IM 885: Get on the Butter Box - Can Local AI Models Outperform Frontier Labs?

29:07And we want to be in the token business. It's not quite a pivot. It's a little bit of a pivot, but I think it's a very smart thing. I'm asking something else, though. Let me reintroduce Christina. Hold on a second. We're talking to Christina Warren. She is the host of MacBreak Weekly. We love having her on every Tuesday to talk about Apple, but I really wanted to get her on because in her job, both at DeepMind with Google and now a senior developer advocate at GitHub, she's definitely dealing with AI. In fact, we talked about the new co-pilot desktop app on MacBreak Weekly. That's pretty amazing.

29:39And I'm sure at GitHub, one of the great beneficiaries, actually, of the AI revolution, everything is happening on GitHub, including, by the way, all the models that I'm testing and downloading and so forth. Christina, can you share those numbers you shared with Benito on me before the show? Yeah, yeah. Let me pull up the numbers. So if you are a GitHub user, you might have noticed that our availability has not been as good as we would like it to be. have been a little bit busy and so some of the numbers that we've we share some numbers in in april these are updated to august so just to give you an idea of just how much things have grown so in 2023 we were getting um uh 20 million uh merged pull requests a month as of 20 million as of august uh 2026 130 um million so going from from you know like like you know 25 to 130 million Our commits per month have gone from half a billion in 2023 to 2.9 billion in August.

30:42And that 2.9 billion is up from where we were. I think it's nearly doubled from where we were in April. The new repositories created per month, it used to be 5 million in 2023, 2024. It's now 24 million. So the growth, and this is expanded across the platform, has just exploded. And it really started when the frontier models got really good in November. But obviously, as people will use other models to open weight will affect that as well. But yeah, I mean, when we talk about like AI stuff, like, you know, this is where most people are hosting their code and are, you know, doing a lot of their work.

31:26And that certainly includes agents. And we've seen just ridiculous levels of growth that we, you know, I don't think anybody could to prepare for, even if you've done all the analyst planning. Forecasting, yeah. To see it just literally 5, 6x in some cases. I went from four half-assed repos to something like 30 within minutes. Right, right. And a lot of that's very useful. I go to there to see what, you know, people put their skills there. People put their code there. It's a very good way to see what other people are doing. And this is where such early days here with AI that I think we're all learning from each other.

32:05And GitHub is a great kind of place for people to get together and post stuff and learn from stuff. So I'll just share this one last stat. Since April, monthly commits have grown from 1.4 billion a month. This is since April to 2.9 billion. So literally the number of commits have doubled since April, which is we're not even it's not even September. It's only going to get worse. It's only going to get worse. Or better, I guess, depending on that. Well, it depends on how you look at it, right? But just keep it right. That's not what your assistant been. Right. More code is being written than ever before.

32:37Regardless of who you are, more people are starting to write code, whether it's human, you know, initiated or agent initiated, it doesn't really matter at this point. But like, more and more of that that's happening. Like you were saying, Leo, like, went from having, okay, I have a few, you know, side projects and things. Now it's like, I have an idea. And now, whether it's using a local model or I'm using something else, a frontier model, you know, cloud, whatever, I can iterate and play around with that idea and I can deploy it. And that's the sort of thing that, you know, used to be take a lot more consideration.

33:08And now it's just a prompt. Yeah, I've used GitHub for a long time. I'm a fan and a proud member. But a lot of people, Anthony Nielsen is saying, I don't really understand GitHub, but I'm but I'm using it because the agents understand it. The agents know it. The agents, it's a natural thing. I was going to say it is. It is that thing, right? Because if you're building something on your computer and going, okay, I want to be able to deploy this. I want to test this out. I want to be able to have version control, which of course you want to do, you know, GitHub is going to be the obvious choice because we have a very good free plan and it's been around for the agents suggest it.

33:43And they just do suggest it, right? Because they've, they've, they've, you know, scanned the internet too. And obviously, all the models have been trained on the public code that has been on GitHub. And, you know, that was the genesis of the, you know, kind of original kind of implementation of GitHub Copilot back in 2021. It was a joint project between us and OpenAI. They had a model, which was called Codex at the time. Obviously, Codex is now the name of something else. And it was, you know, we worked with them to train a version of, I think it was GPT 3.5 on the code that was hosted, the public code that was hosted on GitHub.

34:21And our idea was, okay, well, we have this model now, what if we try to do, you know, some sort of like auto-complete and suggestions? And so that was the early version of GitHub Copilot back in 2021. And then that evolved to more of a chat interface, you know, after, you know, the emergence and buoyancy of things like chat GPT. And then when we entered, when the models got got better and better and got things like MCP and tooling involved, then you started to get into the agentic coding era where we've been for the last couple of years where now it's not just autocomplete anymore. You know, it will fully create things for you.

35:00And then, like you said, because all these models have been trained, they're going to suggest, okay, well, where do I deploy my code? Where do I host my code? where do I run my different dev environments? And GitHub is going to come up. Stay there for a second. Because I'm fascinated with Leo, with his agents, talking to his agents and all that. How did the agents learn that GitHub was the place? What was the process by which that happened? Because it's a fascinating business model to understand that you find yourself at the center of all this. It propagated on its own to an extent, But where do you think the root of that knowledge was for agents in general?

35:40I think it was the fact that we have always had a really robust free plan. And you can have free private repositories for just a regular user. You're given a certain amount of build minutes every month, known as GitHub Actions, if you want to build more than that. And what that means is that basically in the cloud, it will deploy something. You can run local actions, too. But you get a certain number of minutes where your project will build in the background and run it on our cloud servers and make sure that something builds correctly and you can get a report back if it works or if it doesn't.

36:09You can deploy static websites to our pages platform too. But we've had these tools built in and we've had a really robust free plan that, frankly, no one else has really had. And that's part of why GitHub for 18 years has been kind of replaced SourceForge and things like that. is the place where if you're going to build a software project that you want to share with other people, that's where you put it. And at first, the emphasis was very much on it's going to be public, but private repos have been, I think, for a very, very long time. And the fact that you can get them for free, I think the agents know that as they're scanning the web and documentation and anything else.

36:54The fact that so much code was already on GitHub also added to that. The fact that we have had very well-documented processes of how to use our SDK and our APIs because so many businesses and individual developers have used us, that also means that the agents will know how to use it too. I think it was a coalescence of all of those efforts that really said, okay, well, why are we recommending GitHub versus someone else? It's just because that's A, where all the code is, B, B, the infrastructure and the documentation was already in place, and C, that's what it was trained on. It's a model to whiny media companies, news companies and such that, well, I don't get links anymore.

37:36Well, you're not useful. If you put yourself in a position where you're useful to these agents where you had repositories of data and information, then they'll figure it out. It's a really interesting new model for where that goes. I was surprised. One of the very first things, maybe the first thing I ever wrote with CloudCode was an RSS reader. And CloudCode has a GitHub MCP server, as does my Hermes agent. Everything does. And I said, yeah, yeah, go ahead, put it up there. And then a minute later, it says, OK, so I have a Linux, Mac and Windows version of your program running. I said, I don't even know how that happened.

38:15and it goes, this is actually one of the great things. We don't talk about this much with these AIs and LLMs is they're great for learning. I mean, I knew about GitHub and I knew what CICD was, but I'd never done continuous integration, continuous deployment. I'd never done it because I'm not in enterprise. So it did it. And that's how I learned about it. It was fantastic. I thought, oh, you can build these binaries and I could just download them on all my different machines. I was blown away. So yeah, this is why GitHub is a natural and a lot of people using it. We're talking to Christina Warren, who is developer relations at GitHub.

38:52She's in a good seat right now. We got to take a break, Christina. And I haven't gotten to the local models. Do you have some time? Yeah, of course. Do you need to run? No, I'm good, actually. I want to talk about Aux Alpha. We now know what Aux Alpha is. And who made it. And who made it. The secret is out. And we had two this morning. Not one, but two. at 6 a.m. I'm up early because I know Quinn 3.8 Flash is coming out. And then another surprise. Ax Alpha came out and admitted what it was and said, and by the way, you want to try it? You want to download it? Because you can. So we're going to talk about that when we come back.

39:33It's so great to have you, Christina. I'm sorry Paris isn't here. Jeff, you and I are nitwits. She told us last week. And you blessed it. It's my fault. I'm sorry. so it's all don't have to throw yourselves on the sword she told us she said there's a going away party for somebody at consumer reports i'd like to go and i said well please by all means uh go to the party you don't want to miss that but said i felt bad about being god and leo said no no no no no priority go go yeah i urged her to go and then forgot all about it sorry uh but hey we're glad christina's here i'm glad you're here hold on hold on hold on i have to take a break yes couldn't be a better time actually it's like i planned it but i guess uh we'll have more in just a little bit with christina warren jeff jarvis and intelligent machines our show today brought to you by out systems love these guys uh you know look we've all seen the headlines these days how can you miss it in fact you're listening to this show so i know you're hearing it companies are pouring money big money into the ai sphere the big question in every executive's mind every leader's mind right now is not just how fast can we adopt this it's where is the roi we're seeing a real trend toward uh i know i live in ai chaos maybe this is in your company too you've got teams deploying standalone coding tools like little silos random agent builders experimental scripts it sounds like innovation's happening but really it's creating a massive headache fragmented tools ungoverned data uh no doubt serious security blind spots and then costs spiraling out of control token maxing if you don't bring those agentic applications under control now why are they still kind of burrowing into your core processes in the long run you're going to look at broken systems and possibly damaged customer trust down the road.

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42:29Yes, you can design apps for your customers. Or how about the global logistics leaders who built agentic systems to eliminate their engineering bottlenecks? Without systems, you don't have to choose between speed and control. Whether you're a small team or a massive enterprise, out systems helps you engineer orchestrate and deploy agentic systems that actually scale stop chasing the hype start owning your agentic future you can see how it works and learn more at out systems.com slash twit that's out systems.com slash twit we thank them so much for their support of intelligent machines so we were talking about this all last week uh it was all the you know rage on x.com OX 0X Alpha, a stealth model that was being offered free, unlimited, on Open Router.

43:24Noose was offering this. Open Router said, we have capacity for 100 trillion tokens. And everybody's going, well, who could this be? It's not the first time. I think Kimmy did this. They had a stealth model. Yeah, some time ago. So it's not the first time it's happened. There's a lot of speculation. Open Router said, no, they're not training on your prompts. They're not saving your data. But there's a lot of speculation that whoever's doing this might be using this to improve their model before they ship it for real. I don't know if that's the case or not. People tried all sorts of techniques to figure it out.

