They did say, I remember early pandemic, someone did write, hey, you know what? This is good for the planet. Like, hey, we're driving less. This is great. And we're overpopulated. Like, oh.

• 10:31Ed Zitron?

  I mean, I mean, that's a different conversation that maybe I, but in all seriousness, you didn't have mainstream media being like, well, COVID is going to kill everyone. The end, I guess, I guess, you know, maybe we'll just be inside forever. You didn't have this kind of stray, in fact, you had the direct opposite. It was, we need to get outside again. Who cares about this thing?

• 10:52Speaker 07

  Well, okay.

• 10:52Ed Zitron?

  It's just, yeah, go on.

• 10:54Speaker 07

  Yeah. I think that's interesting. And I want to just pull on that thread a little bit because I think COVID, COVID gives an interesting, I think it gives two different interesting observations to go in both directions. Right? So I think you're definitely right. What you're saying is. When the pandemic was coming or was getting bad, really, a lot of the coverage was about what should we be doing or who are the people doing the wrong thing? But it was very much coming from this angle of like, okay, we need to do whatever it is. Like, we need to be better about this. It's got to be vaccines. It's got to be masks. It's got to be, pick your mitigation, whether you like it or not. It was very focused on what should we be doing? Or who is it that's getting in the way of a plan that maybe would get us out of this? And which is where I think you're very right, is that you did not see a lot of COVID pieces

• 11:38Speaker 07

  that were just, well, I'm just going to kind of walk through like all the different ways. You know, you might die and the morgues are going to fill up. And, uh, you know, that's, um, COVID. That's just how life goes. But I also think what the other thing we saw in a lot of COVID coverage is something that we are seeing in the AI coverage. That's where I saw a lot of the directionally true, not factually, but directionally true. There's, there's definitely a period early on in COVID. Because I was, I was following that coverage quite carefully where the papers were thinking, okay, this is the right behavior. They're probably right about a lot of these things, but I just would notice this. There'd be a lot of like, okay, we need people to buy into, for example, the lockdowns or whatever. And there'd be a lot of directionally true reporting where maybe they would like put on

• 12:21Speaker 07

  a photo of a mass grave that was sort of unrelated to COVID. Or you would see a lot of, um, there'd be pushback from like conservatives about schools. And then they put a lot of articles in the paper about teachers dying of COVID, even though it was, they weren't in school, they got COVID elsewhere. And if you really pushed on it, it was because, um, it's directionally true. Like the, the general or more general truth here is like, we need to be worried about this or these mitigations work. It doesn't matter if this, if this photo is actually right. Or if this teacher who died in Orlando, the fact that they hadn't yet been back in a school building yet, uh, it doesn't, it's serving the directional truth. So it's like, it highlights something, COVID highlights something we're seeing now

• 13:04Speaker 07

  that the reporters that are doing directional reporting, like we should be scared about it. I dare you not to be scared now. I dare you not to be scared now. Just trying to ratchet it up. Yeah. But then you also get the contrast, which is this new, uh, style of just like head shaking resignation. And actually, I don't think the reporters think they're going to be safe. They're also like writing is going to go away. The media is going to go away. So it's a, it's an almost like a nihilistic type of approach to this. Like, yeah, I'm screwed. We're all screwed. What are we going to do? And that is definitely different than we saw during that last crisis, which was obviously much more. Actually severe than what's happening now. So it's really confusing me to be honest.

• 13:40Ed Zitron?

  Well, the direction of reporting during COVID, yeah, probably shouldn't have. But at the same time, it was in, it was actually in pursuit of something good. Like it was an attempt to make people take this seriously. Cause that's ultimately what it was. It's take this seriously. Don't go outside. Stay like, don't, don't meet with people. Don't be indoors of people, blah, blah, blah, blah, blah. Great. In this case, it's like, yep, you should be scared of this. And what should you do? Fuck knows. Use chat GPT, I guess.

• 14:07Speaker 07

  Yeah.

• 14:08Ed Zitron?

  And what's, what's really confusing to me as well is you say, oh, these people don't think they'll be safe. For the most part, I just don't, I actually take back what I said. I think a lot of them just don't acknowledge it. They don't acknowledge the core ridiculousness of being like, well, everyone's jobs are going to get replaced. Don't know, like the Garfield meme with him looking at the, the Garfield with the, the cross out on the TV. Yeah. Flawlessly described there. Um, it's just, it's frustrating as well because it is terrifying people without, like, I'm not saying literally Axios or however, but stories like this are what made that, made mentally unstable person throw a Molotov cocktail at Sam Altman's house. Like it's obvious that these people were scared of the AI doom.

• 14:49Ed Zitron?

  Partly because to your point, what the fuck are we meant to do about it? Because using these tools is not, I don't really see how that works because if going along that line of logic, if the answer is you need to use this stuff now, but the eventual endpoint is that it's intelligent enough to do everything for you. How does using it now matter at all? Like what, what's the, surely chat GPT would be seen as like a, a rock versus a shotgun at that point. Like it's just technologically irrelevant if they get to AGI, which they probably won't. And it's just naturally illogical stuff.

• 15:25Speaker 07

  Yeah, I'm, I'm with you. I have been making that same argument, this idea that you need to learn how to prompt. Some generation of a chatbot that exists right now is going to be the key to your long term. I mean, even if, as you say, AI ends up playing a major sustained role in the economy, it's not going to be everyone typing on a web interface to a chatbot that's synchophantic and has a personality. Like, I think, I think I've heard you say this recently, and I agree with it as well. Like, I don't think we should be chatting with technology. We should not be chatting in a sort of anthropomorphized, humanized way. Doesn't mean you can't do natural language processing. I mean, Google is natural language processing. You're writing your Google searches in natural language, but no one's having a conversation with Google.

• 16:08Speaker 07

  It's you, you, you list the keywords as quickly as possible, and Google's pretty good at figuring out, you know, population, Spain, 1982. And you press enter and you get that information. You're not like, hey, so I'm wondering what the population is of Spain in 1982. Can you help me find that question mark? There's, there's something odd about that anthropomorphized conversational interface. I guess we saw a lot of Star Trek growing up, and that's, you know, what we, what we think the future is supposed to be like, but it has all sorts of problems.

• 16:35Ed Zitron?

  Remembering Star Trek, when he would go, computer, do this, the computer didn't go, that's a great idea, Jean-Luc, what a great idea, thank you for it. The computer just did the thing. That's like, I don't have any trouble with natural language queries, because I think the whole reason that, say, ChatGPT has grown comes from search. I think it is the core of it, because ChatGPT and Claude and all them are better at understanding what you asked for. Not saying the data output is necessarily great, but just they understand the, the inference they make from what you say is better than Google, or at least better than Google has been. I feel like it was better before.

• 17:15Ed Zitron?

