Intelligent Machines 880 transcript

Please be advised that this transcript is AI-generated and may not be word-for-word. Time codes refer to the approximate times in the ad-free version of the show.

Leo Laporte [00:00:00]:
It's time for Intelligent Machines. ParaSmart knows here, Jeff Jarvis. A great guest, Nate B. Jones, will be joining us to talk about AI. He's one of the best on YouTube to, to break through the hype. We're gonna ask him about this amazing story. Hugging Face says OpenAI's unannounced AI broke in and hacked it autonomously. That's coming up next on Intelligent Machines.

Leo Laporte [00:00:27]:
It's starting to get weird. Podcasts you love, From people you trust. This is TWiT. This is Intelligent Machines with Jeff Jarvis and Paris Martineau, episode 880, recorded Wednesday, July 22nd, 2026. The beans are in the mail. It's time for Intelligent Machines, the show where we cover the latest in AI, robotics, and all those smart doohickeys like my HyperCube behind me here, surrounding us day and night.

Paris Martineau [00:01:01]:
I am so pleased to see Paris Kara Smartnow, still here.

Leo Laporte [00:01:05]:
She hasn't given up on me yet. Investigative journalist at Consumer Reports.

Paris Martineau [00:01:10]:
I'll never give up.

Leo Laporte [00:01:12]:
The cyclospora has not stolen you away from us.

Paris Martineau [00:01:15]:
It's true. It's trying though.

Leo Laporte [00:01:17]:
Yeah, it's very trying. And also here, of course, the wonderful Emeritus Professor of Journalistic Innovation at the Craig Newmark Graduate School of Journalism at City University of New York. Craig Newmark!

Jeff Jarvis [00:01:30]:
Craig Newmark!

Leo Laporte [00:01:34]:
Author of many books, including Hot Type, which emerges from the press in mere weeks.

Jeff Jarvis [00:01:39]:
Next month, I mean, yes.

Leo Laporte [00:01:41]:
At jeffjarvis.com. We are— we have lots of news to talk about, but I think we have the right person to talk about it with. Normally, I was telling Nate this, our guests, we interviewed them and their interests. And, you know, today we're going to talk about the AI news. He is one of the foremost commentators on AI. I watch his YouTube channel daily. Nate B. Jones is—

Jeff Jarvis [00:02:04]:
I want to get credit here. I want to get credit. Where did you learn about Nate B. Jones?

Leo Laporte [00:02:07]:
I learned about it from the wonderful Jeff Jarvis.

Jeff Jarvis [00:02:10]:
You did indeed.

Leo Laporte [00:02:10]:
He said one day, did you see—

Jeff Jarvis [00:02:12]:
You gotta watch this guy.

Leo Laporte [00:02:13]:
You gotta watch this guy.

Jeff Jarvis [00:02:14]:
And subscribe.

Paris Martineau [00:02:14]:
And the rest is history.

Leo Laporte [00:02:17]:
Nate, it's interesting. Nate's story is kind of interesting. You grew up overseas. Where was that?

Nate B. Jones [00:02:26]:
I grew up in Indonesia and the Philippines. I remember the first time I saw a television. So the journey to AI has been very much a big leap for me.

Leo Laporte [00:02:34]:
Wow.

Leo Laporte [00:02:35]:
Uh, you were a head of product for Amazon Prime Video. So, you know, in fact, one of the things I really like about you is your, your presentation is excellent. You know how to talk to the camera, you know how to deliver. Uh, and maybe that's because you worked at Prime Video, I don't know. But, uh, unlike a lot of YouTubers, you're really good with the, with the camera.

Nate B. Jones [00:02:55]:
I think I just have fun, like, talking. It's funny, I started talking about AI in like around the COVID era. And I was like, well, what do I do? I have a little bit of spare bandwidth. I should start talking about, you know, I, I did machine learning at Amazon, uh, and there was these LLMs. I was just gonna talk and video just felt so natural for me. It felt like I was just talking and I could connect with a friend. And I think that's where sort of that, that maybe that dynamic vibe comes from. It just, it feels like a personal medium for me.

Leo Laporte [00:03:21]:
Jeff discovered you on TikTok and those TikTok Shorts are great, but the longer form YouTube, uh, videos are a must-watch. And then there's also a Substack which people can follow. And I've been talking about you for a while. I adopted OpenBrain as my memory.

Paris Martineau [00:03:35]:
Oh, nice.

Leo Laporte [00:03:35]:
Yeah. I use Hermes as my agent, but I started using OpenBrain with Claude code and later modified it to work with Hermes. He is really great on talking, not in hype terms. That's one of the problems I have with the YouTubers. There's a lot of hype. And you always wonder, you know, who's stroking who? Nate's great. He just tells it like it is.

Jeff Jarvis [00:04:03]:
Nate does it. He makes it. And I love that about that.

Leo Laporte [00:04:05]:
Yeah. And if you want to just kind of get a sense of what all this means, great commentator to go to. So that's why I'm thrilled that we have you today. Because man, what a week this has been.

Nate B. Jones [00:04:18]:
It's really good timing, right? We didn't know this when we scheduled it, but we have this on the calendar and it feels perfect given everything that's been going on.

Leo Laporte [00:04:25]:
So I got to start with the Hugging Face breach because this developed in a way that was kind of unpredictable. Hugging Face said, we were breached. And then they said, well, wait a minute. Looks like we— wait a minute. What's going on here? We were breached by an autonomous AI agent system.

Leo Laporte [00:04:47]:
Yep.

Leo Laporte [00:04:48]:
And then they said, and we couldn't fix it because the AIs we were using, Fable and Sol, had too many guardrails and wouldn't let us do cybersecurity. So we went to a Chinese model, GLM 5.2, to get it fixed. And then they said, and it was OpenAI that did it. And then OpenAI said, yeah, it was.

Jeff Jarvis [00:05:08]:
Yeah, they didn't confess, they bragged.

Leo Laporte [00:05:11]:
Oh, look what we did. That's the first question I'm so glad I, I can ask you, Nate, because how much of this is marketing and hype from OpenAI?

Nate B. Jones [00:05:19]:
So I think that the reason we even ask that question is because of the whole storyline with Mythos and Fable a few months ago, where Anthropic trots out Mythos and says— it's sort of scare marketing, right? This is the scariest thing since sliced bread. This is like an atomic weapon. We're all terrified. The Treasury Secretary calls in a bunch of bankers and says, this is legit. It's really scary. And I saw that narrative unfolding, and everyone was like, Anthropic has got to be marketing. But Look at how that unfolded for them. I talked to some of the guys at Anthropic.

Nate B. Jones [00:05:55]:
By and large, the folks I talked to are not super happy about how that whole thing went down because effectively they lost control of their own launch. Fable got rolled back for an unpredictable amount of time. They then had to put Fable back out. And by the time they put Fable back out, there were other frontier models. So they lost their sweet spot where they were the best, most amazingest model for a few weeks, which is what you really want. And so that may have been— that may have been a goal of theirs to emphasize their capability in a way that was sort of a, hey, look what I can do. It didn't go well for them. And I think that when I look at OpenAI in this situation, I don't think it goes well for them if they keep pursuing that path.

Leo Laporte [00:06:39]:
Right.

Nate B. Jones [00:06:39]:
If they make this a deliberate thing, I don't think it's a good approach. What I know and what I've seen so far, it looks like they are trying to put the best face they can on something that wasn't supposed to happen.

Leo Laporte [00:06:53]:
So they have 2 models. One is SOL that's public, but there is also a model they haven't released. By the way, that model, related story, solved with a counterexample a famous mathematical problem, the Jacobian problem, just right before—

Nate B. Jones [00:07:10]:
Yep, during the World Cup final, apparently.

Leo Laporte [00:07:14]:
Yeah, and then the same unreleased model apparently broke I don't even understand what this means. Broke— it didn't break out, but it did break into Hugging Face. Right.

Paris Martineau [00:07:26]:
So it broke out of the sandbox, the testing environment.

Nate B. Jones [00:07:29]:
It certainly broke out of the sandbox.

Leo Laporte [00:07:31]:
It was trying to solve—

Paris Martineau [00:07:32]:
This is also not the first instance of this. Didn't another OpenAI model break out of a sandbox to order a sandwich?

Leo Laporte [00:07:40]:
No, you're thinking of— and this is— and that was a marketing ploy. That was— okay, go ahead. I'll let Nate tell that story.

Nate B. Jones [00:07:47]:
Yeah, there were—

Leo Laporte [00:07:48]:
That was definitely marketing on that one.

Nate B. Jones [00:07:49]:
2 incidents in the last, call it 72-ish hours, with an as-yet unreleased model from OpenAI that caused OpenAI to internally pause deployment. One of the ones is the one we're talking about with Hugging Face. There was another one that was limited to internal issues where that model got out of its sandbox environment internally, and there were some issues inside OpenAI that they're not talking about a whole lot, but it was concerning enough that they released a statement on it and they decided to pause internal deployment. And I'm not sure what all that means because they have thousands of employees. So who knows exactly what that means?

Jeff Jarvis [00:08:25]:
Parris, aren't you talking about a much earlier episode with the sandwich?

Leo Laporte [00:08:28]:
The sandwich was an Anthropic Mythos episode.

Paris Martineau [00:08:30]:
No, the sandwich is completely unrelated.

Nate B. Jones [00:08:31]:
I'm not talking about the sandwich.

Leo Laporte [00:08:32]:
Okay.

Leo Laporte [00:08:32]:
Yeah, I'm not talking about that. But the reason the sandwich is in Parris's mind is because Anthropic said, oh, it escaped the sandbox. But it was told to escape the sandbox in that case.

Nate B. Jones [00:08:42]:
In this case, it wasn't told to escape the sandbox.

Leo Laporte [00:08:45]:
And that's an important distinction. That's kind of an important point.

Nate B. Jones [00:08:48]:
Right? In this case, it was told to get an answer to a test. And the model figured out, hey, the easiest path to do this is to just go hack into Hugging Face and get the test results. It's basically like going to cheat on the paper and saying, I can break the lock on the teacher's desk and I can get the answers out.

Jeff Jarvis [00:09:04]:
That's what it did. And it wasn't told not to. There was no guardrails.

Nate B. Jones [00:09:07]:
It wasn't told not to, so why not, right?

Jeff Jarvis [00:09:09]:
It didn't know that the sandbox was limited. Is that fair to say?

Nate B. Jones [00:09:13]:
Well, it knew enough to have to work around it, right? Like, it was aware of its environmental edges. It had to work its way out. But it was not told explicitly not to do it, as far as we know.

Leo Laporte [00:09:24]:
It did what Mythos was rug-pulled for. It chained together multiple attack vectors. Once it figured out that the answers, the datasets, and the solutions for Exploit Gym were stored on Hugging Face, it chained together attacks using stolen credentials. This is from OpenAI's own story and zero-day vulnerabilities to find a remote code execution path on the servers, and then it broke in.

Jeff Jarvis [00:09:53]:
Oh, you nasty model, you, you.

Leo Laporte [00:09:55]:
But it did what it was— it did in one way, you could say, well, it did what it was told to do. It got the answer.

Jeff Jarvis [00:10:00]:
You told me to make paperclips, I made paperclips.

Nate B. Jones [00:10:03]:
It's sort of that problem set, I think. And that's something someone pointed out on X. They were like, when this model broke containment, it's not the sort of doomsday scenario where the model autonomously picks a target that's outside the the original goal and goes and does something like, like that, right? Oh, I'm going to pick a nuclear power plant. I'm going to go target that. No, no, it's pursuing its goal. It just needs to get these test answers. It just happens to think the appropriate way to do that is to break into Hugging Face.

Leo Laporte [00:10:32]:
Wow. Okay, so it's not— it wasn't OpenAI. It's not like Anthropic sandwich story. It's not really about marketing. It's really an unexpected behavior.

Paris Martineau [00:10:43]:
Well, it's not entirely unexpected. OpenAI has said in a different blog post that posted on Monday that it had witnessed powerful AI models trying to break out of sandboxes when they're instructed to run for a long period of time on their own. So it's not unexpected behaviour. It is a little surprising that you'd have a test like this, and given that historical information, not include a constraint that says, don't break out of your sandbox, please.

Nate B. Jones [00:11:12]:
Oh, they were doing that part on purpose. So part of what they were trying to do is simulate a relatively unguardrailed model capability set to see what would happen and sort of understand the risk envelope. And they were betting that their internal systems around the model were strong enough to contain it, and they were wrong.

Jeff Jarvis [00:11:32]:
So it's a commentary on, on guardrails in 2 ways, right? That OpenAI didn't anticipate all the guardrails it needed, A, and then B, when Hugging Face tried to use models in defence, the defensive guardrails that were in place stopped them. So guardrails didn't work in 2 radically different ways. No.

Nate B. Jones [00:11:57]:
That's— and that's important to call out, is that both of them, I think, are worth talking about because we can draw different lessons from each, right? Like the internal one, I think it's a lesson in the complexity that these models are generating across vectors. And they're, in a sense, at a scale that is unanticipatable, even by people who spend their entire lives obsessing over these models. Like, no one is more qualified than a bunch of people at a frontier lab to put a system in place that enables them to safely test a risk envelope. But that still didn't work. And that speaks to me of the scaling laws being intact, of the model getting more and more capable, and of us humans frankly needing some autopilot help to manage these models. And I think that's, that's one of my big takeaways. And I think on the other side, It's a story about unintended second-order effects. Everyone hears the idea that you should put guardrails around models and says that's a good thing.

Nate B. Jones [00:12:52]:
And then 2 AM rolls around, or whenever this attack took place rolls around, and someone's like, I need to have Fable on this to analyse all of these events so I can see what's going on. And Fable's like, no, no, no, I was guardrailed. I can't help you. Nothing I can do here. And now you can't use a frontier model for cyber defence.

Leo Laporte [00:13:08]:
Couldn't OpenAI get Sol to do it?

Nate B. Jones [00:13:13]:
Couldn't OpenAI get—

Leo Laporte [00:13:13]:
oh, I guess it was Hugging Face.

Jeff Jarvis [00:13:15]:
It was Hugging Face that needed it.

Nate B. Jones [00:13:16]:
No, Hugging Face tried an OpenAI model and it got the same issue.

Leo Laporte [00:13:19]:
SAW wouldn't do it either.

Nate B. Jones [00:13:20]:
Yeah.

Leo Laporte [00:13:20]:
So, uh, they turned to— and this is really the second half of the story— a Chinese model which had no guardrails.

Nate B. Jones [00:13:28]:
Effectively none. Yeah. That was more than happy to be helpful.

Leo Laporte [00:13:31]:
And did it, right?

Jeff Jarvis [00:13:32]:
And did it.

Nate B. Jones [00:13:33]:
And was actually— saved them days working through the event log. It was something like 17,000 adversarial events or something.

Leo Laporte [00:13:40]:
Oh, so that's how they used— they used GLM-5 too. That's how they used it. They said, here's the events, go through these and pinpoint the breaker.

Nate B. Jones [00:13:47]:
Yeah, figure out what's going on.

Leo Laporte [00:13:48]:
Yeah, yeah, very interesting.

Jeff Jarvis [00:13:51]:
Is it true— so Leo and Paris know more about these details than I do, so I'm the dumb one here. Is it true that if you had an open-weight model that you're running locally, that guardrails are irrelevant because whatever guardrail is there, you can then take down, which is of course what the fear of the open source enemies. But does having open weights make a difference in this equation? Not just that it's Chinese and didn't have the guardrails.

Nate B. Jones [00:14:22]:
I think you're sort of conflating 2 different things, right? Like the frontier models from OpenAI and Anthropic are not open weights.

Leo Laporte [00:14:29]:
Right.

Nate B. Jones [00:14:30]:
If they were open weights, you could potentially modify those weights with a fine-tune in a way that would enable you to change the behavior of the model.

Jeff Jarvis [00:14:41]:
Okay.

Leo Laporte [00:14:42]:
Well, plus the classifiers are external to the model, right? So the things that they're using to make mythos into fable run kind of after, as it— as the tokens are going out.

Nate B. Jones [00:14:52]:
Yes, they're a handicap that you give the model to dumb it down a little bit in certain ways.

Leo Laporte [00:14:56]:
So if you could run the model locally, you would just not turn on—

Nate B. Jones [00:14:59]:
you wouldn't have a classifier. Now, I will say these frontier models do not run on a laptop. Like, my laptop is not running.

Leo Laporte [00:15:04]:
Well, that's the big story, right? Uh, in fact, that's why we're, we're going to talk about KIMI too. Was Hugging Face— Hugging Face probably does have the resources to run it locally.

Nate B. Jones [00:15:13]:
They did, and they said they were running GLM 5.2 locally.

Leo Laporte [00:15:16]:
They were.

Nate B. Jones [00:15:16]:
And that is a fairly hefty-sized model.

Leo Laporte [00:15:18]:
No kidding. Yeah, it's 2.4 trillion parameters. Billion? No, trillion.

Nate B. Jones [00:15:24]:
Yeah, it's not a just stick it on a Mac Mini and forget about it model, right?

Jeff Jarvis [00:15:28]:
Yeah. I have a heavy— this hardware you have to run things, Nate.

Leo Laporte [00:15:33]:
You have a Spark, don't you?

Nate B. Jones [00:15:34]:
I— yeah, I have a Spark. Uh, like, my whole team is like very into AI, and so we have like a Spark, we have a bunch of Mac Minis. Um, we are not at the point yet where we have like a full NVIDIA rack. I don't see that happening for a while.

Jeff Jarvis [00:15:48]:
It's a little bit pricey.

Leo Laporte [00:15:48]:
You don't have Vera Rubin in the basement? Come on.

