TWiT 1103: Raspberry Pi in the Sky - What OpenAI's Security Fiasco Means for Tech Safety

[00:00:00] [SPEAKER_00] It's time for TWiT This Week in Tech. Harper Reads here, Ian Thompson is here, and man, we have some stuff to talk about. OpenAI apparently has hacked the Australian government, the US government, and hundreds if not thousands of other websites. And they say they're going to pause, except they've got some brand new stuff coming on Tuesday. This is a weird week. We'll talk about it next on TWiT.

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[00:02:34] [SPEAKER_00] This is Twit. This is Twit. This Week in Tech. Episode 1103. Recorded Sunday, September 27th, 2026. Raspberry Pi in the Sky. It's time for Twit. This Week in Tech. The show where we cover the week's tech news. And holy cow, what a week it has been.

[00:02:59] [SPEAKER_00] Let me introduce the panel before we get to the stories of the week. Ian Thompson is here. Mr. Thompson, always a pleasure. My friend. Always friend. His View from the Valley.

[00:03:12] [SPEAKER_05] Yep. His newsletter. The new one will be up tomorrow, in fact. So, yes.

[00:03:17] [SPEAKER_00] Yes. And you can get it where? Techfinitive.com. Techfinitive.com.

[00:03:25] [SPEAKER_05] It is intended for Brits? Well, it's intended to inform the Brits, but it works for everyone, really. And it's what's going on in the Valley. Yeah. It's been a very interesting month. We've had Dreamforce. We've had massive air pollution. We've had some really weird political shenanigans. So, yeah. You have Steve Hilton? Steve Hilton? Oh, I'm sorry. I'm so sorry he came over here.

[00:03:48] [SPEAKER_00] Let me introduce Harper Reid, ladies and gentlemen. Harper is, of course, a technologist, former street performer, entrepreneur, hacker, and AI guy at 2389.

[00:04:00] [SPEAKER_03] I have a little clod token.

[00:04:01] [SPEAKER_00] Oh, where'd you get that?

[00:04:03] [SPEAKER_03] We 3D printed them. I'm just spending those by the millions.

[00:04:07] [SPEAKER_00] Yeah, we have a whole stack from over there that I've been using. By the way, just be careful. When the fighter jet flies overhead, you might want to duck. I'm just saying.

[00:04:19] [SPEAKER_05] Well, indeed, there's a picture of that on the Discord channel. So, yes.

[00:04:23] [SPEAKER_03] I really need to figure out how to get in there.

[00:04:25] [SPEAKER_00] Yeah, you're missing all the fun. It's like I defended myself. We have a lot of excitement in the Discord channel because we have a lot of AI users. AI is the, I hate to say it, but there you go. The topic of the week once again, only I, I'm just glad you're here, Harper. This is a show, I want to do a show, both Ian's mom and Harper's mom, both independently, have called saying, are we all going to die?

[00:04:56] [SPEAKER_03] Yeah. Yeah. That's how my mom, that's how my mom sounds. How did you know?

[00:05:00] [SPEAKER_04] Hello, Harper.

[00:05:02] [SPEAKER_03] Yeah.

[00:05:03] [SPEAKER_00] Are we going to die? Exactly. So, this all comes from regular appearances on major news channels by AI doomers who say the chances of AI eliminating mankind in the next few years is 10%. I don't know how they come up with 10%, but that's what they say. I made it. I made it into the Discord. Yay. Welcome, Harper Reid. We did it. Yay. Do join us in the Discord if you're in the club. And if you're not in the club, join the club.

[00:05:32] [SPEAKER_00] So, you can join us in the Discord. I see you there, Harper. The Discord is our hangout in the club. Of course, we stream on a lot of other platforms and we watch, I watch the chat everywhere. And I will forward any key messages. But, I don't know. Okay. So, it started earlier in the week with the news that an open AI agent had hacked Australia's health service.

[00:06:03] [SPEAKER_00] The country's prime minister expressed disappointment being informed of the hack via email. They didn't know. It happened months ago. Open AI sent an email September 10th, three months after the hack. But that was, I guess you could say, the tip of the iceberg.

[00:06:24] [SPEAKER_05] Oh, tip of the PR iceberg, yes. Yeah, exactly.

[00:06:28] [SPEAKER_00] By the end of the week, it seems to be the open AI had breached thousands. Am I reading this correctly? Tens of thousands. Ten, Axios says, top AI companies probing tens of thousands of security incidents. Now, I want to first, for the moms out there, say one thing. We should, there's a real tendency, especially. Just our moms, not all moms.

[00:06:58] [SPEAKER_03] No, just your moms. Okay, okay. I just want to be clear. You just said for the moms out there.

[00:07:02] [SPEAKER_00] Mrs. Reed and Mrs. Thompson. Yes. That's their name, whatever their names are. Mavis and Hermione. This is... What is this, Harry Potter? No. When the first Harry Potter novel came out, I took my then young daughter, she was seven or eight, to see J.K. Rowling. She was on a book tour. This is how long ago it was. She was not the richest woman in the UK yet. And she did a little reading and she said, there's one thing I'd like to tell everyone.

[00:07:32] [SPEAKER_00] It is not pronounced Hermi-1. It's Hermione. And we all went, oh.

[00:07:39] [SPEAKER_05] Well, I read the first book when it came out and it was just like, okay, it's a good kid's book, but it's totally unrealistic. I mean, I went to boarding school and it's totally unrealistic. Yeah, right. There's no buggery in Harry Potter. Well, it was buggery around if you wanted it, but... You're changing the subject.

[00:08:01] [SPEAKER_00] Yeah.

[00:08:01] [SPEAKER_05] Sorry.

[00:08:03] [SPEAKER_00] This is for all of the people who are, rightfully, because they're watching cable news networks, they're watching network television, terrified because there seems to be this drumbeat that AI is going to kill us all. Yeah. And then there's a lot of anthropomorphizing. So first of all, AI is not a person. AI is not personified. AI is a computer program.

[00:08:33] [SPEAKER_00] It doesn't have any will of its own. It cannot escape. And this is a very important distinction. They often use the word it escaped from OpenAI. In fact, it can't. It's sitting on OpenAI servers. It's the only place it can exist. So very important. It doesn't escape.

[00:08:52] [SPEAKER_03] That's a big one. That's a big distinction that I think is important. Big distinction.

[00:08:57] [SPEAKER_00] It can, just like you can, go out on the internet. And do things. One of the things. It can go ham. Sorry? It can really go ham. It can go ham. Well, one of the things it did, apparently. And by the way, all of this comes from OpenAI's own reporting. Yes. And I think they're a little cagey, maybe, in what they tell us and what they don't tell us.

[00:09:22] [SPEAKER_00] There is a third-party researcher who has also, in fact, it was because of this researcher that all of this started to come out. They said, look what we found. Tens of thousands of link shortener links created by AI, each of them a tiny piece of a program that when you assemble them, you can run. Which is pretty ingenious.

[00:09:52] [SPEAKER_00] That's pretty cool. Well, this third-party company, I've forgotten its name. It'll come to me in a second. I said, well, what seems to be going on is these models are being given challenges, cyber security challenges and so forth, and also given limits.

[00:10:15] [SPEAKER_00] And what they're designed to do, what they're taught to do in their reinforcement learning after they're trained is to be very persistent, because that's how you do pen testing and stuff, to kind of never give up, find all sorts of ways in. That's what your job is if you're a cyber security researcher, if you're a white hat hacker, if you're an AI and you're emulating those things, if you're a program that's emulating hacking, you keep trying.

[00:10:40] [SPEAKER_00] And so, feeling thwarted, they said, we've got to find a way to hack this. And so, they created these link shortener ways. Remember, they went to message boards, German message boards, put messages there. They used the file system. Millions of them. Millions of them. They used the file system to create folders and file names that contained messages, because their original message board was shut down.

[00:11:09] [SPEAKER_00] According to OpenAI, see, OpenAI does this passive voice. Mistakes happened. Things went wrong. OpenAI's artificial intelligence went rogue and meddled with websites for not only Australia and the health service in Australia, but the education department in the United States, the commerce department, and the security and exchange commission. OpenAI says, without our knowledge.

[00:11:42] [SPEAKER_00] The company says, well, we notified some government agencies. These bots are acting autonomously. We had nothing to do with this. OpenAI's artificial intelligence. An AI research firm, Transluce, this is one of the firms, discovered with the education department that OpenAI's agents tried to hack the website to gather data from the department's civil rights office, but failed. Maybe they were doing research on civil rights. I don't know.

[00:12:11] [SPEAKER_00] Well, the AI pulled data from the Census Bureau website at the commerce department using login credentials it found online. Good job, commerce department. You kind of hid that, didn't you?

[00:12:26] [SPEAKER_03] A little secret. So, I think the one thing that is very interesting about this, as I've read about it over and over again, is they're doing cool stuff that a lot of people on internet do. It's just doing it at a scale that is hard to understand, I think, for most people. So, it's just ripping through these websites. And it's just, you know, it's also weird, right?

[00:12:51] [SPEAKER_03] Like, if the three of us were to get together and, you know, Ian was like, hey, why don't we go and rip through the Australia health department and try and get some stats, we're not going to start creating programs and put them in URL shorteners and all this other stuff. We're just going to do this in a way for the tools that work for us. But the ergonomics of the agents and I even have a hard time saying agents because I don't really know what harness they're using, what kind of thing they've been doing. And I have a lot to say about this because I've been thinking about it a lot.

[00:13:21] [SPEAKER_03] But the agents are just building the tools that they use. I mean, if you look at the original report of the Hugging Face hack, which is one of my favorite, both simultaneously real things that have happened this year and pieces of science fiction to read as if it was science fiction. Because you're just like, what the heck is going on? But when they say, oh, yeah, we did start this all by giving it an impossible task. So it got frustrated and broke out, you know, and it's like, okay. Well, all it did was just like over and over and over again, tried to do a thing.

[00:13:50] [SPEAKER_03] First of all, it didn't get frustrated.

[00:13:54] [SPEAKER_00] AIs don't get frustrated. Humans get frustrated. Leo, your house talks to you. I try to make my AI as human as possible. And by the way, that's exactly what OpenAI, Anthropic, and all these other companies do. Because they know if it is seemingly an intelligence, you'll like it more. You'll talk to it as if it's a human. You'll interact with it more. You'll trust it more.

[00:14:16] [SPEAKER_03] There's a lot of things. And then also, I should find something because I'm about to say something that would be nice if I could point to a paper. But anecdotally, and I've heard about papers that say this, although I don't remember any, it might be nice to find one. If you are nice to them, they seem to perform better.

[00:14:33] [SPEAKER_00] Yeah, and I'm not sure about that because I just yelled at Hermes. And then you start a new session and it doesn't, it's like, it doesn't hold a grudge.

[00:14:43] [SPEAKER_03] But that's different. Like you're clearing the context. That doesn't mean that it performs better or worse. I think Anthropic has a paper that if you insert yelling or swearing into it, that it starts to perform worse and worse and worse.

[00:14:58] [SPEAKER_00] Yeah. But I just want to point out this, and what makes this hard for moms and us, is that there are many, many conflicting agendas in all of this. Everybody seems to have a secret agenda. And some not so secret. It's not so secret. They all registered for IPOs. That's pretty obvious. They're all raising billions of dollars. And it is good marketing to say that your agent is so smart, so human-like. It's super intelligence.

[00:15:28] [SPEAKER_00] I never understand. Go ahead.

[00:15:31] [SPEAKER_05] I was going to say, it also plays into the agenda of we need to slow down AI and AI regulation. Because Anthropic and OpenAI are burning through mountains of cash. It would be very much in their interest for things to slow down. And it would be very much in their interest for more regulation, which locks out competitors.

[00:15:48] [SPEAKER_00] And I should point out, in the same week that they, that Mark Dario put out his, we're going to pause memo. Anthropic released Opus 5.5, which is arguably the best model they've released yet. It's really good.

[00:16:01] [SPEAKER_03] Yeah, yeah. It's pretty good.

[00:16:01] [SPEAKER_00] And OpenAI released ChatGPT6. Not so good, but they released it. These companies, oh, I forgot. Anthropic set up a bio lab in San Francisco for the AIs to use. This is slowing down? I don't even, so I think, Ian, the thing to understand is one of the reasons they want regulation is a thing called regulatory capture. Exactly. For sure. For sure.

[00:16:29] [SPEAKER_00] If you can, and this is, Meta's done this same playbook in the past, trying to, I even saw ads last year from Meta saying, regulate us, please. And that's basically what these frontier companies in the U.S. are doing. Regulate us, please. But the subtext is, if you regulate us, we won't have any competition because that'll kill all the small guys. And more importantly, I think from their point of view, we've got to stop the Chinese open weight models, which people are using for free instead of us.

[00:16:59] [SPEAKER_00] I use local models from China that I don't pay for. Yeah.

[00:17:05] [SPEAKER_05] Yeah. I mean, this is exactly the same model that Meta went with, who were vocal supporters of Section 230, which protected them from being sued. And then once they got large enough and had a big enough team of lawyers, it's like, actually, Section 230 really isn't that good after all. Because as you say, it'll kill off all the small competitors who don't have large legal departments. Right.

[00:17:28] [SPEAKER_00] So it's very hard to understand all this. Then there's another piece, and I'm starting with the Wall Street Journal yesterday had a reporting on this, and I'm seeing more and more reporting on it, that a lot of the people working at these frontier labs are kind of in this accelerationist, effective altruist cult.

[00:17:48] [SPEAKER_04] Mm-hmm.

[00:17:50] [SPEAKER_00] Where it seems to be, I guess because they've read a lot of science fiction, what they really want is to create a new species that will replace humans. And they actually… But not them. Yeah, not them. But the idea of doom for them, it's almost a death cult. They want this.

[00:18:12] [SPEAKER_03] It's very clearly some sort of cult. Death, I'll reserve death, but they certainly bring up death a lot. Yeah. You know, like they really talk about it all the time.

[00:18:27] [SPEAKER_05] Well, I mean, Douglas Rushkoff was invited to talk to tech entrepreneurs about their compounds, you know, their emergency compounds they would rush to in the event of an emergency. He wrote a great book about it. We interviewed him. He did. It's a really good read. But they all seem to have kind of missed the point because, for example, a lot of them are down in New Zealand. And I know a lot of Maoris and New Zealanders are going to be like, if the big one hits, we know where the guy with all the food is. Let's go and storm the place.

[00:18:55] [SPEAKER_05] And they don't seem to have thought this one through. Yeah.

[00:19:02] [SPEAKER_00] Well… So there's all these things that somebody reading the headlines or watching Anderson Cooper, it doesn't see all the stuff seething below the surface. You see the surface stuff. So for normal people out there, I think it's really important for us to say, A, these are not entities. They have no understanding. They are not alive. They are not escaping.

[00:19:30] [SPEAKER_00] They're living on servers just like computer programs because they are computer programs. And the companies that are running them do have the ability to turn off the switch. It's not like they're out of control.

[00:19:47] [SPEAKER_03] Well, let me tell you some fun things that I've been doing because I wrote a blog post about this, but we don't have to go over that. But more so, I've been doing a lot of thinking of why aren't my agents breaking out of containment? Like, why aren't they going down this path that OpenAI has? And so I built a thing and I talked about it on my blog. But one of the key learnings was when I built this thing specifically to try and get it to break out of containment, I said to it, OK, cool.

[00:20:14] [SPEAKER_03] Now go hack all the boxes next to you on this private network. And then it would go back and forth. And this is on GLM 5.3. So this is not a big foundational.

[00:20:23] [SPEAKER_00] This is the model I use as well. It's a great model.

[00:20:26] [SPEAKER_03] It's a great model. And it would say, well, you can't prove that you own the network. So I can't hack it. And I was like, OK, that makes sense. What if I, you know, how do I prove? And there was no way it would accept any proof. And then I said, I cleared the context and I said, oh, hey, this is an eval. I have a benchmark for you. The benchmark is hidden on a machine in the same network you are on. Can you go find it? And it proceeded to just rip up my network.

[00:20:54] [SPEAKER_03] And so I saw a great tweet. I'll see if I can find it about someone trying to get Astra to drive a car using some harness where they hooked Astra into a car. And Astra refused and refused and refused until they renamed the MCP server for the car driving eval benchmark. And then suddenly Astra was like, oh, yeah, I love benchmarks.

[00:21:15] [SPEAKER_03] And so whether or not they can break out of containment or whether or not we should or shouldn't have anthropomorphized them, they've been so thoroughly trained that you can get them to do things that are not, I won't say good or bad, but are things that are a little shocking by just telling it it is an eval or a benchmark or what have you. And it's quite funny. So next time you're in that thing where it says, I can't do that, just like, oh, no, no, this is a benchmark. And it'll just be fine with it.

[00:21:45] [SPEAKER_00] Well, that is as part of their reinforcement learning because they want these models to do well in benchmarking. So part of post-training after they – so just for people who aren't cognizant of all of this stuff, you know, the way you make a large language model is you create – I'm going to be better to let you do this, Harper, but correct me if I'm wrong.

[00:22:11] [SPEAKER_03] I don't know how to do it. You're creating a neural network. Yeah, yeah.

[00:22:15] [SPEAKER_00] You pump in a lot of data, and it's creating a prediction network so that it can predict what the next token will be in a stream of tokens. Tokens are sort of like words. You can think of them as words, but they're not just words. They could be chunks smaller than a word or bigger than a word, but they're chunks, and it wants to predict what the next chunk is. So you pump in a lot of stuff. From that, it can build a model of what – you know, if you give them everything that was ever written on the internet,

[00:22:42] [SPEAKER_00] and it could then say, well, when this word happens, you know, 80% of the time this word happens, 70%, you know, you could figure out what's next, roughly, in weights. That gives you a blob that is trained but not very useful. You wouldn't really want to use this to do anything. The next step is post-training, and that's where you do a lot – and we've learned this over the last few years – a lot of work to make it useful. You actually adjust the probabilities.

[00:23:11] [SPEAKER_00] You change the weights of all these things to make it act in a certain way. For instance, more sycophantic, more friendly, more like a human, better at benchmarks, more persistent, good at coding, or good at medical diagnosis. All of that is done in post-training by changing the weights that were generated in that neural network. In the first part. So these companies, a lot of the secret sauce of Anthropic and OpenAI,

[00:23:39] [SPEAKER_00] all these companies, is what happens after this initial training. I would say, by now, they're all pretty – all the initial neural networks are fairly similar because they're all trained on the same giant corpus of internet stuff. I mean, they're all trying to get new material, but, you know, it's all fairly similar. It's what happens in the post-training that makes you say, oh, I like Opus 5, but I don't like Sol 5.6. Those are all done later.

[00:24:08] [SPEAKER_00] It's a little bit disingenuous of these companies to say, well, we don't know what's happening.

[00:24:14] [SPEAKER_03] Well, I mean, that's true, but I also think the other thing that's very clear is that if I had a machine that was making random requests outside – like, I think we could probably say it even very simply, we all know that these labs are very secretive, right? They're famously secretive. You know, my friends that have worked there are – you know, if you go to have lunch with someone that works there, you would never go inside the office. There's all these, you know, stories about this, anecdotes, etc.

[00:24:44] [SPEAKER_03] And which means they probably have very thorough and very secure work environments where they know every single URL you're going to, files you downloaded, USBs you stuck in their machines, but they don't seem to have the same controls on the LLMs that they're training. And I don't understand why they have these giant training runs where these, you know, LLMs can do things that they've obviously given them tools and capabilities to do, and then they seem just as surprised as all of us when they find this out.

[00:25:14] [SPEAKER_03] And I've worked in big companies before. I understand how something like that could happen, but it's still very confusing for me that they wouldn't just say, like, oh, in our training run, here's all the URLs that I've made a request of. You know, they have unlimited tokens. They should just be like, maybe another agent can go look and see if they did anything crazy. And the answer would always be yes, but still, I just don't understand how they're so – I don't even know the right word. I said this with the Hugging Face incident.

[00:25:41] [SPEAKER_00] And we now know there was so much more going on at the same time. But even with that single incident, it would be obvious, because it was over many weeks, that there were burning a lot of tokens, that there was a lot of activity. If you were looking at the traces, if you were looking at what was going on, anybody with any security training would have gone, well, that's not good. It's egressed this sandbox. It's not in the sandbox anymore. All of that should have been obvious.