  And I think that had Google not kind of boofed it on this one, we wouldn't be in this spot. But even then, using Google now, it forces you. It forces the AI summaries, and you could do minus AI and all that, but sometimes I don't remember to. And it's just. Is just turn search into this nightmare. But nevertheless, back to what you were saying. I agree. I think the anthropomorphization needs to go. I think that these things need to respond like terminal windows or what have you. They need to respond like computers and go, okay, here you go. Just don't need all that cludge. I don't need to be told. Oh, what a great idea. I know I had it. Or indeed, if I'm being told that, I need to be told if it's a bad idea.

• 17:56Ed Zitron?

  But I don't even necessarily need an answer. I just need stuff to look at so that I can come to my own conclusions.

• 18:02Speaker 07

  I think it's hard, actually. I think it's actually hard to get a language model to do that. Right? Because if you think about, when you go back to the base layer of what's happening in the pre-training is that you're building a language model that's trying to win at the token guessing game. So it's, I'm trying to guess what word or part of word actually comes next to what I assume to be a real piece of text. And then if you do that autoregressively, so you call it again and again and again, adding the answer to the input. So it grows out an answer. What you're going to get is a text expansion. You've given me a text that I'm trying to expand as if there is a real text that exists and I'm trying to match it. You get that like kind of indirectly. So really its idiom is the type of text it's trained on, which for the most part is more sort of prose style text.

• 18:45Speaker 07

  So you can tune it away from it, like you can tune its mood, you can tune its synchofancy. But it might be hard to actually tune an LLM because it deals with human written prose as its main training data. It might be harder than we think to tune that away from being verbose and to just give a table. Now, I guess you could take its output and then maybe run that through another thing that then strips away the other pieces like it's possible. But I, I think the, the anthropomorphized verbocity we see in language models is also, that's kind of the native tongue of this particular, which is why we still have a lot of chatbots being emphasized. And tools that are built upon LLM as the digital brain are still way more scarce than you would imagine outside of maybe

• 19:30Speaker 07

  computer programming and coding harnesses. We just don't have a lot of other examples where we just use the LLM as a general person's digital brain. Because I think this verbocity is okay. Humans can interpret that, but it's not great if the LLM is just a digital brain that's interfacing between you and another computer. It doesn't need to hear that their idea is great or wants to try to parse the different types of text. There's some interesting things going on there about the fundamental nature of these things.

• 19:55Ed Zitron?

  But even then with Google AI mode, it still seems kind, it still like actually seems like it can give fairly short answers. But if you mess, if you argue with it, as I have, it will just provide you with it. Even Googles will provide you with just hot dog shit. Yeah. Like it would just claim something is true. My one, I just did a private equity thing on private credit even. And my favorite thing is being like, what fund is this part of? And it'll go, it's part of this fund. That fund was funded, was founded after this happened. And it goes, okay, well, maybe it's this one, different fund, three years old, doesn't not involved. Do you have proof of that?

• 20:33Speaker 07

  Well, this is what you don't, this is what you don't see in Star Trek is, you know, Captain Kirk or whoever, I'm going to mix up the episodes here. You know, say like, hey, computer, we are approaching deep space nine, prepare docking procedures and computer is like photon torpedo fired, space is destroyed. And you're like, well, no, I said, we're supposed to dock. Oh, you're right, Kirk. I should have fired the photon torpedo.

• 20:54Ed Zitron?

  Thank you for holding me accountable, Captain Kirk.

• 20:56Speaker 07

  That was, I did the opposite thing, you know? Yeah, that didn't happen in Star Trek.

• 21:08Speaker 08

  Cash flow crunch? OnDeck's small business line of credit gives your business immediate access to funds up to $200,000 right when you need it. Cover seasonal dips, manage payroll, restock inventory, or tackle unexpected expenses without missing a beat with flexible draws, transparent pricing, and control over repayment. Get funded quickly and confidently. Apply today at ondeck.com. Funds could be available as soon as tomorrow. Depending on certain loan attributes, your business loan may be issued by OnDeck or Celtic Bank. OnDeck does not lend in North Dakota. All loans and amounts subject to lender approval.

• 21:39Speaker 09

  This is Alexis Christofres for Bloomberg Surveillance. AI is everywhere. Outcomes are not, not because AI doesn't work, but because AI hasn't reached the workflows yet. The campaigns, the launches, the quarterly planning, those workflows are still run by humans alone. AI is making individuals faster, but it's not making businesses more productive. That's the gap Asana is built to close. Asana is the operating system for human agent teams, your easy button for AI productivity across every team. Ready to go AI teammates pre-built for marketing, ops and IT. No prompt engineering, no setup. They show up where the work is happening, already on-boarded in your workflows, ready to deliver. And the more they work with your team, the smarter they get.

• 22:24Speaker 09

  With Asana, your whole company can work on the same plan towards the same goal, whether you're a team of 10 or 10,000. Asana, where humans and agents workflow together. Try it at asana.com. That's A-S-A-N-A dot com.

• 22:39Speaker 02

  Empower is all about helping you invest well so you can go out and live a little. And their free Empower Personal Dashboard shows you your full financial life in one place. You'll be able to see your net worth, monitor budgets, analyze your portfolio, set retirement goals and more. Whether you're saving for something big, want to treat yourself, friends or family, or meet long-term goals, Empower helps you see where you stand. You've worked hard for your money and Empower can help you make the most of it. Download the Empower Personal Dashboard or visit empower.com, not an Empower client paid or sponsored.

• 23:12Speaker 10

  At Oppenheimer, we're proven because we're grounded in discipline. For 145 years, we've been building and protecting wealth through every market cycle with precision, clarity, and the courage to think boldly beyond the moment. This is what market-tested legacy looks like for this generation and the next.

• 23:32Speaker 10

  Put the power of Oppenheimer thinking to work for you. Wealth management, capital markets, investment banking.

• 23:43Ed Zitron?

  So one thing that's really been driving me insane, by which I mean going on Twitter, is looking at people like Aaron Levy of Box and Brian Armstrong of Coinbase talking about like agent spending money and the agentic web and how we need to prepare the web for agents doing stuff. And the agents will do this. Fantastical, doesn't exist. Agents don't do that. Just like, they don't have the ability to, like, oh, they'll use computers. Computer use is basically non-functional in AI, and it takes insane amounts of compute. It feels like a conversation keeps happening, in theory, in the media, on social media, about something that's possibly completely impossible, but the certainty they

• 24:25Ed Zitron?

  discuss it with is insane to me. This whole agent conversation, I've never seen anything like it in my life.

• 24:31Speaker 07

  I mean, it does, it does feel a little bit like crypto to me. I think that, that is kind of a fair comparison, where if you had a blockchain-driven software, like, in theory, that software would kind of work, but it just gave you a worse version of what you could already do for pennies using the actual, you know, Amazon server somewhere. And all you were really gaining was some sort of cyber libertarian philosophical feel-good about like, yes, but this was purely decentralized. I got worse versions of software to be decentralized.