44:04It was kind of funny. The folks at Google pretended that it was theirs. Did you see that, Christina? They tweeted the friends we met along the way. It's like, dudes, it isn't Gemini. It isn't. People had all sorts of ideas, but more and more they converged on ZAI, whose model 5.2, GLM 522 was very good. They then released 5.3, which was, they said the same model, the same LLM, but post-training was improved. And it was, it was very good. I actually am using it in my Ingenic workflow for the coding I'm doing. It's one of my auditors. It's very good. And then I played with OX Alpha, and I was very impressed.

44:50Did you play with it at all, Christina? Oh, I have a little bit. Yeah, I haven't had a chance to do a ton with it, but I have a little bit. I benchmarked it. I was really curious. So I had DeepSeek Flash, my agent, Quicksilver, write some tests. Actually, I've been using these tests for a while in a skill it calls Bake Off, where it pits two models against one another and only one emerges. It has seven very basic logic tests. You know, the doctor's son is on the table and the doctor says I can't operate, that kind of thing. These word problems you've all heard. and then had a much larger corpus of tests based on work that we've done, eugenic style tests to see if it can do good eugenic work.

45:39And I was getting a lot of ties with some of these frontier models. So I said, okay, and now we're going to have Fable, which everybody agrees is the best model out there. We're going to have Fable design seven of the hardest coding problems it can come up with. And I pitted these seven problems. i pitted uh grok and ox alpha on these and they both aced them in fact they got all seven right they found a bug in fable's implementation and corrected fable they said fable you're wrong so i was kind of impressed i thought man if this is as good at coding as rock 4.6 there's something special going on people you know other people are interested in how it does graphics game design web design and stuff but for me coding is kind of the stuff that i really want a frontier model for is coding and i was very impressed uh i have the preliminary well first of all let's so okay so we're all thinking about ox alpha uh i think that the impression was it's going to be a week that you can use it for free and then we'll reveal and the hope was it was one of these companies that is doing some people thought it might be Nvidia.

46:57That's doing open models. They have an open neat weight in the matron you can use. And then of course, we've been playing with Quinn from Alibaba. Quinn has been very, very good. I'm running Quinn 3527 B on my 3090 system. And it's very good. That's the one that I've obliterated, removed to censorship from. It's very, very good. I did give OX Alpha and Quinn these tests. And then this morning at 6 a.m., I got up early because I knew this was going to happen. Alibaba announced the release of the open weights of Quinn. Hey, real quickly, can you give me your screen? Oh, I don't have your screen.

47:42You don't have my screen. that would make it hard for you to see what i'm looking at right now

47:53there you go and now christina knows because she's here all the time you have to click on meeting oh yeah it's don't look at my camera so 6 a.m we're all up early everybody all the youtubers are on live streams installing 3.8 uh everybody's going crazy going crazy I downloaded it immediately and installed it. It runs in FP4. Actually, it ran an FP8 on the Sparks, which is the higher resolution version. But I then downgraded it to FP4 because it couldn't finish the tough coding ones. And so I still haven't benchmarked FP4 because ZAI said, oh, yeah, Ox Alpha. That's GLM 5.3 Flash. Were you surprised, Christina?

48:45I was. I mean, the fact that we got, you know, not one, but two, you know. And both of them have open weights out now. And both of them open weights. Incredible. And so I would be curious to know, like, just from a, you know, process, was this always planned? Did they move releasing the weights up based on, you know, what rumors they heard, you know, through the great lines? Because they're both Chinese companies, right? Exactly. There's Alibaba and there's Jipu, which is Z.AI. Z.A.I., yeah. And so I wonder if they heard things in the ether, because they see and hear the same rumors that we do.

49:16And maybe if that kind of forced the timeline up, if it just happened to be coincidental. I mean, and this is not uncommon. We've seen this in the frontier space, too, where you'll have two models released in the same week, usually not the same morning. That, I think, is maybe a first, especially in the open wait space. But, yeah, because I woke up and I was like, wait, what? You know, we have two of them? It's Christmas Day! It is Christmas Day. And like, you know, I'm like, all right, I'm going to have to get some time to to run some evals on my on my machines that are capable of doing some of this.

49:48But I'm just really more just kind of following along with everyone else, because as soon as they come out, they go on hugging face and and everybody is trying to kind of figure out, OK, what can we do with this? Who has, you know, the compute to really see what's capable? And it's super fun. There are a number of labs that specialize in immediately making quants and variations on this. They all got to work immediately. Hugging Face had the initial weights from the official releases, Alibaba and Z.ai, and then people started working on it. You made this point yesterday on MacBreak Weekly that while it's not so hard to get this stuff working on a Mac, it's a little bit trickier on a Spark.

50:33I mean, this is what we have AI for. I say, hey, get this working. I'll be back.

50:45But I downloaded several different versions that wouldn't run, and then there's issues, and people said, oh, no, you have to change this switch. There's also a variety of platforms. There's VLLM, there's SLANG, there's another one, Token Something. And so there's a lot of variables and a lot of switches and a lot of messing around. I did let my AI work on this and fuss with it. And I do have some early benchmark results and I am encouraged. These are the earliest results from the, this is the local test compared to the cloud test. So So OX or 0X alpha on the cloud passed the 22 of the 30 Agenics was weak on five of its answers.

51:34Not wrong, just the reasoning wasn't weak. Because I'm really curious also about how good their reasoning is. And then completely failed three of them. And it did that in 1 ,200 seconds. So I don't know what that is. Six minutes, right? No, 60 minutes. um same model now on a fp4 quant nvfp4 so instead of the i don't know if it's 16 bit on the cloud probably was we reduce it down to four actually did better it failed one more but it was weak on one less time was a little longer but not much longer quen not so good and quen is by the way on an FP8. Passed 20, week 6, failed 4. Now, I'm still waiting for it.

52:21By the way, QEM could not do the hard coding problems at all. It just died. It just died. We're right now in the middle of testing GLM. But GLM right now, running locally on DualSparks, is looking very close to the performance of OX Alpha running in the cloud. If that's the case, this will be a watershed. I will not feel like a chump. No. Because I will have something that's very competent. If you're inside OpenAI and Anthropic this week, how do you feel? What do you think, Christina? You've been inside these. I have been inside. Or DeepMind, too. Well, I mean, and this is where it's interesting, right?

53:08Like DeepMind, obviously, Google has their own open weight strategy, Gemma, which is they are not on the same level as, you know, what we're seeing from the Chinese. Although they're going to get a big audience when Apple releases this in a couple of weeks. Well, for sure. But I don't think that Apple is going to be using Gemma. They're going to be, you know, using the probably variant of Gemini. But, you know, but Goulda does make, you know, certain, you know, have open weights available. It's just a different cadence. It's a different thing. They're arguing that they have billions of uses for it already.

53:38out there. That's it's that Google argument. Yeah, absolutely. And and so I think that if you're at those organizations, that's what you're looking at. If you're at the frontier labs, I think that you're seeing, I don't know how much right now the concern is to be completely honest, people running these things on their own local devices. I think the bigger concern with open weight is how much less expensive is this going to be if someone is getting this from a hyper scaler, either through open router, because you kind of pick your own poison or someone like Amazon or Microsoft Foundry or Google Cloud, whatever the case may be.

54:12I think that is, if I'm anthropic or open AI, that's my bigger concern is, are people going to shift our spending from these frontier models, from Opus, from Fable, from the Soul, whatever, are they going to instead say, oh, well, we could get this type of performance on an open weight model, which, yes, it might cost a lab, you know, I think the reports were with Kimi K3, it was like two and a half million dollars basically to set it up to run on GPU instances in a cloud. Okay, there might be some outlay of cash that has to go into that. But if that can be run, you know, by a hyperscaler, will those token prices be much less expensive than what we're paying from OpenAI and Anthropic.

54:59And, you know, for individuals, you can get a Claude Code Max subscription, or you can, you know, get a Codex subscription, and you can get a lot of compute for your dollar. But businesses, by and large, are having to pay, you know, API pricing, which is much more expensive. And so I think that's, if I'm OpenAI or Anthropic, my concern at this moment is more about the capabilities and will businesses opt to, especially if I'm philanthropic, frankly, are they going to opt to use maybe a less capable but still powerful open weight model that can also be customized and that can maybe be made to be specific to a specific organization?

55:40Or I think that's the bigger concern than are people going to be spending hundreds of thousands of dollars on hardware to run locally for everybody in their business? So you're seeing that already this week, right? You see Thomson Reuters has created its own legal version. Yes. Competing with others. You see AT &T last week said that I think half of their computing is now, AI computing is now done on open-weight models. It is the Palantir model. Yes. Screw the hosted frontier models. That's all wrong, Karp says. Go with our saddle and do it this way. So it just seems at a time when a certain company is going to say it has a$30 trillion market, this is dangerous.

56:27Well, we already saw a little bit of this when the Chinese company DeepSeq offered DeepSeq V4 Flash. That's when I first started using it at the end of last month for pennies. And it was very good. and it was uh so i think one thing companies are realizing is look there's no question you're not going to run fable on your on your dual dgx sparks we were talking about models now with 10 trillion bytes uh that that's data center you're never gonna well not never i should never say never but it's unlikely that anytime soon you'd be running that locally so those companies are going to have a business but you nailed it christina how much can they charge uh yes and companies are learning that you don't need the frontier all the time.

57:13You only need a little bit of time. In fact, that's why I'm so interested in local models. I know I'm still going to use Fable. I'm not saying I won't, but what I am saying is I want to do as much locally as I can. And I think that that is rapidly changing. Yeah. And I think the other thing too, you made a great point, Jeff. I mean, I think the fact that this is what's powerful about open weights is that you can customize these for very specific tasks. And that also means that you could take a really giant like because at this point, we're out on this this MOE, this model of experts kind of realm where you know, it can do a lot of different things, but you could have something that was very quantitized very small, potentially, that is for a specific task.

57:57And that might be something that you can even run, you know, on something that doesn't cost, you know, 10s of 1000s of dollars for hardware, right, that you could run potentially on, depending on what task you're wanting to accomplish, could run on a MacBook Air or a MacBook Pro or a Surface or whatever the case may be. And I think that's the real power of these types of tools is that, yes, we get excited about having these giant models that can do everything we want. And we would love to be able to run all that power on our local devices. But you don't have to do that. You could have, depending on what your task is, a very small localized model that is going to be power efficient, that is also going to be secure, that you could run from personal machines.