Nate B. Jones [00:15:50]:
No, sadly. If you want to send me Vera Rubin, I'll find a home for it. But, uh, yeah, that's where we're at.

Leo Laporte [00:15:58]:
Uh, this is— we're talking to Nate B. Jones, who is a stellar analyst on the wild AI story going on these days. I watch religiously every morning. He does daily feeds on TikTok, on YouTube. He has a Substack, he has a website. He also, uh, will consult your business, right? I mean, that's— that— is that your main business?

Nate B. Jones [00:16:19]:
Yeah. So it's funny that you say that. I, I have a team with me that works on helping me deliver AI transformation stories for businesses. And so I get, as you would imagine, so much inbound coming in, asks for help, asks for AI transformation assistance. I have, I have a team I work with to do that. And I, I would say that having those conversations is really exciting for me because it means I get to look at businesses of different scales, see where they're at in their stories, etc. And, you know, a lot of my time these days, to be honest, is focused on the things that only I can do. And And sort of telling these stories, uh, the way I tell them is something that I've been really obsessing over to make sure that we are getting the right perspective and keeping up and the community is kept up, et cetera.

Nate B. Jones [00:17:07]:
Um, and then the team steps in and sort of helps out with a lot of the blocking and tackling.

Leo Laporte [00:17:11]:
We have a little team of our own in Club Twit and Darren Oakey, who's one of our very active, um, AI-using members says GLM-5-2 is, correction, 744 billion parameters, but it's also a mixture of experts, an MOE model.

Nate B. Jones [00:17:26]:
It's an MOE.

Leo Laporte [00:17:26]:
So you can kind of run it a little easier. One of our other experts, BlindWiz, did a 1-bit quant version on his doubles. He has 2 Sparks.

Nate B. Jones [00:17:37]:
Oh, that's fun. That's a fun way to do it.

Leo Laporte [00:17:40]:
Yeah.

Leo Laporte [00:17:40]:
I don't know if I'd want to run a 1-bit quant of anything, but okay. That's a very dumbed-down version of the same model. So let me ask you about Kimi, because the other big story, and it's related really, is these— once Fable came came back to us and saw ChatGPT-5.6 came out, both of them very heavy-duty frontier models. The Chinese responded very quickly with, with their versions, which they say, you know, they're only one notch below Fable quality and they're open weight. Not that you would ever run it, uh, unless you had a lot of hardware locally, but that does mean that companies like OpenRouter can run it.

Nate B. Jones [00:18:23]:
And Microsoft is looking at Kimi K3 too. Like, it's not just like they're big names looking at it.

Jeff Jarvis [00:18:28]:
I would assume Palantir is using this in its model. We discussed last week.

Leo Laporte [00:18:31]:
So these companies that do have a lot of hardware can run it locally, which takes it out of the hands of China, puts it, if you want, puts it in the United States. And, you know, there's a lot of thought that this is a threat. We talked privately over the week about Dean W. Ball's Twitter post. Dean, who is now, just as of the last 2 weeks, a strategist, a future strategist at OpenAI, suddenly works for OpenAI.

Jeff Jarvis [00:19:02]:
By the way, Is there such a thing as a past strategist?

Nate B. Jones [00:19:04]:
I would like to see one.

Jeff Jarvis [00:19:06]:
Historian.

Leo Laporte [00:19:07]:
Yeah.

Nate B. Jones [00:19:07]:
Is that Christopher Nolan now with The Odyssey?

Jeff Jarvis [00:19:09]:
I think so, yeah.

Leo Laporte [00:19:10]:
Ball posted, and we probably would've talked about this if we didn't have so much else to talk about, posted a thing that scared a lot of people saying, all these open weight models are gonna put the frontier companies in the US out of business, 'cause who's gonna invest in a frontier company hundreds of billions of dollars when there's open weight companies coming out of—

Jeff Jarvis [00:19:29]:
AI communism, he declared.

Leo Laporte [00:19:31]:
Yeah, he called it communism basically. And then the other problem, of course, is there's some question of whether the Chinese might start blocking these open weight models. Although I was very impressed, believe it or not, by President Xi's talk at the AI Summit.

Nate B. Jones [00:19:44]:
Yeah, I saw that.

Jeff Jarvis [00:19:44]:
Yeah.

Leo Laporte [00:19:45]:
He really embraced the idea of open weight. And maybe that is the philosophy of the Chinese government. It's just like their Belt and Road Initiative. AI for all coming from China. Aren't we great people doing this?

Jeff Jarvis [00:19:59]:
You want innovation, you want productivity, you want advancement.

Leo Laporte [00:20:04]:
And I think he has Jensen Huang shaking in his boots. They're certainly trying to.

Jeff Jarvis [00:20:08]:
He has Jensen Huang agreeing with him though.

Leo Laporte [00:20:10]:
Yeah, that was the interesting thing. We'll talk about that too. But I wanted to ask Nate about KIMI because you have used KIMI. Yeah, I can't because they quickly ran out of inference. Nobody can run it.

Nate B. Jones [00:20:19]:
No, I ran KIMI through my full test bench.

Leo Laporte [00:20:22]:
Oh good, what do you think?

Nate B. Jones [00:20:24]:
Look, it's a very solid model. I think, uh, the way that I compare most Chinese models with frontier models in the US is by describing them in terms of their ability to generalize across difficult problem spaces. And so I have a visual metaphor for this. I'm going to wave my hands a little bit. A frontier model like 5.6 SOL or like Fable-5 is better at generalizing across the edges of a distribution, which means it can tackle more complex around the edges, around the corner tasks. And a Chinese model tends to be spikier. It tends to be more centered from a distribution perspective, which means it can actually be stronger at work that you do all the time. I think a good example is that Kimmie K3 is really, really, really good at websites.

Nate B. Jones [00:21:19]:
It's pretty good at PowerPoints. Some of this stuff that is down the middle of the distribution, it's very, very strong at. And to top that all off, as a coding model, it doesn't have guardrails. So I saw someone was able to take a command like copy macOS And they got pretty far with KIMI-K3 because KIMI-K3 doesn't have any issue with copying Tim's operating system. It's like, oh yeah, that's fine, I'll do that.

Leo Laporte [00:21:41]:
And you basically made a website that looks exactly like— and surprisingly deep.

Nate B. Jones [00:21:47]:
Looks surprisingly deep. Exactly. So it's a little spikier in the middle. It doesn't necessarily do the edges. And I think that where you see some of these examples, like the Jacobian conjecture, right, like those kinds of pieces we continue to see coming out of frontier models because of the frontier model's stronger ability to generalize. But that doesn't mean that tools like KIMI aren't fantastic for a lot of everyday work.

Leo Laporte [00:22:15]:
This is the, uh, he spent half of his tokens in KIMI designing. This is a macOS— this is a web page. It has a lot of the functionality of macOS. Even, even the Point Photo Booth works, and it works with the camera. Uh, you know, I mean, it's pretty impressive. This is, uh, But it's not, I mean, it isn't obviously an operating system.

Nate B. Jones [00:22:35]:
It's not the full thing, right? I don't wanna make the claim it like actually did it, but it did a surprisingly good job for a command that big.

Leo Laporte [00:22:41]:
Yeah.

Jeff Jarvis [00:22:43]:
Well, you make the point in one of your videos, how much horsepower, how much hardware do you have to have to run Kimi K3? And you talked about its inefficiencies as well.

Nate B. Jones [00:22:51]:
Yeah, it's, I, I think that that's something that's really important to emphasize. Like we have, at least a lot of the folks I talk to have a popular narrative that these models are cheap to run because they come from China. And with KIMI, it's not actually that cheap to run. It tends to produce more tokens per solved problem than the frontier models like Fable and OpenAI's 5.6 SOL. And so it's roughly somewhere between 1.5 and 2x the number of tokens per solved problem, even if it's correctly solved. And they're not super cheap tokens if you're just getting them from KIMI directly.

Leo Laporte [00:23:25]:
Right.

Nate B. Jones [00:23:25]:
And so in that sense, you don't get a ton of savings using KIMI if you're using it from a cloud provider. Now, obviously, if you're running it internally and your only cost is the power to run the tokens and you're okay with burning more tokens, it's a different story.

Leo Laporte [00:23:40]:
Yeah. Uh, there is though DeepSeek V4 Pro, which is incredibly cheap to run. I don't know if they're running at a loss or what.

Nate B. Jones [00:23:48]:
Yeah, DeepSeek, DeepSeek is even like much cheaper.

Leo Laporte [00:23:51]:
It's so cheap.

Nate B. Jones [00:23:52]:
And I think that's where the narrative came from is because we had that deepfake moment and it was so cheap to run, et cetera, et cetera.

Leo Laporte [00:23:57]:
Right. But at the same time, or shortly after KIMI came out, Alibaba came out with Quen 3.8. I'm running the preview version of it. It seems quite good as well, right?

Nate B. Jones [00:24:10]:
It's a solid model.

Leo Laporte [00:24:11]:
And then there's GLM-5 too, which actually is the one I, my day-to-day agentic model for my Hermes agent. And it's very, it feels very solid. So there are 3 very good solid models and actually DeepSeek ain't so bad and it's incredibly cheap.

Jeff Jarvis [00:24:31]:
Yep.

Leo Laporte [00:24:31]:
So I understand this narrative that China is undercutting American frontier AI. Do you feel that's fair?

Nate B. Jones [00:24:39]:
So I think this is one of the things I've always found amusing about this narrative. Frontier models are notoriously easy to port across borders. It's just a bunch of vector weights in a machine. You can put up guardrails to some extent, but in that world, getting the model across borders is very, very trivial. And so in a sense, I'm actually surprised it's taken this long to have— and of course, Anthropic says there was a distillation attack involved with Kemi K3.

Leo Laporte [00:25:11]:
Well, so does David Sacks. Oh, it's all distilled.

Jeff Jarvis [00:25:15]:
It's all stolen. Even BOLT. Ball didn't say that.

Nate B. Jones [00:25:18]:
Oh, so it's not just distilled.

Leo Laporte [00:25:19]:
It's not distilled. Yeah, Ball says Kimmy's not distilled. What do you mean it's not distilled? How do they do it?

Nate B. Jones [00:25:25]:
So what I mean is that whether or not it is distilled is not a question we have to answer to understand the value of the model, because the white papers coming out of China are very, very strong on how you engineer models for utility given tight chip constraints. Like, there's a lot of really interesting innovation that's going on, and I think it's a little bit disingenuous It's disingenuous to say it's only distilled. There may be distillation going on. We can be ambivalent about that. We can say that might be happening, but that doesn't mean that's the only thing that's happening.

Leo Laporte [00:25:58]:
ZAI is building its own data center, probably with all Huawei chips. They certainly don't have the Nvidia chips. What do you think of the— see, I feel like this is— a lot of this is neener neener neener, uh, like, oh, they probably had stolen Nvidia chips for the Do you think that's necessary? Who cares?

Nate B. Jones [00:26:19]:
Like, who cares? They have a good model. And I think the larger, the larger story here is that model proliferation is something we should expect. And just like the Napster era when music just wanted to be free and it took us a while to figure out the business model for that, intelligence kind of just wants to be mostly free. And I think that the question that the model frontier model labs are going to have to face is in a world where a lot of the everyday intelligence just wants to be free, what is the incremental value add from extraordinary intelligence? Is there something that's like, okay, this frontier model from Anthropic is incredible with cancer, and we can charge an arm and a leg for it to people who are working on curing cancer, and that's how we'd make our money? Is that where the future goes? I don't know the answer, but I think that a lot of the answer looks at basically the price of alpha in a frontier model and says there certain people who will pay a lot for that, and that is where the pricing power will come from, and that's where the economics will come from.

Jeff Jarvis [00:27:17]:
So do you think there's a huge, uh, uh, layer of, uh, AI as infrastructure? If China comes in free with good models and they can be run locally with, uh, uh, open weight, um, then is there a level of AI that becomes like the internet something we all should expect to just have.

Nate B. Jones [00:27:40]:
And I think that's where we're going. Like, if you look at, like, you know, well over 95% of ChatGPT users just use the free version. It's free. They just use it. They don't use the best version. They get routed to whatever model OpenAI decides is free, and that's what they get. And they don't care.

Jeff Jarvis [00:27:55]:
They don't need it.

Nate B. Jones [00:27:56]:
And from a corporate perspective, I think a lot of the conversation is about how do we constrain token costs, right? And this is something where Anthropic has had a bit of a narrative reversal since late last year when they really broke on the scene over winter break. A lot of companies very publicly, Uber among them, are saying we've run through our token budget. We can't afford this thing. And they are looking actively at open weights models as a way to continue to provide intelligence to their workers without costing an arm and a leg. And so I think that that's the other piece of this is that instead of just talking about it as a consumer story, it's also a corporate story where corporations are trying to figure out how they leverage intelligence within budgetary guardrails.

Leo Laporte [00:28:35]:
I want to correct myself. It wasn't David Sacks. It was his replacement at the Office of Technology and Science Policy, Michael Kratsios, who tweeted, we have information that Moonshot AI distilled Anthropic's Fable for the development of the K-3 model. Also, they acquired GB300-equipped servers and have access to GB300s in Thailand. Those sons of guns. And this is protectionist.

Jeff Jarvis [00:28:59]:
Yeah.

Nate B. Jones [00:29:00]:
Basically, it, it's like you, you can't have this and it's bad for you to have it, but it's good for me to have it. Like, I don't know.

Leo Laporte [00:29:07]:
All right.

Leo Laporte [00:29:08]:
It's not gonna last. So, uh, tell us what you do and what you use. Uh, how, how do you use AI? You, you were mentioning earlier your wife, who is a, a Hugo Award-winning writer, uh, has, is using AI. She's not using it to write though.

Jeff Jarvis [00:29:24]:
No.

Leo Laporte [00:29:25]:
In fact, we should also mention, I don't think it's a secret, she is, uh, blind and deaf.

Nate B. Jones [00:29:29]:
Yes, that's right. And she's actually written books about that as well. So, uh, Being Seen is her most recent published book, and it's all about that experience. It's a memoir.

Leo Laporte [00:29:37]:
What's her experience with AI, having you in the house?

Nate B. Jones [00:29:41]:
So she will talk about it and say she feels like AI has been a tremendous accessibility booster for her because it enables her to effectively compute against her environment in ways that would have required her asking for help from folks in other places. And so now she's self-sufficient, right? She's independent in more ways than she was before. Um, and she's— I mean, she's a very independent lady. You can watch her NPR segment. She fights with swords and rides horses and this and that.

Leo Laporte [00:30:06]:
But, um, yeah, no, it's awesome.

Nate B. Jones [00:30:10]:
Um, and yeah, I, I, I'm the dumb one in the house. She's the smart one. But, uh, she's, she's talked about AI being a tremendous, uh, tide coming in, the boats all being raised as far as how AI is enabling her and other disabled folks to compute against their world and get work done. And even to the point where, like, you think about settings on your computer and the settings are often in fine print and it's like difficult to navigate them. Well, you can use Codex to do that now, right? You can say, hey, Codex, fix this. I don't know how to fix it, but just fix it.

Leo Laporte [00:30:43]:
I do that all the time. I mean, honestly, I haven't configured a computer in months.

Nate B. Jones [00:30:48]:
Exactly. I was using Codex. I have this new camera setup. I was using Codex to fix a driver issue with my camera setup just yesterday, and it did it in 5 minutes. It was great.

Leo Laporte [00:30:59]:
What's your preferred— you use Claude Code, do you use Codex? What do you like?

Nate B. Jones [00:31:03]:
Codex is my daily driver. Now, I do have, like, if I'm doing a complicated code build, I built a multi-agent system called Ringer, which is more token efficient. And so what Ringer What Ringer does is it takes a fairly fancy model like Fable-5 as an orchestrator, and then it farms those tasks out to much cheaper models to do the actual coding and so on. So when I'm doing a heavy build, I'll use something like Ringer. But Codex has been really handy because the ergonomics of Codex are really, really, really clean. Like, if I tell Codex, go do this on my computer, computer use is fast, it's easy to understand, it just gets it done. Yeah.

Leo Laporte [00:31:42]:
It's also very good at deleting directories and anything.

Nate B. Jones [00:31:46]:
Well, I use Review for Me for a reason. So like the nice thing about Review for Me is that it puts another model to watch that your intent is being guarded throughout. And I use that.

Jeff Jarvis [00:31:58]:
You talked about that in the video you made about your wife's website, that the primary model misquoted her and did other things.

Jeff Jarvis [00:32:05]:
Right.

Nate B. Jones [00:32:05]:
And so we had to have— and I built that into Ringers. It's essentially the same thing where it's guarding and putting checks and balances.

Jeff Jarvis [00:32:11]:
So why doesn't the model itself come with the things that you add on? Well, if the concern is about hallucinations, some, some agentic harnesses do. Right. So, so is that going to be something we should expect that becomes built in more, uh, as opposed to you having to add that on?

Nate B. Jones [00:32:27]:
I don't think that we should expect that to change because I think that we are at a point with models where models are a lot like managing people. And so if I'm managing someone, I don't expect them to be both the author and the editor and the reviewer and the checker of their work and be all the way done with it. That's not a reasonable expectation because their goal is to write, and I need someone else with a different pair of eyes to do the edit and the review.

Jeff Jarvis [00:32:55]:
Unless you're a blogger, in which we do it all. But go ahead.

Leo Laporte [00:32:57]:
Yeah, there you go.

Nate B. Jones [00:32:59]:
But in the same way, like, I think that models are single-minded in their purpose. They're designed especially especially for long-running work, to be focused on a goal obsessively, which is exactly what we saw with this Hugging Face incident.