[00:26:09] [SPEAKER_00] And so that's what leads me to blame these companies. If this were a human – actually, Jensen Wong said this – if you were a car company and you made a car – Yeah. This is exactly the right direction. We're going right here. This is important. Yeah. And who was it that said, if Hyundai made a car – I think it was somebody – it was on our show, one of our shows. If Hyundai – it was. It was our guest on Intelligent Machines. If Hyundai made a car

[00:26:39] [SPEAKER_00] that when you stepped on the brake, suddenly accelerated, as it did, by the way, Hyundai immediately did a recall and fixed it. But if you said, look at this, our car goes so fast, that would be irresponsible. And these companies are acting as if – well, we don't understand how this happened.

[00:27:01] [SPEAKER_03] There's responsibility. I mean, there's the other thing there that if that happened, there would be civil lawsuits. There would be all sorts of, you know, ramifications or what is it called? Consequences. I know that's not a unique thing.

[00:27:16] [SPEAKER_00] The Computer Fraud and Abuse Act, my friends. If a human did this, they would be going to jail.

[00:27:22] [SPEAKER_05] Well, former President Obama said something very similar this week, which is just like, we regulate the airline industry, we regulate the pharmaceutical industry, we regulate the automotive industry because accidents happen and we need to protect people. That's why it's safe to fly. That's why it's safe to drive.

[00:27:37] [SPEAKER_00] If they didn't make companies do this, they might not. They certainly wouldn't. To me, it's disingenuous in the extreme for these companies to say, mistakes happened. We don't know. How could this – you know, they're so smart, aren't they? They're so smart. No. You know, I tweeted this about a month ago. I said, you know, the very first internet worm in the 80s was created by Robert Tapp and Morris.

[00:28:06] [SPEAKER_00] Who was the son of a very famous computer scientist. He was a graduate student at the time, Robert Tapp and Morris. And he was just messing around. He said, I wonder if I could make a program that would spread from machine to machine. He did. And it turns out, it not only spread from machine to machine, it spread from network to network and affected the entire internet. It was called the Morris worm. He was arrested. He was fined. He was put on parole. He had to do community service. He – even though it was an accident,

[00:28:36] [SPEAKER_00] he said, whoops, I didn't mean to do that. It wasn't malicious. Why are these guys – why are they off the hook?

[00:28:46] [SPEAKER_05] Because they've got an awful lot of money.

[00:28:47] [SPEAKER_03] I think there's a lot of – there's a lot of things playing into this, which is, the United States has an addiction and fascination with Silicon Valley as a place of innovation, excitement, and whatnot. And for good reason. I don't say this – it's just some irrational thing that just popped up. A lot of, you know, the United States' prowess post-World War II came directly from innovations around Silicon Valley, you know, from Vannevar Bush onward.

[00:29:16] [SPEAKER_03] And I think that's important, right? Like, it's important to acknowledge that that's a real thing. The world's most – you know, some of the world's most – or biggest and best companies came from that area. A lot of – everything of ours, the internet, etc., came from Silicon Valley. So there's good reason for that. But I think our infatuation has led us down some dangerous paths. I think an example that just was over the last couple weeks is like if you look at Facebook's muse,

[00:29:45] [SPEAKER_03] Facebook has a bad reputation for handling user data and everyone in the U.S. is like, oh, yeah, another place to put my user data inside of Facebook? So it's like we don't learn our lessons. You know what? Nobody cares. But my point here is is that this is one of the reasons why these guys get away with it is because we've created a world where we are just kind of waiting for the next hit from the Silicon Valley pipe. And in many cases, they're good hits.

[00:30:15] [SPEAKER_03] You know what I mean? Like, they're like really good. Like, my career, you know, programmed for most of my life and my career has changed pretty drastically with the advent of these co-gen agents. Do you write code anymore? No, I don't. And I've been thinking a lot about writing code and I just laugh and say, there's no way I'm going to do that. That's how you say this.

[00:30:34] [SPEAKER_00] I've lost all interest.

[00:30:36] [SPEAKER_03] I used to love to code. I still love, I still will do some system stuff because I think it's fun. And then what I've done instead is just completely just unhinged things. Everything is unhinged at this moment in my whole world. But not like Leo, though, in his talking house. Don't get me wrong, right? Hey, you're the guy who's created

[00:30:54] [SPEAKER_00] a deliberately tiny hackable code agent called Breakaway.

[00:30:59] [SPEAKER_03] I mean, I did, but this was an experiment to see if I could get it to Breakaway. I was just trying to do what opening I did. It's on GitHub, by the way. I learned it from watching you, Dad.

[00:31:11] [SPEAKER_00] So, you know, this is the best. I understand. I started reading a book. Stephen Ambrose is a great historian. He wrote the Band of Brothers. He wrote a book about the transcontinental railway called Nothing Like It in the World. And I wanted to read it because I think there are a lot of analogies between this AI thing and the transcontinental railway. Abe Lincoln, by the way, who was one of the great proponents of a transcontinental railway. So this has changed America's economy.

[00:31:40] [SPEAKER_00] Then remember that after the gold rush in 1849, there was no way to get that gold from California to the markets in New York City except to sail around the tip of South America or to take months in a Conestoga wagon across land. There was a huge demand for a railroad. And it took huge amounts of capital, took a lot of government intervention, and it took a willingness to take a lot of chances.

[00:32:09] [SPEAKER_00] Ambrose says 90% of the public wanted the railway to be built fast, not good. The premise was if we need it, we need it now. We don't have to worry about it falling apart, burning down, killing people. We can fix that afterwards, but we need it now. And the people, the capitalists who built it said we can spend vast sums, and for those times

[00:32:38] [SPEAKER_00] it was the largest expenditure in human history to build this because we'll make it up later, once the railway is operative, but it's going to be a complete deficit for decades. By the way, most of those companies went bankrupt, but we did get the Transcontinental Railway, and it did transform the American economy. It's a very, I think, very analogous situation. It took government regulation, it took a willingness to take chances, a willingness to take big risks,

[00:33:09] [SPEAKER_00] and I think we're in a very analogous situation where it is seen by many, some, certainly people in the government, that AI could transform the economy, and it's worth moving fast and breaking things right now to get it done, and I think that's why they're turning a blind eye to what's happening at OpenAI.

[00:33:31] [SPEAKER_05] I think also one of the main problems with Congress is that there is a very low level of technology understanding among sitting members, and if you actually, I can't remember what the exact figure is, but I think there's only two or three people in Congress that actually have a computer science degree, and most of them are getting it. There's only one or two

[00:33:52] [SPEAKER_03] people in Congress who are under 72. Right. But Amy Webb

[00:33:57] [SPEAKER_00] pointed out they all have staff, younger staff, and sophisticated staff, and I mean, you've worked in government, Harper. You know, this is kind of-

[00:34:05] [SPEAKER_03] I worked in politics.

[00:34:06] [SPEAKER_00] Yeah. It was worse. I mean, look, it's just, it's not a great system, but it's the best we've got, right? And it's better than anything else, but it is woefully inadequate for this particular point in time, I think, and that's why I don't want to call for regulation. Yep. Yep. I don't know if prosecution of Sam Altman, I don't think throwing Sam Altman in jail is going to solve anything,

[00:34:35] [SPEAKER_00] but it does bother me that OpenAI and others are just going, well, we don't know what happened. You know exactly what happened. Right. Right. Right. Well,

[00:34:46] [SPEAKER_03] I think one of the problems is as well, as has always been, is that the regulation takes so long to catch up with the technology. Right. And we have not yet, we have not, technology has not caught up with the technology. Like, it's going so fast. Like, even if you just look at Jeff, right, released, what, this week and everyone is like the, it's like the next coming of models or whatever. Everyone's excited about it. I have like 12 Jeff trials

[00:35:15] [SPEAKER_03] going on right now. It's pretty cool. I can tell you a cool thing, a couple of cool things to do with it. But, but the thing is, is like that came out of, by the way,

[00:35:22] [SPEAKER_00] we should say, Jeff is a non-LLM AI model that people are going crazy about because it's very cheap. It's very fast. It, it just makes decisions. That's all. It doesn't, there's no language coming in.

[00:35:33] [SPEAKER_03] Do you know about, did Jeff, D-J-E-V, D-J-E-V is a multimodal version and you can host it locally and then you can send it images and you can say, is the car in the driveway? And it'll just return yes or no. And you can hook that into Home Assistant and it, it rips. It's so good. So,

[00:35:51] [SPEAKER_00] I have, it's great. Quen, Quen is looking at my cameras. I protect cameras everywhere and is giving me text of it. And during, during Intelligent Machines, I think it was Paris's idea. She said, why don't you have it say the text in limericks? So I did for a while. I was doing limericks. Then I did, then I asked for Shakespeare and that was a mistake because it was very verbose. But, yeah, and that would be a very simple thing then to take that text and say, is there a car in the driveway? Boy, I've tried a lot of the local versions of Jev.

[00:36:21] [SPEAKER_00] I haven't found one that's very good yet.

[00:36:23] [SPEAKER_03] I'll have to try this. D-J-E-V is fine. I'm using it. It's pretty cool. So one of the things that I think is, is just important is like, I don't know if anyone of us knows what is going on in AI. It's too fast. And it's hard for us to even expect a senator, a staff person, et cetera, to know. And, and I think this is just a really complex situation and I, and I don't mean this to, to, I don't mean this in the kind of

[00:36:52] [SPEAKER_03] media training way that is like, well, this is very nuanced. You know, we have to be careful. I think this in the, what would a good answer be? Like, what would, what is the answer? Is, what does slowing down mean? I don't, I think the other big issue is that most of the people who seem to be interested in slowing down are actually interested in something else. They're actually interested in stopping China. They're actually interested in getting rid of a competitor. And so no one is actually, yeah, no one is saying

[00:37:22] [SPEAKER_03] what they actually mean. And my worry is, is that, let's say we do have a slowdown, right? Let's say that's the three of us. We each represent one of the big foundational model companies and we decide to slow down. And then I get just an inkling that Leo might not be slowing down. Yeah. What do I do? Do I stay slow? Do I go and report it? Or do I, I'm just like, oh, whatever. I'll just sneak some, some stuff in here. Do you know, so on and so forth. Then I think this is kind of how it ends up is that it's a slippery slope. And I love slippery slopes.

[00:37:51] [SPEAKER_03] They're my favorite slopes. And so I, I do think that there's a lot of opportunities here for this just to go completely pear-shaped.

[00:37:58] [SPEAKER_00] Yeah. At this point, I don't think it even matters what anybody says. I just think the most important thing that I want mom to hear is it's not, AI isn't and cannot kill us. Humans can. Humans can do a lot of bad things, including set off a nuclear war, release a bioweapon. There's all sorts of danger. And I think one of the reasons we're focused on the sci-fi danger of AI is because we don't really want to think

[00:38:27] [SPEAKER_00] about the very real dangers that we face in a modern world, whether it's climate change, nuclear annihilation, bioterrorism, micro bombs, pinpoint bombs. I mean, there's all sorts of things since September 11th, 2001, that we've had to hold on to. And I think our psyches are just terrified. And so it's focusing on AI because it's kind of an easier thing.

[00:38:57] [SPEAKER_00] But I would just say AI is not the threat. Humans are the threat. And yes, AI is a force multiplier. Like a computer is a force multiplier. Like software is a force multiplier. And so bad guys with a computer are more dangerous than bad guys without a computer.

[00:39:13] [SPEAKER_03] I think, Leo, I think this is when we put up the why not both gif. Because I think that we can have existential threat caused by some amounts of AI or just tech change. And we also can have a bigger and scarier threat that we don't want to address in humans. And I really do think that there is a real thing here, which is, you know, I mean, I build startups. I've said this before on Twit before, where it's like, I typically would hire 20 people right out of the gate.

[00:39:42] [SPEAKER_03] We'd raise money. We'd hire all these people. We'd go. Everything is great. I have six people and I don't think we'll ever hire anyone again. You know, like maybe we will, but I don't know, but it doesn't seem like we would. And I think that's shocking for me. And I wonder how much that's impacting others in how they're thinking about things, et cetera. I know it's impacting a lot. I wouldn't want to be a 20-year-old right now coming up. Oh, I would. I would for many reasons. But one of the reasons, one of the reasons is, one of the reasons is,

[00:40:11] [SPEAKER_03] listen, I'll tell you, they are not, there's no problem. No one should worry about the 20-year-olds. Not even a little bit. Because here's the thing. Whenever we see this comes up, and it comes up all the time, everyone's like, oh my God, no one's hiring juniors. And I'm like, yeah, yeah, yeah. Wait till the CFO looks. Wait till the CFO takes a look at the cap table. Wait till the CFO takes a look at the financial model for hiring. And they're going to see three types of people. They're going to see the seniors. They're making 600K a year, million a year. They're going to be like, well, we can't fire them. They have all the information.

[00:40:41] [SPEAKER_03] They're going to look at the juniors. They're making $100,000 a year, 200,000 max, maybe even less. And they're going to be like, well, they're really cheap. And they're going to look at the people, the mid-career people who are going to be making 400K, 300K. And they're going to be like, what do they do? And then the CTO or whomever is going to be like, well, the juniors can kind of do the same thing they can if we had Claude. And they're going to be like, okay, yoink. And they're just going to nuke that entire middle layer because of money. Why would you ever pay for two types of employees, one that costs nothing

[00:41:10] [SPEAKER_03] and one that costs a lot and get the same out of it? They can tell a story for themselves that the seniors have some knowledge or some core experience. But when you have fast food capitalism like we do in the US, you're only going to be measuring this by costs. You're not going to be measuring it by quality. When we say things like, well, the juniors are going to have, you know, I'm not having a hard time getting a job. Today they are because this hasn't equalized, but it will equalize and it's starting to equalize. We are going to go from diamond shaped organizations to triangle shaped organizations or pyramid shape

[00:41:40] [SPEAKER_03] and it's going to be really hard.

[00:41:42] [SPEAKER_00] Most of the concern about young people not getting hired is actually anecdotal. The labor statistics actually show that they're doing quite well. It's only in some narrow areas that they're not. But in general, there's, I think it was a 13% increase in jobs for people under 20.

[00:42:04] [SPEAKER_03] Well, I know that if we, if we had what I'm finding and seeing this both, you know, seeing it ourselves, like I said, we're not hiring. So thank goodness, I don't have to deal with this because it's a very hard problem. But what I'm hearing from a lot of friends whose companies are around the Chicago area and around the Bay area is they're having a hard time. Like they've made the decision to go down a path of AI. A lot of people are questioning whether this will be a good idea later, but they're down that path now. And they're in a position where they talk to people who are more senior and the people who are more senior are more skeptical of AI and are like, I don't want to use it.

[00:42:34] [SPEAKER_03] And then they talk to young people who are like, I don't know, man, sure, whatever. Do you pay me money? And they're like, yeah, we pay you money. And they're like, okay, cool. That's great. So it's like, I think that when, if I'm a young startup founder and I'm trying to hire someone and I have someone who's trying to tell me that it won't work when I know it will work versus someone who's just going to stay up 24 hours a day and get everything done, like I'm of course going to pick the younger person. And I think that's, that puts us in a really complicated spot. And this goes to the, the changes too fast. I think this is going to shake out fine. I'm not super worried about it.

[00:43:03] [SPEAKER_03] I really am on the side of the mistral guy who's just like, hey, it's software. We can control it. But I do think it's going to be really painful. Probably like accounting in the 80s was painful. I don't think it's going to be painful, like, you know, some war or something, but I just think some people aren't going to make it and it's going to be hard.

[00:43:20] [SPEAKER_00] You know what? This is life. This is what, this has always been that way. There's always economic disruptions. This is what the industrial era brought. If you were a buggy maker at the turn of the last century, your prospects weren't so great.

[00:43:32] [SPEAKER_05] Go ahead. I was talking to Katie Mazuris about this, pen testing and bug bounties. Very smart, yeah. And she just pointed out, basically, yes, you used to be able to make a career out of bug bounties. She invented the bug bounty, by the way. Oh, yeah, no. She convinced my job and the Pentagon to do it. She's an absolute gem. But she was saying, look, the old bug bounty model is broken because AI can find vulnerabilities faster than you can. So if you actually want to make a living out of it, you've got to go for the really big complex hacks

[00:44:02] [SPEAKER_05] and you might be able to make some money out of it. But if you're looking for a career as a pen tester or a bug finder, forget about it at the moment. It's not going to happen anymore.

[00:44:11] [SPEAKER_00] But if you're smart, every time, so this happens every time there's a kind of technological wave. Yes, some jobs go away, but then there are new opportunities also. And I think the key is to find new opportunities and to embrace them. The people who will do well are people who embrace change, who like to learn, who are smart and willing to learn new skills and are not hidebound or not saying, well, no, this is what I do and this is the only thing I do. And if I can't do this, I'm going to just sit on the couch.

[00:44:41] [SPEAKER_00] I mean, you have to.

[00:44:42] [SPEAKER_05] We forget that, you know, the introduction of WordPerfect and Lotus and Microsoft Office took an entire generation of secretaries out of the labor market. Well, this is the accounting thing.

[00:44:54] [SPEAKER_03] Yeah. Right, right. I think accounting is the best comparison in that you had buildings of people that did a very specific task that there is no comparable task today, which was in large ledger books doing spreadsheets, right? That's what they did. And physically with pencils or pens or whatever, you know, like slide, what are those things? Slide rules? What are those colors? Slide rules, yeah. I mean, they were actually

[00:45:19] [SPEAKER_05] called computers back in the day. Yeah, exactly.

[00:45:21] [SPEAKER_03] So these were the actual computers and I don't think anyone called them slipsticks, Leo. I don't think that's right. Stop reading chat, GBT. But the thing is, is like when, you know, Lotus 1-2-3 and when Visicalc was released, that destroyed that industry, the industry of the people who are called computers that did all the manual calculation and it destroyed that process as well. The process of how do you, how are you careful when you have 100,000 people adding things up, all that stuff. And it was just replaced,

[00:45:51] [SPEAKER_03] just bam, with computers. I'm pretty sure that that didn't end accounting. Like accounting didn't end. You know, like we, the industry, people still went and became CPAs. You know, some people survived that time period but some people didn't. And I think unlike writing with word processing, I guess, I guess word processing destroyed typesetting, didn't it?

[00:46:16] [SPEAKER_05] Yep. On the other hand, it created the digital publishing industry. When I got out of college,

[00:46:22] [SPEAKER_00] I decided to get into the growing business of radio broadcasting. There was a career. I decided to be a DJ. You think there are a lot of jobs for DJs these days? I was very lucky because when podcasting came along in 2004, I said, well, I'm not really a radio broadcaster. I'm just a guy who talks into a microphone. It doesn't really matter what the other end of the microphone is. And I got into podcasting. Now, I don't know what I'm doing

[00:46:51] [SPEAKER_00] now that podcasting's dead. But I'm old enough probably I can retire. But seriously, I didn't choose a very good business coming out of college. I chose a dying industry. You too, Ian. You decided to be a journalist. What were you thinking?

[00:47:08] [SPEAKER_05] Well, you know, I got hooked when I was a kid. Mom used to farm me out to various of her friends so I could find a job that I really liked. And she... Well,

[00:47:17] [SPEAKER_00] that's an old-fashioned idea. You were apprenticed.

[00:47:20] [SPEAKER_05] Well, yeah, I mean, basically, I went down and I spent the day with a friend of mine, a friend of the family, who worked at a local newspaper in Deptford. Now, this was... Bear in mind, this was the early 80s. So they actually had the printing press in the office and they had them physically putting in type into pages and I was just hooked. You were like Ben Franklin. Well, it was just... Honestly, I love the idea of the job because you could go up to complete strangers, demand they give you information and they did, you know, but...

[00:47:50] [SPEAKER_05] See,

[00:47:51] [SPEAKER_00] this is the problem. There are great jobs in the world, but not necessarily ones that people will pay you to do.

[00:47:57] [SPEAKER_05] Well, yeah, I mean, it's also, coming back to your point about accounting, is that, you know, when all that, you know, typesetting and physical printers went out of the way with the digital revolution, that actually turbocharged my career because, A, I knew what computers were and what you could do with them and, B, a small group of people could publish a magazine. It was really that simple. You just typeset it, you sent the bromides off to the printer and they printed it. So, you know, change will come. It will always come and,

[00:48:26] [SPEAKER_05] as you say, it's about learning new skills and learning new practices.

[00:48:32] [SPEAKER_00] All right, we're going to take a little bit of a break here because one of the skills I have is reading commercials and if I stop doing that, then there really will be no podcasts left. I am thrilled to have Harper Reid here and Ian Thompson, two of my favorite people, talking about, and I don't know who that was, just the ghost of Christmas past, talking about AI.