• 25:03Ed Zitron?

  But now no one can control it.

• 25:05Speaker 07

  This is what, like, early agents, I mean, okay, so here's what, I've been writing about agents. I've been thinking a lot about it. I mean, the issue is, I don't think people understand what they are. I think people think that it's a new type of digital brain that is now able to go on and do more autonomous activity. I always see this get mixed up. It's just like people talking about Mythos breaking out of its sandbox to do XYZ. Mythos is a language model. You can give it an input and it can give you a token. You're talking about a program that is calling Mythos and then taking actions based on what it called. And this is really what we're talking about with agents, is the digital brains are LLMs. And then you write a program that will say to the LLM,

• 25:46Speaker 07

  "Give me a plan for doing X." And then the LLM spits out what seems like a reasonable text that seems like a reasonable plan. And then you execute that plan. The program executes that plan on behalf of the LLM. And I wrote about this.

• 25:58Ed Zitron?

  Like a script.

• 25:59Speaker 07

  Yeah. And I wrote about this earlier this year. LLMs are bad, you know, as a digital brain, are bad planners. It's not really, you're not going to get consistently usable plans, because what an LLM is actually trying to do is finish the story you gave it. So all it wants to do is produce a story. That sounds reasonable. So it's giving you reasonable sounding plans like, yeah, that's what a plan for doing this would more or less sound like. But what it's not doing is actually doing step-by-step evaluations. It doesn't have a clearly isolated goal that it's trying to measure how close you're getting to it. It doesn't have a world model to evaluate what's going to happen with the steps that that are going to unfold next. And so in almost every context, it turns out, oh, a digital brain by itself being an LLM doesn't lead to good agents.

• 26:42Speaker 07

  In programming, it seems to work a little bit better. But I do think Gary Mark, I don't know if it was a scoop, but Gary Mark has captured in a recent newsletter, something really important. When Anthropic leaked the code for their Claude code coding harness that sits on top of their LLMs to do coding, it turns out they've added a huge amount of old fashioned, hand-coded, symbolic AI-style rules and pattern recognizers and special if thens. That's so they've just been sitting there tuning this program for specifically doing computer programming. And the LLM is being a little bit more isolated to just the code production. So they've kind of just gone back to old fashioned. This is like an old fashioned system that is plusing up an LLM. But I'm with

• 27:27Speaker 07

  you. Yeah, it's very hard. Just asking an LLM, tell me, give me a plan for doing X. For almost any scenario of X, you really can't trust a plan from a model whose goal is primarily to finish text, to finish the story you gave it in a reasonable style way. That's not how we plan. That's not how we think about planning. And it doesn't give you consistently usable plans. So yeah, but but you're right. It's magic. Like, the agents are coming. They've been saying this. I mean, I wrote the article I wrote, you know, in January. It was like, what happened to the year of the agent? 2025 was the year of the agent. All we had was coding agents. That's the only thing that we worked on that whole year. It was supposed, I mean, I have the receipts. Early 2025, all of these executives saying, your work as a knowledge worker, now as a computer programmer,

• 28:12Speaker 07

  but just as a knowledge worker, is going to be largely done with agents. You're going to have agents are going to be a major part of your workforce in just a normal office setting. And none of that happened, because it turns out, just asking an LLM, give me a plan for doing X. Does it often actually produce a workable plan?

• 28:32Ed Zitron?

  And as a result, the only way to make agents work, which they do not, is to build a bunch of symbolic or if this, then that shit, just like scripts. Like, I mean, if you use Manus, for example, it's just writing a shit ton of Python. And it's writing it to do stuff that it, it's like, oh yeah, let me just do this. And it just writes a Python tool to fill out a spreadsheet. It's insane. It's really insane. But what's more insane to me is that the conversation around agents is as if they're already here. I'm about to read you something from Box CEO, Aaron Levy, the CEO of a, of a public company. "One corollary to the fact that AI agents take real work to set up in a company at scale is that the role of the forward deployed engineer, or whatever it gets called in the future, isn't going away anytime soon.

• 29:15Ed Zitron?

  When a vendor sells any kind of agents into an organization, you're no longer just selling a software tool that gets implemented and you're done. You're fundamentally selling some sort of actual workflow being done by your technology." What are you fucking talking about? What are you talking, you are a cloud storage and collaboration. What do you sell? And the answer is nothing. They don't sell any agents. Agents don't, oh, agents are going to do this. What you are describing is a different kind of technology. Just, that's it. Like, it's something else that doesn't exist. But this is everywhere. You go, you look at any consultancy right now, any conference right now, there will be a speech about agents. Even Meredith Whitaker, who I deeply, deeply respect, went on stage last year and was like, yeah, AI agents using money that booking plane tickets.

• 30:00Ed Zitron?

  No, they're not.

• 30:01Speaker 07

  They're not.

• 30:02Ed Zitron?

  That's not happening. And I said, I say this again, deeply respect Meredith. I said this online, people flip their shit at me. It's like, oh, she's directionally correct.

• 30:11Speaker 07

  Yeah.

• 30:12Ed Zitron?

  She's directionally correct. It's like, let's be scared of the things that exist, because I think it's perhaps scarier for a different reason, that we have large swaths of the tech industry. Talking about something that doesn't exist. Like just like agents don't like they don't. They don't exist. They don't like people are talking about the agentic internet. I keep reading about even on the verge, I read about it. I read it all over the shop where it's like, oh yeah. Well, the internet needs to be rebuilt for agents to use. It's like, what do you mean? And they never say, because the answer is when we come up with something else. Because I don't even think neuro symbolic makes sense for this.

• 30:55Ed Zitron?

  I mean, neuro symbolic being the one where it's they have a deterministic system that they access. From what I understand, like. The other thing as well, now that I think about it out loud is. How would they actually browse the internet? Where are they being housed? Are we using GPUs to make them browse the internet? That's insanely insanely. That's very, very convoluted and probably quite expensive to do. And to what end?

• 31:19Speaker 07

  That's the that's the real question, right? I mean, I've seen these proposals. I mean, basically where a lot of these proposals go, I mean, it's. The agents were supposed to, we thought that we could just make AI do anything. So we'll just, we'll have it use the mouse and just use our computers for us. Oh, that's hard. We don't know how to do that. All right. So what we'll do is we'll rewire all applications that anyone uses in the internet. So that we don't actually have to use the mouse. It can have a text interface so that an LLM like they do, the coding agents do. Can give, you know, description of how to do something in Excel in text. Without having to actually move a mouse or click things around. And then these these evolve to say, okay, well, what's the one type of instruction that we're good at producing? Because they get when LLMs produce plans, they they're they're directionally correct plans.