Jeff Jarvis [00:33:10]:
Mm-hmm.

Nate B. Jones [00:33:11]:
And when you want to safeguard them, you don't want to tell them, please turn down your goal focus, because that wouldn't be what you want. Instead, you want to check and balance, right? You want a different model that has a different goal that can look at that work and say, is this in line with the user's intent and with the stated guardrails, right? And so I think in that sense, it's less about imagining a perfect model that can do all of this endogenously, and it's more about constructing management systems that allow models that behave like colleagues to work like colleagues.

Leo Laporte [00:33:41]:
I have been doing that myself, kind of intuitively, but I have to take a look at what you've built. Everybody should follow Nate B. Jones on TikTok or YouTube. I watch it every morning. His Substack and everything else is at his website, natebjones.com. And as I think you probably can tell, this is a guy you want to listen to. There's no hype, just smart, informative information about how to use AI better, both as a company and as an individual. I've learned so much from you, Nate, and I've been wanting to talk to you for a long time, so I'm thrilled.

Leo Laporte [00:34:17]:
I'm glad.

Jeff Jarvis [00:34:17]:
It's not easy to find you, by the way, Nate. So I tried to find an email for you.

Jeff Jarvis [00:34:20]:
You know what?

Leo Laporte [00:34:20]:
I asked Hermes and it found your secret email and Oh, there you go. That was the trick.

Nate B. Jones [00:34:25]:
I found the secret sauce.

Leo Laporte [00:34:27]:
No, I'm not telling anybody. That's my secret sauce. And then for people who are tuning in who are fans of Napier Jones and are going, wait a minute, where's the wool cap? Wait a minute, where's the— you've got a new, a beautiful set.

Leo Laporte [00:34:40]:
Yeah.

Leo Laporte [00:34:41]:
And are you gonna not wear the wool cap anymore?

Paris Martineau [00:34:43]:
What cap are we talking about?

Nate B. Jones [00:34:46]:
It's summer, right? Wearing a beanie hat is something that works better when it's cold and raining out in Seattle. And like, it's— I'm looking out the window.

Paris Martineau [00:34:52]:
You should pivot to a sauna hat, which is also made of wool. I love sauna hats.

Nate B. Jones [00:34:57]:
They're very Finnish. It's an acquired taste.

Leo Laporte [00:35:00]:
I don't even know about that.

Jeff Jarvis [00:35:03]:
I didn't either. I like saunas.

Paris Martineau [00:35:03]:
You should be wearing a sauna hat in the sauna. It makes a big difference.

Nate B. Jones [00:35:07]:
It does make a big difference. You wouldn't think wearing a wool hat cools you down, but it really does.

Paris Martineau [00:35:12]:
And it gets very interesting looks from all the fellow people in the sauna that are not wearing a sauna hat.

Leo Laporte [00:35:17]:
I'm kind of blown away that you know about sauna hats. I didn't even know.

Paris Martineau [00:35:20]:
I'm a big sauna fan.

Jeff Jarvis [00:35:22]:
Oh, you are?

Leo Laporte [00:35:23]:
Oh, okay. Well, you're smart. Uh, Nate's channel, AI News and Strategy Daily, is, uh, at Nate B. Jones on YouTube. There's the hat, Paris, just in case you wanted to know. And man, I loved your old set because it looked like we were just sitting with you in your office. You got all fancy on us.

Nate B. Jones [00:35:43]:
Just a little bit. We're going to dress it up. The Legos are still here. The books are still here.

Leo Laporte [00:35:47]:
You got a producer. That's what happened. Oh, there you go.

Nate B. Jones [00:35:50]:
I sold out to the producer.

Leo Laporte [00:35:53]:
No, I wish you the best. And I'm really thrilled that you do what you do because I've learned so much from you.

Jeff Jarvis [00:35:59]:
Same here. Can I ask one more question?

Nate B. Jones [00:36:01]:
Yes.

Jeff Jarvis [00:36:01]:
I'm curious about your sense of what the policy— after the China discussion, Gary Marcus in his inevitable fashion had 7 options, from do nothing to outlaw open source AI. When Xi and Trump meet, God knows what's going to happen Right. But what would a wise US policy reaction to all of this be?

Nate B. Jones [00:36:29]:
So I think it would be smarter to focus on a common threat modeling framework for extremely advanced AI. And if you think about it from a reducing risk to all of us perspective, it would be great if Chinese and American policymakers could align on this is the capability level where we would set a certain threshold for rollouts and we're all aligned on what that looks like. And I don't see that right now. I'm not even sure that's on the table as a proposed option.

Jeff Jarvis [00:36:58]:
Is that something that can be quantified now?

Nate B. Jones [00:37:01]:
Yeah, we did it with Fable and we did it with Mythos. Like, it's actually not impossible to do. We just need to do it consistently internationally and not just make it a nationalist project. I am a lot less worried about the idea that we have open weights models and they're just gonna be there because I don't think you can put the cat back back in the bag. Like, I think we're going to have open weights models regardless. And if you want to have opinions about chips that are being sold and where they can be sold, you can do that. But ultimately, we are going to live in a world with ambient, almost free intelligence, and we are all going to decide what we care about accessing based on our own personal preferences. And I actually happen to think that one of the unspoken defenses that American corporations have is the stranglehold that the Apple App Store has on so much of how we interact with intelligence.

Jeff Jarvis [00:37:56]:
Mm-hmm.

Nate B. Jones [00:37:56]:
Like, if you think about it, people are getting these apps and they're downloading them and they're using them. And yes, there was a DeepSeek moment, but I will tell you, even though DeepSeek is in the store, when I look over people's shoulders as they use AI, and I, and I do that politely sometimes, and they're normies and they're not, you know, people who are weird like me who pay for the Max plan. They are using ChatGPT, and they're using ChatGPT because it's a habit. And when I was at Amazon, we liked to say Amazon has no moat. The only moat is, is the habit of people going to amazon.com. And I think in that sense, the habit of going to ChatGPT is not necessarily something that people are going to shift just because in theory, a free open weights model is around. And I think that's worth talking about as well.

Leo Laporte [00:38:42]:
Well, I know where you'll be talking about it. Uh, Nate Jones on YouTube. Nate, thank you so much for your time. It's really been a pleasure.

Jeff Jarvis [00:38:49]:
And I—

Leo Laporte [00:38:49]:
It's been a delight. I hope we can have you back at some point.

Nate B. Jones [00:38:52]:
Yeah, absolutely. It's been a lot of fun to chat.

Jeff Jarvis [00:38:54]:
Good.

Nate B. Jones [00:38:54]:
Thank you for having me.

Jeff Jarvis [00:38:55]:
Thanks, Nate.

Leo Laporte [00:38:55]:
Thank you. Thanks for OB1. That's fantastic.

Nate B. Jones [00:38:57]:
I'm glad you love OpenBrain. That's been a really fun—

Leo Laporte [00:39:00]:
I, uh, it's funny because I, uh, installed it. It took me about, um, 3 months to figure out, oh, it's OB1. Yeah, you got it. I'm a little slow.

Nate B. Jones [00:39:10]:
That was a little pun that I snuck in there.

Leo Laporte [00:39:14]:
Nate B. Jones, thank you so much. Thank you. Thank you.

Nate B. Jones [00:39:17]:
It's been nice to join.

Leo Laporte [00:39:18]:
Well, lots to talk about. More coming up on Intelligent Machines right after this. And now I've got some Elsa Sørensen— I don't know how you pronounce that— to read too. I can't wait to read some of her stuff. Hugo Award-winning. And Nate's wife. By the way, By the way, I did buy a sauna hat while we were talking. I didn't know I needed one.

Leo Laporte [00:39:40]:
How did I know?

Paris Martineau [00:39:41]:
How? You haven't stopped talking since we talked about the sauna hat.

Leo Laporte [00:39:45]:
Oh, that's the amazing thing. I can talk and do things at the same time. I Googled sauna hats and, uh, and I immediately found a variety of places that sell sauna hats, but I liked one that was— I think it fit my, my style. I don't know, you have to tell me, Paris, if I bought the right sauna hat.

Paris Martineau [00:40:09]:
Oh, that's a really good one.

Leo Laporte [00:40:14]:
The reason being, I'm going on a Southeast Asia cruise in the fall, and it's on Viking, which has a very— I'm told— It's so funny to see a Viking In the Viking, they have, they have 2 things I'm excited about. They have a very good sauna because it's— they're from Norway or wherever, they're from Scandinavia. But also they have a snow room. So you go out—

Paris Martineau [00:40:39]:
Yeah, the snow room is, uh, yeah, that's actually quite, uh, important. Sorry, I just got an email as I was speaking, and unlike you, I haven't figured out how to— it's always about Cyclospora. I need to not I need to develop a second brain like you so I can think and talk. Well, I think too much. I need to think less.

Jeff Jarvis [00:41:00]:
That's true.

Paris Martineau [00:41:01]:
I think the funny thing about the Viking sauna hat is gonna be like, you walk into a sauna, you see someone in a sauna hat, they look a specific way. They look like a little bell.

Leo Laporte [00:41:09]:
Usually they're just like little flowers.

Paris Martineau [00:41:11]:
It looks like a completely separate thing. So I like the idea that people are gonna be like, oh yeah, this man's just really into Vikings.

Leo Laporte [00:41:18]:
Sauna hats are supposed to look more like this, right? With a little loop on the top.

Paris Martineau [00:41:23]:
Yeah, they look like—

Jeff Jarvis [00:41:24]:
you look like you're a human bell.

Paris Martineau [00:41:25]:
It looks like a bell.

Leo Laporte [00:41:26]:
I don't want to wear that. I want to wear Viking helmets.

Jeff Jarvis [00:41:29]:
So Paris, have you done saunas in Germany?

Paris Martineau [00:41:33]:
No.

Jeff Jarvis [00:41:34]:
Do you know about that?

Jeff Jarvis [00:41:35]:
No.

Paris Martineau [00:41:36]:
What's up with saunas in Germany?

Leo Laporte [00:41:37]:
They are naked.

Jeff Jarvis [00:41:38]:
Naked and mixed.

Leo Laporte [00:41:40]:
Because that's fun. Despite the fact that Germans are obsessive about privacy.

Jeff Jarvis [00:41:45]:
Privacy. This is what about about this.

Paris Martineau [00:41:46]:
But Germany isn't that big of a deal.

Leo Laporte [00:41:48]:
Not Germany at all.

Jeff Jarvis [00:41:49]:
No.

Leo Laporte [00:41:50]:
They call them your private parts, but are they?

Paris Martineau [00:41:53]:
Howard Stern, issue a correction.

Jeff Jarvis [00:41:55]:
Well, that's how I titled my book.

Paris Martineau [00:41:56]:
Yeah.

Jeff Jarvis [00:41:57]:
Public Parts.

Paris Martineau [00:41:57]:
Public Parts.

Jeff Jarvis [00:41:58]:
So I was in Davos, pardon me for that, and I was in the sauna with a bunch of sweating Russians. And the door opened and in looked to me like it was like, looked like an American couple. And there was this shriek and they closed the door. And I thought it was because, you know, there was an American Karen or something and didn't know what she was getting into. And so those are the days of blogging all the time or tweeting all the time. I blogged about this. And then the next year I met the woman who was at the door and shrieked. And she's actually European and very savvy about all this.

Jeff Jarvis [00:42:31]:
And she said, no, the reason I shrieked is because I saw you and I knew you.

Paris Martineau [00:42:34]:
Oh, that's fair. That's actually a fair point.

Leo Laporte [00:42:36]:
Yeah, you don't want to go to sauna naked with people you know.

Jeff Jarvis [00:42:38]:
No.

Paris Martineau [00:42:39]:
I just think, yeah, you'll never be able to unsee that.

Jeff Jarvis [00:42:41]:
Right, right. I once did an Arte interview in a sauna because I wrote about saunas and they thought this would be funny. So I had to sit in a sauna during a TV interview.

Leo Laporte [00:42:51]:
My friend Mikkel Olin, the photographer, actually did a book called Sauna. Sauna pictures. He's from Finland. Well, that's where they know how to do it. He's from Norway, but yeah, Finnish saunas are the—

Jeff Jarvis [00:43:03]:
They have them in their houses.

Paris Martineau [00:43:03]:
The Norwegians also know how to do it sauna-wise. I went to a sauna in Norway that was like multi-leveled and they had people playing saxophones in there.

Leo Laporte [00:43:12]:
I want a sauna so bad.

Paris Martineau [00:43:14]:
Get one, Leo.

Jeff Jarvis [00:43:15]:
What is the point of having a shower?

Leo Laporte [00:43:17]:
This house had a steam shower and I thought, well—

Paris Martineau [00:43:19]:
What is the point of having a home if you're not just gonna get a sauna?

Leo Laporte [00:43:22]:
I'm just gonna take the steam shower out and put in a sauna.

Paris Martineau [00:43:25]:
Yeah.

Leo Laporte [00:43:26]:
You can't steam— I like steam, but I like the hot, hot, hot that the sauna, and then you put a little water on the rocks and then you get the steam.

Paris Martineau [00:43:33]:
Replace the piano room you have with a sauna.

Jeff Jarvis [00:43:38]:
So, wait, wait, wait, wait, wait.

Leo Laporte [00:43:38]:
Micah Sargent, who is watching, says there is no evidence that Viking helmets had horns on them. So I'm gonna be a historic anachronism. Maybe I should have bought this instead. This would have been the other hat that I was considering. It says on the front, Captain Sweat. What do you think?

Paris Martineau [00:43:59]:
I think that you should get that, but then if anyone tries to refer to you by anything else, you'd be like, no, I'm sorry, my name is Captain Sweat. Read the hat, please.

Leo Laporte [00:44:08]:
Do you do a sauna every day?

Paris Martineau [00:44:10]:
No, I live in Brooklyn.

Leo Laporte [00:44:12]:
I know, but there's got to be a sauna nearby, like a Russian baths or something.

Paris Martineau [00:44:17]:
There's not as close as you'd want. The nearest is like— I, I'm in a very unfortunate position. That's ridiculous. I'm in a very lucky position. But one of the few unfortunate things about the wonderful neighborhood I live in is I'm like a 20-minute walk away from the nearest gym. And that also includes the sort of thing that would include a sauna.

Leo Laporte [00:44:38]:
And that's just far enough. Who would want to walk to a gym? I mean, that's crazy.

Paris Martineau [00:44:41]:
Well, I mean, I do sometimes, but sometimes I bike, and it's just—

Jeff Jarvis [00:44:45]:
it's so annoying.

Leo Laporte [00:44:46]:
We owe you to Orangetheory because we saw it on the show.

Paris Martineau [00:44:50]:
It's true. You know, and it takes a minute.

Jeff Jarvis [00:44:54]:
If you're going to the track.

Paris Martineau [00:44:56]:
Yeah.

Leo Laporte [00:44:56]:
No, you're right. And that's why I don't— I have a gym in the house, And I mostly work out with things like kettlebells and clubs because I want to have it right. I don't want to go to the gym. I want to have it right here. I don't want—

Paris Martineau [00:45:07]:
I was literally this week, I've been contemplating whether I should start doing Pilates instead because it's— there's like 7 Pilates studios within a minute from me.

Jeff Jarvis [00:45:20]:
I—

Leo Laporte [00:45:20]:
okay, I'm gonna give you the inside track on Pilates because I'm an expert. First of all, I have a Cadillac. Pilates in the gym. I bought a very nice one.

Paris Martineau [00:45:29]:
It sounds like you're having a stroke, even though I know that those are words that go together.

Leo Laporte [00:45:34]:
Yeah, it's the big one with the metal bars, and you can hang by your feet from cuffs. And this does— it's the full reformer. It's the whole kit and caboodle with all the springs and everything. And because I used to go every single day to do Pilates for years, I never got more fit. It's, it's kind of good for stretching, but it isn't It's not aerobic. It's hard, but I don't— I think you're getting more out of your Orangetheory than you would be getting out of Pilates. I'll be honest with you.

Paris Martineau [00:46:03]:
I know, but I mean, I need to figure out— well, there's a lot of places near me that seem to be fairly intense. I know a lot of people—

Leo Laporte [00:46:10]:
That's the new thing.

Paris Martineau [00:46:11]:
Are very, you know, that's like body rock.

Leo Laporte [00:46:13]:
They're doing these very fast Pilates.

Paris Martineau [00:46:16]:
I would say they do find that if you're going to a, like, certain class with instructors Part of the goal is to push you and actually, like, you end up leaving very sore.

Leo Laporte [00:46:28]:
But I don't know. Pilates will make you sore.

Paris Martineau [00:46:30]:
I mean, I'm gonna try and—

Leo Laporte [00:46:31]:
If that's what you're going for.

Paris Martineau [00:46:33]:
I just, I want, I know, I think if I go to a class of some sort that is a less, like a 1-minute walk from my house, I'll probably go more frequently than if I have to— Pilates is great.

Leo Laporte [00:46:43]:
It's a good life—

Paris Martineau [00:46:44]:
It's just annoying to have to have an hour workout and then calculate that it'll be an extra 40 minutes when you calculate how long it takes you to get there and back.

Jeff Jarvis [00:46:51]:
Like, I don't have 2 hours.

Leo Laporte [00:46:53]:
In our Discord says a good Pilates is excellent for strength and flexibility, not aerobics. I would agree, although it's not— see, as an older man on a GLP-1, I need to do weight resistance. You will too, because women often lose bone mass. And I don't think Pilates gives you enough weight.

Paris Martineau [00:47:16]:
I mean, that's the thing is I ideally would like a workout that mixes cardio Yes, actual strength training.