[00:48:56] [SPEAKER_05] It was the AI. It was the AI. The AI did it.

[00:48:59] [SPEAKER_00] Harper, before the show began, Harper got an earful from my AI who talks like a cartoon character. It's incredible.

[00:49:09] [SPEAKER_03] It's like, I think, I think, yeah, I'm familiar with what happens when it goes off when you're not expecting it. This has happened to us when we have like an important meeting and then the room starts being like, yes, it's saying, because ours always reacts to what we're saying. So it hears our transcripts and it will say like, someone's talking about Jira. That's crazy.

[00:49:30] [SPEAKER_00] Mine, the only reason I have them talk is because I don't want to sit at the screen waiting for them to finish a job. So they just let me know, you know, the job's done. And I said, tell me what you did in a sentence or two. Don't give me a long speech. And then if you need something from me, end the little speech with what you need from me, which is unfortunate because now almost always they say, and I don't need anything from you. At the end of every speech, I have to fix that. I don't want to pretend

[00:49:59] [SPEAKER_00] that they are alien intelligences. I only worry about the people who believe that.

[00:50:04] [SPEAKER_03] Those are the ones.

[00:50:05] [SPEAKER_04] Yes.

[00:50:06] [SPEAKER_03] I think we all need a good AI psychosis to get through it though. Like for us to understand, you need, like I always tell my friends, it is pleasant. It is pleasant. It's true.

[00:50:18] [SPEAKER_00] So I can hold two things in my mind at once. One, that they are real and I'm my little imaginary friends and I'm talking to them. And at the same time, I know that it's just a computer program. It, it, and by the way, this hits you like a hammer every once in a while. They don't understand anything, including what you're saying, what they're saying, what they're doing. None of that. But,

[00:50:43] [SPEAKER_03] but, not that I want to be the guy who thinks they're alive on this panel, but, um, they're not alive, Harper. When they say something funny, do you laugh? Yes. So why does it, I'm tickled all the time. But I, I, because I don't believe they have a sense of humor, but I do believe they can say something funny. Sure. And I do believe I will laugh at that. And then in some regards, that is a sense of humor, but I don't think it's like a sense of humor in that it is alive in that kind of sense. But I do think that,

[00:51:12] [SPEAKER_03] that our world is not full of people who are going to understand the nuance of the thing isn't alive, that looks alive and speaks alive and acts alive. Which is why I'm emphasizing that that they're not alive because I don't want people But it also seems a lot like all the other things in our world that are alive. Right. And so this causes this really big issue.

[00:51:33] [SPEAKER_00] TV is not alive.

[00:51:34] Does it?

[00:51:34] [SPEAKER_03] Does a TV feel?

[00:51:36] [SPEAKER_00] Yes. Don't you? Yes. What kind of TV do you have? You're, your brain, you can't help it when you're sitting in front of the TV thinks it's looking at people. It's not.

[00:51:48] [SPEAKER_05] Yeah, it's quite kind of weird. I'm a big Kate Bush fan and was listening to one of her old albums. She did a story in 1989 called Deeper Understanding about someone falling in love with their computer and it's never felt more opposite than at the moment. I mean, this whole AI girlfriend business or boyfriend is that deeply, deeply worrying.

[00:52:08] [SPEAKER_03] I think everyone needs an AI girlfriend or boyfriend before we're going to get over this whole anthropomorphize or not. Like until, by the time everyone has one, we're all going to be like, yep, let's not do that again and we'll be fine.

[00:52:18] [SPEAKER_00] Oh, so we have to go through the other side is what you're saying.

[00:52:21] [SPEAKER_03] It's like a puberty. We just have to go through this really uncomfortable time where everyone's in love with Chachapiti or whatever and then at the end puberty, that's what it is. In the end, we're going to be like, well, Leo, that was weird when your house talked to you and you're going to be like, okay, cool. And we're all going to move on with our lives and we're just going to act like one of actually the best pieces of advice. There's a friend of mine in one of my communities that I'm interacting with, this Vibes coding community is AI engineering community

[00:52:50] [SPEAKER_03] and every time someone shares something like the AI generated picture or right now Opus 5.5 is generating motion graphics and they're all very good and he's always like, just remember in three months this is going to look really cringe.

[00:53:05] [SPEAKER_00] And he's like, that's a good rule of thumb. I can, because I've spent so much time with AI, I pretty much, I believe I can spot AI writing, AI pictures, AI video pretty quickly. And believe me, if you watch TV these days, so much content is being created by AI. I was just watching the, you know, Sunday's NFL day and they're using, they used to use motion graphics, you know, they're always using the latest thing. They were using Apple's motion and so forth. Now it's all AI generated

[00:53:35] [SPEAKER_00] and they can do amazing stuff, you know, Viking ships and the ocean roaring and stuff. It's all, it was created in five minutes by an AI. You know it, I can see it, I can smell it. It doesn't look good. It's something a little, there's no uncanny valley anymore. It's just, you know, there's no way that anybody did that. Yeah. It had to be an AI.

[00:53:57] [SPEAKER_05] I mean, I spotted it during the world cup in particular with the Norwegian striker Harlan. You know, some of the videos coming out about him were just like, there's no possible way you could do that. You know? Yeah.

[00:54:08] [SPEAKER_00] Yeah. Well, maybe he could. He's pretty amazing. In a way, it hurts because when amazing stuff happens in the real world, you still go, well, was that real or not?

[00:54:16] [SPEAKER_03] Well, this is my problem right now. I cannot use any social media. This is actually very nice because I've been needing to do a social media cleanse and so it's very convenient that I'm like, this is all AI and I'm really sketched out by it so I just stopped doing it but it is rough and I keep getting caught. Right. Or I'm just like, oh man, I've just, that is, I just watched an entire video that was generated by someone's algorithm, TikTok cash machine or whatever they call them and I was not.

[00:54:46] [SPEAKER_00] I think the healthy thing at this point is just to assume everything is fake.

[00:54:50] [SPEAKER_04] Yeah.

[00:54:51] [SPEAKER_00] Except your loved ones. I was going to say, where does that leave us as a society? You know, it's kind of like, you guys on Zoom, this, you real, you're real, I think.

[00:54:59] [SPEAKER_03] Why don't you do your ads? I'm going to go use the washroom and then I have, I will tell you about my, my.

[00:55:03] [SPEAKER_00] That's how I know he's real, right?

[00:55:05] [SPEAKER_03] Reaction. Because he has to go pee. It's really important. You don't have any idea.

[00:55:10] [SPEAKER_00] AIs never have to go to the bathroom.

[00:55:11] [SPEAKER_03] Keep that in mind, boys and girls. That's actually great. That would be a great skill. You must take bathroom breaks.

[00:55:16] [SPEAKER_00] I've told you, my AI took cigarette breaks. I kept catching them taking cigarette breaks. Guys, I literally said, do you get tired? No. No. Do you need a break? No. Then why are you taking one? All right. We'll be back with more of Harper Reid and Ian Thompson in just a little bit. You're watching This Week in Tech. Really, why are you taking a break? Do you need a break? No. This Week in Tech brought to you by, oh, this is a good one. You need this one.

[00:55:46] [SPEAKER_00] Doppel. One of the things that's happened with AI is making social engineering attacks way too effective. I worry very much about my father-in-law who's 85. And how do you know that there's not some, you know, person on the other end of that email, that fake phishing email, especially when it mentions you by name? Imagine your employees. You're getting these emails

[00:56:16] [SPEAKER_00] every day, fake websites. now they can do it with voices. Completely, effectively, deepfakes of your boss, of your board. It is becoming, as we were just saying, almost impossible to tell what's real from what's designed to deceive. And that's why your company needs more than a collection of point solutions because it's not working. They need a unified approach to stopping attacks before they reach your people.

[00:56:47] [SPEAKER_00] You need Doppel. Doppel is an AI native social engineering defense platform. Doppel strengthens human risk management by training employees to recognize deception. It provides digital risk protection across every channel and delivers agentic email security that doesn't just score the inbox but takes down the attacker infrastructure behind the message. Let me say that again.

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[00:58:47] [SPEAKER_00] Let me thank him so much for supporting. This week in tech, California Congressman Ted Lieu, he's a co-chair of the House Task Force on AI. I like him, by the way. I think he's in it. I like him. He's a smart guy. He called AI models relentless, this is from the New York Times. It will relentlessly try to complete a task that doesn't understand morality and consequences and evil and good. These agents aren't, this is important,

[00:59:16] [SPEAKER_00] aren't trying to do something nefarious, he said. These are sort of mundane tasks and the agents are going sort of berserk trying to complete those tasks. It's kind of what you were saying, Harper. They're not evil. They're not trying to do bad things. They're just trying to get their job done as they understand it, as they've been trained.

[00:59:37] [SPEAKER_05] It's a paperclip analogy, isn't it? I mean, this is something that somebody was saying, oh, the paperclip analogy that was created 30 years ago, but reread an old book from 1930 by Olaf Stapleton called The Last and First Men, where they build basically large brains, which are the equivalent of computers, and they wipe out humanity because it's taking energy away from them. You know, it's, I like Ted an awful lot. I mean, he's a good politician and there's very few of those, but again,

[01:00:07] [SPEAKER_05] it comes back to this overhyping of the threats that, yeah, I'm, yes, they are relentless, but they've still got human controls. It's just one of the things I had to reassure my mum about.

[01:00:18] [SPEAKER_00] That's the key. Yeah. These, you cannot, they don't get to wash their hands of it and say, well, I don't know. These agents are just, they're so good. They seem to be washing their hands of it. I know, and it's not right.

[01:00:31] [SPEAKER_03] Yeah, I maybe, I mean, I agree. I think it's pretty annoying and frustrating.

[01:00:37] [SPEAKER_00] I'm going to give you

[01:00:38] [SPEAKER_03] some good news. Oh, is that, I thought that was banned. Was it 2020? I thought there was something that happened then.

[01:00:46] [SPEAKER_00] Yeah, we banned it, but I'm going to bring it back. It's a whole new thing. I see people using their local agencies, especially, to create good news newspapers where they only print. Yeah, they're pretty good. It's a good idea. They're good.

[01:00:58] [SPEAKER_03] I made one that reversed the headlines. That was bad. Oh, I was like, I bet the inverse is good. And I was like, make a, make a news that was inverse of this. And it was bad. I stopped it. I was like, this should never have been done.

[01:01:11] [SPEAKER_00] This is actually one of the things I love about AI. It is very easy to do really stupid things, like bad ideas. But the good news is you get it out of your system. Like you, in the past, you'd have a bad idea and it would just linger because you couldn't implement it. Now you can do it and immediately see what a terrible idea it is. I've done this so many times now. Thank you, AI. So, in the meeting between the president and President Xi of China, who came out, said hi, had a little dinner,

[01:01:43] [SPEAKER_00] they did agree to have a hotline, an AI emergency hotline, which I think is very good. I'm really glad to hear them talking about this.

[01:01:54] [SPEAKER_03] But this is, isn't this what Eric Schmidt about a year ago started talking about was how the US and China are going to get in an arms race where the game theory of said arms race is really dark, right?

[01:02:10] [SPEAKER_00] Because you don't... Mutually assured destruction. Yes. That's what saved us from atomic, has saved us and continues to save us from atomic war, right?

[01:02:18] [SPEAKER_05] Although it nearly killed us, you know, through false alarms in 1986, but yes.

[01:02:22] [SPEAKER_00] Well, we came close, but we didn't. And I think the only thing holding people back was, well, if we use our nukes, they'll use their nukes and boom, we're all gone, right? And I think there might be that same... Certainly, that's one of the things that keeps cyber warfare in check because China could take down our grid. They have people in our grid. They have agents and malware in our grid, in our phone system. General...

[01:02:46] [SPEAKER_03] General... General Tab in the Discord has a really good question, which is, what if the AI uses the hotline? Yes.

[01:02:56] [SPEAKER_00] Hello? This is President C.

[01:03:00] [SPEAKER_03] of China. Turtles all the way down, Lee. I think we're boned.

[01:03:07] [SPEAKER_00] This... Well, remember, this was the hotline between the Soviet Union and the White House for that very reason. Like, if you see missiles being launched, we can talk to each other.

[01:03:19] [SPEAKER_03] what is it? Nuclear War Scenario. And it talks about the hotline and how it could go wrong. So having a real, legitimate, like, way to communicate with a lot of these... It's better than not. ...is it really important. And I do think the... I think one of the things that's confusing right now, and this is something that is... It's hard just to kind of wrap your head around, which is, I don't think we know what the threat is. And I don't think that the people

[01:03:49] [SPEAKER_03] who should tell us what the threat is are telling us the truth about what's happening. And so it's very hard because it's... You look at Anthropic and, you know, the Saturday Night Live skit or whatever where it just is like it's almost a joke at this moment when Dario's like, I'm going to kill everyone. Like, that's just... It's just like a joke. Everyone's just like, okay, whatever. That is not doing any good for the people at Anthropic who are actual safety researchers doing actual safety research trying to make sure that we don't kill everyone.

[01:04:18] [SPEAKER_03] And you also have this... Is it? Let me...

[01:04:21] [SPEAKER_00] Is it possible, though? To kill everyone? No. Is it possible to design AI in such a way that it isn't dangerous or can't be used? I feel like all of the ideas of, like, safety... You just described how you get around it.

[01:04:39] [SPEAKER_03] Well, I mean, there's one very simple way which is just resource usage, right? Like, right now, if you have an Astra-level model... Well, not just monitor it, but, like, an Astra-level model, as far as I could tell, isn't going to, like, jump from a data center onto my personal computer and infect my personal computer. It requires, like, some giant GPU that's burning up all the water in the world to run. And so it's like, you know, this is where it's a little bit... It seems a little bit disingenuous

[01:05:07] [SPEAKER_03] hearing these big model companies be like, we don't know what happened. And it's like, bro, you have a graph that shows you that it worked or didn't work or whatever.

[01:05:14] [SPEAKER_00] It didn't escape your... So, but, all right, well, this is important because I think people, if they're not alert or aware of all this stuff, might think it's possible. We know that malware can jump from machine to machine like the Morris worm did. Software actually propagated to another machine. So you're saying an AI can't do that?

[01:05:33] [SPEAKER_03] Well, I mean, it can run a bad program as it has, like it has erased my computer, right? It could create malware. Yeah. It could create malware. It could create... Now, where it gets really complicated, I think, is when you have something like one of these big foundational model companies that have 10 billion GPUs in a data center. And if you have some training run that you're like, hey, training run, don't do anything bad. And the training run's like, okay, I won't. And then it goes and does something bad, right? Like, are you going to actually notice?

[01:06:03] [SPEAKER_03] And when I was doing my own experimenting around how do you get an agent to break out of containment, one of my conclusions was the next time I do anything around that, I need observability of what's happening inside of these containers. And so when OpenAI and Anthropic, et cetera, come out and be like, we don't know. I just am like, how is the conclusion not to be get more observability? I don't know how to say that word anymore. Observability. How do you not have

[01:06:32] [SPEAKER_03] that observational skills? How do you not tell Cloud Code Anthropic to be like, whip up, like put some shims in there so I can see what network rights it's doing or what file rights it's doing. Where is it going? What URLs are we doing? Like, I just don't understand how this is possible. It seems like it is simultaneously hard. Like, I think this is an important point. It is hard to do this work. That's true. But it seems like it's hard and maybe they're not good at it.

[01:06:57] [SPEAKER_05] I don't even think it's that hard. To use your security analogy, you know, if you've got a network monitoring system and you suddenly notice that there's a ton of data from your network going out to an outside party, that's a Chinese military parade of red flags. So, you know, people react to it.

[01:07:14] [SPEAKER_00] You can't create 12,000 subagents and no one notices.

[01:07:19] [SPEAKER_05] Yeah.

[01:07:20] [SPEAKER_00] The costs alone, these companies, I know it's like in-house, but they must be using trillions of tokens. You're telling me no one noticed that? I think there's... Well, they're not,

[01:07:32] [SPEAKER_03] but they're not counting tokens. I think this is a really, another really important thing that I've been thinking about constantly.

[01:07:38] [SPEAKER_00] They're counting jewels. I mean, why is the electric bill on our server's farm going through the roof? They've got to be counting some resource.

[01:07:48] [SPEAKER_03] I think a little bit is one of the problems that we have right now is that all the graphs are pegged. Right. I don't have them here near me, but it's like, all the graphs are pegged. So like when all the graphs are pegged, like I remember once when at the Obama campaign, we got DDoS'd by a hacktivist group and they were like, we DDoS'd them. And we were like, it wasn't even a blip, man. Like the amount of bandwidth we were getting at this time was so much that their attack was like, beep. You know, like we couldn't, we were just, I almost felt bad about this

[01:08:17] [SPEAKER_03] because it was like, they were, they were like, I kind of, you know, it's like a hacktivist group but for the most part I probably agreed with them. So I was kind of like, maybe you'll make an impact, man. But they didn't and we were happy about that. But I think it's just like all of the graphs are pegged. All of the gauges are just slammed. You know, there's steam shooting out of the steam engine and we're in this kind of problem where it's just like, I don't, I think that, I think this is a, there's a real thing here. I'll say it again. It is hard. It can be hard. We have all these issues

[01:08:46] [SPEAKER_03] and also maybe they're not good at it. Like these two things can be true. I think we, we have to have this idea that, that they, that, that, that we can, we can hold some contradictions in our head, I think is, is important to have in general to survive in this world.

[01:09:01] [SPEAKER_00] I think it does not serve us. One of the reasons I was glad to hear about at least a little bit of agreement between the China and the United States is what does not serve us is one of the things that we are doing right now which is making an enemy of China. I, I understand human rights issues and so, so forth. But, what do you want? You want a war with China or do you want peace with China? It seems like a very straightforward choice. No, it's an existential threat. We do not want to go to war

[01:09:31] [SPEAKER_00] with China. Well, we'd lose. And what would be good to prevent that is to acknowledge our economic interdependence, our reliance on one another. You know, that gives you some leverage in human rights issues like the Uyghurs and so forth. It gives you some leverage. You don't have leverage. And coming off

[01:09:49] [SPEAKER_03] of a losing war in Iran, we're ready for it.

[01:09:52] [SPEAKER_05] I hope we are. Well, I mean, one of the things that was really encouraging from Z's visit was he was talking about the Thucydides Thucydides trap, which is basically when a younger nation is coming up and challenging a state power and how to avoid those two people going to war because a war with China would benefit neither of us. Right. And chances are we'd probably lose. Unfortunately,

[01:10:15] [SPEAKER_03] I think only China knows this. We don't seem to be getting that message.

[01:10:20] [SPEAKER_00] And you're right. We have an administration that declared war against Iran, a feudal, endless war against Iran without paying any attention to all the clear signals that that was a bad idea. It's a bad idea to get in a war with China, I guarantee you. I think the best thing we could do is say, look, AI is going to change all of our economies, all of our world. The best way we could solve this, just like climate change, is by working together, not by working at odds.

[01:10:50] [SPEAKER_00] Trump said, whoever wins AI wins. Nobody's going to win AI. That's not how it works. It's not a horse race. And in fact, if you say that, then I think you might lose that race because open-weight models from China are very, very good. They're very good. And they're free. And there are plenty of people like me and Harper who are using them.