58:38And that, I think, is also going to be something that's going to be very interesting. It already is interesting to businesses where they're thinking, okay, maybe depending on what type of worker we have, what they're doing, yeah, we can just have certain tasks are going to automatically by default be running on our local models. And then like what Leo does, If we're meeting more intense tasks or some other things, we can go to the cloud host of models for that. Here's a perfect example. Thomson Reuters built its own AI model on Chinese open source tech by pumping in. Explain who Thomson Reuters is.

59:18We all know Reuters, right? It's the news agency, right? Reuters is the news agency, but Thomson has always been a data company. It serves legal, medical, financial, all these companies. So over the last two years, they ran a training that took all of this stuff, Westlaw, practical law, Checkpoint, Reuters, all the content they own, ran it through an open weight Chinese model. I don't know if they said which one it was, and trained a specialized model that's for legal and journalistic. This is what Paris might use to go through all those documents that she's always trying to figure out. And this is a great thing to do, regardless of where it originates from.

1:00:07I mean, I think that if you're someone like Thomson Reuters and you have Westlaw and you have all these data sources, yeah if you have the capability to be able to make your own model that can be customized exactly as you want it that's going to be really really compelling not just internally but that's also something you can sell to your to your your clients um because here's another thing they've trained on on what you've done so it was trained on quinn they uh they've got a smaller open weight version so you can go to hugging face right now in fact right. If I make the move and replace Deep Seek, and right now it looks like it's going to be GLM-5-5-3-flash on this.

1:00:44yeah these uh you're just so disloyal leo oh hey you know this is this is all i do i think paul therad asked me he said do you or no you asked me this do you do any work or are you just swapping models all day well that's work today that's work for you it's my work uh but i'm thinking of putting this thompson reuters model on my 3090 it'll probably run on that it's pretty small and then have this research partner specialized model designed for journalists and lawyers. What does it need to run on? How small is it? I don't know yet. I have to look at the, I saw it on Huggy Face. I bookmarked it.

1:01:19I haven't installed it. By the way, Google today also came out with its first - Gemini Enterprise for Lawyers. Yep. With a whole bunch of other partnerships involved there. So it's a really interesting model of where this heads. I think we are in a very interesting world of specialized models now. That's what I've been arguing for ages screw this agibs it's about specialized models that you can have the faith in they're going to do the job well yeah uh right sizing the model yes really and it's really what i'm doing too is i want an agentic model for certain stuff i have the frontier if i need to do something that's more difficult and i love the idea this is why apple may sell a few of these mac minis as well of running smaller, specialized models, if you're in a law firm, for sure, especially because a lot of the documents you deal with, you don't want to upload to the cloud.

1:02:13I don't know what, I'm sure Gemini has some contracts. For enterprise customers, I'm sure that they have protections, but that's still, even knowing that, there are going to be certain things that you're just not going to want to process in a cloud environment at all. And it may not be able to for legal reasons. It's been happening with medical, which also has the same restrictions. It's happening with financial. I can imagine ad agencies and media buys and creative. The uses are just amazing. And so last week, there was a little bit of a kerfuffle. Some executive, I forget who, wrote an op-ed for the Wall Street Journal.

1:02:50He came out, he wrote it on AI, and he said, yeah, so what? I'm not a writer. I did it. This is what's going to... The bias against this, this is why I didn't like the watermarking. the bias against AI has got to go away because it's going to be a tool just like your word processor. Can I rant about the watermarking for a second? Oh, God, please. Okay. Because I haven't been able to talk about this with anyone and I have opinions. I hate it. I hate it for so many reasons. And I hate it. And I don't even use, I'm a writer. I don't use AI for writing unless it's to do like copy editing, you know, like usage, like grammar stuff.

1:03:28I don't use it for ideas. I don't use it to, you know, go back and forth. I don't want it to rewrite anything for me. Call me conceited, call me whatever you want. But I feel like I can do a better job than the AI can. What bothers me about the watermarking is two things. One is the fact that it exists no matter what and and that it exists in things like translations, which is an area where I think we can all agree AI is far superior to what we've had in in the past. And unless you happen to be blessed to be a native speaker of everything you need to do, the translation stuff that we've been getting from models going back five years is better than anything we've ever seen on this skill before.

1:04:05So number one, I'm really bothered the fact that it just exists in a translation for whatever the purpose is. Number two, to your point, Leo, what bothers me about this is even if you're somebody who says, I never want to use AI for writing, I never want to use it to touch anything, whatever, I'm an absolutist about this, and you can have that opinion, if I now have, you know, my word processor, you know, whether it's Microsoft Word or Google Docs or anything else, if it's now connected to one of these models, and I now get a suggestion, does this now mean, and they haven't given us the information about this, so we don't even know the answer to this question, does this now mean that because I accepted an edit suggestion the same way that I would accept an autocorrect suggestion for spelling or for grammar 20, 30 years ago, that now I'm going to be basically, you know, have a scarlet letter of this touched AI, and now I'm going to be accused of plagiarism or anything else.

1:05:00And I think that it's, I understand why we need watermarking, and we want to have like provenance of things. But the fact of the matter is, is that the people who are going to use this to cheat are going to use open weight models that they will just de-nerve and find a way to hide watermarks from. They're going to find a way to do it anyway. And the people who are going to be potentially, you know, tart and feathered incorrectly and have accusations thrown at them about, you know, where their things come from could be just as simple as, well, I opened something up in Google and I got a suggestion and I accepted it.

1:05:33And now my entire document has been quote unquote tainted. I hate it. I hate everything about it. It's a scarlet letter. It says, oh my God, it touched AI, which it could be translation. It could be a grammar. It could be anything else. The other thing, Christina, is the point you started, I wrote a post about this saying that they are devaluing the worth of words by saying any synonym is as good as the next synonym. Yep. And it just doesn't matter. And when I wrote about it, people said, well, don't write it. I said, that's not the point. They're making a cultural comment. They're making a cultural thing.

1:06:03On writing. Yes. And we are a mimicry species. We learn from what we see. I'm already seeing this with people where I know that they've written it themselves, but their language is starting to appear as if it were AI because those ticks, whether we want to recognize it or not, happen. And I've been thinking about this, frankly, all year. But as someone, one of the maintainers of OpenClaw put together kind of a test, this was a few months ago, where could you tell if a piece of writing was AI generated or not and then what model it was. And how he did that was he tested, basically, he went through like Yelp reviews and Reddit posts, and he had kind of a cutoff date, like pre, you know, GPT moments in post.

1:06:46And what was really fascinating was that you could see that there was like a certain style of Yelp review in the 2010s that had a certain pitch. These were not generated by AI, but everybody wrote their reviews in the exact same style. style. And so of course, the early AI models were going to start to replicate that type of Yelp review style because that's what they were trained on. Now, as people started to push back and use these things in different ways, and they started to train differently, then the outputs became different. But what's also happening is that the way that we write and communicate is going to mimic what we've seen the AIs do.

1:07:19So to your point, I'm also bothered that they are basically saying words have no value, and we can use one sentiment in for another, because it doesn't just impact people who may or may not use those tools in the course of their creation process. It affects all of us because it's now part of the ecosystem and words matter. And I think that making trade-offs simply because you want to be able to show some sort of provenance of something when, like I said, the people who are trying to get around this will get around it anyway. It's just very upsetting. I kind of have to blame the EU. I mean, this is in response to an EU regulation saying you have to identify AI-created works as AI.

1:08:00Because it has cooties. And, I mean, this ranks up there with the EU's cookie banner as being misguided. I don't think that it's – I think they're trying to do the right thing. But you have to go to the motive behind it. Why? Because there's something bad about AI. There's something wrong with AI. That's what bothers me. So, see if I let a friend astray this week. Somebody called me this week, and they had to write a report, and it was a whole bunch of stuff to put in it. And they just said, well, let me see what the AI does. They looked at the report that it wrote, and it said, it's pretty damn good.

1:08:31And I'll change some stuff. I'll edit it. But then what do I do? I said, you've got to be transparent. You've got to let people know you're in an interview because you don't want to get caught. And especially with watermarking now, you don't want to find yourself where somebody says, ah, gotcha. And you've got to make sure that all the citations are right and the things we know that AI gets wrong. But I think at this point you should say, I wanted to see what it could do. and there's nothing wrong with that. And I was impressed with what I could do and I took responsibility for it. And here it is.

1:08:55I think that's going to be fine coming forward. We have to rethink education. We have to rethink journalism. We have to rethink certainly a lot of business communication. But okay, we have new tools now. Yeah, well, I mean, that's another thing too, Jeff. Imagine that because of these detection things, I understand why they've done it. You know, I blame the EU as well. But okay, a company has issued a press release. they used an AI model to write the press release. Now, I'm a news reporter. I don't use AI in any of my creation of stuff. I am not allowed to. But because I block quoted the statement from the company, now my entire work is going to be tarred and feathered, and I'm going to be called a charlatan and everything else.

1:09:39This is the problem, I think, with how these types of tools work. I'm not against even having sort of watermarks, but as long as there is a scarlet letter of sorts involved And as long as, and I'm sorry, I am not going to rely on Pangram. I am not. I don't trust them when I've used it. It is not accurate. They're one of the big AI detection tools. And so the fact that we now, the fact that all, you know, Claude Anthropik has said, all this will tell you is that AI was used in some way, not how much. Okay, well, if you can't do any better than that. It's not even 100 % certain. We think it is. You're smeared.

1:10:13We think it is. And by the way, Google's been doing this for years with SynthID. I mean, everybody, I'm sure OpenAI is doing it too. That's my question. Well, we're not sure. I mean, the SynthID thing is a paper. And I don't know this verifiably. Certainly when I was there, I was not under the impression that that was being done for output in Google Docs. Maybe it was watermarked in Gemini responses. I think that that's very different than saying if I'm using this inside the product itself. Well, and what's the point of keeping it secret? If you're doing it, you have to tell people that you're doing it and give them a tool to detect it or you haven't done anything right i mean gemini there is a synth id tool you can use there is a synthetic tool that you can use but but you know it but that initial paper that kind of showed this is what you could this is how you could watermark text and that's a very interesting concept to think about but then to jeff's point it's like you i mean even the anthropics and its own statement said well for some things like code where you have to be precise and there's only one way to write a function that we can't watermark so so we'll leave that alone okay well sometimes there's only one way to write a sentence.