• 32:04Speaker 07

  They don't actually get the thing done. But they said, oh, what LLMs are good at is producing code that compiles. And we can actually like check that it works. And so this is where this whole vision has changed is that all applications and internet websites. Should have a code accessible API that you can expose. And then an LLM can write a program that will then access that API. So we don't need to teach the LLM how to use Excel. It'll write a it'll write a Python program that'll call hooks into Excel. The problem with this is no one wants to open up their application. To just agents in general. If I'm Microsoft, I was like, I don't want, I want to write a custom tool for my program. Why would I expose my program for anyone else, anyone else to use it?

• 32:46Speaker 07

  But your, your original question is a big one. To what end? Like I, I've been writing about this recently, especially with work and AI. You gotta find the real bottlenecks, right?

• 32:55Ed Zitron?

  Yeah.

• 32:56Speaker 07

  It's, it's the drunk looking for the keys under this, under the streetlight. There's a lot of this going on where this is what we can do with AI right now. Then this now becomes like the key to productivity. But the real bottlenecks in people's work is often not the things that we're trying to aim AI at. Like, I don't know, people are super frustrated at booking a plane ticket online.

• 33:16Ed Zitron?

  Yeah, it's really easy.

• 33:17Speaker 07

  How often do you book plane tickets? You kind of want to know, like, let me, let me see, maybe this time will be better. What seats available? It takes five minutes. So it was, it was a huge jump to go from a travel agent to a web interface. But this is not a bottleneck in people's life now, where I want to give complicated.

• 33:33Ed Zitron?

  Time. Yeah. And they're easy. They're so simple. I can do it while sitting on the toilet. I don't want an agent to choose. And then people are like, oh, your calendar will tell it. My calendar doesn't lay out my entire day. I don't have every single thing I do on there. It's just strange.

• 33:50Speaker 07

  Well, I had the same argument with like, social science researchers who are like, we, if, if you're, you know, geeky enough to learn coding agents, they're like, this is good, this is revolutionary, revolutionizing science research because now, for example, you could have it write a program to process a data file and then format it into a plot. And that might have taken you four hours to do and it, and you work with it for a half hour and you get that result. This is revolutionizing research. And I'm saying, well, it's not, the bottleneck for social science researchers is not analyzing data and producing plots. You're not sitting there doing that eight hours a day, every day. And if I could do this twice as fast, I'll produce twice as many papers. I might write one paper in a three month period. Yeah. In there, there's like four hours I spent

• 34:34Speaker 07

  making a plot. And sure, it'd be nice if that four hours became 30 minutes. But that's four hours out of like a multi-month process of sort of thinking about this paper.

• 34:42Ed Zitron?

  What is a plot, by the way?

• 34:44Speaker 07

  Like a graph.

• 34:45Ed Zitron?

  Oh, right.

• 34:46Speaker 07

  The computer science term. But yeah, it's like, that's nice. That got a little bit faster, but that's not the bottleneck. That's not, that's not what's going to unlock a lot more research. It's like, man, I would write more papers if it wasn't for how long it took me to draw a graph. And if you could, I have five.

• 34:59Ed Zitron?

  The problem, data?

• 35:01Speaker 07

  Getting the data.

• 35:01Ed Zitron?

  Like actually collecting data?

• 35:03Speaker 07

  That's what it is. I wrote about this, talking to like a well-known business school professor years ago for my book, Deep Work, and he talked about, he just realized, oh, being a business professor, publishing papers is about data access. I have to spend most of my year talking to people, building relationships, trying to set up a, you know, an agreement with a company where I can get good data that I can get three papers out of. In all of that work, there's one day in there where you're crunching the numbers and making a plot. And it's nicer if you could do it a little bit faster, but it's not a productivity bottleneck. It's a, it's a marginal efficiency. I think there's a lot of that going on right now with AI and productivity as we look at what the AI can do and then try to make that thing into somehow being the key to getting things done.

• 35:44Ed Zitron?

  I just, my productivity problem is that the UI and UX and everything sucks. Everything's disjointed. Setting up Riverside is always fun. They move the menus around. Projects are in a different place. That takes up time. Moving files places also takes up a lot of time. This morning, when I put out my private credit piece, I had to do these threads. I had to click around a website and put in the alt text, but I had to tweak it slightly. It's like, I don't know how AI would possibly help me here and they're not working on that.

• 36:14Speaker 07

  Well, they tried. They tried though. I thought that was going to be, this is what I was excited about earlier, the Gen AI revolution. I was like, okay, here's the real value prop is natural language interface into advanced features on software, where I can just say, all right, I want you to go take this, this column in the spreadsheet and get rid of all the rows that have values before this. And then I want to make a, make a pie chart and because I don't want to learn how to do all that in Excel. I don't know how to do that. And they tried it. I mean, this was Microsoft Copilot, but it turns out we underestimated the degree to which when we as humans are interacting with a chatbot that we're incredibly gracious, we're able to adjust and kind of get the gist of what it means and filter out the part of the chatbot response that's not really relevant or

• 36:57Speaker 07

  ask the follow-up question. And when they tried to just use LLM responses to automate actions within programs, it would, there's just, it's just not accurate enough. So they wanted that to be the case, that like you could just be talking to a Riverside bot and you never would have to press a button ever again in Riverside. It's just not accurate enough. LLMs, it's fine for human conversation. It's just not, it's just not accurate enough in this general case.

• 37:21Ed Zitron?

  Also, that thing you're describing with how they want the agentic web to just be a series of APIs, so that every agent writes Python or what have you to use them. That's a massive computational increase for no reason, because you're basically saying, instead of someone clicking a mouse and hitting a keyboard, we will write code for everything.

• 37:42Speaker 07

  Yeah.

• 37:43Ed Zitron?

  What an insane, what a truly insane idea. I mean, it's, it's just very like Salesforce today. I don't know if you saw they announced that they're doing Salesforce headless 360. Marc Benioff needs to fire everyone in marketing, but they've made it so that you can do everything with Salesforce firing API, which is, I mean, the first question I always ask is what does Salesforce do? Because I've talked to so many people and they can't tell me. There's like 21 different features. No one knows what they do. But it's like, it's just a very bizarre thing. It's very much a cart horse thing. But also, what agent? Like, that's what, this is the thing that really drives me insane. They're talking about, we built this API for

• 38:24Ed Zitron?

  the agentic web for agents to use it. Which one? What agent? What are you talking about? Well, it will be in the future. What do you, you change something materially with your publicly traded company worth $300 billion because it might happen while we're getting ahead of it? What the, and it's, you talk to members of the media about this and they just go, yeah, you know, yeah, you know, it will happen. It's, it's obviously going to happen. They wouldn't put this much money behind it if it wasn't going to. It's like, I don't know, especially with Salesforce. And I'm like, you don't think Salesforce would spend a bunch of money for no reason? Well, buddy, you've not been following Salesforce at all then.