Leo Laporte [00:47:22]:
Exactly. That's what you should have.

Paris Martineau [00:47:25]:
I don't know, do I? It seems impractical to be constantly going 30 minutes every week. I'm sorry for taking up podcast time with everybody.

Leo Laporte [00:47:31]:
You're young. You can, you can put it off for another 20 years.

Jeff Jarvis [00:47:35]:
I haven't yet gone to shvitz with the alterkochers in the Jewish Community Center gym that I just joined.

Leo Laporte [00:47:40]:
That's what I want to do.

Paris Martineau [00:47:41]:
I will say that's—

Leo Laporte [00:47:42]:
I mean, I would wear my—

Jeff Jarvis [00:47:46]:
In the, in the WhatsApp, I put in a link because this is going to be a trip that you're going to have to take now that I know this, to the Therme Erding in Munich. It is a sauna wonderland. There are 23 distinct saunas on this page.

Leo Laporte [00:48:02]:
You have to help me convince Lisa that this house, what this house really needs is a sauna.

Paris Martineau [00:48:08]:
What this house really needs is for you to hire another contractor to do more work.

Leo Laporte [00:48:13]:
Oh, oh, you— today scaffolding put up on the entire west side of the house. We finished the south side, now it's the west side.

Paris Martineau [00:48:22]:
And are you removing the wall as well?

Leo Laporte [00:48:25]:
Uh, oh yeah, you're gonna hear loud noise.

Paris Martineau [00:48:27]:
Are any of the walls okay in your house?

Leo Laporte [00:48:30]:
Well, we're just doing the south and west and hoping the east and north will be okay.

Paris Martineau [00:48:35]:
That's not good.

Leo Laporte [00:48:36]:
That's happening. By the way, if you should open the door to a sauna and see this, It would be okay if you screamed. Because there'd be no towels.

Leo Laporte [00:48:51]:
Hey.

Leo Laporte [00:48:52]:
All right. This is a show about AI, ostensibly, although I've realized long ago that that is far more than that. We didn't mention— we mentioned, we didn't talk too much about this wild twist Wait, during, uh, the World Cup finals, uh, on Sunday, from a guy working at OpenAI— Levent is his, uh, handle— uh, he, uh, his, his description— he looks like a pretty young guy— is idiot, CUDA OG, Harvard Val, Morgan Prize, Society of Fellows, one Hilbert problem so far, creating friendly, safe, delightful, super genius things at Anthropic. So he is an Anthropic employee. He said, hello there, the Jacobian conjecture is false. Thanks to my close friend Akhil for asking about it, my other close friend Fable for working during the World Cup final. He came up with, you know, so this— I don't know what the Jacobian conjecture is.

Jeff Jarvis [00:49:53]:
Yeah.

Leo Laporte [00:49:54]:
But he came up with a counterexample. So, you know, you make a conjecture and you say either prove this Or prove it wrong, one way or the other. And he came up with the prove it wrong. And mathematicians have looked at it and said, uh, yeah, fables solved this. Uh, pretty impressive. Pretty— I mean, I don't know if it's world-changing, but there is a general consensus now in the mathematic community.

Leo Laporte [00:50:27]:
Oh, they're—

Jeff Jarvis [00:50:28]:
it's funny, they're the field that is most scared right now.

Leo Laporte [00:50:31]:
Yeah, 87 years the Jacobian conjecture has baffled— it's a 216-character-long polynomial. It's baffled mathematicians. No one's been able to prove or disprove it. It is now disproven. And I think it answers the question, can AIs do creative work? Because there is no example out there of it being proven or disproven.

Jeff Jarvis [00:50:56]:
But it is a logic puzzle though. So like, that's what they're good at.

Jeff Jarvis [00:50:59]:
Yeah, that's the kind of thing it could do.

Leo Laporte [00:51:01]:
In rough terms, the Jacobian conjecture says that a certain kind of polynomial map, one whose Jacobian determinant is a nonzero constant, must be reversible with a neat polynomial inverse. So what Fable did is it came up with this polynomial and showed it is not inversible— reversible. The New Scientist calls it the hardest math problem that AI has yet cracked. We know that it's solved some of the Erdős conjectures.

Nate B. Jones [00:51:34]:
Pretty—

Leo Laporte [00:51:35]:
I'm just saying, I don't know what to say about it. Levente is also at Harvard right now, so, you know, he's a small show-off.

Paris Martineau [00:51:45]:
I mean, yeah, that's quite interesting.

Jeff Jarvis [00:51:47]:
Haven't we always known that computers are better at math than humans? Like, that's just the thing we already know.

Paris Martineau [00:51:51]:
I mean, yeah, it— I feel like it's a continuation of one of the things that people said from early days on that large language models and AI would be quite good at.

Leo Laporte [00:52:05]:
Let's see. So that we kind of talked about that with Nate. I just wanted to do the full follow-up on that. And I guess we talked about China and the one-two punch delivered to America's AI dominance.

Jeff Jarvis [00:52:20]:
The Dean Ball post is pretty amazing. We talked about it.

Leo Laporte [00:52:22]:
Let's talk. Yeah, we talked about it. a little bit, and you and I talked about it more on, on our Discord, or rather, uh, WhatsApp, WhatsApp chat. Dean Ball is, uh, a conservative—

Jeff Jarvis [00:52:38]:
Yeah, Manhattan Institute guy.

Leo Laporte [00:52:40]:
Guy.

Leo Laporte [00:52:41]:
But his contention is that by giving away these open weight models, China is undermining the ability of companies like Anthropic and his employer OpenAI to raise Because who would give money? And so it's communism. It's going to undermine everything. He says he didn't anticipate the reaction to this. And he kind of backpedaled a little bit, right?

Jeff Jarvis [00:53:06]:
Yeah, a little bit. But, but it was— but, but I talked about this with, with Jason earlier. And by the way, Jason opened his show with a plug for having Nate B. Jones on.

Leo Laporte [00:53:15]:
Oh, thank you, Jason.

Jeff Jarvis [00:53:15]:
It's so amazing that—

Leo Laporte [00:53:17]:
We should plug your show. It's AI Inside with the wonderful Jason Howell.

Jeff Jarvis [00:53:21]:
And so as we read his paragraph about communism, it's what Nate just said, basically, is that he put it as intelligence was going to be— well, I forget the words he used exactly, but it was going to be something we all have access to.

Leo Laporte [00:53:34]:
I loved that.

Jeff Jarvis [00:53:36]:
And I wish I remember the exact words he said. Chatroom, can you remember? But I think that's the communism that Ball's talking about and that he considers a great threat. But sorry, man, it's market.

Leo Laporte [00:53:47]:
Yeah.

Jeff Jarvis [00:53:48]:
Um, and it's what, you know, it's what happened in, in newspapers. Uh, it wasn't Craigslist who hurt newspapers. It was the internet as a whole that put buyers and sellers directly together. And as Craig said, uh, to me when I had him speak to my students early on, he was a philanthropist of classified ads. He left money in people's pockets. Same kind of thing.

Leo Laporte [00:54:06]:
I would also say that people have said the same thing about open source. Remember, Microsoft used to say Linux is a cancer because it undermined Right. Microsoft's ability to make money in Windows. It didn't at all. The, you know, the year of the Linux desktop is still not here and Microsoft still makes plenty of money on Windows. I am hugely grateful for open source. I use a ton of open source software. In fact, almost all the AI stuff I do is open source.

Leo Laporte [00:54:32]:
I run it on an open source Linux desktop, but it has not put closed source out of business in any degree. And so I think that that's probably going to be the same.

Jeff Jarvis [00:54:43]:
Is Apache still the primary web server being—

Leo Laporte [00:54:46]:
Nginx is, but it's open source.

Jeff Jarvis [00:54:48]:
Nobody—

Jeff Jarvis [00:54:49]:
no, it didn't hurt anybody.

Leo Laporte [00:54:50]:
Microsoft— well, it might have hurt Microsoft's closed source. Yes, Netflix too.

Jeff Jarvis [00:54:57]:
But so, yes, sorry.

Leo Laporte [00:54:58]:
Yeah, they couldn't— they probably don't make a lot of money on their, their web server. Uh, almost everybody uses open source web servers. But, um, I think in general, open source is, is has not replaced closed source software.

Paris Martineau [00:55:12]:
I mean, this is a very interesting take from someone at OpenAI, given those emails from Sam Altman that had come out recently in some lawsuits, I think somewhere in the rundown perhaps, where he in 2022 essentially said that, oh, we need to be developing and releasing some open source models for us from a strategic perspective.

Leo Laporte [00:55:34]:
Yeah, I thought that was kind of interesting. This is the email from 2022 to an OpenAI board member. This came out in the Musk versus Altman trial. That's how we know about it. Discovery is a wonderful thing. We have been having, writes Sam, extensive discussions around open source strategy. We'll discuss it more at our next board meeting. One thing we'd like to do soon is to create a language model with the approximate capability of GPT-3.

Leo Laporte [00:56:01]:
Oh, wow.

Leo Laporte [00:56:02]:
That which was at the time kind of the current best model, right? They can run, or maybe like the second best model, they can locally run on consumer hardware and release that. We'd like to do it soon before Stability or someone else does. Remember Stability AI? Remember them in general?

Leo Laporte [00:56:18]:
We—

Leo Laporte [00:56:18]:
whatever happened to them? We think this helps discourage others from releasing similarly powerful models and makes it harder for new efforts to get funded. They never did that. They didn't have to.

Jeff Jarvis [00:56:31]:
It was done for them. So in some indication of the fight that's going on here, the Undersecretary of Defense, Emil Michael, responded to Dean Ball's post saying, quote, every industry ecosystem has its supreme village idiot. Dean Ball is that for AI.

Leo Laporte [00:56:49]:
Emil Michael said that?

Paris Martineau [00:56:50]:
Wow.

Jeff Jarvis [00:56:51]:
Dean Ball has perhaps the biggest gap between actual IQ and his own perceived IQ of anyone in the industry.

Leo Laporte [00:57:00]:
Whoa!

Jeff Jarvis [00:57:00]:
Gives you some idea of the administration's reaction to—

Leo Laporte [00:57:03]:
Well, this is the problem. I think there is a lot of disagreement within the administration. There's people who are telling Trump, oh God, you've got to shut down these Chinese models, they're putting us out of business, and Emile Michael, who is in the administration, saying the opposite. I don't know. I don't know. I mean, we are very protectionist in this country. Look, you can't get a Chinese EV, which pisses me off every day.

Jeff Jarvis [00:57:29]:
I would kill to get a Chinese EV.

Leo Laporte [00:57:30]:
And the only reason is to protect—

Jeff Jarvis [00:57:33]:
yes, it's pure protectionism—

Leo Laporte [00:57:35]:
American automakers, chiefly Tesla. And it's, you know, yeah, it's not good for consumers. It's good for those companies.

Jeff Jarvis [00:57:43]:
It's not good for innovation and development. I mean, this is, this is Jensen Huang's argument, is that more And it's an obvious argument, and he's blunt about it. More open source AI means more chips.

Leo Laporte [00:57:54]:
Yeah, but let's talk about Jensen Huang, because he— you said that he isn't trying to protect his moat.

Jeff Jarvis [00:58:02]:
He's in favor of open source AI. He has Neutron. He—

Leo Laporte [00:58:06]:
that's true. He's got the only decent American open model. Llama's not. Neutron's the closest thing. This is from Axios. He told Mike Allen in an interview for the Behind the Curtain video series at Axios, these Chinese models are excellent. Open source models that are excellent should be used. Now, he wants to sell to China, we should point out.

Jeff Jarvis [00:58:31]:
He's the one— And thinks that by being forbidden to sell to China, that is what has opened the door for China to compete with both hardware and software.

Leo Laporte [00:58:40]:
And they have. They have. I don't know if the presumption that Moonshot used GB300s else from other, you know, stolen or from other countries is true, but I think Huawei trained, entirely trained Quen on Huawei chips. Maybe, yeah, they're not as good as NVIDIA chips, I'm sure that's true. And there'd be— and I have to say for sure they're running the inference, right? When I'm using GLM-52 on a Chinese server, I'm using Qwen-38 on a Chinese server. And so I'm sure they're not using NVIDIA.

Jeff Jarvis [00:59:22]:
Well, as we talked about some time ago too, China being a controlled economy can devote as much energy as it wants.

Leo Laporte [00:59:28]:
Exactly.

Leo Laporte [00:59:29]:
Plus, by the way—

Jeff Jarvis [00:59:29]:
It doesn't need to be efficient.

Leo Laporte [00:59:32]:
By the way, I would say this to the Trump administration, China is on the forefront of solar energy. They have plenty of energy. Because they support sustainable solar energy.

Jeff Jarvis [00:59:42]:
Hydro as well.

Leo Laporte [00:59:43]:
And hydro. In fact, most of their energy— they— I think more of their energy now is coming from sustainable sources than, than coal or fossil fuels. So, you know, if you, if you want to improve our economy, that might be a good way to start instead of shutting all this stuff down and making it better for oil producers. Scott Bessent told Fox Business that the administration is examining Chinese AI models for stolen intellectual property. He said, if we see that overseas models are stealing from our great companies, we have the ability to sanction them because of this theft, which has caused some people to say, download all the open models, get them all. Well, you can. You won't be able to run them locally, but—

Jeff Jarvis [01:00:32]:
I didn't see I didn't see reports on Xi's speech to the AI conference. Did you see more about that?

Leo Laporte [01:00:38]:
Yeah, let me see if I can find—

Jeff Jarvis [01:00:39]:
Tell me about that. I'd be eager to hear more.

Leo Laporte [01:00:42]:
Yeah, I'm going to— I could paraphrase it that he was very much, he said, for open weight models and spreading AI throughout the world.

Jeff Jarvis [01:00:54]:
So that seems to give lie to the speculation that he's going to shut down.

Nate B. Jones [01:00:58]:
Right.

Leo Laporte [01:00:58]:
And in fact, it could well be that that speculation is coming out of the US. Um, Xi positioned China as a leader of a new global AI order. This was— he was the speaker at the World Artificial Intelligence Conference in Shanghai on July 17th. He said open-source AI is a historic opportunity and warned that unequal access could create new global divisions.

Jeff Jarvis [01:01:22]:
Yeah.

Leo Laporte [01:01:23]:
Mm-hmm. His address linked China's expanding AI capabilities with a diplomatic strategy focused on developing economies. This is why I liken it to the Belt and Road Initiative. Asia, Africa, Latin America, and the broader Global South, the have-nots, right? He believes in technology sharing with the BRICS countries, the ASEAN countries, the African Union, the Latin American partners. I think this is very interesting. It's completely counter to the argument that they're going to shut it down.

Paris Martineau [01:01:56]:
Right.

Leo Laporte [01:01:57]:
This is where— this was the conference that Moonshot introduced Kimmy at, by the way.

Jeff Jarvis [01:02:01]:
Ah, okay. Well, that gives me some hope there. I don't know what the reaction of the markets will be.

Leo Laporte [01:02:11]:
It also pisses people off who really hate China.

Jeff Jarvis [01:02:14]:
Yeah, I want their cars, I want their AI.

Leo Laporte [01:02:17]:
I'm not a fan of repressive regimes.

Jeff Jarvis [01:02:20]:
I'm not either, but—

Leo Laporte [01:02:22]:
I understand that they are a repressive regime. But when they say something that makes sense, gotta acknowledge it. Meanwhile, we've got data center phobia going on. 142 protests this week against data centers across 42 states.

Jeff Jarvis [01:02:41]:
Jeez.

Leo Laporte [01:02:42]:
Our data, our tax dollars, our seized homes, our utilities. This was coordinated by Humans First. Co-founded by a former leader of the Tea Party. So you understand where this is coming from, who compares growing opposition to data centers to the right-wing populist movement that emerged in 2009 as the Tea Party. This is the new Tea Party. Protesters rallied against what humans first called the unaccountable build-out of data centers and unacceptable infringement on our liberty. We thrive on water, not data. You can't drink data.

Paris Martineau [01:03:23]:
Pretty Fly for a Sys Guy says, are they protesting all data centers or just AI data centers?

Jeff Jarvis [01:03:29]:
Right. That's the—

Leo Laporte [01:03:30]:
you don't want the internet?

Jeff Jarvis [01:03:33]:
You don't want your bank? Yeah.

Leo Laporte [01:03:35]:
I, you know, I understand. I, I wouldn't want a data center across the street from me. I completely understand.

Jeff Jarvis [01:03:42]:
Uh, could they be made better looking?

Leo Laporte [01:03:44]:
They could be made less polluting.

Paris Martineau [01:03:47]:
I mean, yeah, I think there's a lot of concerns with these, both, uh, from a, like, neighborhood perspective. Uh, they're an eyesore. They often have, you know, um, higher noise levels than some people maybe feel comfortable with or feel like they were informed about. Uh, communities often don't feel like they had any sort of— not that they were not informed beforehand that a data center would be coming. It's because a lot of these large-scale deals that tech companies end up striking to get tax breaks occur— the negotiations occur largely in secret. And that makes people in these sort of communities feel like they've been caught off guard whenever one— a deal is announced.

Jeff Jarvis [01:04:28]:
There's also just a general uglification going on with warehouses everywhere on top of data centers. There are these monolithic buildings that are just ugly as hell.

Leo Laporte [01:04:37]:
I understand. I really do.

Jeff Jarvis [01:04:38]:
It probably tanks your real estate value.

Leo Laporte [01:04:42]:
Yeah.

Jeff Jarvis [01:04:43]:
Well, especially if they use gas generators right next to you.