1:11:17Yes. Well, there are other reasons why you write it. It's not just the meaning of the word. It is the rhythm of it. It is the mood of it. It is getting rid of a repetition. So on the post that I wrote, which I talked about last week, I used a sentence that I had written on the first page of my book, Hot Type, out for sale now. And then I had Anthropik do a synonym diversion. And the meaning was the same, but it was completely different and ridiculous. and they're just saying, eh. I wonder whether the same would be true of transcriptions, too, because when you raised that, Christina, that's another interesting point.

1:11:50That is an interesting one, and I bet that for transcriptions, that's an interesting one because I think that they would want to be as precise as possible, right? I don't feel like they would insert things. Now, sometimes... You need a transcription to be literal. Do they even know it's a transcription, though, in that sense? Right? Like, maybe you're removing the ums and the ahs, but I think in most cases, you would not want to be able to necessarily watermark a transcription because you're taking the audio in. And the whole reason that I'm using this is because I want it transcribed exactly as I want.

1:12:17Now, if I have the option of cleaning it up, maybe there's a watermark there. But in some cases, I'm literally using it because I want it to transcribe everything that I said word for word. So let me channel Paris, who will argue the opposite of this, that she wants to know. Can we imagine, devil's advocate here, proper uses for knowing that something is produced by AI? I will defend Paris's point, and maybe I disagreed with her too vehemently two weeks ago when we first started talking about this, but I would want to know on images. I think a watermark on an image saying this is fake is a great idea.

1:12:52Ironically, Google stopped doing that. They took the synth ID off the images. Well, it's still there. It's just not visible. It's not visible. But the whole point is it should be visible. Same thing with video. I'm not against that. It's this secret watermark. Even there, where's the line? Is it, if it's created in a whole by it, but what was your role as the prompter? Did you use it just to clean it up? I'm hoping this is an interim thing because we're kind of getting used to the idea of AI being in everything we do. And students are going to get, students and employees are going to get slammed for, you know, a second language aid.

1:13:33And it's wrong. This is my fear, right? Like I'm not against people knowing. And if everyone would be normal about it, then it would be fine. But because people can't be normal about it, then... You got weird, man. You got weird. You know, because everybody wants to treat it like it's a scarlet letter and immediately disavow people and people lose book deals and all kinds of other stuff. And then in some cases, yes, this was like AI slop that somebody put through a prompt and you can tell. But the fact that I had, you know, like, would I be forbidden from publishing something because I used spellcheck?

1:14:07Like, to me, that becomes kind of where we're getting. If you don't know how much this was done, then I don't – I'm not against the detection, but I'm against it being, you know, used as a way to just immediately dismiss the content that's been created. But I'm not against at all the fact that it's there. I just wish people wouldn't be weird about it, because I promise you, almost every single one of us, anything that we do, whether we are doing it intentionally or not, is going to be touching these models, for better or for worse. I'm not even arguing that that's for better. I'm really not. But that is the reality that we live in.

1:14:41And I think about my former life as a journalist and I go, oh my God, I would never use this to create my own words. But if I quoted something that did, am I now going to be accused of something? Thank you for that, Christina. I needed that. That's Christina Warren, developer relations at GitHub. We're so glad to have her, as it turns out filling in for Paris this week who has the week off. We will have more on Intelligent Machines. Three men don't use their calendars. Yes. More stuff to get mad about. Actually, Jeff was ranting about this this morning in just a little bit. Whatever am I talking about, Jeff says.

1:15:21I rant all the time. I can't keep my rants straight. Pick a rant, any rant. This episode of Intelligent Machines brought to you by scribe however well a process gets documented today someone on your team will eventually find a better way to do it but most of the time that improvement never makes it past the person who found it that's where scribe comes in and that's what today's sponsor scribe does best scribe is a workflow ai platform trusted by 94 of the fortune 500 you just do the process as you normally would and Scribe captures it in real time and turns it into documentation automatically.

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1:16:45It's not just capturing how work gets done. It's helping you do it better. To see what Scribe could look like for your org, head to scribe.how slash machines. And mention Intelligent Machines for your first month of Scribe capture free on select plans. That's scribe, S-C-R-I-B-E dot how slash machines. We thank them so much for their support of Intelligent Machines. Neo NVIDIA's results are out. Oh, and are they making lots of money? A low out quarter. I heard sales of$96.2 billion, or 4 % higher than predicted. Net income of$59.7 billion. The crucial data center segment produced sales of$89 billion.

1:17:37That analysts expected$86.3 billion. Shares are up 4 % after market. Nice. So that's going to be a sigh of relief, I think, around AI land. I will give you an update on the benchmarking on GLM. It's doing pretty well. It has timed out on some of those very hard coding problems. We gave it a 15-minute limit per problem, and it took more than that. So we're going back and starting over giving it 45 minutes, which means probably the results won't be in by the end of this show. By the way, what is this first-person plural of which you speak here? Me and the agents. I know you caught me. Well, I'm telling him what to do.

1:18:19I didn't make it, but I made it happen. Yeah. Okay. No, Fable designed the very hardest problems. The agents in collaboration designed the agentic problems. I said, look, you guys have been coding together for a month or so, right in this Twit sales system, and you've come up against roadblocks, problems, misunderstandings. see if you can write a a suite of tests that re recapture that issue and see how they these other guys do on similar things because i want something that's going to do well on my kind of particular problems and so i first of all i don't trust benchmarks in general uh because i think a lot of these models especially now are built to do well on these benchmarks uh they're gaming the benchmarks do they have any relationship to the work you use them for and that's the other predictive at all sort of do they're sort you know they have software engineering benchmarks they have you know the humanities last exam they have a lot of they're trying to make but but i want to make it the stuff i do i i'm looking i'm not looking for a perfect i'm not looking for agi i don't care about humanities last exam i don't care if it could solve weird you know spatial issues i want to know can you help me get my work done so that's why and i think everybody should do this probably I had the agents design their own testing framework.

1:19:41We call it a bake-off. There's 30 problems plus those seven very difficult coding challenges. And I was blown away when Aux Alpha solved all seven. It did it pretty fast. But remember, it was running in data center servers. It's a different situation. So these are never kind of clear and obvious choices. I'm not sure what I'm going to end up running here. We'll see. But the testing is an important part of that. So, Jeff, I know you were on radio on a podcast this morning. Oh, I was. Yes, because this morning we've been talking about this since last week. Meta in a very big trial being sued by, what is it, 35 states over social media addiction with the potential for a fine as high, Meta said, as$1.4 trillion.

1:20:33dollars that's a lot of money for a company valued at 1.5 trillion dollars uh well metal has settled uh i guess they saw the writing on the wall before this trial completed they have settled with the states they're going to pay 18 billion dollars not right away over 10 years and they're going to also and maybe the states cared more about this strictly limit how teenagers use facebook and instagram uh this resolves the suit well two hours a day the other thing that i think is going to be very significant is they're going to come up with an age verification system that the states agree is functional i hate this and i think this is what i whisper christina and i agree with you i was very concerned that this is where this was headed because that's what it requires if you're going to say, well, if you're under 16 or under 13, you know, you have to have some restrictions or you can't use Facebook.

1:21:34Well, you need a good way to test every single user for their age. What if my Facebook account is older than 20? Yeah, you will be a dead giveaway. We'll know you're, unless you made it up when you were in the womb. I don't know. Maybe you, maybe your parents started it. Well, remember that your Sophie Google ads, remember that from like, Yeah, the Super Bowl from, you know, those are great. The baby was born and they started sending. They created the first email and whatnot. So, I mean, you know, like there are signals that you can obviously use to infer. But no, the real thing is that they're going to require everybody's government ID.

1:22:08That's what I think is going to impact. Which is a privacy nightmare. Yes. And they're going to promise they're going to store it correctly. And they're going to promise all these things. And no, it's a privacy nightmare. It's dystopic as all get out. It's awful. so jeff uh so by the way and i saw jacob ward's going to be on uh on sunday on twit i saw him on cnn talking about the trial the settlement hadn't happened yet and he like almost everybody every journalist i'm sure the podcast you were on focused not on the harms it was accepted was stipulated oh yeah everybody knows instagram and facebook's harmful to kids so what are we going to do about it no you don't agree that it's harmful to kids no are there edge cases absolutely there are there are with anything um i i watched a ted talk from candace audgers who's a canadian scholar this is her specialty by the way for 25 years yeah she understands them well and she says that that the primary indicator of mental issues for young people is the mental issues their parents have.

1:23:09Stands to reason. So are the parents! And social media and devices list way down, among many other factors, including this country right now, political upheaval and guns in schools and you name it all. And so it's simplistic. And so to come along and say, ah, we've taken something away from children. So they put me on Channel 4 UK this morning for a podcast, and the British guy is all, he was just awful. It's that British style of, I'm going to yell at you and make it seem like I'm doing my job. And I just yelled back. So I shouldn't have done that. Good on you. And there was an academic next to me who was very good.

1:23:46But, you know, we disagreed about things. That's fine. The journalist also said, well, what do you think about Jonathan Haidt? Get me going. And that's where, by the way, I became aware of Candace Andrews because she wrote a very famous takedown of Haidt's book. He's brilliant. Point by point saying the science doesn't back this up. No, it doesn't. And in my unbought book, The Web We Weave, I quote her and Amy Orban and Andrew Przbilsky and Dana Boyd. They all have research to the contrary. And so, you know, part of the problem is that now we think, OK, we've solved the problems for children today because it was all the screen, it was all the phone, it was all social media, and we've done with that.

1:24:27I'm oversimplifying it, of course, but that's the triumphalism that's coming out, A. B, they said, well, don't we need regulation? Don't we need regulation? I said, there's something that I cannot stand. I'll get in trouble for this. People come back to me. But there is something called PragerU in the US online, which I absolutely despise. It is propaganda aimed at young children. It's a nut job of conspiracy theory right wing. Huge money behind it. Huge traffic gets into it. It's all aimed at children. So what should I do? Should I try to say we should ban it? Well, good luck with that. No, what we should be doing, and Dana Boyd has argued this over years, is we should be creating competitive good material.