• 39:06Speaker 07

  I mean.

• 39:06Ed Zitron?

  But, yeah, go on.

• 39:07Speaker 07

  Yeah, I was gonna say, how much did Meta spend on the Metaverse?

• 39:10Ed Zitron?

  Over $70 billion. Where did that money go? Where did it go?

• 39:15Speaker 07

  They spend money. Customizing floating dinosaur avatars.

• 39:21Ed Zitron?

  Not building legs, but let's change.

• 39:23Speaker 07

  That's the second 50 billion, right? If they had gotten the second half of the investment, they would have got to the legs. They're just not there yet.

• 39:29Ed Zitron?

  Another 100 billion will have toes. Um, so changing subject a little. Mythos has been one of my favorite media hysterias recently. I genuinely wonder, like, if they ran War of the Worlds again today, I think Axios would have a headline two minutes and it'd be like, there are aliens, they're attacking. I heard it on, I heard it on a podcast. I've looked through the system card. I don't know if you have for Mythos.

• 39:54Speaker 07

  It's wacky.

• 39:55Ed Zitron?

  It's wacky.

• 39:55Speaker 07

  It's wacky. I can't believe we're, we're letting people get away with having a psychologist talking through the chat bot like in your system. It's nuts. What, it's all gone to marketing.

• 40:08Ed Zitron?

  They had a psychiatrist or a psychologist, I can't remember, talk to it and be like, yeah, we found these emotional features. How is, like, we need regulators to stop this stuff? Because I, I've heard, and people's response to this is, well, banks are having meetings about it and the government's having meetings about it. Governments have meetings about NFTs. There was a, Gavin Newsom signed an executive order about, uh, Web3. These people will meet and talk about anything. Oh, it's scary and they're not talking about it, which means it's powerful. Well, how is it powerful? What does it do? Because I think you probably saw this as well. It didn't list how many false positives there were. It also didn't mention that the freed BSD bug that they talk about, that they found, the,

• 40:53Ed Zitron?

  wasn't actually exploitable. I think it was something about like the, about the level, like the level it was at. I forget, I'm not, I, I don't do programming. Other than, other than very simple Python, the, a dog's Python.

• 41:07Speaker 07

  Yeah. I mean, Free BSD Kernel is full of bugs. All these things are full of bugs.

• 41:11Ed Zitron?

  Cause they're open source.

• 41:12Speaker 07

  I had to have this, I had to have this conversation with someone, uh, recently where they were like, Mythos, can you believe of all the places it found a bug? In the kernel of Linux, like in Linux, they found, I was like, are you kidding me? All day long is just bug fixes having to be pushed into that repository. Yeah, the Mythos story, I think, I mean, A, someone needs to get a Nobel Prize in Marketing, because it was, it was absolutely brilliant what they did there. I've spent a lot of time on it. It's complicated because, again, you can't really trust the system. The system cards are just gonzo that Anthropic puts out, and it's not publicly available. But there, there were, I think, a few very telling things. So there's two features they say Mythos has.

• 41:54Speaker 07

  One is finding vulnerabilities in source code, and two is writing programs to exploit them. It's first really important that people understand this has been something that people have been doing with LLMs since the beginning of publicly available LLMs, right? There is, not only is there nothing new about that, but I found, I put this on my podcast, almost word for word from the Anthropic system card, them, they said in the Anthro, uh, the Opus 4.6, rather, systems card, right? A publicly available model that's already been out for many months. Almost word for word for what they said about Mythos, except for no coverage of it and no fear. They said, "We have found 500 zero-day vulnerabilities, including some that had been existing for decades without having been discovered."

• 42:40Speaker 07

  That is what they said about what Opus 4.6 could do. For Mythos, they said the same thing. They just replaced the word 500 with thousands. But when Opus 4.6 came out, there was no, "Oh, my God, they have found many hundreds of zero-day exploits, many of which have been around for decades," because they didn't push that marketing button. No one particularly cared about it. I went back to my podcast and showed multiple papers. This has been a huge concern, and it's a real concern, by the way, right? Is that partially what slows down slightly cracking, right? The breaking into systems is the fact that it's annoying and hard. And LLMs have made it easier. GPT-4 was good at finding exploits, right? And this was a big deal. They were like, "GPT-3.5 wasn't great at it, GPT-4 is."

• 43:22Speaker 07

  And then as we got to more recent models, they've been much better at writing code to exploit them because we had better agents for it, and they're more, they're, they're They're able to produce multi-step software goals and so they can better build software to exploit them. This is a real issue, but it's not new with Mythos, right? Yeah. But Mythos was presented as if some Rubicon had been passed, but there was a couple of things I noticed right off the bat. One, they made the mistake of listing a bunch of the exploits that they, vulnerabilities they had found to try to brag. Look at this thing in Free BSD. Look at this thing in FFPNG or whatever. Like they showed all these exploits they found. They didn't count on, a lot of security researchers said, well, wait a second. Why don't I get like a much smaller, cheaper model aiming at that same source code and say, can you find any vulnerabilities?

• 44:07Speaker 07

  They could find the same ones. So this, so the evidence that it's finding vulnerabilities better. We don't have any way of knowing that's true. And if anything, we actually are getting a lot of reports that they were paying big bounties for security researchers. I'm going to give you access to Mythos. I'm going to pay you for any bugs you can report that you found with it. So they had security researchers, just who knows how many false positives were coming out of that. And then on the exploitation side, we only really have one study. It comes from AISI, who I do not trust. But it's the only independent study. The fact that they gave them access itself should make us maybe a little bit suspect. But it basically just showed like normal progression. No massive leap.

• 44:47Speaker 07

  Model by model gets a little bit better on some of these tests and benchmarks and Mythos has no out of scale leap. It's just like on some, it's about the same. On some, it's a little bit better. And yet it got covered as if we had just turned on, you know, Whopper from the movie War Games. Like we had just some new entity that was like on its own undermining security. And I do not think that, I think that was highly credulous coverage of what almost certainly is just like a standard slight jagged move forward on these various capabilities that we've been seeing for the last three years.

• 45:30Speaker 08

  OnDeck is built to back small businesses like yours. Whether you're buying equipment, expanding your team, or bridging cash flow gaps, OnDeck's loans up to $400,000 help make it happen fast. Rated A+ by the Better Business Bureau and earning thousands of 5-star TrustPilot reviews, OnDeck delivers funding you can count on. Apply in minutes at ondeck.com. Depending on certain loan attributes, your business loan may be issued by OnDeck or Celtic Bank. OnDeck does not lend in North Dakota. All loans and amounts subject to lender approval.