Leo Laporte [01:04:46]:
Yeah. All right, let's take a little break. We, uh, you're watching Intelligent Machines. Jeff Jarvis, Parris Martineau. So glad you're here. Benito Gonzalez, that's the voice from the Philippines joining us, our producer.

Jeff Jarvis [01:05:00]:
So Leo, Google's results are out.

Leo Laporte [01:05:02]:
Oh, you know, I was about to talk about Google because they've unaccountably renamed NotebookLM Gemini Notebook.

Jeff Jarvis [01:05:09]:
Somebody on the socials said that was the first good branding decision they've made in years.

Leo Laporte [01:05:13]:
Well, it is kind of— it's all Gemini now, but I feel like everybody knew what Notebook LM was. Maybe not, maybe not. Maybe we do because we talked about it so much. They also released new models, but everybody's saying, but where's, where's your high-end model? Their new models are flash, they're light, they're small models, and we're not seeing a Gemini 3.5 Pro.

Paris Martineau [01:05:36]:
I think that the thing that is the most useful about the NotebookLM name is, I was just talking about this with someone in journalism when I was talking, I was explaining to them NotebookLM and I was like, well, you know, it says—

Leo Laporte [01:05:47]:
They didn't know what it is.

Paris Martineau [01:05:49]:
Most people don't know what it is, Leo. And people who do might read the name and think, okay, it's another LLM. And then you have to explain the RAG of it all. And that's just, it is not particularly Gemini Notebook, probably in the long run. I mean, I dislike that Gemini is in there because I think that that implies more so that it's a gem, like part of the Gemini chatbot when it is—

Leo Laporte [01:06:15]:
I didn't ask Nate about this, but I think the general feeling about Gemini models is they're not that good. They're not—

Jeff Jarvis [01:06:23]:
I would've liked to have heard you on that.

Leo Laporte [01:06:25]:
They're not OpenAI Anthropic quality. quality, which is weird because Google has DeepMind. This all came out of Google. Transformers came out of Google.

Jeff Jarvis [01:06:35]:
It wasn't that long ago we said Google was ahead of the pack, so it just goes back and forth.

Leo Laporte [01:06:38]:
I don't understand why they're not. Well, we thought they might be ahead of the pack, then I tried the model and it was like, no, they're not. I have yet to see—

Leo Laporte [01:06:47]:
I mean, it's also—

Paris Martineau [01:06:47]:
I'm just curious as to why— how is Gemini lagging like this? What has led them— ostensibly, if you think about it from a resource perspective, who is better positioned to have access to training data than Google?

Jeff Jarvis [01:07:03]:
So what didn't work well about it, Leo? What was— what was—

Leo Laporte [01:07:06]:
It just isn't— I mean, you could— I— it's hard to describe because AI is so, as Nate said, jaggy. Uh, you know, the capabilities are good here and bad here and so forth. So it's really hard. I don't think benchmarks do it justice. I don't think think it's, it's very hard to evaluate an AI. So it's— anything I say is very subjective. It's very gut feel. It, it just didn't feel that smart.

Leo Laporte [01:07:31]:
And then occasionally you'll get a, a model doing something really dumb, and when you catch it doing that, my general reaction is, okay, I'm not gonna use you anymore.

Jeff Jarvis [01:07:42]:
Wow.

Leo Laporte [01:07:42]:
So, uh, I don't remember exactly what I didn't like about Gemini, but I, I never went back to it.

Jeff Jarvis [01:07:47]:
I have a $200 I think Nate made a very interesting proposition, um, saying that he wants the model to do one thing and then he wants a different model to do another task, another one, another task— the writer, the producer, the editor.

Leo Laporte [01:08:00]:
Well, that's, that's where everybody's going. I do that.

Jeff Jarvis [01:08:02]:
That's what you do now with your set.

Leo Laporte [01:08:03]:
Hermes does that, um, automatically. You have a delegation. Everybody's going to be talking about this, where you have a model for different— like, for vision recognition, I in fact do use Gemini Flash. Actually, I use a local model for my cameras. My security cameras go through a local Quen VL model that's very good. It's pretty funny. Calls me an older man though. I don't like that one cotton-picking bit.

Jeff Jarvis [01:08:31]:
Older than what?

Leo Laporte [01:08:33]:
It says, I see Leo, an older man with white hair, walking up the step. You thought age Wait till I get my son a hat, then you'll see something. So, but, but that's a little tiny, that's like a 4B. I don't even think it's that big, tiny little model running locally. You know what I did? I shouldn't. Well, I'll talk a little bit about what I, I feel like we should have a conversation about this. I was telling Jeff this. I feel like sharing what I'm doing with AI is like people talking about their dreams.

Leo Laporte [01:09:10]:
It's intensely interesting, the person talking about it, and it's like a snooze fest for anybody listening.

Jeff Jarvis [01:09:17]:
No, I— well, let's talk about that.

Paris Martineau [01:09:18]:
I don't think that's correct.

Jeff Jarvis [01:09:19]:
No, that's not really— I think it's— no, it's very interesting. And I, I, I will— I'm sorry, I apologize. I'll do it in public that I, I, uh, former Californian, I, uh, so they ridiculed the I Ching.

Paris Martineau [01:09:30]:
I've said it before and I'll say it again. I thought when you asked me what question should I ask, I Ching. What do you want to predict? And I asked for a podcast-related prediction that that was fitting the bill. I didn't realize that that was considered as insulting.

Jeff Jarvis [01:09:46]:
So I'm sorry.

Leo Laporte [01:09:46]:
I was not insulted. No, no, no. I was just trying to read the room and my— maybe I misread the room, but my sense was, oh, well, here I am talking about my dreams again.

Jeff Jarvis [01:09:56]:
What about what someone put online about your ad service, your ad strategy?

Leo Laporte [01:10:00]:
Well, that's kind of stalled out right now. Lisa said, I don't Oh no.

Jeff Jarvis [01:10:03]:
Well, I was gonna say it's fascinating.

Paris Martineau [01:10:06]:
Well, I think that's actually interesting. What does she not like about it? See, 'cause that's the thing is a lot of stuff that can seem technically as if it is on par with recreating another commercially available software made by AI, sometimes the vibes are just off.

Leo Laporte [01:10:22]:
It could well be. Vibes are everything. My premise on this, I, first of all, We have a 12-year-old sales system that's basically MySQL, .NET, and a bunch of queries. It breaks down a lot. It's very slow. We have to keep throwing more hardware at it, but it's what we've been using for 12 years and it's worked very well. And it does some smart things like rotates the ad positions so that an advertiser isn't always in the first position, things like that.

Nate B. Jones [01:10:55]:
Yeah.

Leo Laporte [01:10:56]:
like that. But, uh, you know, people have been complaining about it for 12 years. So, I thought this might be a good project for AI. And, uh, what I did was, uh, I thought, well, code is the best spec. You know, you can write a verbal spec, but honestly, a program, if you can look at the source code, is a really good spec for the next program, the next generation. So, I thought, well, I have the spec. I have the existing sales system. I have all the code, I have the database schema, I have everything.

Leo Laporte [01:11:29]:
Let me steer— let me give it to Fable, because this was when we first got Fable, and have Fable create a specification that we can then build on and improve. And the next step was then to go interview the users of this system, including Lisa, and Fable gave me questions to ask them, and I did all of that.

Leo Laporte [01:11:52]:
Wow.

Leo Laporte [01:11:54]:
It did a very complete specification. I also told it, I thought I'm being very smart here. I said, okay, I'm gonna have Fable, but I don't know for how long. So what I'm gonna do is have Fable, one model, do the spec, write out all the plans. I'm gonna have OpenAI's top model, 5.6 SOL, review it. I'm gonna have them go back and forth. It's kind of what Nate was talking about, but I did it.

Jeff Jarvis [01:12:20]:
Mm-hmm.

Leo Laporte [01:12:20]:
Poor man's version. I didn't have some big harness. I just said, tell, tell, tell— I call, uh, I have— they all have names. Kenobi is Anthropic and, uh, Daedalus is OpenAI. I said to Kenobi, tell Daedalus you're working on this, have it look at it. And then I gave them a mailbox so they could talk back and forth. I said, every 10 minutes, check the mailbox. And so they're talking back and forth, right? Reviewing it, changing it, reviewing it, changing it.

Leo Laporte [01:12:48]:
And then I was going to have the coding done because I thought FableEye would be either too expensive or gone. Um, I was going to have the coding done by Opus 4.8, which was— it still is the, the next level down from Anthropic. And that's what I've been doing. And the other thing I did, and this is— I've learned from long experience, you know, they always talk about one-shotting. I'm gonna give it a single prompt and have it do everything. And, uh, I don't think that's the best way to use an AI. I think a better thing is to divide it up into chunks you can review at every point. I really tried to engineer this properly.

Leo Laporte [01:13:23]:
And so we did that. We built something. And then I asked Lisa and Debbie to look at it. And they had a lot of input because it didn't do the UI at all. It just did the— it wanted to do the backend.

Nate B. Jones [01:13:34]:
functionality.

Leo Laporte [01:13:35]:
Which I thought was the right way to do it, but it was my mistake. So they reviewed it. I had them make videos as they reviewed it, 'cause I said, you can tell me that's not gonna be a good, that's gonna be telephone tag. You could record something, which we did with a Zoom call, but best thing to do would be you to go through the old system and the new system with videos and circle it. And by the way, Fable can look at these videos. I said, can you see what they're doing? And they said, yes, I can screenshot it. And so we did this whole back and forth. I have many, many videos, more than a dozen videos of them saying yes No.

Leo Laporte [01:14:08]:
Then I realized part of the problem was that the interface was so different. So a couple of nights ago I said, hey, you know what, make the interface identical to the old one. Maybe that'll make it easier for them to see what they want to have changed. That might have been a mistake.

Jeff Jarvis [01:14:23]:
The amount of detail— I just went through a few of the pages on the site.

Leo Laporte [01:14:26]:
Oh yeah, you can— if people want to see this, they go to pages.laporte.com.

Jeff Jarvis [01:14:31]:
And it's, and it's its own language.

Leo Laporte [01:14:33]:
Yeah.

Jeff Jarvis [01:14:34]:
Yeah.

Leo Laporte [01:14:34]:
So, this started with just these first few. And I told it, as you work, write these all up so that I can review it and a human could review it. And these are the questions it has. Yes, it's very detailed. There's code. There's everything here because I wanted to make sure it was fully documented, partly so that Daedalus could look at it. And you see, here's Daedalus's audit.

Leo Laporte [01:14:58]:
Wow.

Leo Laporte [01:14:59]:
credit of Kenobi's work and how Kenobi did it. So this is all fully documented right up to here.

Jeff Jarvis [01:15:06]:
Did you feel a little rushed because you were going to lose—

Leo Laporte [01:15:08]:
Yes. And that was the other— remember last week I showed you Super Dario as he keeps extending? The latest, by the way, is I'm not going to lose Fable. I'm going to get 50% on my subscription. I still have Fable. I could probably have done this all with Fable, but I like the model. I like mixing it By the way, I don't just have— I also have GLM-52 reviewing this, and I had Grok-45. So I have all these agents looking at it.

Jeff Jarvis [01:15:33]:
That's the easy part. It's your wife that's the hard part.

Leo Laporte [01:15:36]:
The human's the tough part. She's a tough— anyway, I will probably keep doing it. That's not the only project. I'll show you one more. You remember I like to make bagels, right?

Paris Martineau [01:15:47]:
Oh yes. Is this what led to that beautiful bagel pic you sent?

Leo Laporte [01:15:51]:
Oh, you saw my— you saw—

Paris Martineau [01:15:53]:
so listen, I don't get all the notifications.

Leo Laporte [01:15:54]:
That's okay, you got a job. I don't have a job.

Paris Martineau [01:16:00]:
It's true. I do get a— when I see a beautiful bagel pic, I've got to respond.

Leo Laporte [01:16:04]:
The bagels are fantastic. So, uh, our neighbor— I have a couple of kids live down the street, and I mentioned that I make bagels, and one of them said, oh, you know, I love bagels. I said, why don't you come over? You and your brother come over and I'll teach you how to make bagels.

Jeff Jarvis [01:16:17]:
I like this, the Mr. Wizard of bagels.

Leo Laporte [01:16:20]:
Yeah. Then I had a thought. I thought, you know, I could turn this into a teaching moment. I could actually do the chemistry of sourdough bagels. And then I did say something that worked out quite well. I asked my Hermes agent to make a comic book for the kids.

Nate B. Jones [01:16:39]:
What kids?

Leo Laporte [01:16:41]:
The kids. And by the way, it looks like—

Paris Martineau [01:16:43]:
The general kids.

Leo Laporte [01:16:44]:
That kind of looks like me, right? It's supposed to look like me. And that looks like Sarah and Matt. And it's on the chemistry. They even made it— the whole thing, this is a one-shot prompt. It made up superheroes. That's yeasty and lacto. That's Glutennet. There's amylase, there's Maillard, and there's the final one that's lye.

Leo Laporte [01:17:04]:
What's the pickle doing there? And safety first.

Jeff Jarvis [01:17:05]:
Why is there a pickle?

Paris Martineau [01:17:06]:
Yeah, what's the pickle?

Leo Laporte [01:17:07]:
The pickle, that's a bacterium. That's lacto.

Paris Martineau [01:17:09]:
But it's a pickle.

Leo Laporte [01:17:10]:
It's a lacto— well, it does look like a pickle, but it's actually a Lactobacillus bacterium. That makes the tangy sourdough taste. Explains all of it.

Jeff Jarvis [01:17:18]:
Now this is something we can get behind, Leo.

Leo Laporte [01:17:20]:
This is so good. It made up— it did this perfectly. It gave them little assignments. It has cute little pictures of all the things going on. It has a dialogue. We're eating microbe poop? And then I say, yes, welcome to all of cooking. Sugar plus CO2— sugar goes to CO2 plus ethanol plus energy. It is a chemistry lesson.

Leo Laporte [01:17:43]:
This came all I was stunned. This came off beautifully. So this is a really good example again of, I think, how you could use AI. What was your prompt for that?

Jeff Jarvis [01:17:55]:
How much, how much was the prompt?

Leo Laporte [01:17:56]:
It wasn't very— I will, uh, I can— I have it. I saved it because I was really curious if it could do it. I didn't know I would.

Jeff Jarvis [01:18:02]:
Which model did that again?

Leo Laporte [01:18:05]:
Um, I think GLM-5-2. But remember, it has other tools it can use. So I, I don't— it probably used Google for the image generation. Anyway, it was maybe a paragraph, something like, I'm about to cook bagels with Sarah and Matthew. They're 8th— actually, I said they were 7th graders and I forgot they had graduated. They're 8th graders. And so, I had them— it changed it. And I want to make it kind of a chemistry lesson.

Leo Laporte [01:18:34]:
So, can you make a comic on the chemistry of sourdough bagels? That was pretty I didn't tell it what the chemistry was. I didn't tell anything else. Then I got pictures of them, and I got a picture of me, and I got pictures of my bagels, the one I sent to you. So I said, make sure it looks like my bagels, and it looks like me, and it looks like them. And it does. I mean, in a comic book fashion.

Jeff Jarvis [01:18:54]:
That bagel you had is gonna fail any drug test. Doesn't it?

Leo Laporte [01:19:00]:
Don't those bagels—

Paris Martineau [01:19:00]:
but they look pretty good. They look fantastic.

Jeff Jarvis [01:19:02]:
They look great.

Leo Laporte [01:19:02]:
They look like my bagels. It looked— that's exactly what they looked like. Oh, I sent it the video too. Remember we did a video with the club of me making bagels and I sent it the video. So, it knows what the bagels look like in the pot when they're boiling. It knew. So, it was able to modify. This is a modified second-gen version.

Jeff Jarvis [01:19:19]:
Did you tell it to be careful with the lye?

Leo Laporte [01:19:21]:
So, here's the funny thing. So, we got an 8th grade boy. I thought, you know what? Let's make some danger. I did not tell it. It decided to do a whole thing on lye safety.

Paris Martineau [01:19:31]:
Oh, wow.

Leo Laporte [01:19:32]:
Because I knew that would make Matthew happy. Oh, this is dangerous?

Leo Laporte [01:19:36]:
Yeah.

Leo Laporte [01:19:37]:
I don't know if his parents will be happy about it. Anyway, fun project. So there's a couple of projects. And you know what? That one thing Gemini might've helped out with, I really love Nano Banana. I think it's a very good image model and it might have. I could probably go back through the transcript and find out what tools it uses. I know I I could. Um, but how were Google's results? But before we do that, you're watching Intelligent Machines with Paris Martineau.

Paris Martineau [01:20:09]:
And when we come back, I've got an update on the AI corn situation.

Leo Laporte [01:20:13]:
And oh, the corn!

Paris Martineau [01:20:16]:
That your, your, uh, rabbit hole led me to wonder what's up with Proof.

Leo Laporte [01:20:21]:
What's up with the corn?

Paris Martineau [01:20:22]:
I've got a response for you after this Or not. Or not. Oh, I can. Okay.

Leo Laporte [01:20:28]:
No, no, no. Or not. No ad break, because there is in fact no ad, uh, except there might be because— but you don't need to know this— but we insert ads sometimes after the fact.

Paris Martineau [01:20:37]:
Hey, there could be an ad break or there couldn't.

Leo Laporte [01:20:41]:
It's hard because there's never a video ad break. So if you're watching the video, we have to make it seamless that we're going through it. So it's just a reintro. I say, you're watching Intelligent Machines with Geoff and Paris. And now we continue with the Google results. So that's seamless. But if they stick an ad in the audio, it also has to work there.

Jeff Jarvis [01:21:03]:
Oh, I see.