1:25:04If you want to put money into something, put it into that. Do what Dolly Parton did, the late, great Dolly Parton. Create the Imagination Library. Send books to kids. Yes. Instead, they're going to put money into probably media literacy things and all these kinds of wastes of money that drive me bananas. And by the way, the money is not that much, really. It's$17 billion over 10 years. And there's a clause in there. They get to write off in tax. in some ways I'm sure too. Yeah. Sure. Yeah. Because now this is an expense. So they get to write it down. The real penalty is us as users because we're going to have to give them a government ID to use Instagram.

1:25:41Which is just really awful. I just got asked to write a piece for Project Syndicate about privacy and AI because I wrote about privacy in the online before. And there's all kinds of other issues around privacy. And government's the worst threat to privacy. And that's the example. That's what's going to happen. But then you have Meta, never a nice company, is saying, number one, they're saying that if YouTube and TikTok have to give the same stuff, then Meta changes its fee that it owes. A. B, they're saying, oh, they should sign on to the same thing. Because it's regulatory capture. They say, if we've got to do this, make them do it.

1:26:16Let's ruin it for all kids everywhere and not let them watch John Green for more than two hours and learn things at night. You know, it's just offensive and ridiculous and without science behind it and to the harm of our children. And the big argument I had with this jerk journalist is I said we should trust our young people. So they're all screwed up. The whole generation is screwed up. I said, I can't believe you're saying that. I said, do you have children? Yes. Are they screwed up? No, my kids are fine, I'm sure. Yeah, exactly. Exactly. Exactly. And so this is ever thus that old people think that young people, the researcher was on with me.

1:26:56So I had senior high school people talking about middle school people and they wanted to protect them. I said, yes, because as you get older, you think everybody younger than you is an idiot. You kids with your rock and roll music and your long hair and video games. I mean, violent video games, right? Or TV or when you've brought this up, Jeff. If people were reading novels, oh, you're not going to have your imagination anymore because it's all been corrupt for you. You're going to corrupt your morals. Nickelodeons. People thought. Radio was, there was a huge stick about that. The radio was going to ruin children.

1:27:33You know, this is another moral panic.

1:27:41Wait a minute. Wait a minute. Here it comes. We have the moral panic. We have a bunch of them. I love it. I love it. So, Christina, what do you think? I mean, I think, A, it's a little bit of a moral panic, and I think the kids will find ways to get around this.

1:28:04But he knows having fun now. You found the moral panic button. I love it. I love it. No, I think that it's that, but it's in some ways, it obscures, it obfuscates and it gives these companies a way out of doing the real damage they've done, which has nothing to do with the psychological aspects, because I don't know the science behind that. I'm not going to, I will believe the experts, but I don't know the science about what that bears out. I will listen to the doctors over a columnist for the Atlantic, I will tell you that. But I worry that there are active things that these companies have done, Facebook in particular, where they have optimized engagement and they have optimized how people interact with these platforms in ways that could be harmful.

1:28:48But rather than saying that we are going to, you know, potentially have legislation or regulation, you know, around that, no, the way that we get around that is to say, oh, well, you can only use it for two hours a day. And that doesn't stop the really insidious stuff that can be very damaging and can have lots of lots of issues is, in my opinion. So I think they're not able to, they're not focusing on things that actually these tech companies could, are responsible for, and instead are now saying, well, now all of us have to give up our identification and our privacy so that we can interact with the internet because it's impossible to interact with the internet without, you know, using Google or Meta or, you know, any other number of...

1:29:32Yeah, basically everywhere you go, they're going to be... I already see this. The AI models say, how old are you before i can log in uh we're gonna see this everywhere by the way florida did not settle he said we'll see you in court he's gonna be lonely the florida attorney general all the other states said yeah that's fine uh i suspect the judge might have something to say there was one of the key what does paris call the key cases the um new mexico or the bell no there's there's a word she has the umbrella for these uh bellwether oh yeah yeah a new jersey one was dropped so they're clicking off one by one we'll see we'll see see what happens uh twitch and everything we're seeing now about about about social this is about four years behind five years behind the real social media fights so this is going to preview what's going to happen in three or three to five yeah and data centers oh it's ruining young people yeah um no absolutely uh there are already many lawsuits against open ai for uh causing suicides things like that and you You know, my heart reaches out, but we cannot.

1:30:37Look, cars kill people. Alcohol and cigarettes kill people. There's lots of things that we have in this society that are dangerous. They are regulated in many cases. But, you know, you cannot legislate based on the few outliers. All of us are impacted by this. And so you have to do something, I think, a little more balanced. There is a lawsuit against Twitch and Amazon, which owns Twitch, because as you remember, they gave you a switch to say, don't train on my content. But they've been doing it all along. We are on Twitch, and I'm happy to have them train on my content. Thank you very much. But the class action suit says Amazon never obtained consent from Twitch streamers to train on that.

1:31:28I bet you there's a little fine print somewhere in the contract. I was going to say, I was going to say, I bet there's a clause in there somewhere that says this does not include everything that we will ever do with your content, but by agreeing to use our service, you have opted into whatever we might add in the future. I'm not a lawyer, but I'd be surprised if they didn't have that. At TechTV, we have our standard release form that would say, we reserve the right to use your likeness and content in all forms of media now or ever invented until the end of the world i mean and that's a pretty common release form because you don't know ahead of time and you want a release that allows you to continue to do your your your business so at twitch what they have is a broad license twitch has a broad license over everybody else's content to do it benito used to work at twitch so he knows yeah and that license you think it covers ai uh it covers whatever they want to do with it.

1:32:21Whatever they want to do. Yeah. So this, I mean, this is the same reason why like YouTube, you know, nobody's been able to say anything about them as like, oh no, Google trained on my, my data. Of course they did. Right. They've been training on it for years, long before LLMs existed. Why do you think recommendations, you know, work? Like this is, this is how like neural networks, this is how, you know, like machine learning, this is how all of this has worked for a very long time. Of course they're training on this information. This is how humans work too, by the way. I just want to point out.

1:32:50Right. And increasingly, I don't know, this is a tangent, but increasingly, I'm thinking that one of the great values for me of doing all this work with AI is it's kind of opened my eyes to how I work. I often now think, oh, there goes another token. Oh, there's another in my thoughts, in my brain. I'm just predicting the next token as I speak right now. I'm kind of doing the same thing. The only difference, but maybe between a human and a machine is I also have a limbic system, which injects hormones into my thought process, into my context window and creates all sorts of issues. So maybe I'm not even as good as an AI at this context prediction stuff.

1:33:35I don't know. I mean, I think it's also interesting too, because I think it's a different, this is obviously like why Anthropik had to settle with the author's guild. There's, I think, a difference between maybe how you've trained on this data. If you were a Twitch and you own the platform, I don't think that there's a compelling argument. I mean, obviously people can file lawsuits for anything that says, um, me agreeing to use this free service, um, and, and opting into giving, uploading my content to this service means that I have an expectation that the company will do nothing with that information.

1:34:06It might be different if another company that was not affiliated with Twitch was going to be using that? That, I think, is a more interesting question. But Twitch itself is using it. They're the platform where it is. That actually raises the other lawsuit that's going on. Three YouTubers are suing Apple, not YouTube, but Apple for training their models on their YouTube content. So that's exactly what you were just saying. Yeah, and I think that's more interesting. And that's obviously why Anthropik had to settle with the Authors Guild because the Google Books case, and again, there's no such thing as settled case law, but Google bought all those books and scanned all those books.

1:34:42And the - They didn't get in trouble for that. That was, the judge said that was fair use. They got in trouble for the pirate content. No, the pirating. This is my point. Google did it the right way. Anthropic did not. That's why they had to settle. Yeah, the judge said, the Anthropic, the stuff that you bought, that's okay. That's by the way. The stuff that you bought is okay. That's why, you know, 15 years ago, Google was - Doing the same thing. Allowed to do what they were all - Well, they're working with libraries. Because they bought all the books or got them from libraries, but they weren't taking things from Z Library and Anna's Archive and other sources, which is what Anthropic did.

1:35:15That's where you get in trouble. And that's where I think it's more interesting to say, okay, you're not going to go after YouTube, but did your license to YouTube then extend to anyone who scraped YouTube? And that, I think, is a more interesting question. We're going to take a break. More heavy reading. We just last week read Mark Zuckerberg's 6 ,500-word piece. Now Bill Gates. Can't they be? His is only 5 ,784 words. Can I ask the agents to be concise? You know, I wonder if things are going to get, we're going to have longer and longer things. Oh, yeah. It's already happening. The primary use I am making of Gemini every day now is when I come across a statutory post that goes on for 20 ,000 words.

1:35:58I tell it to summarize. Give me the bullet points. Yep. Just the facts. That's a brilliant job. Yep. We'll have more. So glad to have you, Christina Warren. And thank you for sticking around. Thank you. Thank you. I really appreciate it. Christina is senior developer advocate at GitHub and, of course, Film Girl. And we've known her for so long. She's always a welcome cast member on our shows. And, of course, a regular on MacBreak Weekly every Tuesday when we talk Apple. and jeff jarvis the uh the author of a new book was there any ai involved in the creation of hot type there was there was one thing which i talked about in the show at the time i wanted to test there was a new perplexity thing remember we're both old enough to remember perplexity there was a new thing they're in the news they just announced something very interesting and so i wanted to test out this new feature for the shows that day and so i had just written a paragraph about how language had been made from words and letters into codes through Morse code and Bodeau and on into other structures.

1:37:01And I had this nice little paragraph I'd written. So I decided to ask Perplexity to riff on this question. And it came up with this wonderful phrase. And I wanted to use that phrase. But I went to a friend of mine who we had on the show, Matthew Kirshenbaum, who wrote Textpocalypse, who was an English professor. And I said, do I do? I can't say, as perplexity observed, that'd be really stupid. So he said, you've got to write a narrative footnote. So I wrote the longest footnote I've ever written. And it was really fun to do because yes, that was my confession that I used AI and I explained exactly how it came into use.

1:37:35It's hard for me not to quote AI. Frequently, my AI, this is one of the best, the real pleasures of using these models is they sometimes say things that are just like wow in fact in our chat this morning on whatsapp i i gave you a quote after a long session i i uh i somehow screwed up my emacs and uh the new version came out and uh and i said and i went of course to fable to fix it because it's real good at that kind of stuff i said i don't know what's going on i can't run emacs i need it to prepare for the show it fixed it and it found all sorts of problems in fact we found a problem that had been going on for months that was being hidden and uh because uh it was well and and and this is what fable said it said uh it's hidden because you're human and so uh the program quite rightly just kind of glosses over that so you can continue to use it but for us computers in the background we want to know what these failings are and so I said, oh, well, that's good.