• 46:00Speaker 09

  This is Alexis Christofres for Bloomberg Surveillance. AI is everywhere. Outcomes are not. Not because AI doesn't work, but because AI hasn't reached the workflows yet. The campaigns, the launches, the quarterly planning, those workflows are still run by humans alone. AI is making individuals faster, but it's not making businesses more productive. That's the gap Asana is built to close. Asana is the operating system for human agent teams, your easy button for AI productivity across every team. Ready-to-go AI teammates pre-built for marketing, ops, and IT. No prompt engineering, no setup. They show up where the work is happening, already onboarded in your workflows, ready to deliver. And the more they work with your team, the smarter they get.

• 46:45Speaker 09

  With Asana, your whole company can work on the same plan towards the same goal, whether you're a team of 10 or 10,000. Asana, where humans and agents workflow together. Try it at asana.com. That's A-S-A-N-A dot com.

• 47:00Speaker 02

  Empower is all about helping you invest well, so you can go out and live a little. And their Free Empower Personal Dashboard shows you your full financial life in one place. You'll be able to see your net worth, monitor budgets, analyze your portfolio, set retirement goals, and more. Whether you're saving for something big, want to treat yourself, friends, or family, or meet long-term goals, Empower helps you see where you stand. You've worked hard for your money, and Empower can help you make the most of it. Download the Empower Personal Dashboard or visit empower.com. Not an Empower client paid or sponsored.

• 47:33Speaker 10

  The world is transforming faster than ever and standing still isn't an option. At Oppenheimer, we're working at the forefront of the innovation economy to invest where progress begins, finding opportunities that build and protect wealth for individuals and institutions that want a seat at the edge of tomorrow. Put the power of Oppenheimer Thinking to work for you. Wealth Management, Capital Markets, Investment Banking.

• 48:05Ed Zitron?

  Also, when you said that, so the difference between Opus 4.6 and Mythos 500, 2000s, makes me ask the very simple question of, did they look as hard? To your point about the security researcher.

• 48:17Speaker 07

  They didn't.

• 48:17Ed Zitron?

  Like, did they, did they spend as much time? Probably not. So they probably could have found them. Also, by the way, I immediately was looking it up. AI Safety Institute is of course heavily linked to effective altruism.

• 48:28Speaker 07

  Can I say why I'm upset at AISI? I talked about them. Two weeks ago, I did a, or through, I don't know if this is coming out, but I did a podcast in whenever, March, where I looked at this report and mainly I looked at the Guardian's coverage of this report done by AISI, but it was just the most inane thing. The headline was, "Massive Increase in AI Scheming Is Detected." And they had a chart.

• 48:49Ed Zitron?

  Jesus fucking Christ.

• 48:50Speaker 07

  And they had a chart and bad line went up. And it went up in like January and it goes up. And if you read this article about this study, they're like, something's going on, scheming has been increasing rapidly recently. And they like gave some examples of it or whatever. And so I look at this, like, I want to look at it. What is going on here? So I look at this chart. What are they charting? Oh, they're charting tweets per day that they've detected tweets about AI doing things that you didn't want it to do. And I said, huh. So when does this line start going up? The week that OpenClaw was released to the public and everyone just started building their own bad agents and then tweeting about how bad they were?

• 49:30Speaker 07

  And you know what word was not mentioned in that article? Open Claw. And even though the examples they were giving, so they just said scheming just started rising. I guess AI is becoming sentient and all they were measuring was people-

• 49:42Ed Zitron?

  Multiple tweets paraphrasing the same viral story to use their own fucking language.

• 49:47Speaker 07

  And then I looked at, and then I looked at the biggest spike. I was like, well, this day in February on this chart had the biggest spike. It was like, oh, there was this one tweet about open claw, like erasing someone's emails. And then it got retweeted. It went super viral. I was like, okay, great. You just, the real headline of this article, letting people write their own agents leads to terrible agents. That's, that's it. But the whole, anyway, so that's, that's AISI.

• 50:14Ed Zitron?

  I'm looking at the tweets as well. One of them is from a 47 follower account with AI art called underscore underscore just underscore underscore Lisa. And it's, this is really bad. Opus is editing files and making up reasons it's deleting out content. So hallucinations.

• 50:31Speaker 07

  And also Opus is not doing that. The stupid open claw program you wrote that's prompting Opus and then taking action on your computer based on what it says is deleting your files. The program you wrote that you gave access to your files and just said, whatever we get from this prompt, execute it is erasing your files. Opus can't do anything. It can produce tokens. But here's the other point I want to make about Mythos that I don't think is being made. And it reminds you of the Sherlock Holmes story of the dog that didn't bark, right? Where the actual piece of evidence that mattered is not what you heard, but what you didn't hear. This is what I think the real story here is, is you did not hear Dario Amadei in the lead up to the Mythos release in the last year, let's say, or the last two years.

• 51:13Speaker 07

  You did not hear him talking about what we're working on and why AI is important is because we're going to be able to find vulnerabilities in software that have been long hidden. We're going to build the ultimate cybersecurity machine. This was not discussed. That's old fashioned stuff. That's boring stuff. That's stuff that we are worried at. Even GPT two, people are worried about that. What we've been hearing about steadily was jobs are going to be automated. We're going to have like whole creative industries wiped out. We might have sentients coming and at the very least like AGI and these massive disruptions. This is what they've been focusing on again and again. And then their biggest, best model, right? Their newest, greatest, bestest model that they train forever and use all the electricity. What did they say about it?

• 51:54Speaker 07

  None of those things. They didn't talk about any of the things they said the key AI was, the things they were afraid of, the things they're excited about. Instead, they went back and talked about a boring, parochial old feature that has been an issue that nerdy security researchers have been talking about for a half decade now. That to me is if I was an investor, I would say, take off your like Greek helmet cosplay mythos is coming to disturb. Well, hold on a second. Is this better at automating jobs? Is this better like producing code? Is this is this is this age? Like, why are we talking about finding bugs? We're worried about that with GPT-4. Like, that's a problem. But it's like the that's not something new. Uh oh, something must be going

• 52:37Speaker 07

  on. You just put a lot of money into a new model. And the best thing you could find to emphasize was it's good at finding bugs. I think that is a problem. It's what they didn't say about this model. They would have much, much, much rather be able to brag this model is now much better at any of those things that they've been saying is the key to the AI future. And you didn't hear him talk much at all about any of those.

• 53:01Ed Zitron?

  Yeah, and that's the thing. If it was so powerful, like here's the thing. I don't know what would make me convince that LLMs were the future, but a step toward it would be we typed create a Slack competitor, which they claimed they did once, and then didn't show it and refused to. And they said, oh, it worked autonomously for 30 hours, but then wouldn't talk about it. If they were like, we created a Slack clone, here it is, and it was bug free. Like, if it actually just worked, and we're like, we now we have done this. Because theoretically, if this SaaS apocalypse story was was true, which it's not, that AI is going to replace all software, if they actually did that, if they because what someone from Anthropic just left the board of Figma, and they created a Figma clone, and the stock went down because the markets run by toddlers.