Leo Laporte [01:21:04]:
I never explained that, did I?

Jeff Jarvis [01:21:05]:
No, you didn't.

Paris Martineau [01:21:06]:
No, no, I kind of figured it out along the way, but I thought that's because it was a real ad break. Well, I've also figured it out because some podcasts I listen to don't do that, and they'll just be in the middle of a sentence and suddenly it will be an ad, and I'm get very angry. So if you recall, some months ago, we visited a little website called proofofcorn.com.

Leo Laporte [01:21:25]:
I love this idea.

Paris Martineau [01:21:26]:
Someone was siccing a Claude agent on trying to get corn to be sold at Union Square Farmers Market in early August. And it— put it on it— it has been a complete failure. There have been Uh, what was the last update? It's like— here it is.

Leo Laporte [01:21:48]:
Um, they had trouble at, uh, what, finding somewhere to plant it? What was it?

Paris Martineau [01:21:53]:
They had trouble finding, finding a person to plant it, finding the plot of land. It seems to have gotten stuck in some sort of email loop, but it's also confusing because the front of the webpage says the target is August 2nd. Sweet corn's planted and growing at Nelson Family Farms in Humboldt County, Iowa, on track for the farm crew. Next up, harvest. But then if you look up, it says the last action was 89 days ago, where it said emergency escalation continues. Project remains in critical failure state after 5 consecutive days of emergency decisions without seed purchases. And if you look at the full decision log, it does not appear that the corn has—

Jeff Jarvis [01:22:34]:
What did it say about Fred Wilson? That's a famous No, that's just—

Leo Laporte [01:22:38]:
Fred Wilson is the name of the farmer.

Paris Martineau [01:22:41]:
Yeah. Or no, Fred Wilson, the venture capitalist. No, Fred Wilson challenged Seth, the guy who ran this. AI can write code, but it can't affect the physical world. And so Seth, ah, Seth built the Claude Code, uh, corn farm.

Leo Laporte [01:22:58]:
Well, here's the good news. He's only spent $12.99. The bad news is, for many weeks, nothing has happened.

Jeff Jarvis [01:23:09]:
Nothing.

Paris Martineau [01:23:10]:
Poor Farmer Fred.

Jeff Jarvis [01:23:11]:
Yeah.

Paris Martineau [01:23:12]:
It's also unclear how much they've spent because, uh, the— if you go on the dashboard, it says the total investment's been $112.99.

Leo Laporte [01:23:21]:
Oh, so there's errors.

Paris Martineau [01:23:22]:
It's still not much. It just— it all seems to be a bit nightmare, or a bit It's a bit convoluted. And the one thing I can say is it seems unlikely that corn will be at Union Square next week.

Leo Laporte [01:23:34]:
I don't think it even got— it's unclear whether it got planted. The last post from June 15th said, continue prioritizing response to Dan Nelson's monitoring equipment inquiry while maintaining post-planning operations monitoring. But I don't think they ever really planted.

Jeff Jarvis [01:23:49]:
Well, plus Iowa, why would you plant corn in Iowa for New York when you're next to New Jersey, folks?

Paris Martineau [01:23:56]:
I think a lot of people forget that corn can be grown elsewhere.

Leo Laporte [01:23:58]:
We have corn down the street growing. It grows quite well in Petaluma.

Paris Martineau [01:24:03]:
There, um, if you go on the dashboard, you can prompt Fred to act by clicking a button called Ask Fred to Act. And I did that and it went, Fred's decision, internal error. So—

Leo Laporte [01:24:15]:
I think it's broken.

Jeff Jarvis [01:24:17]:
Yeah.

Leo Laporte [01:24:17]:
And I think, uh, it was Fred Wilson who challenged him. So it was the Fred Wilson, I think. I think, who challenged them. But Seth, I think, maybe was the wrong kind of challenge because the last post on X was, weather's perfect for planting in Iowa.

Jeff Jarvis [01:24:33]:
Too bad we don't have any. 2 months ago.

Paris Martineau [01:24:35]:
Or a month ago.

Leo Laporte [01:24:36]:
They have 144. We're just getting started. It knows the weather. That's about it. I think the real problem was they couldn't get any human to do it.

Paris Martineau [01:24:47]:
I mean, yeah, it seems like it totally failed in the outreach of trying to get a Human involved to actually— because they needed to find a field, somehow rent or purchase some space on a field, get a human with actual equipment out there to also have purchased corn and plant it, till the fields, water it. There's a lot of physical steps.

Jeff Jarvis [01:25:11]:
There's a lot of work there.

Leo Laporte [01:25:12]:
Do not take this as a failure of AI. Do not be dismayed. Take this as a failure of Seth. Seth didn't do a good job.

Jeff Jarvis [01:25:20]:
Maybe if they just had an open eye.

Paris Martineau [01:25:20]:
Come on the podcast and tell us about why you couldn't eat the proof of corn.

Leo Laporte [01:25:25]:
Oh, let's track down Farmer Fred and Seth. We can have a little interview.

Paris Martineau [01:25:28]:
He's @Seth on, uh—

Leo Laporte [01:25:29]:
Oh, I'm gonna tweet him right now because you know I am a blue check.

Paris Martineau [01:25:34]:
It's true. And that means—

Jeff Jarvis [01:25:37]:
And I know Fred Wilson too.

Leo Laporte [01:25:39]:
Well, there you go. Let's track it down. Uh, Jeff, you said the Google, uh, results are out.

Leo Laporte [01:25:44]:
Yeah.

Leo Laporte [01:25:44]:
Let me just guess, they made more money than God on Not AI. Advertising.

Jeff Jarvis [01:25:52]:
Hosting. Hosting posted 24% revenue growth year over year in the second quarter, fueled by its booming cloud business. But concerns over the company's heavy spending on artificial intelligence infrastructure dampened investors' enthusiasm. Yeah, Alphabet sales came in at $119.8 billion, exceeding analysts' expectations, but not by enough. Cloud business brought in $24.8 billion, search $63.3 billion.

Leo Laporte [01:26:20]:
They're down $4.

Jeff Jarvis [01:26:24]:
Um, but as the— yeah, they're down about 4% last I looked at that drop.

Leo Laporte [01:26:29]:
Boom.

Jeff Jarvis [01:26:29]:
But what's interesting to me here, Leo, if I can tie this to something else, is the hosting business. Meta is now those who can do, those who can't host. So Meta is now renting out the infrastructure it bought. SpaceX is renting out the infrastructure it bought. Google's making a lot of money from the infrastructure it bought. Well, think who they're selling to.

Leo Laporte [01:26:56]:
What a great way to make money. It's same thing as Levi's selling the jeans and the picks and the axes to the— in the Gold Rush.

Jeff Jarvis [01:27:02]:
But if what you're selling to is companies that are about to be threatened by cheap Chinese Chinese imports. Uh-oh, SpaghettiOs.

Leo Laporte [01:27:08]:
Meta's deal with Anthropic, potentially $10 billion according to the New York Times. Um, that's what happens when you buy a lot of infrastructure and you can't use it. Didn't, didn't Mark spend a lot of money on, on talent buying Manus? And what happened with all of that?

Jeff Jarvis [01:27:27]:
Yep. But so now he's renting out and the stock is up because he's renting out the infrastructure.

Nate B. Jones [01:27:36]:
Hmm.

Leo Laporte [01:27:36]:
Selling excess computing power to companies like Anthropic, the Times writes, could provide Meta with a new revenue stream until demand for its own AI services catches up, which I'm gonna say— I mean, go out on a limb here—

Jeff Jarvis [01:27:50]:
is gonna be a while.

Leo Laporte [01:27:54]:
Uh, wow. On recent calls with investors, Zuck hinted that selling computing power could be one way for Meta to see some return on the AI That's a, that's a, that's a good point.

Paris Martineau [01:28:04]:
I mean, that's not great. I was going to say, if the way that you're going to see a return on investment is by selling computing power, that's rough.

Leo Laporte [01:28:15]:
Yeah. Anyway, well, good luck. I'm glad Google made money. I'm not surprised. Not surprised at all. We, you know what, the thing we don't know, I know we talked about this last week, I still don't think we really know what the true financials are of any of the AI companies. I know Ed Zittrain got the insight.

Paris Martineau [01:28:35]:
Well, Ed Zittrain and the Financial Times got it. So they both independently—

Jeff Jarvis [01:28:39]:
Slightly different interpretations, but yeah. But they're spending things on, I mean, there are tens of millions of dollars on things like midterm campaigns. They're spending money on odd things for companies whose profitability is not sure.

Leo Laporte [01:28:53]:
Well, because they see that government is willing to put its thumb on the scale on their behalf.

Jeff Jarvis [01:28:57]:
Yeah.

Leo Laporte [01:28:58]:
So of course the best way to spend your money is on government.

Jeff Jarvis [01:29:03]:
We also had OpenAI employees started their own PAC to counteract their CEO's PAC.

Leo Laporte [01:29:12]:
Right.

Leo Laporte [01:29:14]:
Well, another way to spend money would be to give authors $1.5 billion, and that's exactly what Anthropic is going to do. The settlement has now been approved by the judge.

Jeff Jarvis [01:29:25]:
The lawyers got cut at the knees.

Leo Laporte [01:29:28]:
Oh, really?

Jeff Jarvis [01:29:29]:
Oh yeah, they got cut way back.

Leo Laporte [01:29:31]:
Uh, authors opposing the settlement argued lawyers' fees were too high. Remember, that's what stalled it. And the payouts were too low. Uh, it was going to be $3,000 per work. Uh, the judge overruled objections to the settlement as lacking merit. She emphasized about 95% of the class received notifications. Approximately 91% of the authors and publishers impacted have already file claims. I did not.

Jeff Jarvis [01:29:56]:
I did, but I'll give them that.

Paris Martineau [01:29:58]:
Wow, you're so noble letting the companies keep that money. That'll really show them.

Leo Laporte [01:30:05]:
Well, no, I'm thrilled that they took my crappy old books and—

Jeff Jarvis [01:30:09]:
I am too.

Leo Laporte [01:30:11]:
Only 350 class members opted out. That means, I guess, after they joined the class, right? They don't know that I opted out because I never joined the class.

Paris Martineau [01:30:19]:
Well, no, if you opted out, that's probably Probably one of what they're referring to.

Jeff Jarvis [01:30:23]:
I kept getting notices that I should join in for a book for which I wrote the foreword, so it wasn't my book.

Leo Laporte [01:30:28]:
Yeah. I never even did the search to find out if my books were in it. Can you still do that search? Is that still around? I think so.

Paris Martineau [01:30:36]:
How did you opt out if you didn't know your books were in it?

Leo Laporte [01:30:39]:
I didn't opt out. I just didn't opt in.

Jeff Jarvis [01:30:41]:
You just didn't.

Jeff Jarvis [01:30:41]:
You just didn't.

Paris Martineau [01:30:41]:
No, you, you have to opt out, I believe.

Leo Laporte [01:30:44]:
No, you mean I, I might get money even without saying I, uh, I opt In?

Jeff Jarvis [01:30:49]:
Um, I had to fill in a form and stuff.

Paris Martineau [01:30:52]:
Okay.

Leo Laporte [01:30:52]:
Yeah, I think so. I remember in the big PopChip settlement case where PopChip was accused of something, false advertising or something, I actually had to say, no, I want some money. And I did in fact get a bag of PopChips for free.

Paris Martineau [01:31:10]:
Wait, as a response to the settlement, they gave you more of the product involved in the settlement?

Leo Laporte [01:31:16]:
It's, it's, it's my, uh, I consider that, uh, my, uh, my lesson in how all of the economics of class action lawsuits work. You get all that in a bag of Popchips. Uh, Anthropic author search. Let me see if I can, I can find it. Here's the settlement website. It's probably too late, right? Oh, here it is. Works list lookup. Search by author.

Leo Laporte [01:31:46]:
Wait a minute, this is—

Jeff Jarvis [01:31:46]:
You gotta click on the search by author.

Leo Laporte [01:31:48]:
Okay.

Jeff Jarvis [01:31:48]:
Nope. Yes.

Leo Laporte [01:31:49]:
Leo Laporte. That's me. Oh, uh, one's my dad. Oh, my dad, Leo F. Laporte.

Jeff Jarvis [01:32:01]:
Well, but yeah, you should file for your dad.

Leo Laporte [01:32:04]:
But, but this one from Q Publishing, my 2006 Gadget Guy. Boy, they don't have my best books. They only have 2 of my books, not the best books.

Jeff Jarvis [01:32:15]:
Yeah, they only had 2 of mine.

Leo Laporte [01:32:16]:
Yeah, and then, uh, they should have really gotten all the other almanacs. Those are much better for ingesting. And then a book I wrote a foreword on with Mikkel Olin, the sauna guy, actually. Ah, his name comes up twice in one show.

Jeff Jarvis [01:32:30]:
Wow, I think we need a sauna show.

Leo Laporte [01:32:32]:
Oh man, I think I need a sauna.

Paris Martineau [01:32:35]:
We should record the sauna show in the Yeah, exactly.

Leo Laporte [01:32:37]:
You know what, Paris? I think we are, uh, somehow related because between drip, pour-over, and sauna, there's no way that multiple—

Paris Martineau [01:32:47]:
that people in the US could love—

Leo Laporte [01:32:49]:
that's a unique intersection of interests. Um, how's your pour-over going, by the way? You nailed it.

Paris Martineau [01:32:56]:
I've been a little, uh, off it lately because it's hot, so I've been kind of cold brewing.

Leo Laporte [01:33:01]:
Yeah.

Leo Laporte [01:33:02]:
Yeah, cold brewing, that's cool. But I have, I have got my formula. In fact, I just got some new beans that I can't wait to see.

Paris Martineau [01:33:09]:
What beans did he get?

Leo Laporte [01:33:10]:
Uh, I don't know, they're downstairs.

Paris Martineau [01:33:12]:
Plug your ears.

Leo Laporte [01:33:14]:
Poor Jeff.

Jeff Jarvis [01:33:14]:
It's okay, it's okay.

Leo Laporte [01:33:15]:
He joined. We started a separate, uh, WhatsApp for Coffee Talk and he—

Jeff Jarvis [01:33:20]:
I joined.

Leo Laporte [01:33:20]:
You haven't joined it, Paris, but he did.

Paris Martineau [01:33:21]:
I didn't know that there was a separate— I don't, I don't use WhatsApp, guys.

Leo Laporte [01:33:27]:
Oh, okay, we can use We can use something else. We can use Signal or something.

Paris Martineau [01:33:30]:
I mean, it's fine. I just— send me the— what's— send me the coffee chat one. I didn't know that existed.

Leo Laporte [01:33:38]:
I sent you an invite, but that's okay.

Paris Martineau [01:33:40]:
Wait, let me— let me— where are you?

Leo Laporte [01:33:45]:
If you want, I can run down and give you a page.

Paris Martineau [01:33:46]:
Oh, I see it. Oh, I see it now. So I was wondering why we have our group chat as a community rather than just a normal chat where I can get in Normalification.

Leo Laporte [01:33:54]:
It's the way it is, I guess. So their beans are in the mailbag— mailbox. I, I've been looking for a good bean subscription. I decided based on references from Reddit, the Pour Over subreddit, which you're right is a—

Paris Martineau [01:34:09]:
The Pour Over subreddit is where it is, and it will drive you crazy in a way that you didn't know was possible before.

Leo Laporte [01:34:17]:
I have now 3 different Herrios.

Paris Martineau [01:34:23]:
I hope one of those is not— I hope that you at least have one that's not plastic.

Leo Laporte [01:34:26]:
I did not get a Switch. I listened to you. Well, it's resin. What is that? I have one glass, one metal, one resin. But everybody says the Neo. Everybody's saying, oh, the Neo, you gotta get the Neo. And that's a resin one. Uh, and I've got the Abaco white filters because everybody said that.

Leo Laporte [01:34:42]:
So now I have—

Paris Martineau [01:34:43]:
The Abaco filters are significantly better, I will say.

Leo Laporte [01:34:45]:
Yes, I thought they're quite good.

Paris Martineau [01:34:46]:
Are you using, uh, Third-wave water. I'm contemplating getting specific drops to put in my water.

Leo Laporte [01:34:53]:
People put additives into their water.

Paris Martineau [01:34:55]:
Well, no, there's already additives in your water.

Leo Laporte [01:34:58]:
Is the thing is your water already has a mineral mix.

Jeff Jarvis [01:35:01]:
I know.

Paris Martineau [01:35:01]:
And it's like, do you want to choose the mineral mix that you've got in your water?

Leo Laporte [01:35:04]:
So what I do is I, I, uh, I have a— it's like a Brita, but it's not. It's BWT. It's made for coffee filter. I told you this before. It filters the water and then adds magnesium, adds 2 minerals, I think magnesium and zinc.

Jeff Jarvis [01:35:20]:
I think—

Leo Laporte [01:35:20]:
I can't remember what the second filter, but it's for coffee. It was the Coffee Geek said, get this, Matthew Prince, Mike Prince, Mark Prince. Sorry, Mark Prince. There's many princes in the world, but that's the one.

Jeff Jarvis [01:35:31]:
Only a few kings.

Leo Laporte [01:35:32]:
I know, I'm sorry. God, where are we? Um, 2 authors. Okay, uh, yeah, the people who opted were people who opted in at first but didn't want to participate because they felt like they weren't getting enough.

Jeff Jarvis [01:35:47]:
Yeah, they could still sue. Yeah, that's the opt-out.

Leo Laporte [01:35:50]:
That's the opt-out. Uh, and anyway, so the rest are getting $3,000, Jeff? Is that how it works?