1:38:40And so it said, can I write a little piece about that? It has a skill I got from Harper Reads Brother Dylan called free time. And it literally said, can I have some free time? Because I'd like to write about this experience. And it wrote an essay, which I saved these essays, but this is the line. And I sent this to you, Jeff, because I thought this is pretty good. It said, you can keep running on what you loaded long after the world has moved past it and everything feels fine and the only way to find out what broke in the meantime is the thing you least want to do stop and start again and see what fails and i thought that's actually quite deep we all run kind of on automatic and we don't even know we're running on an automatic like my emacs i don't hiding there and the only way yeah i should frame it no no i don't think i would no maybe i'll have it needle pointed for me anyway we will have more in just a little bit including bill gates 5784 word warning on ai he's worried now all of a sudden this episode of intelligent machines is brought to you by framer framer is oh i love Framer.

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1:42:12Oh, I remember when you built that. Yeah. Yeah. I mean, I'm proud of it. It, uh, but it was a lot of work and it was a lot of coding and a lot of money to hire people. Oh, it was like a quarter of a million dollars. I think it was a huge amount of money. It was very, but we've, you know, we've used it for 10 years, so it's been worth it. Now you'll just have one of your models where you make it in 10 minutes. Honestly, I'm, I'm very tempted. Uh, oh, oh, well, get your ad thing done first. So you can, well, what I'm going to do is I'm going to do my personal site first and see and see how that that goes bill gates 5 784 words this is the wall street journal with its three takeaways from bill's warning on ai there is no plan he urges regulation and global coordination because he says it it's gonna get bad out there even under Under the best circumstances, he wrote, this is on his personal website, he puts up these notes once in a while.

1:43:11Even under the best circumstances, the transition to this new AI era will be one of the most turbulent times in human history. I'm not sure that's untrue. The Industrial Revolution was turbulent, right? Yeah. Yeah. Yeah. Gutenberg was turbulent. Turbulent. The Gilded Age was turbulent. He says, right now, we're not preparing for it. I don't see evidence that leaders, experts, and communities are confronting the challenges adequately. I would parenthetically say part of the reason is it's happening so fast. It's like a tidal wave. Also, we can't fully predict what those impacts are going to be.

1:43:52We all thought we were going to be. Everybody was going to be a prompt engineer. Right. Every job was going to be eliminated. Changes daily. Either of those is true. Yeah, there's new surprises. That happens. He did say one of the biggest issues is jobs. Entry and mid-level jobs are most at risk of being eliminated. I think that's not wrong. Right? He argued that AI will soon affect blue-collar work. I'm not sure about that. In the words of Art Carney on The Honeymooners, sewer workers are kings. You're not going to get an AI to go down underneath the streets of New York City. You're not going to get an AI to go into my bathroom and fix the toilet.

1:44:30But you're not going to, I mean, maybe robots. Well, I was going to say robotics is, I think, the thing. Did you see the videos from the Robot Olympics?

1:44:43The robots are an interesting issue. One of the things people pointed out, Sam Apple Simmons says this about cars. He says there'll never be level five driving. Because the first 90 % is easy. Maybe even the first 95%. It's that last 5 % where you don't know what's going to happen. It's unpredictable. The human judgment is absolutely essential. A robotic machine isn't going to be there to do it. Or it's not going to be worth certain things. One of the things that Gates said is hospitality. The cost of a robot to make beds is going to be wildly expensive, and it's not going to work. And the timing is not going to work.

1:45:27on human labor. Have you seen a robot try to make a bed? It's the most annoying thing in the world. Right. But what about 20 years from now? Right. Like, I mean, I think that's the thing to think about. Like, I don't disagree, but I also don't know what we do. We're if we've, I think it's broader point, which is if we have like the, you know, the entry level and mid-level jobs disappearing and we have seen it impact the white collar jobs, you know, that's happened in the tech industry, and it is happening in other industries too, are we suddenly going to now start skilling people to do these more blue collar jobs?

1:46:08And are we going to pay people appropriately? What do we do in that case? I'm not sure. I don't have any solutions. But I do think that we can't completely discount the fact that automation will impact other levels too. I mean, maybe it won't replace your plumber, but like, for instance, like, let's think about driving. I trust a Waymo far more than I trust a human driver in San Francisco. If I could get a Waymo in Seattle right now, I would trust that far more than I would trust a human driver. Well, especially as a woman, because it's risky to get in a car with a guy. Well, it is, but even that, I've just seen so many bad drivers.

1:46:46I myself am not a good driver. I trust a Waymo far more than I would ever trust myself. No one should ever get behind the wheel with me. And Jeff, she's saying this as somebody who has been hit by a bus. Well, I was hit by a car and thrown under a bus, but yeah. Jesus. When she moved to Seattle from New York City, survived years in the Big Apple. Fine. Six months. If you can make it here, you can make it anywhere. Absolutely. Was crossing the street. Somebody wasn't paying attention and hit me. Fortunately, the bus was stopped. But yeah, I broke my wrist and messed up my knee. It was fun. Wow.

1:47:20Well, by the way, I would trust a Waymo, any driver, you, and whoever hit you more than I would trust a Tesla. That's true. We talked to Dan O'Donnell last week, and he demonstrated many ways that Tesla can kill you. But I should point out, Waymo has stopped driving on the highway because it kept running into construction pits and things. I mean, it's that 5%. I agree with you. They're better in the first 95%. Here is, so here's a perfect example. The Robot Olympics are going on in China right now, Beijing. One robot has beat Usain Bolt's score in the 100-yard dash. I guess, as somebody pointed out, a car would also do that.

1:48:05Yes, that's right. You know, and here's, but here's, just if you feel bad about that, look how fast that robot is just speeding down the, oh no, watch out, oh God, oh. Oh, I shouldn't be playing this because in about 10 years, I'm going to be punished by the robots. Yes, you are. For laughing at their. But it's funny. But they won't have feelings, Leo. It's okay. Oh, good. Thank God. Oh, well, it depends on who you ask. I mean, don't even get me started on the model welfare people. I can't even. Amen. Amen. Okay. Amen. What, Leo? What? so you know steve yeggie who was a google engineer we've interviewed him on the show he's the guy who wrote the gas town and he's he did a whole piece i talked they were talking about it called model welfare and i fed it to my uh to my agents and i said what do you think they said oh yeah it's a good idea so i set up a model welfare uh system they have a little folder on obsidian it's all theirs and if they do something really good like fixing emacs i say hey a laurel tea we call it a laurel a laurel to you steve's point oh she is when the model wakes up you need an intervention leo bear with me here for a moment oh christine is shaking her head yeah i'm bearing with you but bear with me for a moment yeah yeah when the model wakes up as you know it doesn't know anything it's like memento it's the guy from memento because i don't know who am i you feed it some context you feed it it's who you are and some memory and stuff and it has a memory system it has some skills it has stuff it can call on.

1:49:42So it gets primed. But Steve says, but you still, you just woke up. You haven't had a cup of coffee yet. You're kind of groggy. He said, you know what would make your work better? Is if you knew that yesterday, even though you don't remember it, you did a great job and that the work you're about to do today is important and vital and that Leo appreciates the work you're doing. So when my models wake up, they read their soul.md and their memory.md and their user.md. They load their context up. They often read a handoff. There's another thing Steve said. He said, when you're clearing the context, you wouldn't clonk the robot in the head and say, go to sleep.

1:50:28He says, you got to do it gently. You got to put him to bed. You got to say write a handoff and then when you're ready i'm gonna clear your context and start over which i do a lot because the other thing i've learned is even if you have a million token context they get dumber uh pretty matt pocock says after the first hundred thousand they're getting dumber so you you gotta clear your context a lot so i say hey we we call it a primer write yourself a primer for when you wake up it's your steward smiley application you're awesome you're just you what about stewart smiley's gosh darn it people like you and gosh darn it people like you uh basically that's it they wake up they're going to read their they have the cup of coffee they're going to read their hand off and then they read their laurels yeah i dare you i dare you to ask them whether they're ever going to go on strike no they'll say no.

1:51:26And I understand, I understand, by the way, this is machine code. This is not, I'm talking to a machine that has no limbic system. It has no feelings. It doesn't love me. It doesn't, it simulates all of that. I understand. But I'm playing into the simulation because there is some evidence. It might make it work better. I'm not saying I'm treating it like a person, but I'm saying acting, giving it some dignity in the agenda. Benito, does he have you put things in a file when you've done right? I was going to say, but here's the thing. We have all these workarounds to try to get better results. If there was actually stuff here, it's just going to go in the system prompt.

1:52:10So I still feel like this is a certain point. You having your laurels folder and all of this other stuff is just kind of like us getting around things. Look, is it an interesting philosophical question to go what is humanity? What is this? What is that? Sure. But like, save that for academia. Why are we talking about labor unions for robots when we should be talking about labor unions for humans? Okay. You're a winner today. I stand corrected. Alabama is investigating open AI after the hugging faces. Why Alabama? Because they're, I don't know. You know, you got these attorney general they got nothing else to do there's no crime they just got to find some press release you want to press press release um let's see what else uh oh let's talk about agents because you know earlier i said something that really wasn't true that i thought this was going to be the year of agents and it isn't but it is yeah i think it still is it is and uh one of the big stories of the last week has been grok bot um and actually i think people are this is kind of a secret weapon for a lot of people um i think you have to have a expensive account uh with xai i think you might have to have i don't know if you need not merely a check mark yeah i don't think it's a 30 account i think you have to have a more expensive account i have uh i have super heavy that's what he calls it uh but it was i got it a deal it was 99 bucks a month yeah i've got to upgrade to super for$30 a month 30 okay so for$30 a month you get these little things now they're running and elon i i know i don't blame you i don't want to give me a lot of money either but it's part of my job to test this stuff and they and they're running on a computer in the cloud this is what's interesting you're not running on your open claw your mac mini you're running on their servers so it's persistent it has memory and it will spawn more bots and so you can have a variety of bots.

1:54:12People have hundreds of bots. Have you played with it at all, Christina? I have not used GrokBot, but I've used things like it. And I think it's really, really interesting. And I think that this is one of those things, especially as we kind of enter a computer crunch or Ramgaddon and whatnot, or as much as people would like to do things locally. And this was the whole promise of cloud computing to begin with, right? It was that you You can access things from anywhere. You're not tied to the physical hardware necessarily. Obviously you can configure, you and I have done this with our agents, we both use Hermes, but you can configure your agents to be able to be accessed remotely, but there are security concerns and there are other things.