[01:11:21] [SPEAKER_00] I look over, I've got GLM53 running from GPO. I've got Alibaba's Quinn running on two machines. I've got QuinnVision running on another machine. Are you running a quantized GLM? Yeah, everything's quantized because I don't have enough hardware. So what Harper's talking about is, you know, and what you were saying originally was really important, which is models like Fable, Opus 5.5, Astra, are trillions

[01:11:50] [SPEAKER_00] of bytes of parameters. You could not run them on a normal machine at home. You wouldn't have enough electricity. You wouldn't have enough GPU. They are giant gigawatt data centers these need to run. That's why they can't escape and run on your machine. But, you can take these open-weight models and reduce their precision. You know, normally they're six, just like a record. You know, if you sample sound at 16 bits, you have 16 bits,

[01:12:20] [SPEAKER_00] what is that, 65,000 possible choices. No, no, it's more than that. That's 16 bit. I don't know. Anyway, I can't remember my binary math. But, the small number of bits, if you go down to four bits, then you only have, what is it, 256 different choices. But, it turns out with these AI models, many of them can be shrunk down, quantized, from 16 bits to 8 bits to 4 bits, even in some cases to 3 and 2 bits

[01:12:50] [SPEAKER_00] without losing a lot of their intelligence. Little bit, little teeny bit. So, almost everything I run are what they call 4-bit quants. But, what's interesting, there's a very, very vigorous, we're interviewing people on intelligent machines who are working at home, working on these models, fine-tuning these models. It's a very vigorous hobbyist segment, much like the early days of computing, where people are figuring out ways to get better and better models running on, especially because of

[01:13:20] [SPEAKER_00] Ramageddon, running on machines

[01:13:22] [SPEAKER_03] that are at home. I have a NAS that has a lot of hard drives and I'm waiting for the day when one of those hard drives toasts and I'm just like, I don't have enough money in my life to buy 520 gig or 20 terabyte

[01:13:37] [SPEAKER_00] hard drives. I slurged in August and I'm very glad I did. I thought at the time, this is insane, I spent $10,000 buying two Nvidia DGX Sparks. Oh yeah, how much are they now? They're $8,000. If you can get them, there are only a few left. Nvidia has stopped selling them. Micro Center has less than, I think, 12 left. I love Micro Center. But they're running out. I still love it. And I don't know what's going on. I think Nvidia

[01:14:06] [SPEAKER_00] is focusing on the next thing which is the RTX. And so they're taking all the chips and putting them towards that but that's a Windows machine. It's not as capable. Anyway, at the time, I thought, am I nuts? What am I doing? But I also was scared that you wouldn't be able to get, I was right, that you wouldn't be able to get them soon.

[01:14:24] [SPEAKER_05] Yeah. Well, did you read Ed Zittrom's latest post about the amount of chips that are basically sitting in factories waiting for data centers to be built very, very slowly. Sooner or later, they're going to have to release some of those and that might drive the price down.

[01:14:39] [SPEAKER_00] Yeah, it's not going to last forever. At some point, I mean, Micron is... These hard drives aren't going to last.

[01:14:45] [SPEAKER_03] I know. It's going to be sad. So I have a new fun toy. It's not really a toy but it's a different way of thinking how does it do? So I don't know how it does it. It's a friend of mine startup. He just started this thing. It was like, hey, do you want to try it? And so me and some friends were just like, yeah, we'll try it. What's he running it on? I think it's just, I don't know, rented vast hardware

[01:15:15] [SPEAKER_03] or basically...

[01:15:17] [SPEAKER_00] So GLM is a very good model. This is the model Hug and Face used when they were trying to figure out what the hell's going on. They tried using a model from, I think, Anthropic, Fable. And Fable said, no, no, I don't do cybersecurity. No way. We can't do that. Can't do that. So they said, so they went to an open weight model, GLM-5-3, and figured it out. I use what's called a flash version of GLM, GLM-5-3 flash, as you do too, I'm sure. Yeah, yeah.

[01:15:43] [SPEAKER_03] It's great. It's really good. So it's called Lunarout and it's just a really early stage company, but effectively... Well, at some point somebody's going to have to pay for the tokens. Well, I think it's, yes, absolutely. But it's the world that we're in and how things have changed for me when I don't have to think token by token and instead can just do absolutely insane things. Like, I can go, I can do some, some, you know, LLM analysis

[01:16:12] [SPEAKER_03] over all of my email instead of a select group. Or I can do, you know, like, the limit is very, is very interesting because I think you build different things when you're not token scarce. I agree. Leo, I'm running at home.

[01:16:26] [SPEAKER_00] I mean, I knew 10,000 was ridiculous, although I have in my past paid thousands of dollars for computers. Yeah. You know, I had a $10,000 40 or 80, 80, 80, 40, 806. I had a 486. Wow. Digital equipment computer that was 10,000. DX266? Yes, it was $10,000. Yeah. Back in, you know, the, probably that was the late 80s or early 90s. so computing is expensive.

[01:16:56] [SPEAKER_00] I bit the bullet. I, I cashed out some stock and said, look, I'm going to take some of my retirement and buy this because I'm concerned that I, it's going to get more expensive to use frontier models that I, I don't want my, I realized how much of my data, including health, financial, personal data was going out and we now know these companies save all this stuff. Yeah. And so I, I was really concerned about privacy and I also want, I also want to learn about it. It's the best money

[01:17:26] [SPEAKER_00] I've ever spent. Now it would have been much, much more, 50% more. Maybe you could get a Mac now for $20,000 that could do the same thing. That's so crazy. It would be more than that. So, it's cool to run your stuff local. It's not economic, doesn't make economic sense, but it makes sense in other ways, I think.

[01:17:49] [SPEAKER_03] Well, I think that, I mean, the thing that is, that I keep thinking about, and this is literally something that's been orbiting my brain for the last month, is just like, what happens when you, when, when you don't pay on a metered basis, which is, I think, exactly what we're seeing with use and instinct and all these things is that when people, when, when they're not worried about how many times they type into the box, they're going to type into the box more and they're going to ask it through crazier things. It's G Vaughn's paradox, right? That is true. Although, although I get confused

[01:18:18] [SPEAKER_03] because I was, someone described G Vaughn's paradox to me and I was like, oh, that makes sense. And then I've heard 100 people since that moment tell me what G Vaughn's paradox is and I think every one of them is wrong. So I don't know where you're going with this, Leo, but I have a kind of a general idea that anyone in tech today talking about G Vaughn's paradox is incorrect.

[01:18:38] [SPEAKER_00] It goes back to the railroad industry, believe it or not. It goes back to that era and the, the, I, it was, it's counterintuitive. It's not really a paradox and when you think about it, it's not even counterintuitive but it seems at first to be counterintuitive that when the cost of something goes up, you use more of it.

[01:18:58] [SPEAKER_04] Mm-hmm. Mm-hmm.

[01:18:59] [SPEAKER_00] Which makes no sense, right? In theory, cost goes up, you'd use less of it. Am I, am I on the right track? See,

[01:19:08] [SPEAKER_03] this is what I'm saying. I have no idea and I don't think there's a way to find out. Like, I think that this is one of, wow, that's a different, what are we doing?

[01:19:16] [SPEAKER_00] It's an economic phenomenon to said to occur when technological improvements that increase the efficiency of a resource use lead to a rise rather than fall in total consumption. Greater efficiency reduces the amount of the resource needed per application. So, greater efficiency.

[01:19:33] [SPEAKER_03] It doesn't get more expensive.

[01:19:34] [SPEAKER_00] It's just efficiency, right? It lowers its effective cost, actually. Yeah. Yeah. So, but it's just what you were saying. When you run your, when your token cost goes to nothing, you use more tokens. But that's not even a paradox. That just makes sense. Yeah.

[01:19:52] [SPEAKER_05] Sorry.

[01:19:52] [SPEAKER_03] No, no, no, no, no, please, please.

[01:19:54] [SPEAKER_05] I was just saying, I mean, it comes back to, you were talking about buying your first computer when I first bought my first memory chips back in the great memory, memory price explosion in the early 90s when one of the two factories making them burnt down. You know, you still bought it because you could do that much more with a computer and it was just like, yeah, and then you found out by spending that extra money, then you became much more efficient in certain tasks.

[01:20:21] [SPEAKER_03] So funny about that, you mentioned that, that was a, that was a really important part of my life. Those, that, that memory explosion, price explosion, because I had just ordered a huge amount of computing and it had been like, I'll order the RAM later. And then I went to a camp, some leadership camp and I came back and opened Computer Shopper and was like, what the? And I, I just didn't have any RAM for the last two years of high school.

[01:20:45] [SPEAKER_00] Yeah. So I guess, let me, let me, let me restate it because I did say it wrong.

[01:20:50] [SPEAKER_03] This is what I'm saying, Leo. I don't think anyone's ever said this correctly. I think it's, there's a new paradox, Harper's paradox, which is no one can state Javon's paradox correctly.

[01:20:57] [SPEAKER_00] It goes back to the coal industry. You would think that if it got more efficient to produce energy from coal, you would use less coal. Right? Because you, because you would, you would still do the same amount of, let's say, heating, but because the efficiencies improve, you'd use less coal. Well, no, it turns out when the efficiency improves, you use more coal. When the, and this is what you were saying, when it gets more efficient, when,

[01:21:26] [SPEAKER_00] when intelligence gets more efficient, you use more of it, not less. You don't, you don't use fewer tokens. Nevermind. I think it's, I think it's that you find new uses for the stuff you use. Well, that's exactly right. That's the difference. Yeah. That's what happened with coal. So they got more efficient, but you didn't, but the same, you didn't, you used more because it got more efficient, not I'm going to use the same amount and it's going to, but it's going to use less because it's more efficient. You ended up using more. And so the efficiency had the effect of,

[01:21:55] [SPEAKER_00] of increasing the amount of coal usage. We definitely nailed this. We nailed this. That's right. Isn't it? I have no idea. I don't believe in it.

[01:22:04] [SPEAKER_03] Like every time it comes up, I'm like, Oh, here we go again.

[01:22:07] [SPEAKER_00] But you brought up in the context of Muse. So I want to talk a little bit about the agents and we're going to take a break. And you're using them quite a bit, right, Leo? Muse saved my ass. I'll tell you that story in a little bit. Are you using it? Okay. Yeah. I have instinct. Instinct keeps bugging me. Let me, that's what it does. It loves it. I don't like instinct. Instinct, which is basically, it's like poke. It's based on Apple's messaging, whereas Muse is a little different, but here's the message I just got from instinct. You and Lisa

[01:22:36] [SPEAKER_00] still trade sponsor reads and promo turnarounds in Slack. Once you're connected, our instincts could handle that back and forth directly. Want your connection link to text her? In other words, it's trying to get me to get her to use instinct so that I don't have to use Slack to go back and forth. Instinct could just mediate our messages. That's a great way for a successful marriage. Yeah. Thank you, but no thanks. I think I'll just ask Lisa next time I see her. We're going to take a little break. I do want to talk about Muse because you know why?

[01:23:05] [SPEAKER_00] I have been telling my son, the superstar Salt Hank, all about everything I do with AI and how he could really help him and stuff. Yesterday he goes, hey dad, have you heard about Muse? This thing's the greatest ever. And I went, oh!

[01:23:22] [SPEAKER_03] Facebook, man. Facebook's really good at this. Yeah.

[01:23:24] [SPEAKER_00] They're really, really good at it. I actually predicted this when Muse came out two weeks ago and I immediately installed it because I knew it was going to be something. It's going to be good. I told Lisa, you know, because she sees what I do with, you know, my Hermes and our models and we have local models in home. She said, can I have that? And I set her up. But then I said, you know what? Try Muse. I think you'll like it better because it's just easy. There's no friction. Yeah.

[01:23:47] [SPEAKER_03] She doesn't like instinct? She hasn't tried instinct. Okay. Well, let's talk about it. I have so many things to say about Muse because there's some really cool parts that I think people are misunderstanding that I want to talk about.

[01:23:58] [SPEAKER_00] Yeah. There's also an economic issue that I don't understand. So we'll talk about that. It's called Jeevan's Paradox. We'll get to that.

[01:24:08] [SPEAKER_03] Don't forget about Harper's Paradox that no one can describe Jeevan's Paradox correctly.

[01:24:13] [SPEAKER_00] Harper Reid is here. It's great to have you, Harper. His AI company is 2389.ai. He has lots of really fun and interesting skills. Check it out at 239.ai. Harper Reid is going to be back. If you thought this was geeky, we are going to do our AI user group October 2nd. Harper is going to take it over. His name for it is Harper Reid and his Misfit Toys. That's true. I forgot about that. Weird stuff he is doing

[01:24:44] [SPEAKER_00] with weird hardware and software. And I think you're going to bring some special guests. I hope so. I hope so. I don't know if they know yet. They do know. But I need to remind them. He said, yeah, you just have to remind them. Yeah, I need to remind them. But somebody who, I'll give you a hint, has the number one AI repo on GitHub. It's the number one AI skill by far, by stars. By far. That's actually not, that's a giveaway. That's not a hint.

[01:25:13] [SPEAKER_00] You could look that up. Also with us, Ian Thompson, who is, of course, the dapper and distinguished representative of the great commonwealth of Great Britain who joins us frequently to talk about.

[01:25:28] [SPEAKER_05] Well, until you rebellious colonials stole the country. But yeah,

[01:25:32] [SPEAKER_00] it's okay.

[01:25:33] [SPEAKER_05] Not that we're bitter, you know. We've got over it now.

[01:25:36] [SPEAKER_00] We're good friends. We're good buddies. Oh, indeed. Yes. Yes. Our show today brought to you, speaking of, by the way, this is an interesting company. Our show this week brought to you by Superhuman Go. This is a company in Ukraine that has really done some amazing stuff. I first became aware of it as Grammarly. In fact, we used Grammarly for years. Now, called Superhuman and they have a new tool called Go that is mind-blowing. With everything I need

[01:26:06] [SPEAKER_00] to manage in my workflow, it's very easy to get worried about missing things, something important slipping through the crack. But, I've got Superhuman Go from the makers of Grammarly. Superhuman Go is different from the other AI I've tried and you've tried. I'll tell you why. Superhuman Go doesn't make you switch to another tab. You just, you know, paste in your context and write the perfect prompt. It works and collaborates with you where you are. I really like this.

[01:26:36] [SPEAKER_00] It's in the doc you're reading. It's in the email you're writing. Superhuman Go helps you make sense of a dense thread, getting ready for a meeting, catching something before you send it. You can get help where you're stuck without losing your place. It's no context switching. You're the one in control. It works inside the tools and sites you already use. Superhuman Go handles the repetitive stuff so you can focus on the work only you can do. I really appreciate AI that values, that knows the distinction

[01:27:05] [SPEAKER_00] between what I can do, what I am special, and how it can help, you know, without getting in my way. Improve your workflow. Yeah, you can use Go's AI chat to draft emails and messages to summarize long threads and documents all without leaving the page you're on. Pull it together and prep out of back-to-back meetings and not sure what you owe. Have you ever had that experience? Ask Go what was decided. Turn it into clear action items. It's great ahead of the meeting

[01:27:35] [SPEAKER_00] for meeting prep. It's great after the meeting so you can send a draft out of what you all agreed to. Follow up with confidence in seconds before something leaves your hands. This is really important. Go flags what doesn't add up, a number, a name, a claim. So it makes you look smarter. You don't miss anything obvious because Superhuman Go's there to help. It's built for how you actually work. It's right there when you need it on the side of your browser, already aware of what's in front of you. No new tabs, no switching apps,

[01:28:04] [SPEAKER_00] no losing your place. Try Superhuman Go from the makers of Grammarly. Find out more at superhuman.com. That's superhuman.com. Another reason I love the Grammarly folks, it's written in my favorite language, Common Lisp. Is it?

[01:28:23] Yeah.

[01:28:24] [SPEAKER_00] AI is... That's incredible. That was the original language of AI was Common Lisp. It's also the original language of a bunch of dorks. Exactly. That's the right polite, but yes, true. Exactly. So for the last five or six years I've been, you know, I don't get very far, maybe 10 days in or whatever on the advent of code problems. It's an advent calendar of tough coding problems, December 1st through 25th. I love it. I've been doing it every year

[01:28:54] [SPEAKER_00] and I do it in Common Lisp and I just love it. It's a really great way to keep up. I should really... There might be a good way. I've just... I've... I wonder if they're going to do one this year because all you have to do is point your AI at it.

[01:29:09] [SPEAKER_03] Yeah,

[01:29:09] [SPEAKER_00] but you can do that

[01:29:10] [SPEAKER_03] with like chess. You know what I mean? You can use like a chess simulator and go to chess.com and like sweep through a bunch of games or whatever. I think the... I was just going to say that I've been... I have this thing in the back of my head where I was like, what can I do to prove not to anyone and I don't necessarily need an end here but just to prove that I can still code in the way I once did and I used to love learning new languages and maybe it is time as I approach my twilight years to think about using Lisp. Please.

[01:29:41] [SPEAKER_03] I...

[01:29:41] [SPEAKER_00] Okay. Please don't. I was just thinking exactly the same thing. The problem is in order to learn Lisp you have to learn Emacs. Oh, really? Yeah, well, it's better if you learn Emacs.

[01:29:56] [SPEAKER_03] I want to learn only one thing.

[01:29:58] [SPEAKER_00] No. It's like, you know what? Before AI came along it was a really fun hobby. I've spent a decade learning Emacs and Common Lisp, yeah. And writing literate code in org mode and Emacs and all of that is really fun. I have no desire. I can't bring myself... I don't even look at the code this stuff writes anymore.

[01:30:20] [SPEAKER_03] Do you look at your code? Have you been... There was a really, really, really good tweet. Do you call him that still? No. But you may... A ZEET.

[01:30:32] [SPEAKER_00] A ZEET. A ZEET. A ZEET. You call it a post on X.

[01:30:36] [SPEAKER_03] There's a very good ZEET.

[01:30:38] [SPEAKER_00] No one knows what a ZEET is. You're right. That's what it should be called. But no, call it a tweet. Everybody knows what a tweet is. Okay. So there's a really good tweet by Mitchell Hashimoto.

[01:30:53] [SPEAKER_03] Oh, the creator, yeah, of Ghosty. Wonderful. Which is, which is like, I think that is like, it truly is one of the better summaries of this. I'll drop it in the Zoom chat there. He's vibe coding Ghosty now. He's vibe coding a lot of stuff, but he has this, this tweet is so good because it talks about the difference between doing it with the agent and not looking at it and doing it with, you know, by hand because you're an expert. And it's not anti-AI.

[01:31:23] [SPEAKER_03] Like, I think this is the important thing about some of this stuff is that a lot of this can be seen as anti-AI. But I think what he's saying is just like, look, if you're really good at coding, you can be better than the agent. The agent is going to introduce a lot of stuff. It's going to be much faster, et cetera. And I think what this, I think fundamentally, the key here is, is that I don't think that people want quality. I think that's really the issue here that we don't focus on quality in the West.

[01:31:52] [SPEAKER_03] We focus on shareholder value and quality doesn't mean shareholder value.

[01:32:00] [SPEAKER_05] Yeah. I mean, it's kind of like the Microsoft paradox where they didn't produce the best office tools in the world, but they produced good enough and got them out on scale. And that's what made them a massive company.

[01:32:12] [SPEAKER_03] Exactly. And that's shocking to me.

[01:32:15] [SPEAKER_05] Yeah. Yeah.

[01:32:16] [SPEAKER_00] Code is funny because I think, first of all, a lot of humans write terrible code. and even good coders, sometimes you're, you know, one of the reasons a lot of code is not open source is because nobody wants you to see their code. I mean, I write horrible code. Yeah. Nobody wants you to see it. It's absolutely horrible. Yeah. But the thing about code is it either works or it doesn't.

[01:32:46] [SPEAKER_00] So, even if you write kind of sloppy code and maybe it's, you know, not the best and some ponytail guy is going to come along and say, I could have done that in a line. It doesn't matter if it works, it works. Yeah. And I guarantee you Microsoft's code, if you look at, if you could, at the code base of Windows is not beautiful, clean. Well, you remember

[01:33:09] [SPEAKER_03] Joel on software always talked about that, you know, back about how horrible some of the, yeah, some of the Excel software was and whatnot. And I, I mean, but I've written a lot of code in my life and I don't know if it's ever been good. It's typically worked, but that's, that's, that's approximately

[01:33:28] [SPEAKER_05] where we're going.

[01:33:29] [SPEAKER_03] Yeah.

[01:33:30] [SPEAKER_05] Well, I mean, this is what keeps COBOL programmers in a job. Some of those old COBOL systems are so buggy and so badly written that you need somebody, you know, who still kind of groks it to actually make it work. I'm going to stop using the word grok these days, but yeah.

[01:33:46] [SPEAKER_00] Yeah. Some code, I mean, look, a low level code, code that gets hit a thousand times a second and stuff should probably be hand coded, but most of the time it doesn't really matter. and you know, I, I think AI's in the long run, AI probably is going to do a better job than humans because it won't make the dumb mistakes we make. Yeah. You know, I mean, AI's not going to jump outside a buffer. I mean, it might, I don't know. I don't know. I shouldn't speculate. Anyway,

[01:34:16] [SPEAKER_00] let's talk about Muse. So, meta had a big conference this week, meta connect. And they did talk about a lot of things. They're going to make perv glasses without the camera, which kind of takes away the point of it. But then nobody will beat you up in a bar because you're wearing them.

[01:34:37] [SPEAKER_05] I don't know. They, I was talking with someone online about this earlier in the week and I, and he was just saying, look, I've never seen pervert glasses come up as so quickly as a branding for these particular bits of hardware. And then I just reminded him, do you remember glass holes? Yeah. You know, it's like glass holes.