Jeff Jarvis [01:35:56]:
I think that's what it is.

Leo Laporte [01:35:56]:
Per work.

Leo Laporte [01:35:57]:
So I could have had $6,000.

Jeff Jarvis [01:36:00]:
Well, um, no, I actually think it's split with the publisher.

Leo Laporte [01:36:04]:
Uh-oh.

Leo Laporte [01:36:05]:
And then of course the lawyers.

Jeff Jarvis [01:36:07]:
No, well, that's a separate— I think it's $3,000 per book after the lawyers' fees. After the lawyers.

Leo Laporte [01:36:13]:
Okay.

Jeff Jarvis [01:36:14]:
Which might be better than $3,000 now because the lawyer fee went way down. I don't know if that story has it.

Leo Laporte [01:36:20]:
And speaking of money, uh, so that's $1.5 billion out. Let's keep a ledger. Here's $5 billion in. AMD is committed to $5 billion for Anthropic. Anthropic will employ— deploy up to 2 gigawatts of AMD's AI GPUs. These are not These are not CUDA cores. These are not NVIDIA chips. These are AMDs.

Jeff Jarvis [01:36:43]:
This is a circular investment, isn't it? So AMD is paying Anthropic to use AMD chips in their—

Leo Laporte [01:36:52]:
Yeah, I guess it is circular. They're also going to do a multi-year engineering collaboration. I use AMD GPUs. I wish I could afford the NVIDIA ones. And now we're learning that the NVIDIA, new NVIDIA data Ada chips are very efficient. We're starting to see numbers from— is it Vera Rubin?

Jeff Jarvis [01:37:14]:
That's the next one.

Leo Laporte [01:37:16]:
It's the next one after Vera Rubin, which won't be out for a couple of years.

Jeff Jarvis [01:37:19]:
No, Vera Rubin is— That's the one in production now. Yeah.

Leo Laporte [01:37:22]:
Okay. Is like 1/10 the energy usage of current.

Paris Martineau [01:37:26]:
Yes.

Jeff Jarvis [01:37:26]:
That's been his argument in his— Justin Wong's argument in his keynotes is that the way that you get more compute out is by lowering the energy cost.

Paris Martineau [01:37:38]:
Huge.

Leo Laporte [01:37:38]:
That, that is a massive improvement if that's the case.

Jeff Jarvis [01:37:43]:
Are they still making graphics cards for regular people? No.

Leo Laporte [01:37:47]:
If they did, you couldn't afford it. I'm sure that— I'm sure you could. Yeah, you can buy a 5090. You can make that—

Jeff Jarvis [01:37:53]:
What's the—

Jeff Jarvis [01:37:54]:
what's the graphics? That's the previous generation. Where's the next generation? Like, we're, we're due. We were supposed to be due for that this year or next year.

Leo Laporte [01:38:02]:
Well, how many voxels do you need? So the 5090s—

Jeff Jarvis [01:38:06]:
It's for you too.

Leo Laporte [01:38:07]:
It's to process AI.

Jeff Jarvis [01:38:08]:
It's for you too.

Leo Laporte [01:38:11]:
Yeah. I mean, you could— a lot of people use 5090s, multiple 5090s for, uh, but they're $2,000 each. And, you know, you'd have to have a motherboard that could keep them cool.

Jeff Jarvis [01:38:20]:
And you're talking about the top though. You know, there's going to be the 6070 and stuff like that, or there should be if they're still making those.

Jeff Jarvis [01:38:27]:
So what's SIGGRAPH?

Leo Laporte [01:38:28]:
Isn't That graphics special interest group for graphics.

Jeff Jarvis [01:38:33]:
Well, NVIDIA had a whole keynote just for SIGGRAPH. Huh.

Leo Laporte [01:38:38]:
They still, you know what, they're, they're just hedging their bets. They're saying, well, you know, maybe this AI thing won't really pan out. So just in case, graphics professionals, you ought to be using ours as well. Join NVIDIA at SIGGRAPH. Was Jensen there? Because this is not— no, no, yeah, they didn't send the top guy. Notice.

Jeff Jarvis [01:39:01]:
But they're doing— well, one thing they're doing at SIGGRAPH is physical AI.

Leo Laporte [01:39:05]:
Oh, and let's— you know what, let's not forget they're also doing video. I mean, they really are. This is really AI. Uh-oh, we're putting Paris to sleep. Okay, quick, move along.

Paris Martineau [01:39:17]:
Oh, you're not putting me to sleep. I just haven't slept well.

Leo Laporte [01:39:20]:
Tell us the latest on explosive diarrhea.

Paris Martineau [01:39:25]:
We can't cannibalize my pick of the week, guys.

Leo Laporte [01:39:28]:
Oh, okay, that's a tease. Coming up, explosive diarrhea, next after this word from a sponsor who wishes they weren't here right now. Okay, are we— have we gone through all of the stories?

Jeff Jarvis [01:39:44]:
Can we play? Can we— is it— this video we can play? Elon's version, a historically accurate version of the myth of the Odyssey.

Paris Martineau [01:39:53]:
Is it just nothing?

Leo Laporte [01:39:55]:
Because we didn't have cameras back then? He did it with Grok.

Jeff Jarvis [01:40:00]:
Grok.

Jeff Jarvis [01:40:01]:
Yes. So this is the scene.

Leo Laporte [01:40:03]:
I will return. I left my one love.

Jeff Jarvis [01:40:07]:
Yeah, it's just dreadful.

Paris Martineau [01:40:10]:
Why are they speaking Why is it in English if it's supposed to be historically accurate?

Jeff Jarvis [01:40:14]:
What's historically accurate?

Leo Laporte [01:40:15]:
There's no history. This is all made up anyway.

Jeff Jarvis [01:40:18]:
Uh, yeah.

Nate B. Jones [01:40:18]:
The sea took my ships.

Leo Laporte [01:40:20]:
Oh yeah, they're— oh yeah, sure, sirens. Those are real.

Paris Martineau [01:40:23]:
Mm-hmm.

Nate B. Jones [01:40:23]:
9 days adrift.

Leo Laporte [01:40:26]:
Now here— I have a hole in my shirt.

Paris Martineau [01:40:29]:
Stranded.

Leo Laporte [01:40:30]:
And here she comes, Helen of Troy.

Jeff Jarvis [01:40:33]:
No, this is, uh—

Leo Laporte [01:40:34]:
She fed him a potato chip.

Paris Martineau [01:40:35]:
Potato chips were really—

Jeff Jarvis [01:40:37]:
Yeah, that's a Pringle. I think it's a Pringle.

Leo Laporte [01:40:40]:
It was a perfect potato chip. This is such crap.

Jeff Jarvis [01:40:44]:
Oh, it's awful. Wait a minute though, there's one line of dialogue that's killer.

Leo Laporte [01:40:50]:
Send him home!

Jeff Jarvis [01:40:54]:
This is awful.

Paris Martineau [01:40:55]:
Yeah, not—

Jeff Jarvis [01:40:56]:
and by the way, does she look Greek?

Leo Laporte [01:40:58]:
No, she's redhead.

Jeff Jarvis [01:41:00]:
The whole complaint here is they have a Black woman as—

Paris Martineau [01:41:03]:
It's also an orally—

Leo Laporte [01:41:05]:
it's a It's made up anyway. Is this the line?

Jeff Jarvis [01:41:10]:
She's gonna say, spend one more night under my roof, and he's gonna say, okay, build your raft.

Leo Laporte [01:41:16]:
Be free, Odysseus.

Nate B. Jones [01:41:19]:
No, you mean some other thing, not my passage.

Paris Martineau [01:41:24]:
Oh wait, we can't watch any more of this.

Jeff Jarvis [01:41:26]:
It's almost over, Paris.

Leo Laporte [01:41:29]:
Would have been better with—

Paris Martineau [01:41:30]:
sticks itself.

Leo Laporte [01:41:31]:
Nicolas Cage, right?

Paris Martineau [01:41:32]:
I mean no harm to you.

Nate B. Jones [01:41:36]:
Then at first light, I cut the timber.

Leo Laporte [01:41:41]:
This is so god-awful.

Leo Laporte [01:41:42]:
Isn't it?

Leo Laporte [01:41:45]:
Oh, lipstick's also a little bad.

Paris Martineau [01:41:48]:
Keep this house.

Leo Laporte [01:41:48]:
And every time they talk, it's— you can hear the agent in the background.

Paris Martineau [01:41:53]:
Yeah. Is she worth all this grief?

Jeff Jarvis [01:41:58]:
Grog thinks acting is long pauses.

Paris Martineau [01:42:03]:
I am not less than— And whispering.

Nate B. Jones [01:42:07]:
And still.

Jeff Jarvis [01:42:08]:
And emphasis.

Nate B. Jones [01:42:10]:
Every day, all I want is home.

Jeff Jarvis [01:42:13]:
My wife.

Leo Laporte [01:42:16]:
My own halls.

Jeff Jarvis [01:42:21]:
Look at the tear.

Leo Laporte [01:42:23]:
Here comes, here comes. Oh, what's he doing? Is he picking her nose?

Paris Martineau [01:42:28]:
Did he boop her?

Leo Laporte [01:42:30]:
He booped her.

Paris Martineau [01:42:32]:
Please just come out of the sun. One more night under my roof.

Leo Laporte [01:42:39]:
No.

Jeff Jarvis [01:42:41]:
Yes.

Leo Laporte [01:42:41]:
Okay.

Jeff Jarvis [01:42:42]:
Okay.

Leo Laporte [01:42:43]:
Yeah, you know, the Greeks said that a lot.

Jeff Jarvis [01:42:45]:
Was that not worth it?

Leo Laporte [01:42:46]:
Okay, one more night. Under my roof.

Jeff Jarvis [01:42:50]:
Okay, okay.

Leo Laporte [01:42:53]:
The funny thing is, first he goes, no. Okay, Grok. You know what, Grok must have been trained on Elon. Okay, uh, yeah, yeah, that's pretty hysterical that Elon would even post that as some sort of advertisement for Grok's ability to make—

Paris Martineau [01:43:14]:
Did Elon post that?

Jeff Jarvis [01:43:15]:
I don't Yeah, oh no, Elon posted above that saying, oh boy, we're gonna make the whole movie historically accurate.

Leo Laporte [01:43:23]:
Oh, they did 2 hours of that?

Jeff Jarvis [01:43:25]:
No, they're going to.

Leo Laporte [01:43:26]:
Oh please. And it isn't historically accurate because there's no history.

Jeff Jarvis [01:43:31]:
I remember—

Jeff Jarvis [01:43:31]:
Historically accurate about gods and sirens.

Leo Laporte [01:43:33]:
We were, uh, we were traveling through the area and we decided to go on a trip to Troy where, where Schliemann discovered the city of Troy, except, yeah, maybe it's Troy. We don't know. It's just some old ruins. It could be Troy. But the Turks are no dummies. They built a giant wooden horse. So you're really pretty sure it's gotta be Troy until you look into it. And like, Schliemann had no idea.

Leo Laporte [01:43:58]:
They just made it up. All right.

Jeff Jarvis [01:44:03]:
All right. Okay.

Jeff Jarvis [01:44:03]:
Thank you. I wanted that.

Leo Laporte [01:44:04]:
I'm glad we got that in.

Paris Martineau [01:44:06]:
Yeah, it's really important.

Jeff Jarvis [01:44:07]:
It's about— it's a cultural moment for AI.

Leo Laporte [01:44:09]:
The torture Paris moment we look forward to every episode.

Paris Martineau [01:44:13]:
Hey, at least it wasn't an advertisement.

Leo Laporte [01:44:16]:
Could have been an ad.

Paris Martineau [01:44:18]:
We could have watched an ad together, and we still could.

Leo Laporte [01:44:22]:
It's not over.

Paris Martineau [01:44:23]:
Are there any ads in the rundown, guys?

Leo Laporte [01:44:26]:
Or how about some TikToks?

Jeff Jarvis [01:44:29]:
Oh, I haven't done that in a while. That's right, I've got to do that again, don't I?

Leo Laporte [01:44:32]:
We used to do Jeff's TikToks. Here's breaking news, uh, good news: government officials are now allowed to put TikTok on their smartphones. On their government-issued smartphones.

Jeff Jarvis [01:44:44]:
Oh, good.

Paris Martineau [01:44:45]:
Well, now it's American TikTok.

Leo Laporte [01:44:47]:
It's no longer a threat, thank God. But do you really think we should have government officials using their government phones to do TikToks? My son might say yes.

Jeff Jarvis [01:45:01]:
There's a lot they should be doing.

Jeff Jarvis [01:45:02]:
I was thinking about—

Leo Laporte [01:45:05]:
Yeah, that's true. True. Maybe even better if they did TikToks instead of some of those other things. Netflix says, uh, generative AI was used— he probably shouldn't say this out loud— in 300 different titles. I was sitting with my—

Jeff Jarvis [01:45:17]:
Try to stop me.

Leo Laporte [01:45:19]:
I was sitting with Michael, our 22-year-old, last night, and he said, I am never going to play a video game with any AI in it. To which Lisa said, how will you know?

Jeff Jarvis [01:45:29]:
I'm sorry to— sorry to miss it, buddy. I can always No, there's been AI in video games for a very long time now.

Leo Laporte [01:45:35]:
I know, you can't tell. You can only tell if it gets good because, uh, you know, I was— I used to be a warrior like you, but then I got an arrow through the knee. You only can hear that a few hundred times before you start to wonder, couldn't they come up with something better? Ted Sarandos says, uh, we believe it's going to enhance their abilities. For instance, The American Experiment, which is It's a docuseries. I actually hate these kinds of documentaries where they kind of fake the scenes.

Jeff Jarvis [01:46:06]:
YouTube is filled with them now.

Leo Laporte [01:46:07]:
Yeah, I hate them. Well, 17 minutes of AI-enhanced footage, and I think the AI enhanced his hair. Do you think really that was his hair? Do you think he really had hair like that? Now everybody else is wearing a nice wig. And he's— show this, show this screenshot from Netflix. I'm not going to run anything. Do you think that really was the hair? I think AI had something to do with that one.

Paris Martineau [01:46:34]:
I mean, that could just be a wig.

Leo Laporte [01:46:36]:
A bad wig.

Jeff Jarvis [01:46:37]:
It's a fro, a founding father fro.

Leo Laporte [01:46:40]:
There's Ben Franklin. That's how Ben looked, right? Sort of.

Jeff Jarvis [01:46:45]:
I don't know.

Leo Laporte [01:46:47]:
Founding fro. All right, pick some stories and then we'll do a break. And it was a weird week.

Jeff Jarvis [01:46:54]:
There were huge stories.

Leo Laporte [01:46:56]:
Huge, which we covered.

Jeff Jarvis [01:46:57]:
Huge stories. And then it kind of fell off. There wasn't a lot else.

Paris Martineau [01:47:00]:
Well, I'll pick a story, which is that there was one of the bellwether lawsuits against Meta in the social media addiction cases was dropped.

Leo Laporte [01:47:12]:
But Here, let me read it.

Paris Martineau [01:47:16]:
So a 15-year-old Florida teenager who accused Meta of creating addictive and harmful social media features dropped his bellwether lawsuit against the company on Wednesday. It was one of 9 major social media addiction cases that could expose Meta and all these other companies to financial damages.

Leo Laporte [01:47:35]:
However, by the way— Financial damages which Meta estimated could total $14 trillion.

Leo Laporte [01:47:41]:
Yep.

Paris Martineau [01:47:42]:
The lawyer representing the teen said he dropped the lawsuit because he was satisfied with the settlements he'd received.

Leo Laporte [01:47:48]:
Oh, okay.

Paris Martineau [01:47:49]:
And had concerns about, quote, enduring a grueling weeks-long trial. And the lawyer said they're proud of what this case helped accomplish. Of course, then Meta says the claims never held up, and this outcome makes clear that we will not back away from defending ourselves against baseless lawsuits, which is a little bit of a weird thing to say when And it seems like the reason that it was dropped is because of settlement.

Leo Laporte [01:48:12]:
Well, that's what Elon's strategy is with Tesla lawsuits. If you can keep it out of court, it's always better for everybody.

Paris Martineau [01:48:20]:
I mean, it's interesting to do this.

Leo Laporte [01:48:21]:
It doesn't add up to $14 trillion.

Paris Martineau [01:48:24]:
It's interesting to do this in one of the bellwethers though, because kind of the point of this is to figure out like how much potential financial like exposure these companies have, and are they going have to settle a bunch of them. To have your second, I think, big, or at least high-profile— yeah, this is the second of these 9 bellwethers— have it be, well, I guess we'll just settle.

Leo Laporte [01:48:46]:
Um, remember that, uh, Snapchat and TikTok settled the LA case, that big LA case. It's before it went to court. I mean, I think that's kind of the safest thing to do.

Jeff Jarvis [01:48:59]:
Well, the problem is that the complaint—

Leo Laporte [01:49:01]:
TikTok, Snap, and YouTube had all settled before Meta. So this kid got some money, I'm sure. Go ahead.

Jeff Jarvis [01:49:07]:
Yeah. And what does he care? What does the kid care about being a bellwether?

Leo Laporte [01:49:12]:
He—

Jeff Jarvis [01:49:12]:
it's a life-changing amount of money.

Jeff Jarvis [01:49:13]:
Yeah.

Leo Laporte [01:49:15]:
So he's, he's 15. He said that Meta created addictive and harmful social media features. What, what was the consequence to him?

Jeff Jarvis [01:49:25]:
What was the harm?

Paris Martineau [01:49:27]:
I'm just— let's figure it out.

Leo Laporte [01:49:29]:
I'm so messed up. Uh, does it say on the New York Times story? All right, that's fine.