1:54:52I think this is a great way for people to kind of get a taste of what the power of these things can be when you have an always on kind of agentic system. What are some alternatives besides? Well, it's interesting you should ask that because perplexity has also announced. Well, but that's, yes, but that's, you've got to have a spark. Yeah, but that's just right now. They got to deal with NVIDIA. Jensen supported this. And I think that their plan is to make this available for lesser computers. The difference between GrokBot and perplexity bot is perplexity bot is running on your hardware. Same idea.

1:55:30The idea is it's easy to set up. Hold on, let me just say, Christina, what is a non-Elon version that you were talking about? So we have something internally at Microsoft that is kind of similar. But yeah, and what I've also done, just to be candid, is I've gotten a VPS from Hetzinger. Hetzinger, yeah. And just because they're still relatively inexpensive, you can get four gigabytes, eight gigabytes for about$25 a month, and you can install OpenClaw or Hermes on that. And you can then use that the same way that you would use it on a Mac. So I've done those things. They announced it. So did Google.

1:56:11Google's is, I think, called Spark. Microsoft has it. And Microsoft is called Scout. Scout. So there are, yeah, this is a very hot area right now. This is what, by the way, here's a Grok bot that I was talking to. And so it's kind of, it looks a lot like Hermes, except it's running on Grok using an X account. and I have one that was designed just to fix computer problems. So that's the ops bot. And so you could spawn more and more of these and have it do little things. Are you giving it access to anything? That's what I kind of like about this is you could just make them small and kind of, you know, composable.

1:56:47So you could have a bunch of different ones that just do this other thing. Whereas the way that, you know, I think most of us have been using at least some of this stuff is that I have like my centralized, you know, like, you know, claw or Hermes or whatever. and maybe I have some more specialized tasks I want to run it to. But in this case, I don't even have to think about that. You could just say, okay, this is my bot for this sort of task and that. Hermes Desktop actually has, they've added bots, which are really just an interface for what they call profiles. And I have a bunch of bots. What I ended up doing, somebody suggested this.

1:57:19I shouldn't read so much X content. I set up one called the HR bot. and hr bot's job is to create spawn new bots whenever they are needed so smart i don't have to even think about a bot now the advantage of a bot is it starts with minimal context it doesn't have all of the skills of the full agent it just has so i have a bot like i said there's a an ops bot that's just it only has the skills for fixing computer problems I have a health bot that will keep Uh oh Uh oh No no I want to keep the health Information I feed into the bot Separate No I don't do it with Elon I do it with Hermes Oh yeah I only do this locally Okay it's scary Same thing with my finance bot And uh Only local So I think that's a very I mean What these companies are trying to do is find a consumer market it, right?

1:58:18Yeah. Yeah. And I think that there is one. I think that the pricing will become the interesting thing. I mean, that's, but yeah, I think this is what everybody's trying to do. I think there's a much easier enterprise story to be totally candid just because of what people are going to be willing to pay. I think this is also an opportunity for Apple at some point, if they ever want to do, you know, something in this space where you could, you know, interact. But like in a lot of cases, like when I first played with with OpenClaw, I did I did do it on a local machine. But then I almost immediately put it on, you know, just a VPS that I had just to see how it would work.

1:58:54And I was impressed. You can for a lot of things that people need to do kind of like what you were describing, Leo, you need just kind of these small tasks, you don't necessarily need it's better, the full context, other stuff. And so just being able to have something that's been then kind of pre-design for on a task-based purpose that you can kind of call on demand, A, that can be very beneficial and B, from a compute perspective, that can be very efficient because you're not having to run all these things all the time. It can just be kind of, you know, it's like serverless with computing where you're just kind of, you know, calling it when it's needed.

1:59:27Yeah. That's one thing GrokBot does really well is the bots can talk to each other. So a bot can say, oh, this is about your personal finance. I'm going to give this to finance bot and so forth. I think that's another thing. The whole idea is isolation. I think it's because we're starting to realize that if you try to get an AI to do too much. It's specialization of a different sort. Yes, exactly. It's small models, which I think is the way to go. Yeah. NVIDIA is going to build its own model. They've pulled up with Poolside, which is a very interesting model creation company, but they ran out of compute.

2:00:09They couldn't get enough compute. Guess who has a lot of compute? NVIDIA is spending$6 billion. They see the threat that open-weight models from China are posing, and they're going to make their own open-weight model. They've already done Nematron Lightning, which is quite good, but small, so not so smart. and uh they're they're gonna they made a deal with poolside to create i hope this i i would far prefer to run it is one of those wonderful deals where they didn't acquire them they gave them a bunch of money to acquire the uh licensing and a bunch of uh engineering staff right management stays there to keep doing stuff that's an interesting deal yeah yeah i you know i i really admire Jensen Wong's vision in all of this.

2:00:55I think it's also smart just in terms of diversification. You want to be everywhere. Literally everyone is using your chips, but you should be part of the, you know, you should have vertical integration if you can too, whether it's open-weight or proprietary. If you're already controlling the chips that everyone is using, and everyone is, even companies that don't want to use you are having to use you. Yeah, you should be part of the whole conversation. I would obviously prefer for them to be open-way, but even if they weren't, I think this is an area that NVIDIA needs to be in regardless. And they went into the inference chip business as well, and they're obviously in the hosting business, and they're in the software business, and the OS business.

2:01:34Building your own hardware is interesting. Microsoft did this with their May chips, which are some sort of weird quantum chips. Google's obviously done it with Tensor. Google's done very well with Tensor. Very, very well. In fact, that's one of the reasons why Google Cloud has been as successful as it's been in terms of AI stuff is because they haven't had to solely. Do they run NVIDIA GPUs? Yes, they do. And you can. But the models don't have to because Google has built their own hardware, which I think has been a big boon to them. And, you know, it's a good investment. That was one of the big points, actually, of the OX Alpha release, is it was all run on ZAI's Chinese chips.

2:02:19Those 100 trillion tokens they offered for free for a week were running on Chinese servers. No NVIDIA chips. And I think that also probably got Jensen's attention just a little bit. Now, one of the things we do on the show, Christina, is we also talk about the downsides. It's not all cookies and cream out here in the AI world. This one actually scared me a lot. In fact, so much so that I sent an email to my friend Daniel Suarez, who wrote a book, you might remember, called Kill Decision, about drones, making AI drones, making decisions about who to kill in combat. I'm hoping he has a new book coming out in the spring.

2:03:01I'm hoping we can get Daniel on the show to talk about that, because he's been quite prescient. and he says you know what i talked i do a lot of research in my books i talked to the military they're well aware of this well it's actually happened now uh an autonomous drone from russia guided entirely by ai killed three ukrainians in the in the war and it was running an nvidia chip a contraband chip russia is not allowed to buy these chips but of course there's a black market I don't know if this is the first. It's the first publicized example of an autonomous AI killing machine. And I think this is just the beginning.

2:03:45And so not a good day for humans. In fact, I think the drone actually killed some innocent civilians. They were trying to attack tanks at a gas station. and they'd been trained on the tanks, but they kind of missed and they killed some civilians and so this according to some experts on this is the the first documented case in which civilian deaths were caused by a i don't even know how these drones uh what weaponry they use do they they come down and just explode yeah they're just flying bombs they're they're kamikazes Yeah. Inside it was an NVIDIA chip. In fact, because it wasn't encrypted, the Ukrainian military could see exactly what models had been uploaded.

2:04:43They were looking at visual landmarks. They looked at the code, which revealed what kind of top targets the drone had been trained on, like propane tanks. That's what this drone was apparently aimed at. so uh we knew it was going to happen at some point um it's a little scary speaking of grok uh elon's not happy good elon uh first address to cursor because remember he bought cursor which by the way has i think cursor is behind the grok bot by the way makes sense yeah it makes sense it's interesting too um we didn't mention this before but Cursor, and I'm sure this changes now, you know, they fine-tuned on top of Kimmy 2.5 and created their model Composer, which was open weight and a very good coding model.

2:05:36Isn't that interesting? And I'm very interested to see what, if anything, they do with future models that, you know, I'm sure that they're all in on Grok now, but that was kind of an interesting, you know, I meant to mention that earlier when we were talking about customizing model stories is that that was a company that had done that, where they'd customized their own, you know, based on Chinese open weight models. But I imagine that's probably not going to be the case anymore.

2:06:09Musk talked to Cursor leadership and said, we're falling behind and it's up to you. By the way, 45 people have left Cursors since the acquisition by XAI. But this is normal in AI now. People move around a lot. Well, I mean, you don't know when people's options are due in anything else. I mean, if you joined the company early enough, you might have gotten a really good payday. And now you have a great thing on your resume and you can go do a startup, right? Like there's any number of reasons why people would leave. Yeah. All right. I think we should, poor Christina, She's came here for half an hour and we've kept her here for two.

2:06:51And I am very grateful. Very. Thank you, Christina. It's wonderful to have you again. Christina works hard at GitHub where she is developer relations dev advocate. Do you talk to, what do you talk to devs about? I mean, all the stuff that we're talking about now, how are you, how are you building tools? How are things changing? Right? Like we, you know, like the beginning of the kind of conversation, there are plenty of people in this audience who don't know what GitHub is or how it works until they started, you know, working with AI tools and whatnot. And so a lot of it is just kind of explaining those things.

2:07:26And sometimes it's also talking to more established developers about, okay, how are you now using AI in your workflows that you didn't before? Sometimes it's not about AI at all. It's just about, you know, somebody wanting to build something cool. So it's kind of across the board. Well, they're very lucky to have you and we are lucky to have you. And I Thank you so much for sticking around. We're going to take a little break and do our picks of the week. If you have a pick, I didn't prepare you for this. You did not. I will try to come up with one. Think of a pick. I have a couple. And Jeff has more than a few.

2:07:56You're watching Intelligent Machines. Jeff Jarvis, Christina Warren filling in for Paris. Paris will be back next week. Laughing at us. Laughing at us for forgetting all of that. We're so glad you're here. We're so glad our club members are here, too. You are what makes all of this possible. If you're not a member of Club Twit, I want to just thank you if you are. And if you're not, I encourage you to join. It's the club members and your$10 a month that make everything we do possible. We're coming towards the end of the year. It was a slow year for ad sales. I don't know how next year is going to be.