• 53:43Ed Zitron?

  If they were like, we've released a clone of Microsoft Word, it's like, we've done Anthropic Word, and we now sell that as part of our subscription. That would actually be quite something. But the thing is, they're not. It's kind of, it gets back to the old talking point of if they made AGI, why would they sell it? Wouldn't it be a massive competitive advantage to keep this? And I think you're right. I think maybe Mythos is not as powerful as they say, and they've just had to dress it up. But it gets back to the thing of the direction, the true media coverage. It's like, well, this is scary, right? I mean, ah, that system card's like 180 pages long. I don't got all day. I have to write three 100-word blogs a week. I couldn't possibly spend time reading this. And it's just, it's disgusting.

• 54:26Speaker 07

  We need so much more skepticism. We need so much more skepticism, right? I mean, this is why, again, like, the most skeptical, we're not skeptics, but like, I call it the East Coast computer scientist. So those of you who are technically minded, and we're not near Silicon Valley. So we're not in that world. It's very hard to be a professor in a world where there's just hundreds of millions of dollars being handed around, and they try to like, ignore it. But the East Coast computer scientists are all baffled by, you talk to any East Coast computer scientist, they're all baffled by, like, oftentimes, there's claims that are just not true or widely exaggerated. Why are we so credulous? I mean, it'd be one thing if it was like, a government agency, we didn't realize, was like, trying to, you know, protect the fact that there was UFOs. And they're just straight up lying. And we've never encountered that before.

• 55:11Speaker 07

  Like, I didn't realize that, you know. No, it's a business, right? And the credulity with which we're taking these claims. Like, Mythos is, I think, the most important story there is, yeah, this is another example of what I wrote last summer about AI has hit a bit of a wall, in the sense that all of the improvements that have come, really, since over the last two years, have almost all been either on post-training, or more importantly, on the harnesses that you built. So it comes in the software you're building to take advantage.

• 55:37Ed Zitron?

  What is a harness? Just, I've seen this word used a lot. I think it's good for the, me and the listeners, to hear the exact definition.

• 55:43Speaker 07

  I think of it as like, a computer program that can do stuff. You can talk to it, can do stuff, and it uses, it'll prompt or talk to an LLM as like, its digital brain. So the harness might actually be able to touch your file system, write the files, compile code, move things around. But to figure out what actions to take, it will also then prompt an LLM and say, okay, what should I do next? And you can put it on different...

• 56:06Ed Zitron?

  Is that just a wrapper?

• 56:07Speaker 07

  Yeah, it's a wrapper.

• 56:09Ed Zitron?

  So this

• 56:10Speaker 07

  But that's where all the progress has come. All of the progress in coding agents since about a year has come, especially starting this fall, has come from better wrappers, better harnesses. It's all in, let's build better, just hand coding, no machine learning, no intelligence, no Skynet here, but just hand coding these programs that will call LLMs. Let's just keep tuning and tweaking those to be better and better. And of course, the programmers building those particular programs, they're building them to do their type of work. So it's a field they understand really well. So they can really just sit here and twist and tune. And also like programmers are very adaptable. They like tools and they'll adapt around the weaknesses or not. So it's a kind of like a best case scenario. But this is another indication of we're not getting these fundamental

• 56:51Speaker 07

  giant leaps in the capabilities of the digital brains. It's either some benchmarking, like we tuned it to do better on a particular benchmark, or we built better programs around it. So when you put the money that they put into Mythos, and if really the best thing you had to emphasize when it was done is we have a cybersecurity benchmark where Opus 4.6 was at 66.7 and this is 83.1, that doesn't necessarily going to justify what's going on. Or that AISI has this, there's only one thing in there where they see a leap from Mythos at a particular contrived security scenario they came up with. And this big leap that got them all worried was Opus 4.6 could, on average, complete

• 57:31Speaker 07

  16 out of 32 steps in this challenge, and Mythos on average could do 22 steps out of 32.

• 57:37Ed Zitron?

  Wow.

• 57:38Speaker 07

  Like that's, like, that's hundreds and hundreds of millions of dollars of training, electricity, or whatever. I think that's an issue.

• 57:44Ed Zitron?

  I just, I think that, and maybe this is a simplistic point, I don't think they know what they're doing at this point. Like, I don't get the sense that Anthropic, or even OpenAI, has a strategy, because today, as we're speaking, so this will be out next Wednesday, but they released Anthropic Design, the thing I mentioned, the Figma clone. It's like... Why are you fucking cloning Figma? What are you doing?

• 58:08Speaker 07

  You're trying, I thought you were gonna automate the economy.

• 58:10Ed Zitron?

  Yeah, I thought you were gonna, you're gonna replace AI, so you've made a Figma clone. What like, we heard the rumors last year that they were gonna do a product, um, and OpenAI was gonna do a productivity suite. It's like, why? It's like they're doing everything they can to ignore the core problem, which is the core technology is not going anywhere. Like, because Mythos appears to be, they called it a step change, but that's a nice way of saying incremental improvement.

• 58:38Speaker 07

  That's 100% correct. Yeah. And let me tell you why I would be worried if I was them. Here's the worrisome thing about Mythos, right? Is again, they, they talked about these vulnerabilities hidden for decades that, you know, Mythos found or what have you. And they replicated multiple different independent security teams were able to find most of those vulnerabilities using three to five billion parameter open weight models. So put that in perspective, right? A, a, a model like Mythos is gonna have hundreds of billions, if not a trillion parameters. And they use a three to five billion parameter off the shelf. You could run this model on a chip inside your

• 59:15Ed Zitron?

  Sorry, 10 trillion.

• 59:17Speaker 07

  10 trillion. Oh, okay.

• 59:19Ed Zitron?

  10 trillion parameter.

• 59:20Speaker 07

  That's crazy.

• 59:21Ed Zitron?

  Love the number, bro.

• 59:22Speaker 07

  Is that true?

• 59:24Ed Zitron?

  Yeah, that's what is

• 59:25Speaker 07

  Oh, my God. 10 trillion parameters is insane. Like, you better be, uh, that better be either gaming the stock market and creating billions of dollars a day and like fancy option returns or changing lead in the gold. Because to run something that has 10 billion, 10 trillion parameters to do almost anything else is a, a, it's like, we're gonna launch ourselves in the space to, to do something and then land every time. That's so incredibly expensive, but the, the real fear then is like, well, wait a second. If they could do most of this stuff with a free, cheap model that I could just run on a, a machine at home. That's what keeps, I think, Dario Amade up at night. That's what keeps Sam Altman up at night. It's the future. Look, I've been pitching this, right?