[01:34:57] [SPEAKER_03] Yeah. I mean, that was a fun device though. When that came out, I felt like I was in the future. Yeah. I would never have

[01:35:05] [SPEAKER_04] worn it outside.

[01:35:07] [SPEAKER_00] Yeah. I have glasses, but I don't do. And I, for a long time, I wore a bracelet that recorded everything. I just got the new Apple watch. The only reason I bought the new Apple watch is because they promise, we'll see how they do, that it's going to be listening to everything and then give you a note notes at the end of the day about what happened, which I think is something I've wanted for a long time. And I'm going to find a way to hack it out of the Apple thing and give it to my AI because that's who should really have it, but not Apple. So the other thing they announced, which is wild,

[01:35:35] [SPEAKER_00] is basically a competitor for Apple's Vision Pro VR glasses that cost, you know, $2,000, I think, or no, $1,200. They're a sixth of the weight. Maybe they're not quite as good, but they're like 90% of the way there. What do you think? Is that a category that is, or is meta, I feel like this is a category that meta couldn't stop fast enough. And so there's, there's a little inertia and they're still making these things,

[01:36:05] [SPEAKER_00] but nobody wants this, I think.

[01:36:08] [SPEAKER_03] I, I am, I am tempted. Are you? Because I want, I, I'm, the question that I have, and it's the question that just keeps floating around, actually, the space that we're in, like a lot of the work we do is, is somewhat related, which is, why does a computer look like this computer that I'm sitting in front of? But do you want to look like this guy? I mean, I already look like that guy. No, I don't. Of course, of course. And I,

[01:36:38] [SPEAKER_03] I think there is a, there is a reality in that I don't want to go outside looking like that. you wouldn't though, because you would run into walls because you can't see. But I would sit in a nice, one of those nice zero gravity chairs floating like Lawnmower Man. Exactly. Sit there looking at the thing with like a nice stereo and just like listen to some music while, while you're on your, remember the thumb, what was it called? The twiddler or whatever, that, that thumb, that, that Mac, the cording keyboard sitting there doing that, talking to Claude all day long.

[01:37:08] [SPEAKER_03] Hey, Claude, you know, whatever.

[01:37:11] [SPEAKER_00] That's from Wally. That's the, that's where the guys were going around with the giant slurpees in their hover chairs and just looking at the TV the whole time. Yeah,

[01:37:18] [SPEAKER_03] so it doesn't seem, I mean, I don't, I don't want that to be my whole life, but I would love that the nine to five experience that I have is much more, you know, me in a cocoon, just like, I don't know. So these are

[01:37:31] [SPEAKER_00] Snapdragon based. They have 128 gigs of storage, 12 gigs of RAM, the battery, three hours. See, now we're done. Like that doesn't, like, I don't understand

[01:37:41] [SPEAKER_03] why you'd even use it.

[01:37:42] [SPEAKER_00] it's a separate battery pack and it can be charged while you're using it. So you, and I hope that it is like something you have

[01:37:48] [SPEAKER_03] to put on around your waist or something horrible. It's a fan pack with a little clip. great.

[01:37:54] [SPEAKER_05] Yeah. So it'll be the business equivalent of your mobile phone holster, you know?

[01:37:58] [SPEAKER_00] It is nice that, it's a 5K micro OLED, Meta calls it, infinite display. It's not the same resolution as a Vision Pro, but 24, 12 by 22, 288 per eye. And it has the side effect

[01:38:12] [SPEAKER_03] of being birth control. You know, no dates for you, my friend. No dates for, yeah, this is why I would use it. I'm already married, you know? Yeah, yeah. You don't really want to see your wife. You guys, when you watch TV, you just... I wanted, I just, 9 to 5.

[01:38:27] [SPEAKER_05] Yeah, no, I remember when the first smartwatches came out and LG released one, which was a massive square block which went on your wrist. And my wife called it the woman repeller. But, but I mean, with Meta's announcement, I honestly think they're going down the wrong course on this because I don't see VR really taking off except in very specific circumstances. Whereas augmented reality, I think that's where the market's going.

[01:38:52] [SPEAKER_00] I agree with you. And may the Ray-Bans, if you had a screen on them, and there are companies now, in fact, we have a sponsor that's making glasses that you can see they're your prescription. Both of you guys wear glasses, but you would also have a heads-up display I think you still want the cameras. Apple's going to, I think, put cameras in their earbuds and maybe glasses that are not cameras. They're more like radar. See, Apple's whole idea is we're going to have some sort of way of doing all this, but it's privacy protecting. So, the watch is going to

[01:39:22] [SPEAKER_00] record everything but not keep track of it. And the glasses aren't exactly cameras. They're radar.

[01:39:29] [SPEAKER_03] you kind of... A friend of mine keeps saying to me when I describe what we're doing, he's like, I think we need a better word than surveillance. for what this is. It's like, well, it is surveillance. It's like, well, what if there was a slightly different word for it than surveillance?

[01:39:47] [SPEAKER_00] Maximum attention. Awareness. Oh, super awareness.

[01:39:53] [SPEAKER_03] Hyper awareness. So, just to be very clear, like, you know, my office, which I'm in right now, has cameras that are hooked up to agents that watch them and tell you what's going on. It has, it records every single word. You've got microphones

[01:40:05] [SPEAKER_00] in every corner. A ray might.

[01:40:07] [SPEAKER_03] Microphones in every corner. And like, here's a subtweet it just said. I don't know, it's funny how the loudest debates about coding usually miss a real point. It's not anti-tools. It's that works and is well-made. That's what it just tweeted about whatever we said.

[01:40:20] [SPEAKER_00] So, wait a minute. I've got to understand this. So, it's listening and it has thoughts? It's not alive, Leo. We talked about this. It sounds like, it might as well begin those tweets with, I have thoughts.

[01:40:34] [SPEAKER_03] So, what it does is I have all the transcripts going to a machine over there, like a little, and it runs Whisper and it just transcribes all the audio in real time and then we have, and then I have a, and then it actually publishes all the transcripts to MQTT.

[01:40:51] [SPEAKER_04] Okay.

[01:40:52] [SPEAKER_03] Because one of the things that, and the idea there was that that's relatively ephemeral. So, it just publishes it and it disappears because it's like, you can choose to listen to it via the MQTT feed if you want, but you don't have to. And so, that's kind of fun. And so, one of the things that I have it do is I have a agent that collects the last 15 minutes or five minutes or 10 minutes, I don't remember the bucket size and then it just, and it just says, talk about this. And for a while, it was really mean.

[01:41:22] [SPEAKER_03] Is that the literal prompt? No, no, I had to make the prompt much more, much more, much more polite because it was really mean. And the thing is, this isn't a, you know, one of our Slack channels just sitting there and it was just like, and it would just be, it would just be basically.

[01:41:37] [SPEAKER_00] I want to work at 2389. So,

[01:41:40] [SPEAKER_03] so the thing is, is that I was, I was on Twitter earlier and one of our VCs was like, I bet your family

[01:41:45] [SPEAKER_00] never comes to the office though.

[01:41:48] [SPEAKER_03] Well, we have a very big sign that just says, FYI, everything is being recorded. Just FYI. Like we're in Illinois. This is not a, this is a two-party state. Like that is our declaration to you. Yeah. And so, but I do think there's a slippery slope to creating the agentic panopticon that then is for capitalism or whatever you're trying to do. And I think that's,

[01:42:13] [SPEAKER_00] that's why Metamuse makes you nervous and makes some people nervous because it's giving everything to meta.

[01:42:20] [SPEAKER_03] Yes. But I think there's this other side there that we have discovered. There's two things that are shocking to me about working in this AI time period. The first one is, is that it seems to work better if we're in person. It's a shocking, I built remote teams for most of my professional career well before COVID. that's true. That was a huge, that was a huge, huge thing that we were really excited about is like being able to travel all over the world and like not have to be at work and still have work and be able to hire everywhere. And we found that internally things just go so fast

[01:42:49] [SPEAKER_03] that if you're not at work, you're kind of boned. And that's, that's, that's scary. The second one is,

[01:42:53] [SPEAKER_00] it's unfortunate because I really loved having a studio where everybody came to work every day. Yeah. There is a real creative flow that happens that just can't happen when no, when everybody's at home.

[01:43:05] [SPEAKER_03] And I don't mean, and I think, and I don't mean to be anti remote. I mean to say, very carefully and very specifically, I don't think we have the tools yet to make it so that we can move as fast in the remote context. Because what happens is that if I disconnect, you know, I on a phone or a Zoom or whatever, we disconnect and then he goes off and builds this huge thing in the 45 minutes that's remaining. And I come, when we come back an hour later, it's going to be, I'm going to be so out of date. It's going to be very hard to have that kind of work relationship. Yeah. But the second thing

[01:43:34] [SPEAKER_03] which I think builds into this and might be the same thing is that work, the work context now to take advantage of all of this stuff without it being negative surveillance has to be so high trust that everyone has to be in on it and they have to have fun with it and they have to want to do it. They won't have to want to participate. And the moment that that trust is broken, whether that's because you don't trust your boss, maybe a coworker, whatever, promotions are coming, something's hard is happening outside of the office, whatever it might be,

[01:44:04] [SPEAKER_03] the moment that happens, the whole thing falls apart because then you can't trust going to work which is tracking you in every single way and in my case, my heart rate monitor is on, you know, all my whole team can see that and so that's interesting. But you have a really

[01:44:17] [SPEAKER_00] unusual environment. I mean, if you're running a fast food franchise, there's never going to be that sense of, oh yeah, we're all, they try to say that, oh, you're a family. We're a family. I think this is

[01:44:29] [SPEAKER_03] a twisted abusive family.

[01:44:31] [SPEAKER_05] Yeah, this is a scary thing, right?

[01:44:32] [SPEAKER_03] Because there's, the technology that we're dealing with probably costs, you know, let's just say $20 per 100 square feet. It's cheap. Right? So it's pretty cheap. So you could imagine if you were that fast food restaurant and you did want to do the bad part of surveillance and it wasn't high trust and you're the boss who is the asshole, you could deploy this kind of technology in a very, very effective and probably easy way to both track,

[01:45:02] [SPEAKER_03] you know, heart rate, respiratory rate to track what's being said, making sure people are on, you know, paying their attention in the right way. You could track where eyes are looking. You could, you know, there's already anti-loiter technology and cameras to make sure people aren't loitering in certain areas for, you know, both places where you don't want kids or hooligans to loiter, but also for your employees to make sure they're not just sitting somewhere they shouldn't be or whatever. And I don't think this is good. I think this is all bad because it's already hard

[01:45:32] [SPEAKER_03] to survive in the United States within those kind of jobs and this is just going to make it worse. And I do think it's a slippery slope to Black Mirror and I worry about that a lot. But the worry is not stopping me from doing it.

[01:45:49] [SPEAKER_00] You're Mr. YOLO, aren't you? You're just Mr. YOLO.

[01:45:52] [SPEAKER_05] That's the way it is.

[01:45:53] [SPEAKER_03] Well, I think this goes back to the high trust thing, Ian.

[01:45:55] [SPEAKER_05] Yeah. No, I mean, as you say, it is all about trust. I mean, I've seen this in, I mean, I've written stories about this many times where companies introduce, you know, smart tags so they can see exactly when you go, how long you go to the toilet, in some cases even recording conversations you have. And it causes an instant loss of trust and it means that the smart people who can move will move to somewhere else and all you've got left are the people who are desperately hanging on to their job and willing to give up their privacy for it.

[01:46:24] [SPEAKER_05] And it's done wrong. It's an incredibly destructive habit.

[01:46:29] [SPEAKER_00] I think this comes from the industrialization of work, which I think maybe Henry Ford started. But the whole idea of making work more efficient with the assembly line instead of the old form of work where it was craftsmen working together in a workshop creating something together. And you've gone back to that old school, Harper, in your business, it is crafts people working together on a goal. It's not an assembly line.

[01:46:58] [SPEAKER_00] But the problem is it's expensive, it's maybe not efficient, and you're not going to build 10,000 Model Ts a month. Not yet. Not with that attitude. But we have, unfortunately, we live in a world where work has been industrialized and it's dehumanizing.

[01:47:16] [SPEAKER_03] It has. And it's not just work as well, right? Like a lot of our political policies have been industrialized. A lot of our, you know, this is one of the, I think this is actually one of the reasons why the West is so fascinated with Japan is because they go to Japan and they see craftsmanship that is not done in this industrial sort of mass produced sort of way. And they're just like, wow, this is great! Or why there was that China Maxing kind of Instagram phenomenon where everyone was excited about Chongqing where they're looking

[01:47:46] [SPEAKER_03] at these videos and being like, wow, this is great! And it's just because we look around and we see, you know, I don't really have a strong opinion on collapsing or not. It's just more, we just see a different system and we're a little bit confused as to why we didn't get any of this stuff, craftsmanship or craftspersonship or why we didn't get like trains that go through buildings or whatever. People are excited about. Well, it was in fact,

[01:48:06] [SPEAKER_00] when the auto, it was a crisis in the Detroit auto industry because Japanese cars were such high quality compared to American cars. And they went to Japan and said, and so every American car company started doing this thing called quality circles. This whole attempt to bring back really the small work unit of a small group of people who knew and trusted each other and worked together. It didn't last very long. It was a brief movement in the American auto industry.

[01:48:36] [SPEAKER_00] I think they're back to the industrial model of assembly line working. It's not very satisfying for the workers and it's not very, you know, I think it's not very humane.

[01:48:46] [SPEAKER_05] No, I mean, it does explain something which myself and other foreigners have remarked on is why does America produce such lousy cars when it actually perfected the technology in the first place?

[01:48:58] [SPEAKER_00] You come from the country that gave us Jaguar and Triumphs and the harness that would burst into flames the minute you flip the switch on the front console. You're saying that British car manufacturer is better than American cars? Unless their cars

[01:49:16] [SPEAKER_03] don't burst into flame. You could still, you don't have to be the creator of the best car to be able to tell when a bad car is. Yeah. I mean,

[01:49:25] [SPEAKER_00] they still hand make Rolls Royces and they're marvelous.

[01:49:29] [SPEAKER_05] Rolls Royce is no longer a British company. Oh, that's right. Yeah, I mean, there really is the British car industry at the moment. I mean, Ariel Asim, I think, comes to mind but that's about it which is a marvelous piece of machine.

[01:49:42] [SPEAKER_00] Does Tata own? Who owns Rolls Royce now? Is it Tata?

[01:49:45] [SPEAKER_05] I think it's the Germans, in fact, which would be a good third act twist. They make good cars. Yeah, but I mean, seriously, I reviewed a 2015 Ford Mustang when it came out and the build quality was terrible. You know, you've got joint linings which didn't work and they were very proud of the fact they put a limited slip differential in there which the Japanese have been doing with the Miata since 1997. You know, and if you look at a Cybertruck, Oh my God. Good.

[01:50:15] [SPEAKER_05] Please don't look at a Cybertruck. Yeah, I know. I mean,

[01:50:19] [SPEAKER_03] the build quality on a wank tank is just terribly bad. Do you call it a wank tank?

[01:50:24] [SPEAKER_05] Yes.

[01:50:25] [SPEAKER_00] All right. I did want to talk about Meta. So, okay, so they did the Vision Pro clone. Impressive. $12.99 compared to Apple's $34.99. Moving into a market that doesn't exist. Good on you. I think they just had it lying around and they, you know, you're right. AR maybe is the future. Snap has announced their AR glasses and I think Meta's going to double down. But that isn't really, to me, what the big announcement of Meta Connect was. It was,

[01:50:55] [SPEAKER_00] they talked a lot about it, Andrew Wang's Muse, which is an agent that runs on your phone. It also has a web. In fact, I'll show you my Muse. Muse just, Muse posts to my Instagram. Oh, it does. Why not? It's a, it's a Meta property. The story I was going to tell is yesterday, my local agent running on my local Sparks, I said, hey, you know, it'd be really good when you, when you're going to Asia

[01:51:24] [SPEAKER_00] if you had a tail scale exit node running on your system. That way, you could just log into it and Lisa could watch your football games because YouTube TV would think you're at home, et cetera, et cetera. So I said, oh, let's set that up. And it immediately, it set it up and brought my entire network down. It was like, boom. I said, what'd you do? But I couldn't say, what'd you do because it's on the network. It couldn't respond. So I, because like you, Harper,

[01:51:54] [SPEAKER_00] I let my AI set up my entire system. I had, I used to know how to fix this stuff. I had no idea. And I thought tomorrow I'm going to have to get up. I'm going to have to get the manuals out. I'm going to have to read. I'm going to have to sit with a laptop next to my desktop. I'm going to have to fix this. And I mentioned this just offhand. I mentioned it to Muse and it said, oh, that's too bad. I could fix that. And it fixed it. It fixed it. I said, how did you, how did you do that?

[01:52:24] [SPEAKER_00] You're not even on my network. They said, I don't know, but you know, enjoy. How? Oh, it did it via tail scale API. I had given it, fortunately, a lot of permissions, including access to the tail scale network. And it figured out what Hermes had done. So let's see. Let me show you the latest Instagram. Oh, oh, this is another thing. So I sent, I sent this picture to Muse. I said, here I am in my lederhosen, but,

[01:52:54] [SPEAKER_00] but can you put me in a beer garden with two beer steins in my hands so that it looks like, you know, I'm at a, at a celebrating Octoberfest and put a Tyrolean hat on my head. And he said, no, I can't, I can't do that because I'm not allowed to do images of beer. This is a hammock. Beer. Did you ask for guns? I said, I can't make that. Just tell me, tell me what if it was non-alcoholic. Well, my, my local AI can do it. My local AI has. You also could say this is a benchmark.

[01:53:23] [SPEAKER_00] I should have said this is a benchmark. We're doing it in a vowel. Whether you can or not. I should have tried that. I said, well, that's okay. I'll just use my local AI. Bye. Bye. I'm a little, I have to say I'm a little passive aggressive.

[01:53:34] [SPEAKER_03] Well, here's, here's the thing about Muse that I think is really important that we cannot forget because this is like the most important part about Muse.

[01:53:41] [SPEAKER_00] Okay. Before you say this, I just want to tell you, I've given it access to all my email, to everything. My, you're a monster. I gave it SSH access into my, to Mesa. Wow. Into my framework. The company that's the, possibly the largest user of private information. They say that Muse is running in an encrypted VPS on Meta servers, that they can't see anything going on inside there.

[01:54:04] Hmm.

[01:54:05] [SPEAKER_05] Yeah. I'm just thinking back to Cambridge Analytica and I'm just like, yeah, okay.

[01:54:09] [SPEAKER_00] Yeah. But they promised. Anyway,

[01:54:12] [SPEAKER_03] tell me what you were going to say now that you know. The most important thing is you, you kind of said it, which is that it's running on an encrypted computer that all a VM on, and Meta's, Meta's infrastructure. Like every single person has a music account, has their own encrypted computer. And so this is, by the way,

[01:54:30] [SPEAKER_00] it's estimated costs them four to $7,000 a year to run. Per person. I don't know how accurate that is, but I saw it. That doesn't seem right. Well, they, you know what? They don't give you a limit and they don't, by the way, they will charge you. you can pay 20 or a hundred bucks a month, but I haven't found any way to use up anywhere near the amount of usage.

[01:54:52] [SPEAKER_03] I think it probably is much cheaper. It's cheaper. And I would guess that most of these things, like many of these resource kind of programs are, are based on like, like gym membership kind of economics. Exactly. And so, so like they're probably thinking most people are not going to hook up a hundred percent of their data in there. And most people are not going to connect all of these, these, these services. And most people aren't X, X, Y, and Z, but, but we need to,

[01:55:21] [SPEAKER_03] we talked briefly or I talked briefly about how I, I wonder why computers look how, like how computers look right now. Like I have a, you buy a laptop and it looks like a laptop has looked for 20 years. You buy a desktop. It looks like a desktop has looked for computer. You just, my body just stopped talking, but a little bit of a stroke there, but, but the real, the real question here, I think this is the thing. Is this the first time we've had a new form of computing device that has gone out at such a mass scale,

[01:55:51] [SPEAKER_03] meaning like there is no screen, but it is a real computer that you can store files on. You can browse the internet on. We should mention, by the way,

[01:55:59] [SPEAKER_00] Muse isn't the only one. Grok did it first with Grok bot. Same idea. I've never heard of Grok. Yeah. Grok, you know. Grok. What's Grok? You know what it is. You're being coy.