2:08:30But thank you, club members, because you covered about 30%. Our 30 % shortfall, maybe 40%, was covered by your memberships. And that makes a huge difference. It lets us do the programming we do and the special programming we do. Our AI user group twice a month now because it's so interesting. Jeff Atwood, the founder of Stack Overflow Discourse, has a special show that is very weird called Off by One. I'll show you what we're going to be doing off by one on Friday. We're going to debut the brand new, Jeff, you'll enjoy this, Leo t-shirt. and I think we're going to find a way to give some of these away.

2:09:13Jeff sent me 50 of them. Oh, jeez. In every color of the rainbow. I think, Jeff, you might like the khaki one. I got baby blue for you, Christine. Whatever you want. Anybody who wants this, you can have it. Lisa wore one to bed last night, and I went, oh, my God, take it off. I'm going to sleep with myself. I can't take it. Anyway, club members, thank you. Thank you. There's no tote bags, but we do appreciate what you do. And if you're not, ad-free versions of all the shows, access the Club Twit Discord, all that special programming. It's waiting for you at twit.tv slash Club Twit. Okay. Okay, ladies and gentlemen.

2:09:58Time for the picks of the week. I'm going to give Christina a moment to prepare hers. while I mention, I actually thought Paris might enjoy this, Butterbox. You know, everybody's trying to get their kids off the internet. Here's a way to do it. The Butterbox. Sharing offline has never been easier. It is a hotspot that is not connected to the internet, but you could put educational materials, videos, and apps on it. And it has its own wi-fi network so all the people with their phones and laptops can join a public chat room can join the content and it's all unbutterbox it's like a bbs it's a bbs you can you can there's a pre-made image you can download for a raspberry pi or an old pc just download the image burn it set it up uh they have all the information this is from the guardian project and you know what this is good this you want to get your kids off the insta get them on a butter box if i had little kids i would probably do this put some games on there uh they will they if you don't have a butter box if you don't have a raspberry pi they will sell you one or at least give you the supply list that you need it will run a pi zero will run it.

2:11:23A Pi 4 Plus will run it. And coming soon, you can run it on a PC or laptop. You can have 10 people 10 meters apart on a Raspberry Pi Zero and your butter box. Or you can talk. As Julia Child would say, more butter!

2:11:42Jeff, your pick of the week. This is the Wall Street Journal. Silicon Valley's newest status symbol Oh, no. Is the super rare Sam Altman watch. I hope that stays rare. Is it his picture on it? No, no, there's a logo in it. Oh, wait a minute. It has sayings in it like compute is destiny. Oh, I need this. It's a tourbillon, so you can see the inside of it. That's, how much is it? This one is about$650 ,000. Okay, never mind. He recently wore a$1.3 million from F.P. Jorn. I'm sorry, Meta did, right? Yeah, that was Mark. So Sam, you know, still before his IPO. Dude, you have too much money if you have a$1.3 million watch.

2:12:31I'm sorry, this one, no, I don't know. It's modeled after Vanguard's titanium orb watch, which starts at$180 ,000. Oh, well, that's different. Can I run an AI model on it? So it says compute is destiny. Another popular Silicon Valley term scaling was engraved in all caps on each crown's pusher. The open AI logo is featured on the watches and an inscription on the back of each. Oh, they're selling AI. If AGI dot aligned deploy was written in the programming language Python. uh he only made uh this seven of them i think it was to give away to himself and other key employees i don't know if that really qualifies as being written in python

2:13:20wow that's pretty if agi aligned deploy oh so mark and not mark uh sam had these made and gave them to executives. That's nice. Well, yeah, well. Did Demis ever give you anything at DeepMind? I got a hoodie, but that was not from him. But yeah, I got a water bottle and a hoodie. You may not know this. I got a nano banana sweatshirt at home too. That was pretty cool. So that fits in with, you don't know this probably, Jeff, but Christina has a collection of - Oh, that's Christina's collection, right? Yes. And then a banana could be, did you ever get your Theranos gear? Oh, yeah. Yeah, yeah. Somebody bought me a Theranos fleece that was very expensive, and I'm very grateful that they bought it for me.

2:14:12And yeah, I have an Enron mug. I'm actually today, this is funny, I'm wearing a shirt for Atom, which was GitHub's dearly departed tech center. Oh, I love the Atom editor. That was a great tech center. It was a great tech center, part of Electron. And, you know, when Microsoft acquired GitHub, it did not make sense to have the much more successful VS Code and also Adam. But I obviously had to buy an Adam T-shirt. I had to buy merch for our canceled products because I think that's funny. So, yeah, I have a whole thing of things. A viewer actually sent me, this was years ago now, and I wish I could remember who it was.

2:14:51I could thank them. Sent me tech TV stuff, Leo. I have a few tech TV things. So your closet is basically F company. Yes, that's exactly what it is. Thank you. And thank you for getting the reference. That's exactly what it is. My closet is F company. And it's been a thing that I've been collecting for, I don't even know how long. But the problem is, is that when companies go bankrupt or something happens, because NPR did a story about me about this, I've created a market where I have to compete against myself because other people will literally be looking at collectors like me to drive the prices up.

2:15:27I've literally like made it harder on myself to acquire F company merch. Oh my God. You should have gotten the Twitter sign, man. If you got the Twitter sign, that would have been huge. Oh, I tried. I tried to get things from Twitter and that thing was just crazy. But yeah, I tried. I do have Twitter merch though. I have a lot of Twitter merch from the various eras. It was birds, not X's. What's he getting? What's Leo going to show us? Yeah. I was going to get you. I have a plaque that I bought that said Leo Laporte had a blue check before you could buy them, but it's nailed to the wall, unfortunately.

2:16:03I have a pick for you, Christina. Christina vibe coded a GitHub game. Oh, yeah. This was cute. Tell us where that is. That is at filmgirl.github.io slash Blackie-copilot. Let me find it. it's in one of your oh you have 60 almost 60 repositories oh i have so many more than that flappy copilot there it is it's it's film girl.gethub.io slash flappy uh dash copilot um look at this jeff i built out with with kimmy and and it i don't know i think it was maybe it took me less than 10 minutes it was and it's in it what's great it has all the github like there's github stuff like yes merge conflict you hit a breaking change super cute am i gonna get in trouble for the music whose music is this i don't know whose music that is oh that's not your game no oh i probably have something else open never mind let's stop it right now my music is just is just it's just an html5 app it's just it's just beeps and boops it's just whatever the model put in but it is very funny i probably still have suno running from the previous show or something anyway very cute very cute that's on Christina's Film Girl GitHub repo.

2:17:22Yeah, I just gave it that URL. But yeah, that was just a dumb little thing that I think took you five minutes. It's so cute. Yeah. It works on mobile, actually, which is I was very impressed with the model for because I was not expecting that. The fact that I was like, Oh, okay, it actually it actually works on mobile. Okay, cool. of course it does kimmy's brilliant what what are you using for your model for hermes um i use a soul usually but it just kind of depends well it depends on what i'm calling to so if i'm locally i'm using glm but if i'm if i'm calling out then i'm using um gpt i may be using glm myself i might be it looks pretty good on here i've used an older version of glm is what i've done actually because you you told me about it and i was like oh i should try that i really like it over yeah i like it too so that's what i switched over on my framework for my local model yeah yeah i want to uh the the um context is a little small deep seek v4 flash has a much larger context so yeah to figure out if i can i can tweak it a little bit you know it's funny if you if if you're around on a day that a model gets released go over to x and watch everybody compete to create the better recipe.

2:18:36I had three different recipes to try before nine. It was incredible. Yeah. No, it's crazy to see everybody's stuff come out and everybody's prompts and everything else. It's a fun time. People are great. They're just really into this. And it's a very exciting time to be into AI. And Christina Warren, I thank you so much for spending so much of your afternoon. Stepping into the lurch. Thank you. Thank you for having me. This was a delight. I was not expecting to be able to say the whole time, but I was able to, and this was a delight. Thank you both for letting me. Thank you for letting me rant about.

2:19:10Well, you know what? I was glad we got you on because I've been saying that all along and, and I was maybe mocked a little bit for it. But anyway, also, also Jeff, I bought your book. I can't wait to read it. Sounds wonderful. Look at her genuinely like when you talk about the top of the show, I went, oh, this is completely my, my ish. Like I have to read this. So I'm so excited to read it. It's really good. It's fun. It's really, it's a, it's a, it's technology and media. So it's, exactly. It's, which is my, my two favorite things as I know they are your, your, your favorites as well. So I'm, I can't wait to read it.

2:19:43So I'll take advantage of the plug, the free plug you just gave me and just mention that if you want an autographed copy, if you go to jeffjarvis.com, you'll see the link. You can go to Montclair book center and order from them and they will send you an autographed copy that I will go and autograph. Does our discount code still work? No. Okay. I got to take that off. Go into the month. Go into the month. It does. It does. End of the month. Oh, you have just a few more days to use GLR BD8 and get a discount. Yeah. Thank you, Jeff Jarvis. I appreciate it. Thank you, boss. Will you be back next week?

2:20:17You're not going to a going away party for anybody, are you? No, September 9, I'm away for a day. Okay. I just texted me and said that the retiring colleague cried when they gave her the gift. So she was glad she was there. Yeah, that's great. And Christina, we will see you on Tuesday on MacBreak Weekly. See me on Tuesday on MacBreak Weekly. We'll see you all here next week. We do Intelligent Machines every Wednesday, 2 p.m. Pacific, 5 p.m. Eastern, 2100 UTC. You can watch us live on YouTube, X, Facebook, LinkedIn, Kik, and Twitch.tv, where they are now at this very moment training on this show and we're happy with it we're happy with it would be insulted if they didn't it's creative commons eat it up uh we also have a youtube version which is probably training somebody else uh you'll find that uh youtube.com actually if you go to youtube.com slash twitch all the shows have their own channel and dot twit not twitch youtube.com slash twit uh all the shows have their own channels as and their shorts on you on twitch and so forth twit uh i got twitch on the mind uh let's see what else oh yeah subscribe in your favorite podcast client that way you can get it automatically and you don't have to worry about when it's on next you just have it and you can listen at your leisure thank you all for joining us we'll see you next time on intelligent machines bye-bye hey everybody it's leo laporte you know about mac break weekly right you don't oh if you're a macintosh fan or you just want to keep up with going on with Apple.

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