• 1:00:08Speaker 07

  I, I think the, the useful and the only ethical and sustainable future for AI is what I call distributed AGI. And I think it's just what the future is going to be, which is you have Specialized applications for different things where, oh, we want to do this thing over here. We built something that has some AI in it and maybe it has an LLM or it's a modular architecture and it has a billion parameter model in there in a world model and it's really good at doing this thing and it's small and it mainly runs on chip and now this program can do this thing that I used to have to do. And you multiply that across 10,000 different use cases and you're like, oh, we kind of have AGI, right? There's all these different things that have AI tools that like do pretty well. That's like a completely, probably the most probable future.

• 1:00:53Speaker 07

  It's a future I really like for a lot of reasons. There'll be a lot of things that we can't make progress on, a lot of things we will, but it's a much more heterogeneous future. There's no giant HAL 9000 brains, it's economically more interesting and diverse, it doesn't have all the sustainability issues. That has to be the future, but the problem about that future, if you're Sam Altman or Derry Amade, is that their entire moat is unless you need 10 trillion parameters, they want that to be the key to the AI future because that moat is something that no one can cross. And if that's not the moat, if it's just, oh, if I want to build a poker playing AI that's really good, I just need people who are good at poker and to spend a couple of years and figure out a cool custom system and that thing now does well. If that's the future, you don't need OpenAI and you don't need Anthropic.

• 1:01:38Speaker 07

  And I think that probably might be the future and I think that's terrifying and they're trying to race to an IPO and they're marketing out of their butts, like what can we do to kind of keep things going so at least we can get our stock on the market? That's what would keep me up at night if I was them is actually the future, there might be a lot of AI in the future and it's not going to be nearly as sexy as they're hoping.

• 1:01:56Ed Zitron?

  What if there's also, by the way, that 10 trillion number, I can't source it to Anthropic. I've seen it reported multiple places. This is the, this is a problem.

• 1:02:04Speaker 07

  They never talk about it.

• 1:02:05Ed Zitron?

  We have an issue with news right now. We're just like mythology spreads, ironic considering the name. But the other thing is as well, it's like hundreds of billions of trillion parameter, you're just using a nuke to kill a single gofer.

• 1:02:20Speaker 07

  Yeah.

• 1:02:21Ed Zitron?

  Like you're just like, we're going to throw everything we have at it. To the point that I don't know if you've been seeing the amount of trouble Anthropic has had keeping its service online and how they're making the models dumber.

• 1:02:35Speaker 07

  Yeah.

• 1:02:35Ed Zitron?

  It just feels like we're in this weird hysterical moment where no one knows why they're doing this, but everyone's ready to accept whatever anyone says. Like, it's just like, oh, we're all doing this insane thing. So we're just going to repeat what kind of informs the bias and makes us look less dumb is the more excited we are.

• 1:02:54Speaker 07

  I think the frontier models are like F1 cars and the equivalent of points on the F1 circuit are your positioning on the benchmark leaderboards. Like, so you do this, you build these giant models and you spend all this money, electricity, and they're so big, they're not even economically viable to like have people use, which might really be what's going on with Mythos is like, we have to make this seem super premium because otherwise people are going to get charged $5,000 a month. And just like if you're Red Bull or Ferrari, you're F1 car doing well on this leaderboard just lets people know this company builds good cars and then you can sell your normal cars. I think that's a lot of what's going on here is that they want to be high on that leaderboard means we know how to do AI,

• 1:03:35Speaker 07

  we AI smart, even though the future of actual consumer deployed products is going to be much more like a Honda Odyssey minivan than it's going to be like a top Formula One car.

• 1:03:48Ed Zitron?

  Well, Cal, it's been an absolute pleasure having you as ever. Where can people find you?

• 1:03:52Speaker 07

  You can find me at calnewport.com. My podcast is Deep Questions. On Thursdays, the Thursday episodes are all AI reality checks where I take a fun story. Actually, Ed's coming up or he's, he may have already been on it by the time this comes out, or maybe it's the day after this comes out. So now you have to check it out. The AI reality check episodes get a double dose. You bring this out of me, Ed, by the way. You bring out my sort of ornery side. I'm normally like the very, very cut of staid professor, New Yorker writer, just like, well, on the one hand, on the other, you bring this out of me. I love it.

• 1:04:24Ed Zitron?

  You're, the thing is, you're critical only of things that need to be, you're still willing to humor these things as long as there's something to humor. And that's why I like having you on because people claim I'm just a, just a hater. So we've got to have, got to have people for a little balance. But thank you for joining me. Thank you, everyone, for listening. You have a monologue coming up as well on Friday. Thank you all.

• 1:04:52Ed Zitron?

  Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matt Osowski. You can check out more of his music and audio projects at mattosowski.com. M A T T O S O W S K I dot com. You can email me at [email protected] or visit betteroffline.com to find more podcast links and of course my newsletter. I also really recommend you go to chat dot where's your ed dot at to visit the Discord and go to r slash betteroffline to check out our Reddit. Thank you so much for listening.

• 1:05:24Speaker 05

  Better Offline is a production of Cool Zone Media. For more from Cool Zone Media, visit our website, coolzonemedia.com, or check us out on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

• 1:05:58Speaker 02

  Empower is all about helping you invest well so you can go out and live a little. And their Free Empower Personal Dashboard shows you your full financial life in one place. You'll be able to see your net worth, monitor budgets, analyze your portfolio, set retirement goals, and more. Whether you're saving for something big, want to treat yourself, friends, or family, or meet long-term goals, Empower helps you see where you stand. You've worked hard for your money, and Empower can help you make the most of it. Download the Empower Personal Dashboard or visit empower.com. Not an Empower client paid or sponsored.

• 1:06:29Speaker 11

  OnDeck is built to back small businesses like yours. Whether you're buying equipment, expanding your team, or bridging cash flow gaps, OnDeck's loans up to $400,000 make it happen fast. Rated A+ by the Better Business Bureau and earning thousands of five-star TrustPilot reviews, OnDeck delivers funding you can count on. Apply in minutes at ondeck.com. Depending on certain loan attributes, your business loan may be issued by OnDeck or Celtic Bank. OnDeck does not lend in North Dakota. All loans and amounts subject to lender approval.

• 1:06:59Speaker 03

  With LPL Financial, we provide the services to help push you forward. When it comes to your finances, your business, your future, the only question should be, what if you could?

• 1:07:07Speaker 04

  Paid advertisement. Anna Kendrick is not a client of LPL Financial LLC and receives compensation to promote LPL. Investing involves risk, including potential loss. Principal LPL Financial LLC member FINRA, SIPC.

• 1:07:14Speaker 12

  With the American Express Platinum Card, you can access over $3,500 in annual value with benefits and eligible purchases across travel, entertainment, and more. There's nothing like Platinum. Learn more at americanexpress.com/explore-platinum. Enrollment requirements, monthly and other limits and terms apply.

• 1:07:29Speaker 08

  This is an iHeart Podcast.

• 1:07:32Speaker 08

  Guaranteed human.