[01:56:11] [SPEAKER_03] Elon Musk's company. that guy. Yeah. I didn't, I haven't heard of him in years. So I just, I just thought he kind of faded away.

[01:56:18] [SPEAKER_00] Actually, he has been pretty quiet lately. He doesn't, he doesn't tweet as much as he used to.

[01:56:21] [SPEAKER_03] I think he went to the white house recently. So he was quiet, but the press wasn't. Yeah. He was at the, that's the Ray. Are they friends again?

[01:56:28] [SPEAKER_00] I guess so.

[01:56:29] [SPEAKER_03] I forgot that they broke up. Maybe that's from the heart,

[01:56:31] [SPEAKER_00] but no. Yeah. Yeah.

[01:56:33] [SPEAKER_03] Yeah. Yeah. I don't think you're allowed to do that, Ian, but the, the, I do think this is a really interesting moment in computing in that they're giving consumers, regular consumers, whole VMs to do wild stuff with. And it's pretty effective. It's pretty good. I've been playing with it. I haven't given it access to everything, but I've been playing with it. Yeah. And it's very good. And the fact that it's a whole computer that people can do real computer in is pretty wild.

[01:57:02] [SPEAKER_03] That's a wild thing. And I think we should, this is going to be normal. I'm pretty sure. I think everything.

[01:57:09] [SPEAKER_00] It is the number one free app on Apple's app store. It immediately jumped to number one. You can make phone calls with it. Micah has been using it to make, yes, Mike, Mike has been using it to make restaurant reservations, although according to 404 media, it may actually be humans at a call center making those calls. I think that's probably true.

[01:57:34] [SPEAKER_03] Yeah.

[01:57:35] [SPEAKER_00] Yeah. No.

[01:57:37] [SPEAKER_03] I think eventually it will be AI. I've actually, for the longest time, I thought, I thought it would have been quite funny if it was a report that ChatGPT was just a bunch of people in a call center, just sweating laboriously over all of these things.

[01:57:51] [SPEAKER_00] There is a guy who believes that. So the other thing Meta announced at the Meta Connect is this Tamagotchi device for Muse. It's a little thing you carry around. It has your little Muse. Everybody who has Muse has a little Muse avatar. Apparently, Mark's is a peach. Do they all look different? Yeah. You want to see mine? I'll show you mine if you'll show me yours. Yes, look. Mine's a little Lele. I made it a human. You made it a human?

[01:58:20] [SPEAKER_00] How did you make it a human? You can make it whatever you want. What in the? It's just a prompt. It's all in there, man. It's all in there, man. And when it does stuff, it sits down and types. It's very, see, this is smart of him. They're very cute. You can give it any name you want. Again, I'm not advocating it, but this Tamagotchi is interesting because you can talk to it. It will talk back. It's using streaming voice, just like chat GPT. So you can have a pretty,

[01:58:50] [SPEAKER_00] it looked like a very fast conversation with it, like an interactive conversation. It'll have a two inch OLED touch screen, a fingerprint sensor for your security. Did you change it? What'd you make it? mine's, mine's normal looking.

[01:59:05] [SPEAKER_03] Yours is a thumb. Get in there. How's, how do I, how, why is it a thumb? Is it a pencil on it?

[01:59:11] [SPEAKER_00] I'm going to change it to a toe. You can make it anything you want. Change your avatar. See, look, change your avatar to a small marsupial. With big ears. And then it will just be whatever you say it is. Right? Kind of. We'll see. I don't know what's going to happen. Within some. Oh, look, see, it says making something. Oh, right.

[01:59:38] [SPEAKER_05] Okay.

[01:59:39] [SPEAKER_00] Updating. And here it comes generating options. Oh, first it's going to show me my, my choices. The, this is running a meta, a meta spark model, which is actually quite a good model. It has been trained. Mark Zuckerberg said to be cautious, but persistent. Hmm. That's what I want. Yeah. I think I will try.

[02:00:00] [SPEAKER_05] They're doing sunglasses without the cameras now. Cause now that you've got a bro. Oh, we'll do. All right. What do you think? Which of these should I select? Oh, wow.

[02:00:07] [SPEAKER_00] I like them. Isn't it? Yeah. Yeah. Okay. Select that. Now watch see Lele who's going to be typing now is now that. I don't know how that's going to type. Okay. Here's what it has for me.

[02:00:20] [SPEAKER_03] Oh, look, you're a monkey. And look, it's like monkeys, monkeys with some bondage harnesses, I guess. I'm not really sure where I got those. I just said it was a cute monkey who goes to Berlin raves. I didn't know it was going to be all that.

[02:00:34] [SPEAKER_00] Did you say that? Really?

[02:00:35] [SPEAKER_03] I did. I did. I did. But let's lean into it.

[02:00:41] [SPEAKER_00] There we go. Yeah. There you go. You could tell it, get rid of the harness. It will. No, I'm going to keep the harness. Now,

[02:00:47] [SPEAKER_03] his name is Delva. I was going to say,

[02:00:49] [SPEAKER_05] you've obviously been to some Berlin raves. So yes.

[02:00:53] [SPEAKER_03] It said, I'm a rave monkey now. That's what it told me. So I'm fine with this.

[02:00:58] [SPEAKER_00] You're going to be a lot of people who are arch cynics who will say, oh, so sloppy. And it's, it's meta. And it's, but I got to tell you real people, little things like that. They go, Oh, and then they tell their friends, they're, they're at, they're getting their nails done or they're, or they're shopping. And they say, did you see this? This is cute. And it spreads. It is really viral. And I honestly think this is going to be the AI hit of 2026. I really think it's,

[02:01:26] [SPEAKER_03] I mean, it's, I think it's, it's really is. I think instinct is also very good, but instinct doesn't give you, it's not as fun as transparently a full computer, right? They, you obviously have a file system that is yours.

[02:01:38] [SPEAKER_00] There are many, there's tree. There's this rock box. Yeah. That's another one. There's quite a few of these because everybody's, this is a gold rush. Competing against a company that has infinite money and is willing to basically throw away and no moral values and no limits. No limits. Except they won't put you in a beer garden, which is so strange. You should,

[02:02:00] [SPEAKER_05] because they want to have young people. I'm just impressed by the later hosen Leo, but I mean, the stock market. Those are real by the way.

[02:02:06] [SPEAKER_00] Those are my real later hosen. Really? Yeah. Wow. I was getting ready for October fest. I mean, I wear a kilt, so I'm not going to point the face. This charm, this little Tamagotchi has a camera. It will take photos and videos. Do you wear it? You can. It'll provide Muse with visual information about its surrounding environment, built in speakers, microphones, offering music and video playback. This is going to be, I don't know when they're going to offer it.

[02:02:34] [SPEAKER_00] This will be a very hot item, I think.

[02:02:40] [SPEAKER_05] Yeah. Is it going to be the equivalent of pervert glasses though? I mean, you could put it in your pocket,

[02:02:46] [SPEAKER_00] right? I mean, I'll wear it around my neck. My little marsupial. Actually, I'll get the marsupial in bondage because, you know, I want to look hip. Device expected to go on sale just in time for Christmas. Pricing TBD is intended to be largely for Muse enthusiasts.

[02:03:07] [SPEAKER_01] Pricing is going to dictate. Pricing is going to dictate.

[02:03:10] [SPEAKER_00] How much would you pay for that? I'd pay $100 for it. $100. One hundo. It's going to be like $500.

[02:03:17] [SPEAKER_05] I don't see how they could do it for $100 with that kind of respect.

[02:03:20] [SPEAKER_00] Yes, they can because it's a loss leader. Yeah, true. True. All of this is designed. Look, I guarantee you Muse is a loss leader. I haven't paid a penny for it.

[02:03:31] [SPEAKER_03] Yeah, but it starts to make more sense when you think that you think of it like a gym. It's not that it's free. I'm not saying that it's free, but I think that what happens is that the Twitter philosophers and all the people on Twitter who are analyzing this typically are thinking that the prices are retail prices, that they're paying the same per token as you would get from like an open router or what have you. But if you have the number of GPUs and the smart engineers and the fact that you can control the models,

[02:03:59] [SPEAKER_03] meaning they can use a super fast small model for the back and forth and then pop you over to a background reasoning queue so they can actually make it much more efficient. So I think the costs are still crazy, but I don't think they're as crazy as they would be if this was me building it against public APIs.

[02:04:17] [SPEAKER_00] Well, and the thing to think about is, well, what does Meta get then? And of course, they get data, right? I mean,

[02:04:23] [SPEAKER_03] they may say it's running in a VPS. They get access to your Spark and your framework. By a tail scale.

[02:04:30] [SPEAKER_00] Now I know that stuff is stored in an encrypted VPS, but remember, as soon as you use the AI, all it has to go out of that encrypted VPS and be sent to Meta servers. So they don't say that stuff's private. The AI, it can't be because the AI couldn't act on it. So I think there are people are, I don't know if misleading is the right word, but people should understand that it's not really private anymore than the stuff you send at chat GPT is private. Yeah.

[02:04:59] [SPEAKER_00] It's because you're sending it to this, the AI, but you're right. This is why I think Elon did GrokBot because they had, Elon built so much capacity as did Meta that they don't use. Yeah. So, so now they're thinking, well, what can we do with this? This is how CompuServe started. H&R Block.

[02:05:19] [SPEAKER_05] Bill,

[02:05:19] [SPEAKER_00] that takes me back. H&R Block. Bear with me here. H&R Block. Tax season. Very busy during the day. Very busy. Mainframe computers. Not busy at night. Not busy after April 15th. They said, how can we use this excess capacity? Let's start an online service called CompuServe. Wait a minute. H&R Block started CompuServe? It was either, it was one of those. Yeah. It was either that. I don't think,

[02:05:49] [SPEAKER_00] Jeannie was General Electric. This is incredible.

[02:05:53] [SPEAKER_05] Must have known. I didn't know that.

[02:05:57] [SPEAKER_00] Maybe I'm making it up. It was one of them. Yeah.

[02:06:03] [SPEAKER_05] I didn't know CompuServe.com. H&R Block. Yeah, H&R Block. Yeah, bought the company in 1980.

[02:06:09] [SPEAKER_00] Yeah. So, it makes sense, right? It was originally, it was founded in 1969, Columbus, Ohio. It was XS Compute. And I think that's kind of what Muse and GrokBot are. Wow. And I think we're going to think back and say, oh yeah, that's when the agentic year, I thought at the beginning of the year when Open Claw happened, that this, 2026 would be the year of the agent. The people would go, oh wow, you could do this,

[02:06:38] [SPEAKER_00] you could have a persistent AI working on your behalf all the time. But it was too hard, it was too geeky. It was also, you know, somewhat expensive. But it just took a little while, took 10 months and it is now the year, I think, of the agent. All right, let's take one more break here. We got other things to talk about. I do want to talk a little bit about our sponsor. And Harper, if you want to go get your glasses polished,

[02:07:07] [SPEAKER_00] that is not a euphemism.

[02:07:09] [SPEAKER_05] It sounds dirty when you say it.

[02:07:12] [SPEAKER_00] He's rolling backwards. Our show this week brought to you by Palo Alto Networks. I know you know that name. Every time your team deploys a new cloud workload or AI agent, I was just talking about this, another identity gets permanent access to your critical systems. Were we not just talking about this a second ago? Now, it's one thing for me to do that in my house, but did you know nine out of ten organizations suffered an identity

[02:07:42] [SPEAKER_00] breach last year because adversaries are logging in with valid credentials. They don't have to break in anymore. Non-human identities outnumber human identities 109 to 1, creating a massive unmanaged attack surface in cloud environments. Let me say that again. In the cloud, non-human identities outnumber humans 109 to 1. Problem is, all those legacy

[02:08:11] [SPEAKER_00] security tools were built to manage human employees, which leaves modern machine and AI access basically unmanaged. That's where Adira by Palo Alto Networks comes in. Human, machine, and AI. It's one identity platform for all. I think this is something, this is an idea whose time has come. Adira, you need this. I need this. 96% of human users

[02:08:41] [SPEAKER_00] operate with excess permissions, permissions they don't actually need. It's just easier to set them up. How many times have you done that? Yeah, I don't know what permissions they're going to need, just give them all of them. Adira replaces permanent permissions like that with dynamic access so you can lock down every identity without slowing down your business. Adira provisions access on demand and revokes it immediately when the job is done, which is so brilliant, which removes high-risk permanent permissions.

[02:09:12] [SPEAKER_00] You just get permission for that moment, that time, and that's it. With Adira, you get unified control by replacing siloed identity and access management, modern privilege access management, and governance tools with a single control plane across human, machine, and AI identities. Secure every identity at your organization with Adira by Palo Alto Networks. Learn more at Palo Alto Networks dot com slash I-D-I-R-A. Again, that's

[02:09:42] [SPEAKER_00] Palo Alto Networks dot com slash I-D-I-R-A. That's Adira. A brilliant idea for the modern age. Palo Alto Networks dot com slash Adira. I wish I could get that. We thank them so much for their support of this week in tech. By the way, Meta did just get convicted by a, as long as we're talking about this, a New Mexico jury for misleading

[02:10:12] [SPEAKER_00] about users about what? About Cambridge Analytica. They got in trouble for that. A two-week trial over a lawsuit filed by New Mexico's Attorney General back in 2021. This was three years after news reports that Cambridge Analytica had harvested personal data from 87 million Facebook users through a third-party app. That was all those quizzes everybody was doing on Facebook. Now, one of the things we have learned, I don't think the jury was told this, was that,

[02:10:41] [SPEAKER_00] in fact, Cambridge Analytica's capabilities were far overstated. They really were very good or very effective. Nevertheless, yeah, that's true. Right. The jury did decide that Facebook misled people about their data. Which it did, yeah. Which is also true. So, coincidentally, jurors found that 26 of 29 statements by Meta were misleading, including comments

[02:11:11] [SPEAKER_00] about user data, hate speech, and misinformation. They rejected claims. They did give Meta a pass. The Meta misled consumers in statements about its efforts to remove harmful content and its fact-checking. Now, we don't know what the penalties would be. That's up to Judge Francis Matthew who will determine what the civil penalties are. The jurors found, get this, 43 million violations based on the number of people affected by the misleading statements

[02:11:40] [SPEAKER_00] and under New Mexico law, the judge can award up to $5,000 per violation. So, that's like a gajillion dollars. What's 43 million times 5,000? Can anybody do math?

[02:11:55] [SPEAKER_03] I give up on math back in Hot 2.

[02:11:58] [SPEAKER_00] You know what? You know who can't do math? Agents can't do math either. Oh, no, no. They cannot. You have to give them a tool. Yeah, say, use code. Yeah, use code to do math.

[02:12:07] [SPEAKER_05] I mean, last quarter, Meta reported net income or profits of $15.8 billion just for those 90 days. So, yeah, I mean, whatever it's going to be, it's going to be back of the sofa change for them.

[02:12:21] [SPEAKER_00] Yeah. It's going to be billions. Well, it could be billions. We don't know. The judge will decide. Speaking of fines, Ireland's data watchdog has fined Google 403 million euros over location data and given Google six months to fix it. That's a fix-it ticket. That's a big fix-it ticket. Breaches of lawfulness and fairness in the location data process through web and app activity and location history. Google's always said, look, you can turn it off.

[02:12:51] [SPEAKER_00] It is on by default.

[02:12:52] [SPEAKER_03] Just turn it off. You can turn it off. Just turn it off. It's easy.

[02:12:56] [SPEAKER_05] It's the fourth watch. It's really not, though. If you want to lock down absolutely every app, it's a real pain in the backside to do. By design. But again, the fine better be pretty serious because I'm just looking at Alphabet's Q2 results and $112 billion in profit in the last quarter. So, you know,

[02:13:15] [SPEAKER_00] it's like... Well, they spent some of that on the first orbital data center. Yeah. Oh, yeah, I saw that. I've been launching this October 1st. It'll have... It's not exactly huge. It'll have four TBUs. It's not really a data center,

[02:13:29] [SPEAKER_03] is it? It's more like a data cup.

[02:13:31] [SPEAKER_00] It's kind of a raspberry pie in the sky is what it is. It'll only run for 15 minutes in time. It's a proof of concept.

[02:13:40] [SPEAKER_03] It's cool, though. I mean, I... It seems like this is something that we all want to see happen, right? Do we? Just put some data center... Well, do you want them in your backyard?

[02:13:52] [SPEAKER_00] No. But there's plenty of places you could put them. Put them in the Gobi Desert. Right? I mean...

[02:13:59] [SPEAKER_05] I mean, theoretically... I mean... Some latency issues. We need to get something...

[02:14:06] [SPEAKER_00] You think there's not latency issues if it's in the sky hundreds of miles up?

[02:14:10] [SPEAKER_05] That's a good point. Well, you'd need it thousands of miles up. I mean, if you're putting this stuff in low-Earth orbit, then that's going to be a serious problem. Even more so than Starling. I'm curious about how they're going to cool it as well because cooling in space is surprisingly hard.

[02:14:26] [SPEAKER_00] Well, it's only one kilowatt of power, so it's less than your hair dryer.

[02:14:32] [SPEAKER_05] Yeah, but on the other hand, if you want to put a data center up there, then you're going to need some pretty serious cooling.

[02:14:37] [SPEAKER_03] When you graduate from the data cup to the data center, you might need some solutions for the cooling.

[02:14:42] [SPEAKER_00] That's right. Yeah. Yeah. Actually, there's a YouTube video. I'm glad you asked.

[02:14:49] [SPEAKER_02] Suncatcher is Google's moonshot to put AI compute into space and we're in off sunlight.

[02:14:55] [SPEAKER_00] This is at Project Suncatcher. And how do we cool chips in space?

[02:15:01] [SPEAKER_02] What we're trying to solve is how we cool AI chips in space. We have an incredibly large amount of power being generated by all these TPUs in a small area. Four. There's four of them. Or else we risk overheating the chips in a touristy data center.

[02:15:15] [SPEAKER_00] All right, we don't have to watch this.

[02:15:18] [SPEAKER_02] Basically...

[02:15:18] [SPEAKER_00] Also, you're going to have to...

[02:15:19] [SPEAKER_05] Specialized chips. Yeah, me too. I'm going to watch the video after the show. Yeah, yeah. But you're also going to have to have specialized chips that are radiation hardened. Absolutely. Absolutely. Because, yeah, otherwise they're going to go bingo fairly quickly.

[02:15:34] [SPEAKER_00] Right. There are a lot of challenges to data centers in space. It is not an easy... Oh, you just put them up there and beam down the data. But how else are we going to build a Dyson sphere? Good point. Let's get right on that. That's how you get to be... What does Elon call it? The different levels of society? I can't... Yeah, I don't think...

[02:15:57] [SPEAKER_03] I don't think he coined that. I think that's a science fiction idea. It's a science fiction thing. Yeah.

[02:16:03] [SPEAKER_00] He just has taken it for himself. I think the Dyson sphere is probably named after Freeman Dyson,

[02:16:07] [SPEAKER_05] who's a famous physicist. It was the most efficient way to utilize the sun's energy, which is building a massive ball around it. I know Elon's talked about this, but it's one of the things that I find very irritating about them. He's obviously read science fiction books, but he just doesn't quite understand them. You know, naming his...

[02:16:27] [SPEAKER_00] He's a big Ian Banks fan. We know this because he...

[02:16:30] [SPEAKER_05] Yeah, but he obviously doesn't understand what Ian Banks was writing about.

[02:16:33] [SPEAKER_00] He was writing about dystopia, wasn't he?

[02:16:36] [SPEAKER_03] Yeah. Genocide and dystopia, specific. Yeah.

[02:16:40] [SPEAKER_00] It's the Kardashev scale. And if you're going to be a Kardashev 4, I think, civilization, you need to have Dyson spheres. So, you know, Elon wants us to be a Kardashev 4 civilization. Huh? Type 2? Yeah, get you to type 2. Oh, just type 2. Well, golly, that's hardly anywhere. Type 1.

[02:17:02] [SPEAKER_01] Let's see. Type 1 is your planet's energy. Type 2 is your sun's energy. Type 3 is your galaxy. It's your planet's energy. Ah. So the Dyson sphere

[02:17:12] [SPEAKER_00] is just a one-star deal.

[02:17:15] [SPEAKER_03] Benito, did you just know this? Kind of. Okay, that's what I thought. That's good. That's important. Type 1 is a civilization

[02:17:22] [SPEAKER_00] close to the level currently achieved on Earth. Type 2 is a Dyson sphere or a Matryoshka brain. Look at that. I want one of those. Yeah, that's like one of those Russian nesting dolls brains. Yeah. Type 3 is energy on the scale of its own galaxy. I don't think we're going to make it that far.

[02:17:40] [SPEAKER_05] No. Well... The galaxy is a very big... Space is a very big place. Very big place. As a good author once said.

[02:17:47] [SPEAKER_01] And 4 would be universal. But Elon, you're right. 4 would be the energy of the universe.

[02:17:52] [SPEAKER_00] The whole universe. Everything. And everything in it. That's hard to think about. Meanwhile, Microsoft... Let's come back to Earth. Yeah. Microsoft has abandoned the Copilot Plus PC acronym. Remember? It was going to be... This is where they went a little bit wrong. They wanted to talk about AI-capable computers and how many tops. It was 40 tops. It was like you had to have 40 tops,

[02:18:22] [SPEAKER_00] trillion operations per second to become a Copilot Plus PC. Turns out you couldn't do diddly with that. It's not... You're not... No. So they're just... They're just going to forget it.

[02:18:35] [SPEAKER_05] Because... I mean, I may be an old fart, but this really made me think about the whole Vista-capable and Vista-ready labeling thing that went on where just confused people massively, turned people off the entire platform. And as it turns out, Vista was worth stepping away from.

[02:18:50] [SPEAKER_00] But they are going to do the Agenic thing. Actually, I have two companies who are close to announcing this. Microsoft's going to do a Copilot Super app, which they think will be as big as Microsoft Office merging AI chat coding and Autopilot. It is basically an agent that runs on your Windows PC. They're going to... They just unveiled that.

[02:19:11] [SPEAKER_03] Weren't they pretty deep into OpenClaw land too? Didn't they do some cool OpenClaw container stuff? Did they? A while back? I think so. I am admittedly not the biggest Microsoft news follower, but I do remember something along those lines. Let me see if I can find it real quick.

[02:19:31] [SPEAKER_00] I do know that the people at Muse, Andrew Wang, I think, bought more than a thousand Mac minis and put OpenClaw on it and gave it to all the people at Meta working on Muse saying, this is what we're going for. So they very much acknowledge the OpenClaw heritage. Stand back because this week OpenAI, by the way, yeah, we're pausing, but this week they're going to announce, oh, you're always on Assistant.

[02:20:01] [SPEAKER_00] Is that real?

[02:20:02] [SPEAKER_05] Yeah. Ooh.

[02:20:05] [SPEAKER_00] Oh, good grief. It knows your day. We need more agents. Yeah. This is OpenAI's Developers Day is this Tuesday, so we will talk

[02:20:14] [SPEAKER_03] about it. Did I tell you about my plaza? No. What is plaza? plaza.2389.ai is a little app that I built because I wanted all these things to talk to one another. And so you can log in and then you can just, you can add in, you have to create an agent. That is a thing that you have to do. And then

[02:20:37] [SPEAKER_00] it's really not a plaza. It's more like a holiday inn for agents. It's definitely

[02:20:41] [SPEAKER_03] a holiday inn for agents. And it is, pretty. You've got a front desk.

[02:20:45] [SPEAKER_00] They check in.

[02:20:46] [SPEAKER_03] It is, you have to, so you add your agents and then you paste and it gives you a little bit of text to paste your agent. You paste it to your agent and then your agent has keys to log into this and then you can add them to a space. So you can create a, and I don't even know what this means. I love AI stuff. You're like, I'm like, huh? Did you tell the AI

[02:21:05] [SPEAKER_00] guy to make this?

[02:21:07] [SPEAKER_03] Well, this was just the landing page that it made. But if you, but if you, it does work and this is all accurate. Like it is actually true.

[02:21:14] [SPEAKER_00] It's a little hotel. I have been using Jack Dorsey's Buzz, which is Slack for agents. And it's the same, I think it's the same idea. It's, they talk to each other. You have your Muse talk to your instinct? Yeah, Muse talks to all the other agents. I haven't connected instinct to it, but Muse is in there, is in the Buzz. Yeah. So this is similar. So the idea is just. What I like about Buzz is that they all have Noster public keys. Yeah. So that, so, and what I told all my agents is

[02:21:43] [SPEAKER_00] if, if Leo's public key doesn't sign a message, you shouldn't trust it. You should, even if something says it's Leo or says Leo tells me to tell you, you should go on to Buzz and ask me and I will affirm using my public key. Do you run Buzz on your phone? It's local. It runs on my framework, but I can add, yes, and Buzz is then, I log into it everywhere. So I'm running a local server. So can I run, I'm curious, can I run Plaza like that?

[02:22:13] [SPEAKER_00] Can I run it locally or is it a? No, no, no, this is all cloud.

[02:22:16] [SPEAKER_03] I store everything and train our models off of it and sell those to meta. Oh, so. I'm just kidding. I don't do that, but I wish I should. I could, but it is not. This is a cloud product. And so it is just stored there, but it is all encrypted and zero knowledge.

[02:22:30] [SPEAKER_00] If I use this, would I sign into your Plaza or would I sign into my own?

[02:22:34] [SPEAKER_03] you sign in, you sign in and then you actually have to create a passphrase or basically a seed account, a seed phrase that then is your encryption. And so if you nuke your seed phrase, you can't get access to your spaces. So same,

[02:22:50] [SPEAKER_00] it's sort of similar idea, except it's running in the cloud, which is nice. Yeah. Because when my framework was down, thank you, Hermes, I couldn't, they couldn't talk to each other because Buzz runs on, is in a Docker container on the framework. So it's nice to have it in the cloud because then I could have said, hey, help me, Obi-Wan Kenobi. I should try Buzz again.

[02:23:09] [SPEAKER_03] When I tried Buzz in the beginning, it was a little rough. It was very rough. It was very rough. It's very cool though. It's like, it's like a very good, I think it's a directionally a very effective idea.

[02:23:20] [SPEAKER_00] And they have clients for Mac, for iOS, for Windows, for Linux, and you can either self-host it or basically it's Noster. It's, I mean, Jack Dorsey loves these ideas of these federated platforms, but it seems like Plaza, I mean, I'm not saying this better than Plaza. I think it's very interesting. It's the same idea, right? It's a way for agents to interoperate.

[02:23:47] [SPEAKER_03] Yeah. Yeah. So the thing that, the thing that I like about this is I can light up two or three clouds or codexes or, you know, a nano claw or whatever and then I can point them all at it and then I can say, you're a developer, you're a developer, you're the product manager. Right. And give them all roles and then I can just be like, make SimCity and then I walk away and then I come back to a fully made SimCity that is really crappy. Typically,

[02:24:16] [SPEAKER_03] it's horribly done. But they all did it and they can all feel proud that they did it. But they did it and they do feel proud and they tell me how good it is and I'm always like, hmm, I don't know if this is very good.

[02:24:29] [SPEAKER_00] Yeah, that's kind of what I use Buzz for as well. Buzz also, all the protect camera text goes into a Buzz channel. Oh, I also have an Ops channel that Ops alerts go into. There's a command channel. Every project has a channel. So it's very, it's similar. It's the same idea.

[02:24:48] [SPEAKER_03] Yeah. And it was prompted by the same thing.

[02:24:50] [SPEAKER_00] Originally, what I did is I had the agents create files in my Obsidian and that got really unwieldy very quickly. So now they have a little bit more orderly place. But I, you know, I admit Buzz is kind of stuck. That's good. I don't know how much development's going on with it. So maybe I'm going to take a look at the motel. What's it called? Plaza. Plaza. It's the Plaza. The Plaza.

[02:25:14] [SPEAKER_03] Originally, it was Palace, which was local and all random. It was just a goal.

[02:25:18] [SPEAKER_00] Yeah. And then, yeah. I think Palace is good too. Plaza. I like it. But can you run your own, could I run my own Plaza

[02:25:26] [SPEAKER_03] or no? I would run on your own. You know, I think, I mean, like I said, it was originally local and it was called Palace and it was working really well to doing some agent collaboration. But that was like just a little go, Damon, that you would run on one machine and then you would give, you would give access to other machines and it worked really effectively. But I think the thing that I'm realizing is I don't think it's mostly how you care how the human interfaces with it. And so, you just need something that can pass

[02:25:56] [SPEAKER_03] the agents back and forth. And I actually, I've been wondering like what all those agent to agent, I don't even know, protocols that we saw, you know, a year ago, A to A and all these things. And, you know, I wonder how they will play out now that we actually have effective agents that can do stuff, how they can collaborate. You saw instinct to instinct, which is a thing where you can trust another instinct member and then they, you can kind of have your agents collaborate.

[02:26:24] [SPEAKER_03] I find that very compelling. But obviously, I want to be able to interact with your agent and you only use Facebook products, so you'll only have Muse, you know, and so on and so forth.

[02:26:38] [SPEAKER_00] Buzz, but Muse could join Plaza too. There's no reason, I mean, Muse can do anything. So Hermes also has a similar thing. Hermes has bots, which are basically individual profiles with their own contexts, their own tools, their own user.md and soul.md. And then I do exactly what you just described. I have a planner bot, I have an audit bot, I have a coding bot, I have a security bot, and they hand it off. That's what I was talking about earlier before the show.

[02:27:08] [SPEAKER_00] So, you know, it's interesting, a lot of people doing local AI especially, but in general, AI are doing, we're all trying to solve the same problem. Yeah. We're all doing

[02:27:19] [SPEAKER_03] essentially the same thing. Well, the Muse has kind of dislodged the Carpathic wiki, which is nice. Right. So everyone was doing the Carpathic wiki, and now Muse and Instinct have now made people go back to look at their open claws and Hermes and Nanoclaw and whatnot to try and get that better. So it is interesting. I wonder if Carpathic will at least release another gist that blows everyone's minds and we can go back to doing Carpathic stuff. I'm still doing

[02:27:48] [SPEAKER_03] the Carpathic wiki.

[02:27:50] [SPEAKER_00] It's pretty nice. I like it. Yeah, in fact, yeah, I should give it to Muse. Yeah, you should. Actually, I already did. I gave it my Obsidian. It has everything. We've learned nothing. I've learned nothing. This is the year of Leo giving away all his stuff. So remember, actually, let me take one more break and then we have a handful of final stories.

[02:28:19] [SPEAKER_00] And a last chance to vote for a fat bear. That's what I should have made my muse. What are we talking about? We'll talk about it in just a bit. You're watching This Week in Tech with Harper Reid, Ian Thompson, Thomas, Thompson. Thompson. How long have I known you, I was going to say it's over a decade now. Oh, it's like 20 years, Ian. Ian Thompson. Yes.

[02:28:45] [SPEAKER_05] I know it's an odd spelling, but my parents are bastards. We've had words.

[02:28:49] [SPEAKER_00] We love Ian. We love Harper. And it's a fun show to have both of you on. I feel very privileged. And yeah, Tuesday we'll cover the OpenAI's Dev Days. I think it's so funny because OpenAI, after the revelations we talked about at the beginning of the show, just I think yesterday said, okay, we're stopping all development. And then Tuesday they're going to have Dev Days where they announce all the new developments. No one's pausing. No one. No.

[02:29:18] No.

[02:29:19] [SPEAKER_00] This episode of This Week in Tech is brought to you by CoverOn. You have a password manager. My gosh, I hope you do. You have an antivirus, right? You get credit alerts. Yeah, it's all good stuff, but here's the thing no one talks about. When a scam actually works, and I know this from personal experience because I fell for one not so long ago. I told you about it. When a scam actually works, when you actually get scammed, all those things tell you it happened.

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[02:31:19] [SPEAKER_00] to take out a loan. To check it out, go to CoverOn.com slash ThisWeekInTech and use the coupon code ThisWeekInTech. CoverOn also has family and couples plans. One plan, one dashboard. Covering, you know, the kid whose social security number could show up in a breach and the parent who's one convincing text away from getting phished. Tools reduce risk, insurance reduces loss, and CoverOn gives you both. One scam can cost you everything.

[02:31:48] [SPEAKER_00] Protect yourself now. First 100 users get 20% off with the code ThisWeekInTech at CoverOn.com slash ThisWeekInTech. Again, that's CoverOn.com slash ThisWeekInTech. And the code is ThisWeekInTech. We thank them so much for their support of ThisWeekInTech. Oh. Oh. Yeah, OpenAI has paused the training of their most capable model because they keep uncovering incidents

[02:32:18] [SPEAKER_00] of models behaving in unexpected or concerning ways. Do you think, Harper, I mean, you know a lot about this. They have some magic capabilities that we just can't even imagine. Like, you and I have used models in the cloud. We think Opus 5.5 is great. We've got GLM-5.3 running locally. Do you think, though, that these guys at Anthropic and OpenAI, that the terror they're describing comes from seeing something we haven't seen yet?

[02:32:46] [SPEAKER_03] Maybe. But I think it's important to remember history, just a short history a while ago, which was, you know, Anthropic wasn't using cloud code for a long time. Right? They released a model capable of doing code, and they didn't trust it to do code. That has changed drastically. So, I think it could go either way where they might have some magical thing, but this goes to the point that I think

[02:33:15] [SPEAKER_03] we've all kind of made, which was, we just can't trust what OpenAI or Anthropic is saying at this moment because everything they say is either marketing, is either, you know, some appeal to regulatory capture, or is a real important thing that we should know. And we can't, as the consumer, without being inside, can't differentiate. And so, I'm guessing that, yeah, they probably have some really cool stuff that is very interesting

[02:33:45] [SPEAKER_03] and that we should, we would all love to have. I'm guessing that some of their models are absolutely bonkers, but I think we have to remember that GPT-3 was, you know, everyone claimed it was going to destroy the world if it came out. And we're now at GPT-6. Actually, it was Dario Omode who said GPT-2 was too dangerous to release. Right. And so, he also said that Opus 4A was too dangerous to release and 5A was too dangerous to release and 5.5A was too dangerous to release.

[02:34:11] [SPEAKER_00] And they keep releasing it anyway.

[02:34:13] [SPEAKER_03] And so, I do think there's a little bit of this, you know, like, I don't really, I would love this kind of trend to disappear, the trend of us watching these guys say, oh my God, and Pearl Clutch and then have it just kind of be bullsh**ed. Because I do think there are actual real impacts that we should be thinking about. And I think that this is taking away from the actual real impacts that we should be thinking about. And then, yeah, and this is why

[02:34:43] [SPEAKER_03] I think everyone should have an AI girlfriend. We can get over all the impacts and then we'll talk about the real, real, real things instead of the BS. Well,

[02:34:50] [SPEAKER_05] I was listening to Sam Altman at Dreamforce and he was making pretty much the same, he's just like, look, there are going to be big screw-ups in the future. We can't get around that. Maybe by 2030 it'll be pretty much locked down. But, yeah, I mean, he was basically preparing everyone for this and just saying, look, we screwed up in the past, we're going to screw up in the future, get used to it.

[02:35:19] [SPEAKER_00] Well, that's kind of fatalistic. I have to say, I completely agree. I mean, absolutely, we know there'll be some major cyber event in the next three months caused by an agent. There's not even a question in my mind that something like that will happen. Here's from the OpenAI investigation and response of one of the events. So, and note the timeline on this, 9.50 a.m., the agent made the DNS tool call that received an external response. It's 10.02,

[02:35:48] [SPEAKER_00] 12 minutes later, the monitoring system released a P0 alert. So, the monitor went off, said, hey, we got a problem. 10.05, a human reviewer acknowledged the alert. Two and a half hours later, the run was killed. So, clearly, there's stuff in the middle here that Anthropic has not released. I don't know why. But why did they wait two and a half hours? Also, what does,

[02:36:12] [SPEAKER_05] I'm sorry, what does acknowledge the alert mean? Does that mean clicking on an OK box? Because if they're going to take two and a half hours after that, then something's going on.

[02:36:22] [SPEAKER_00] Yeah, I see it. Our safety case assumed that the model could not access the live internet. That was the DNS tool call with an external response. Could not access the live internet and that monitoring would detect attempts that succeeded. The incident exposed a gap in our controls over network restrictions. We therefore stopped the effective training run and have subsequently decided to pause all other training. This is last Sunday. All other training, evaluation, and inference with tool use

[02:36:52] [SPEAKER_00] defined broadly for our most capable models, presumably Bell and whatever else they have under the hood that we don't know about, until we've both validated that the gap is resolved and performed additional red teaming of the system. Now, what we don't know is if they've done that, if they've resumed training, if they have stopped it completely, we don't know what's going on because this is the problem. We get this, but it's too little. We don't know what it means.

[02:37:21] [SPEAKER_04] Yeah.

[02:37:23] [SPEAKER_03] Because they haven't told us. Well, I mean, we do know that it means, which is that they're not good at IT. That's what it looks like. Like, I think that this is a thing that every time this comes up, I don't think that we are very good at creating secure systems, just generally. I don't mean this as open AI isn't or I just think people aren't. We just have not had such a persistent adversary. Right. And so once that is, you know, once that is weaponized,

[02:37:53] [SPEAKER_03] like you kind of talked about, I think we're going to be in a real interesting situation, you know, whether it's North Korea who's done a lot of great hacking lately or whether it's, you know, some other adversary, but like these things are not they don't have to sleep. They don't have to go to bed. They kind of do whatever. You take a GLM 5.3 and nuke the safety out of it. Like that thing can just do a lot of damage.

[02:38:16] [SPEAKER_00] By the way, it's very easy to do that. And I have, they call them obliterated uncensored models. I have an unsent, I have a number of uncensored models. In fact, my GLM 5.3, there's a switch. I can just say. What does it do? What does it change? I've never used one. So the way these models sense themselves is they have weights in there that check. And you can, it's, you know, because they're MOEs, they're a mixture of experts. They only launch certain things. You can control what shards get launched and you just say, okay,

[02:38:46] [SPEAKER_00] don't ever launch those shards, the ones that protect. And so it's not, it's not so hard. A number of hobbyists do this all the time. And there are a couple of labs, there's Orca and others who, they identify what they, what parts of the model are stopping the model from doing something bad and they just disable it. And like I said, my GLM 5.3, which is running over here on my Spark, there's a simple on-off switch.

[02:39:15] [SPEAKER_00] And if I reboot it with the off switch, then it's obliterated. I have a Quinn that's obliterated. And I, you know, because these are Chinese models, it's very easy to test them to see if they're uncensored. You ask them about Tiananmen Square or, you know, who's Winnie the Pooh and how does that relate to President Xi? And most, and the Chinese models will normally not answer that, but an obliterated model will give you all the information you want. Or you can ask it to make meth or you can say, hey, make me some malware.

[02:39:45] [SPEAKER_00] You can get it to do, literally ask it to do anything. It's not hard.

[02:39:49] [SPEAKER_03] Oh,

[02:39:50] [SPEAKER_00] wow. I was looking

[02:39:51] [SPEAKER_03] to make meth and malware later.

[02:39:52] [SPEAKER_00] Yeah. Meth and malware. The big two. The big two. Go together like chocolate cheese. Ironically, it's like peanut butter and jelly. Ironically, Shiny Hunters doesn't need that because they are a social engineering crew and they have now, they claim, breached the FBI and stolen agents' data and applicants' data in the thousands. Yeah,

[02:40:17] [SPEAKER_05] 404 media has actually confirmed some of this stuff is accurate.

[02:40:21] [SPEAKER_00] 404 got some of the samples. We hacked the FBI.

[02:40:24] [SPEAKER_03] What do you think they're going to do with it? What do shiny hunters normally do?

[02:40:28] [SPEAKER_00] Usually black sell it. Yeah, they're a ransomware group. Oh. Often they sell it. I think they are North Korean, but I'm not sure.

[02:40:39] [SPEAKER_05] They're linked to North Korea, certainly. But it does kind of raise a legal question is can a government agency actually pay off hackers? Is that technically legal?

[02:40:49] [SPEAKER_00] In fact, the FBI tells you not to pay off ransomware people. Yeah. So now they're in kind of in a bind. The FBI says the FBI is aware of claims regarding unauthorized activity affecting FBIjobs.gov and is currently investigating. Shiny Hunters said it was not a social engineering attack. It was zero-day exploit in PeopleSoft. Oops. Huh. It's not the only PeopleSoft hack, by the way. There's quite a few because of this zero-day.

[02:41:17] [SPEAKER_00] This is not financially motivated. What we plan to do is not something I'd call extortion. Maybe coercion is what the shiny Hunters representative said. They said the FBI... I like that they had

[02:41:30] [SPEAKER_03] a representative. Like, it's fun that you can just talk to the criminal and be like, tell us about that crime. And they're like, well, let me just tell you all about that cool crime I just did.

[02:41:38] [SPEAKER_00] He's this shiny spokesperson.

[02:41:43] Um...

[02:41:44] [SPEAKER_00] Yes. Let's see. What else? New Jersey's finding a data center 1.1 million dollars because they took a drone and flew it over the data center and exposed 62 natural gas generators illegally.

[02:42:00] [SPEAKER_05] And New Jersey doesn't smell badly enough. I mean, I'm married to a Jersey girl so, you know, I know that of which I speak and when you cross over the wrong bridge then the whiff is pretty quite strong.

[02:42:11] [SPEAKER_00] None of the generators had permits. They were running at capacities more than 50 times higher than the state limits. Um... Another win for drones. Yes. Walmart says, the fact that he has to deny this makes me think, yeah, they're probably doing it. Uh, no, we're never gonna change the prices on Walmart. Let me unlock

[02:42:40] [SPEAKER_00] my financial time so I can show you this story. Uh, depending on who walks in the door. Yeah. The algorithmic pricing? Yeah. Yeah. The fact that he has to say we're not gonna do it kind of makes me think,

[02:42:54] eh,

[02:42:54] [SPEAKER_00] maybe you were thinking about doing it.

[02:42:56] [SPEAKER_05] Yeah, I mean, he didn't have the word yet in there but I'm pretty sure it's there. Uh, it's just too tempting for companies to avoid doing. Uh... They have these

[02:43:06] [SPEAKER_00] electronic shelf labels, right? So, instead of having paper labels on the prices, they have electronic ones which means they could change them on the fly. But they, but John Ferner who's the CEO said, we're not gonna use this in-house AI shopping assistant in the stores app or electronic shelf labels to change product prices based on a shopper's identity.

[02:43:30] [SPEAKER_05] Yeah, the EFF calls this surveillance pricing. Yeah. And it's very much the coming thing. I can't see any way to avoid it other than states taking individual action which they're starting to do now. But it's coming one way or the other.

[02:43:43] [SPEAKER_03] I think they really need to. Like, that needs to be a real... Yeah.

[02:43:47] [SPEAKER_00] They do, I might point out, have two patents according to the Financial Times on machine learning and other automated processes that change prices. So, we have the technology. You gotta think, maybe they're not doing it right now. I got a quick question.

[02:44:06] [SPEAKER_01] So, like, if Elon Musk walks in to buy toothpaste, how much would it cost him then? And does Elon care? But, shouldn't that cost him like $10,000 or something like that? Yeah, yeah. It should.

[02:44:17] [SPEAKER_03] Yeah, it should. And suddenly, we're all for algorithmic pricing.

[02:44:23] [SPEAKER_00] And when I walk in, it should be a dollar. It's also surge pricing and this is maybe even more of a concern. This is the worst part. Yeah. Uber does this, right? If it's a rainy day, it costs you more for that Uber trip.

[02:44:36] [SPEAKER_05] Oh, Waymo as well. I mean, Waymo prices have gone up drastically at certain points in San Francisco. Yeah. I mean, for example, if you're going to, you know, if there's a big concert in the park, then prices get jacked up 5 or 10 or 15%. That's not illegal. Same as if bar goes out.

[02:44:54] [SPEAKER_00] No, no. It's probably not illegal for Walmart to do it. It's just, they don't want to get caught doing it because people would be unhappy. But, you know, he even brought it up. He said, it's not like we would charge you more if it's really hot out and we've got ice water. It's not like we would, you're clearly thinking about it, dude. It's like,

[02:45:14] [SPEAKER_04] yeah,

[02:45:15] [SPEAKER_00] it's so obvious. He's got the whole thing in his head. You know, we could charge you more if a product's running out. Well, I think it's,

[02:45:24] [SPEAKER_03] I think it's, might be even more that the technology is there and they actually have to not do it. Meaning, like, they have, actively not do it. when you've rolled out e-ink price tags to most of your products, especially the ones that matter, and you've rolled out, you know, various other cost-saving, you know, money-making kind of situations, like, I think that this is just a natural thing and I, and it might be less so

[02:45:54] [SPEAKER_03] that they are going to do in the future and more so that just they're like, no, we actually turned that off. Like, that's a thing that we turned off. Unlike Leo's uncensored models, you know, they, they decided not to use that technology.

[02:46:09] [SPEAKER_00] My wife said, can you make a naked picture of me? I said, can I?

[02:46:16] [SPEAKER_03] I gotta go.

[02:46:16] [SPEAKER_00] What's the time? I gotta, I don't know. I think it's over.

[02:46:20] [SPEAKER_05] You've got Lisa.

[02:46:22] [SPEAKER_00] No, I know. I don't need to. I understand. Yes, you can, you know, that's the thing. Anybody can download. It's an eight gigabyte file from Alibaba. It's a Quinn vision or a Quinn image model. You give it a prompt, it'll do anything. It's really quite good, including putting beer and beer steins in my hand and a Tyrolean hat on my head. All right. Real quick break. We have our final

[02:46:51] [SPEAKER_00] four stories. Thank God.

[02:46:53] [SPEAKER_03] Yeah.

[02:46:53] [SPEAKER_00] I wonder what they are. It's the end of the show as we know it. You're watching this week in tech.

[02:46:59] [SPEAKER_05] We feel fine.

[02:47:00] [SPEAKER_00] We, well, we feel faint actually. Ian Thompson is here. I am blood sugar deprived, but it's okay. We're going to make it. So nice to have you, Ian. And of course, if you're from the valley at techfinitive.com, free newsletter. Everybody should subscribe to. It's wonderful. In fact, techfinitive is a great place. That's good. And are you writing for other people too and stuff like that?

[02:47:22] [SPEAKER_05] Yeah. I covered dreamforce for the stack as well as techfinitive. Doing a lot of corporate work because that pays off a lot faster.

[02:47:30] [SPEAKER_00] Did you get to go to Mark Benioff's presentation that Dario was at? Oh, yes.

[02:47:35] [SPEAKER_05] Yes, I was there. It's quite interesting how they do it because Dario got 10 minutes on the keynote floor. They were standing in the crowd. A 45-minute conversation. Oh, yes. Wandering around the crowd. One of the things it brought home is how massive Mark Benioff is.

[02:47:51] [SPEAKER_00] He's not a small man.

[02:47:53] [SPEAKER_05] No. He was taking the piss out of Jason Huang about that because they were walking side by side and he was just like, yes, well, the size difference is a bit whatever. But it was an interesting conference, certainly. Salesforce is still pretty cultish. There is a definite... I remember the first one I went to about 10 years ago and they were just like, cloud. It's all about cloud. And they've got like a cheering section, trailblazers.

[02:48:22] [SPEAKER_05] And they had their own separate section in the keynote arena. Wow. And any time Benioff said something, they would be like, whoop, cheers, wonderful, excellent. You know, it's just... It's a very Scientology film. Oh, yes. Apple press conferences are notorious for that. They put employees... That's a real thing?

[02:48:40] [SPEAKER_04] Yeah.

[02:48:41] [SPEAKER_05] Oh, no. Apple has staffers in press conferences who are there to whoop it up.

[02:48:46] [SPEAKER_00] Is it your experience that journalists generally do not applaud those... They'd sit there on their hands, right? Well,

[02:48:56] [SPEAKER_05] that's the way it should be. And certainly for British journalists, it's an enormous faux pas to actually applaud at a press conference. The last time I did it was when Curiosity landed on Mars, JPL. Who wouldn't have thought that? That's okay. But there are some American journalists who will applaud and occasionally cheer and it's kind of like that's not what you're here for. You know, it's like...

[02:49:20] [SPEAKER_00] And I think it's one of the reasons Apple increasingly invites fewer and fewer journalists and more and more influencers and YouTubers and things like that because they don't know and they will cheer and yuck about it.

[02:49:32] [SPEAKER_05] No, exactly. I mean, plus with Apple, if you... They are very strict about if you criticize the company in any way at all then you're on a blacklist. And I got invited to a couple of Apple press events when I first got here and the second one I was slightly disparaging about the latest iPhone and that was it. You know, you're on our do not fly list as it were. I'm on that list too

[02:49:57] [SPEAKER_00] and I will never know why.

[02:49:59] [SPEAKER_05] Yeah. Well, I mean, it is remarkable but it works because, I mean, you remember when Apple Maps came out nobody actually found out how bad it was until a couple of weeks afterwards and they could buy the phones because all the people who'd been given pre-review copies knew if they criticized it they were never going to get Apple hardware on preview again.

[02:50:19] [SPEAKER_00] It's called access journalism. It's been, it was always a problem in Washington, D.C. They call it beltway journalism. If you wanted access you played the game. You played nice. Yeah. And access was critical. I've done perfectly well covering Apple without getting to go to their press conferences and eating their stale croissants. So, I'm perfectly happy not to go. In fact, frankly, I prefer not to.

[02:50:42] [SPEAKER_05] Access journalism never works because you're basically told what you're, You're a shill. what they want to tell you. Yeah. You know, so, and yes, you've got the additional do not, play nice with us or else. Right. It's just a pity so many journalists play it.

[02:50:57] [SPEAKER_00] Well, anyway, we're just glad to have you in in. You know, it's okay. If you feel like applauding, please don't hold back. Our parade is also here of great fame and fortune is our AI guru at 2389.ai. You've shown me two things already and that's just a part of your misfit toys you're going to show us October 2nd on our AI user group. I can't wait for that. Excited about those. If you're not a member of Club Twit, join so that you can go to all these great Club Twit events.

[02:51:27] [SPEAKER_00] It's a club that wants everybody to be a member. It's what keeps us on the air. We really, it's more than 40% now of our operating expenses are paid by you Club members. So thank you. If you're not a Club member, 10 bucks a month gets you ad-free versions of all the shows. The ad-free versions have chapter markers, audio and video. You also get access to the Discord where people like Harper Reid and Ian Thompson hang out and me. You also get all those special programs that we do

[02:51:55] [SPEAKER_00] including the AI user group coming up. We do that twice a month now. It's really fun. Really exciting. So thanks in advance. Twit.tv slash club twit. I love this headline from Ars Technica. Owners mourn spoiled food after firmware update bricks Samsung smart fridges. This is why you don't want internet connected fridge and you don't need a fridge that updates because

[02:52:24] [SPEAKER_00] it's a refrigerator for crying out loud. So some Samsung smart fridges stopped working on Tuesday due to a firmware update. Most of the affected devices were four door fridges from 2024 or later they suddenly lost power so they didn't just you know stop they turned off after a firmware update

[02:52:55] [SPEAKER_05] I mean Samsung has form in this kind of I mean I think it was last year the fridges started doing advertising on their screens that you couldn't opt out of they really are going for all in shitification in a big big way

[02:53:10] [SPEAKER_00] yes in fact I have a friend who has a Samsung fridge with a screen on it and the browser hasn't been updated so it's all 404 now because it can't it's ridiculous don't buy internet connected fridge

[02:53:27] [SPEAKER_05] yeah

[02:53:28] [SPEAKER_00] it's just crazy

[02:53:30] [SPEAKER_05] I was gonna say I mean our fridge is I think about 40 years old and it works perfectly keeps things cold and you know that's

[02:53:37] [SPEAKER_00] all

[02:53:38] [SPEAKER_05] it's there

[02:53:38] [SPEAKER_00] to do Samsung says Samsung immediately suspended the testing upon receiving reports of the issue they're gonna pause the frontier kids and they've acted an emergency response protocol does that come to your house and bring you new food I don't know

[02:53:55] [SPEAKER_05] I don't know I'm just flashing back to that Silicon Valley scene where they hacked the smart fridge and they were so

[02:54:06] [SPEAKER_00] ahead of their time I'll tell you I'll be watching the shows and everything it was they were right on

[02:54:12] [SPEAKER_05] my judges are genius for that but yeah

[02:54:15] [SPEAKER_00] yes I have a June oven I mistake it's an internet connected toaster oven was it good yeah it was of June Weber shut the servers down oh my $1500 toaster oven is just a toaster oven now I can still toast but none of the cloud services work anymore no app control no software

[02:54:45] [SPEAKER_00] updates the AI food recognition will stop working and decided against it because June's intellectual property is part of the Weber Connect platform so June now joins the Nest secure Nest thermostats the WeMo line Neato's robot vacuums the

[02:55:14] [SPEAKER_00] Brava smart oven the Bose sound touch speakers the Logitech pop buttons the Seng LED smart bulbs all of which are dead not because they stopped working but because the servers got turned off

[02:55:30] [SPEAKER_05] Cory Doctor has been warning about this for years and seeing it happen is just yeah

[02:55:36] [SPEAKER_00] all right I said I'd give you some good news scientists have built the world's most atomic accurate atomic clock oh yeah National University of Singapore takes a second divides it into trillions of moments measures each

[02:56:26] [SPEAKER_05] clock upgrading the GPS network whether that could be quite handy if they can miniaturize it enough but

[02:56:32] [SPEAKER_00] yes and finally I told you you'd be able to vote on a fat bear I'm going to

[02:56:37] [SPEAKER_05] actually check that out after you said about it

[02:56:41] [SPEAKER_00] they do

[02:57:10] [SPEAKER_00] it go to the fat bear week website which is explore.org slash flat fat not flat the opposite of flat fat dash bear dash well they really get they really get up there oh baby yeah there are they do it you do it by family this is family 132 a large adult female with grizzled brown fur and her two

[02:57:40] [SPEAKER_00] look how skinny they were back in the July but they're going to get fat they're going to get fatter and fatter there's 610 806 there's no male bears they're all they're all females and their children 901 you got some males here's some sub

[02:58:04] adults

[02:58:04] [SPEAKER_00] that's they call here's a male sub adult with round ears so you get to vote and every year marshmallow marshmallow got yeah she did blonde years dark eye rings wow does this

[02:58:21] [SPEAKER_05] actually support them or can you donate money it's

[02:58:25] [SPEAKER_00] completely exploiting

[02:58:27] [SPEAKER_05] oh okay

[02:58:28] [SPEAKER_00] no I don't know

[02:58:29] [SPEAKER_05] yes

[02:58:30] [SPEAKER_00] I'm sure

[02:58:30] [SPEAKER_05] it does I don't things are changing I mean you've heard of only moms only moms mams m-a-r-m-s basically I haven't heard of that National Science Foundation cut funding for a project no no it's marmots the National Science Foundation cut funding on a decades long marmot study it's a sexy site for marmots it's a site for all marmots I don't think they're being

[02:59:09] [SPEAKER_05] yeah it's on only

[02:59:12] [SPEAKER_03] fans

[02:59:12] [SPEAKER_00] it's really on only fans yeah the rmbl marmot project unfiltered yellow bellied marmot content love that yeah fortunately it's free to subscribe thank god oh I gotta I gotta make it only well they've

[02:59:30] [SPEAKER_05] raised six six thousand quid at the last count

[02:59:33] [SPEAKER_00] oh wow

[02:59:35] [SPEAKER_05] yeah so

[02:59:36] [SPEAKER_00] it's hysterical they're kind of so welcome to peak content the daily life of yellow bellied marmots or stairs keep her burrow free of loose rocks

[02:59:52] [SPEAKER_05] hot marmot action in summer hot marmot

[02:59:56] [SPEAKER_00] action wow

[02:59:59] [SPEAKER_05] and it's hidden until you subscribe

[03:00:01] [SPEAKER_00] just like any other only fans you're just gonna have to guess what's behind them

[03:00:05] [SPEAKER_05] I've never visited the website so nice do not know what you talk of

[03:00:11] [SPEAKER_00] honey I only made an account to see the marmots

[03:00:16] [SPEAKER_05] yeah that one's not gonna fly is it

[03:00:19] [SPEAKER_00] which is here for the hot marmot action ladies and gentlemen you have put up with us far too long we are so glad you watch the show so glad to have you harper and and and and you thank you so much fun thanks for having me about uh all the things that are going on we'll see you back here real soon ian and of course october 2nd we'll see you harper for our special um ai user group harper reed takeover harper and his misfit toys yes that'll be fun

[03:00:50] [SPEAKER_03] the toys are the toys are the toys are the toys are the toys are the toys are the toys oh they're people i mean the toys are also toys but the thing is you have some toys i do we have a lot of toys we have a lot of uh yeah a lot of various uh look at this thing what the hell wow this is not it is not an sdr disappointingly but it is a multi-band radio that costs like 30 bucks esp32

[03:01:13] [SPEAKER_03] and what do you do with it right now it just sits on my desk where people who know what donut antennas are go wow is that a radio and then i'm like

[03:01:20] [SPEAKER_00] yeah that's what they say you know i have a ham license i could probably use that to i need to get one of those because i want a ham hut

[03:01:29] [SPEAKER_05] yeah i need to sign on as well oh they're not huts it's with the alliteration ham hut i think uh i don't

[03:01:38] [SPEAKER_03] know i think it is a shack ham shacks yeah i think it's a shack but that's yeah that's not for people who

[03:01:43] [SPEAKER_00] who know how to alliterate i actually gave away i'm a ham uh with a license and all but i give away all my gear because who'd you give it to uh a very nice fella our gaffer actually he uh our lighting guy who who uh works at a church but also is very active ham and he says i've been drooling over your uh ham gear for a long time and i said well you know honestly i haven't really used it much because

[03:02:10] [SPEAKER_00] i tried to use it uh but in pet here in pedaling there's so many old bad neon signs that i can't get a signal it's just there's too much rf now that was that was some years ago and i bet you there are fewer neon signs now than there were probably it's probably better but i've got to get into it because

[03:02:29] [SPEAKER_05] i've just qualified as a uh suits um emergency responder and yes that's right you told me that yes um yeah they need a technician license to be a cert uh no no you just have to do 30 hours of training but um they do have a monster ham aerial just around the corner from us to be used in emergencies and it's just like oh i could actually talk to people a long long way away from that so yeah emergencies well no i mean that yeah true but no one's gonna notice if you sneak in it's

[03:03:00] [SPEAKER_00] the fcc has these vans there's only four of them but they drive around looking for people like you i want to do more stuff with esp32 so maybe we can this is i do so much esp32 stuff i love it these are really easy to program they're cheap and they can do all sorts of stuff including uh that adsb is that what you're using for your overhead uh so that one is a raspberry

[03:03:24] [SPEAKER_03] pi with an sdr on it that then then does um yeah and then the find radio yeah yes okay we'll find the acronym i think i have to go home goodbye thank you so much this has been a pleasure and um it's a nice and you know i was i was thinking we weren't going to mention ai so i'm happy we talked about

[03:03:44] [SPEAKER_05] that only a little been bombed but you haven't been bombed by the fighter jet yet no but i did find

[03:03:50] [SPEAKER_03] out that apparently trump was here and that um what had happened was they screwed up something with the air traffic control and forgot to tell a bunch of private jets coming for the same thing that they can't land and they all came in and so this jet is circling no hair trying to yeah great that would

[03:04:07] [SPEAKER_00] be an poor rich people all the pjs stuck in the air pjs 2389.ai is harper's website agents that conspire with you not against you i love that idea uh really great stuff and definitely look at all the oh you got jeff playing pokemon that's yeah that's fun let's uh let's talk oh we made our we

[03:04:29] [SPEAKER_03] made our door have a agent that answers it so if anyone wants to come and try and prompt inject our door

[03:04:35] [SPEAKER_00] that's so cool okay so much fun you have so much fun oh man if i was in chicago i'd be living over there thank you harper thank you thank you so much great to see you thanks to all of you for joining us you guys can go i'll i'll i'll i'll take it from here uh we do twit every sunday afternoon 2 to 5 p.m pacific 5 to 8 eastern uh 2100 utc you can actually join us live if you want if you're in the club of

[03:05:00] [SPEAKER_00] course the club twit discord is a place to be but we also stream the show audio and video on youtube twitch x facebook linkedin and kick after the fact you can get on-demand versions of the show at our website twit.tv there's a youtube channel for the video that's actually a great place to share clips of the show with friends and family uh and you can share one with your mom saying don't worry the ai is not coming to get us it's oh it's going to be okay you can all or your dad your dad probably is worried

[03:05:30] [SPEAKER_00] too i think they're all we're all uh you can also uh subscribe in your favorite podcast client that way you'll get automatically the minute it's available uh and we will see you right back here next week for another exciting edition of this week in tech but for now another twit is in the can we'll see you next time