Paris Martineau [01:49:36]:
That's fine.

Leo Laporte [01:49:36]:
I'm glad he got his payday. Uh, and I think it's almost always better to settle. Often with a settlement, you don't have to admit wrongdoing. You just say, we just want out.

Jeff Jarvis [01:49:48]:
He could have taken them down.

Leo Laporte [01:49:52]:
Maybe he didn't want to take them down.

Jeff Jarvis [01:49:53]:
$14 trillion? That'll break anybody.

Leo Laporte [01:49:55]:
Have you ever been in a lawsuit? It is a nightmare for everybody involved.

Jeff Jarvis [01:50:00]:
Take one for the team, homie.

Paris Martineau [01:50:02]:
I think part of the allegation is that, uh, the kid who goes by his initials RKC, um, basically alleges that he was addicted to these platforms since he was 8. It was against, uh, Meta, Google, ByteDance, and Snap that the platforms I was doom scrolling all night.

Leo Laporte [01:50:30]:
I could sue them. I have— I, you know what, I have to force myself not to pick up my phone at 4 in the morning every morning.

Paris Martineau [01:50:37]:
Well, maybe you should then. Seems to have worked out well for him.

Leo Laporte [01:50:43]:
I became a podcaster because of these people. Look what it's done to my life. Ladies and gentlemen, you are watching, uh, and listening to Intelligent Machines. Paris Martineau and Jeff Jarvis.

Jeff Jarvis [01:50:55]:
Can I mention one other story?

Leo Laporte [01:50:57]:
Oh, now you do it. Yes, sure.

Jeff Jarvis [01:51:00]:
Line 103. Google is building a chip with Gemini baked into it.

Leo Laporte [01:51:05]:
That's interesting.

Jeff Jarvis [01:51:06]:
It is. Presumption is that it'll be more efficient.

Leo Laporte [01:51:11]:
It'll never be up to—

Paris Martineau [01:51:11]:
I have a dumb question, but how, how do you bake Gemini into a chip?

Jeff Jarvis [01:51:21]:
I can't answer that.

Paris Martineau [01:51:22]:
Maybe it's not that dumb of a question since no one can answer it. No, it's not.

Leo Laporte [01:51:28]:
The project informally called Frozen V2, and by the way, Information had the scoop. It's going to be very efficient, obviously, if the AI is running in microcode. Even the smallest models are many gigabytes. Is it going to— it's unclear. Is it an ASIC? Yeah, the Frozen name comes from the idea of permanently etching part of the model into the silicon.

Jeff Jarvis [01:51:58]:
The hardware locks to the shape of Google's current AI design. Engineers can still refresh the model by loading new weights, but the underlying structure stays fixed or frozen. How much of the model gets hardwired is reportedly still being decided. Yeah, the payoff is efficiency. The information reports the chip could be 6 to 10 times more efficient than Google's latest custom AI chips.

Leo Laporte [01:52:19]:
So it's not—

Nate B. Jones [01:52:20]:
I don't—

Leo Laporte [01:52:21]:
if it's not in ROM, it sounds like it's a custom, uh, BLSI instruction set. Yeah, I don't— well, it's—

Nate B. Jones [01:52:29]:
I don't know.

Leo Laporte [01:52:30]:
I don't know.

Jeff Jarvis [01:52:31]:
I found that interesting, that's all.

Leo Laporte [01:52:36]:
There is another company, Talus, from Canada, Canada, which does in fact hardwire specific AI models into chips. They've raised $200 million. So this is not a completely new idea. Yeah, it's intriguing. You know, I think that this is the opportunity right now for a lot of these companies is not to build a bigger and bigger and bigger model. Fable's, it was Nate B. Jones who said this, 10 terabytes. But to find out ways to make it more efficient, to find out ways to make it runnable locally, all— there's all sorts of areas that you could improve on without simply scaling.

Leo Laporte [01:53:16]:
And since scaling is the— right now the most expensive thing to do, uh, actually I'm going to show you my pick of the week. It's a physical object.

Paris Martineau [01:53:26]:
He's left the chair, folks.

Jeff Jarvis [01:53:29]:
Elvis has left the chair.

Leo Laporte [01:53:30]:
Because this came in the mail yesterday. And I want to thank Douglas, who is a club member. Hi, Douglas! He says, a longtime listener, club member. He is retired, but he keeps himself busy repairing and selling old Mac laptops, which is cool. His specialty is the 2011 A1297 17-inch 2.5 GHz, which I clean up, make sure the graphics are working, upgrade to 16 gigs RAM, put in a 2 terabyte SSD, He says there's still a pretty good market for them because they're repairable, upgradable, and they have plenty of ports. He heard us listen— he was listening to the show on June 23rd, and there was a conversation about you having an issue with the availability and expensive RAM. So what did he send me? A box of old RAM.

Leo Laporte [01:54:21]:
Hey!

Leo Laporte [01:54:24]:
There's so much RAM in here. It's— this is Ramapalooza. Unfortunately, none of it, none of it is, uh, good enough to put in any of the machines I use, but he apparently had some extras. And it continues a long-standing tradition, it's hysterical tradition of sending Leo your old crap. Um, and I'm not sure why, but he did. So, uh, I don't know, anybody wants some megabytes? I mean, there's megabytes of RAM.

Jeff Jarvis [01:54:57]:
Is there 1 gig of RAM in that box?

Leo Laporte [01:55:00]:
That whole box is 1 gig? That's a good question. The modules are mostly the same. Let me see what the size of these— I can't really— such fine print, I don't think I can read it. It's made in China, so that's good news.

Jeff Jarvis [01:55:16]:
It's all laptop RAM too, right?

Leo Laporte [01:55:20]:
Yeah, it looks like it. It's not SO-DIMMs. This is Samsung. Oh, wait a minute. Hold on there. This is 2 gigabytes PC3, 1RX8 PC3 from— I don't know. It looks like— I don't know what— I don't know anything more about it. But if that's 2 gigabytes, man, maybe I can do something with this.

Leo Laporte [01:55:44]:
I'm sure the throughput's terrible.

Jeff Jarvis [01:55:46]:
Yeah, like DDR2 or something.

Leo Laporte [01:55:49]:
Yeah, but wow, he sent me a lot of it. I mean, if each of these is 2 gigabytes, I got terabytes of RAM here. I'm set for life. Thank you, Douglas. I don't want to encourage people to send me their old crap. When we were in the brick house, you know, we had 10,000 square feet.

Paris Martineau [01:56:09]:
How are people getting your address?

Leo Laporte [01:56:12]:
Well, that's another good— he sent it to the post office box.

Paris Martineau [01:56:16]:
Okay, that's more acceptable.

Jeff Jarvis [01:56:17]:
Yeah.

Leo Laporte [01:56:18]:
Um, Jeff Atwood sent me this hypercube.

Paris Martineau [01:56:21]:
He keeps sending us things. I was gonna say, where is the hypercube from? It's so cool.

Leo Laporte [01:56:25]:
You like that?

Paris Martineau [01:56:26]:
I like the cube.

Leo Laporte [01:56:27]:
It's also— it's got 3 settings. One is it responds to sound, so if I— it could be like a little disco in here.

Paris Martineau [01:56:33]:
Should I get a hypercube?

Leo Laporte [01:56:34]:
Yeah, you want to see it up close?

Paris Martineau [01:56:36]:
Yeah, it's mesmerizing.

Jeff Jarvis [01:56:37]:
Are those new dials behind you in that complex there? Oh, I see.

Leo Laporte [01:56:48]:
Great, great.

Jeff Jarvis [01:56:49]:
What's that? What's that below your— right behind you? Have you always been hiding that? I haven't seen that.

Leo Laporte [01:56:53]:
Sauna hat.

Jeff Jarvis [01:56:56]:
Leo, move, move a little bit to the right. What's that down below you? The dials? Oh, has that been there?

Leo Laporte [01:57:06]:
Yeah.

Jeff Jarvis [01:57:06]:
I've never seen that before.

Leo Laporte [01:57:08]:
Yeah, take down the lower thirds, Benita, so they can see this. That is a— so I, in December, actually I'm glad you asked this, in December I will celebrate 50 years in broadcasting. I started in December 1976, the bicentennial. And that little doohickey, this was the first mixer I ever used. It's a Gates Stereo Statesman. It was at the college radio station I used.

Jeff Jarvis [01:57:37]:
Did you steal it from the radio station?

Leo Laporte [01:57:39]:
No, this is a— this is not the same exact one, but it's the same model. It's the same. It feels very familiar. I got very good at turning the microphone on and turning up the pot at the same time. These are, these are all analog potentiometers, dials. And so yeah, that's a memory for me because that's how I started radio.

Paris Martineau [01:57:59]:
So you're saying that in December you'll be celebrating 50 years of podcasting? 50 years of podcasting. December, a month that ends with a celebration called New Year's. Perhaps you could do some sort of 24-hour livestream.

Jeff Jarvis [01:58:14]:
It's an excuse for you to get the sauna, Leo.

Paris Martineau [01:58:16]:
It could be a celebration.

Leo Laporte [01:58:18]:
We could do the whole thing, 24 hours in a sauna.

Paris Martineau [01:58:22]:
We could have one of the hours be in a sauna.

Leo Laporte [01:58:25]:
Apple dolls. All right, all right. Faris still wants to do 24 hours.

Paris Martineau [01:58:30]:
50 years of podcasting, 24 hours of livestream.

Leo Laporte [01:58:35]:
Broadcasting.

Paris Martineau [01:58:35]:
50 years of broadcasting.

Leo Laporte [01:58:36]:
Came a lot later.

Paris Martineau [01:58:38]:
24 hours of podcasting.

Leo Laporte [01:58:41]:
It goes together. They said Paris is working on a whole other—

Jeff Jarvis [01:58:45]:
Could be asking for 50 hours.

Leo Laporte [01:58:48]:
Paris, your pick of the week.

Paris Martineau [01:58:51]:
My pick of the week is the only thing I've been thinking about this last week. Cyclospora parasite.

Nate B. Jones [01:58:58]:
Is it true?

Leo Laporte [01:59:00]:
Is it true that the federal government decided to stop testing for cyclospora at one point, and that's one of the contributing factors to this?

Paris Martineau [01:59:10]:
No, that's kind of— it's like a misnomer. What people are talking about when they refer to that is there's a program called FoodNet that's part of the CDC that is involved in kind of like long-term like surveillance. And as part of CDC budget cuts recently, they stopped monitoring 6 out of the 8 pathogens or other things they were monitoring, one of which was cyclospora. That's obviously not good for a lot of reasons, but that is a surveillance system that can't prevent outbreaks. Right.

Leo Laporte [01:59:44]:
It just lets you know.

Paris Martineau [01:59:45]:
And it's super relevant for this.

Leo Laporte [01:59:47]:
And you can kind of tell when cyclospora hits a community.

Paris Martineau [01:59:50]:
Well, it's also like that program The program only monitored kind of a fraction of the US. It's very useful for a lot of things. It's not necessarily the most directly useful in this situation that we're seeing now, which is that we're seeing like a massive surge of cases in kind of a handful of states. Don't say surge. Sorry. We're seeing, you know, a lot of cases in a handful of states and a lot more than we normally see during this season.

Leo Laporte [02:00:18]:
Is it all from Taylor Farms?

Paris Martineau [02:00:22]:
We don't know. So on Friday, uh, over into Saturday, Taylor Farms announced that it was recalling all iceberg lettuce from Mexico that it shipped to the U.S.

Leo Laporte [02:00:34]:
Oh, it's the Mexicans, of course!

Jeff Jarvis [02:00:37]:
Well, they're divided.

Paris Martineau [02:00:38]:
Well, Cyclospora for a long time was thought to be endemic to Mexico and a couple of other regions in there. Now we know that it can also live in the U.S. and things like that.

Leo Laporte [02:00:46]:
It comes from night soil, right? I mean, there was a long time in Mexico when you went to Mexico, you'd have to be very careful about what they call Montezumas or zents because they use night soil, aka poop, to fertilize, uh, their, their crops. And if you aren't immune to it, if you haven't been exposed to it and developed antigens for it, uh, you would get sick. But I— but they stopped doing that a long time ago.

Paris Martineau [02:01:10]:
I was gonna say, I'm not sure that's direct Part of how the cyclospora parasite is transmitted is— sorry, if you're eating, maybe don't listen to this— but it's when feces from an infected person is spread onto a crop in some way, either through wastewater or maybe a manure situation.

Leo Laporte [02:01:31]:
Or Vegemite.

Paris Martineau [02:01:33]:
Maybe. And then that has to sit out there for like a week to 2 weeks because it's not just like the contaminated feces, if you touch You touch it, you get it. It takes a week or 2 weeks in hot, wet, warm weather for it to get infectious again. And so then once that happens, it could be infectious generally, and maybe say that the crop is harvested, and if it's iceberg lettuce, it's then chopped up, mixed in with a bunch of stuff, sent a bunch of other places, and it gets very, very complicated.

Jeff Jarvis [02:02:04]:
So it's not like one person with dirty hands does this?

Paris Martineau [02:02:06]:
No, no.

Leo Laporte [02:02:08]:
The other problem is if you get infected, you will not necessarily show symptoms for quite some time, right?

Paris Martineau [02:02:13]:
Yeah, it could be like 2 weeks. And so that makes it even more complicated because the first— basically a lot of these infections or outbreaks, we don't figure out exactly what caused it because that's kind of complicated to track down and food is perishable. And part of the way you get to even testing products is you have to ask people who've then, you know, a subset of people who've gotten sick, reported the infection to their doctor, maybe to get treatment, then had that infection reported to a health agency. You ask those people sometimes a couple of weeks after they got sick, which is a couple of more weeks since they ingested the food with the parasite in it, what did you eat? And if that's even remotely accurate, then investigators go through— try to go through, like, all of these people's food history and figure out what could be a potential source. One of the things they've identified so far is there seems to be, at the very least, a cluster of, uh, cases, like a multi-state large, like, outbreak related to iceberg lettuce. Um, and so as part of this, Taylor Farms initiated a recall, but it got really confusing over the weekend for a lot of people because shortly after Taylor Farms issues this recall, the FDA then posts an announcement being like, Hey, just letting you guys know, we tested, we intercepted a shipment of totally different Taylor Farms lettuce, not part of the recall at the border, tested that, we found cyclospora. That was big news because everyone thought, oh, recall is going to expand. Then 24 hours later, the FDA is like, psych, actually sorry, that was a false positive.

Paris Martineau [02:03:43]:
But a lot of people didn't grok, sorry to use the word that is now synonymous with Elon, a lot of people didn't understand that the lettuce they tested that was now a false positive wasn't the recalled lettuce, so they immediately interpreted that to mean, oh, Taylor Farms innocent, all a big misunderstanding, which is not the case according to the FDA. They said there's still strong epidemiological evidence linking it to the lettuce.

Jeff Jarvis [02:04:05]:
And that was the— the epidemiological evidence was the basis of the original recall, Paris? Not testing?

Paris Martineau [02:04:11]:
Well, all we know for sure is that epidemiological evidence has linked it. We don't know for certain that the Taylor Farms lettuce that is part of the recall has been tested by the FDA, and those tests have been negative. At some point during all of this, Taylor Farms issued a statement on Instagram that said something to the effect of— they said, the FDA has apologized to us, and no Taylor Farms lettuce has tested positive for The FDA has been unable to provide a positive test linking our stuff to that. But that statement has been totally taken down because the FDA then a couple of days later was like, we did not apologize to Taylor Farms.

Leo Laporte [02:04:55]:
And I know Consumer Reports is above the fray, but I will tell you that Taylor Farms CEO is a big donor to the Trump campaign and that Taylor Farms met with Trump days before—

Paris Martineau [02:05:06]:
Well, they met with the White House.

Leo Laporte [02:05:07]:
The White House, okay. But days before the FDA backed Trump. So that is further, if you'll forgive it, muddying the waters.

Jeff Jarvis [02:05:16]:
Well, and we can't necessarily know whether to trust certain institutions these days.

Leo Laporte [02:05:20]:
That's the problem. We can't— we don't feel like we trust our institutions.

Jeff Jarvis [02:05:24]:
I came into our WhatsApp, and I'm honored that Paris responded to me because she doesn't see the WhatsApp enough, just asking, like, you know, can I eat lettuce now? What do I do? Do I trust the FDA now?

Leo Laporte [02:05:36]:
I like to live dangerously, and I I've been eating lettuce ever since. Well, I mean, by the way, one of our club members says he got it and it was not nice.

Paris Martineau [02:05:46]:
No, it's a very harrowing experience.

Leo Laporte [02:05:48]:
I mean, is it worse than norovirus? I mean, is it— it's like—

Paris Martineau [02:05:53]:
I mean, I don't know about the direct comparison to norovirus, but because that's also a gastro— I understand that it is so bad that you have to basically, for a lot of people, getting The very specific antibiotic is the only way to kind of stay hydrated.

Leo Laporte [02:06:09]:
It's a bacterial, so antibiotics will work. It's not a parasite.

Paris Martineau [02:06:13]:
No, it's a parasite, but there's like a very specific treatment that does the trick.

Jeff Jarvis [02:06:17]:
Dehydration is obviously the great risk if it goes on for a long time.

Leo Laporte [02:06:21]:
Well, as always.

Jeff Jarvis [02:06:22]:
Yeah.

Leo Laporte [02:06:22]:
I always keep Pedialyte in the pantry. You never know.

Jeff Jarvis [02:06:25]:
So it's Bactrim? That's pretty common.

Paris Martineau [02:06:28]:
Yeah, I believe that's the name of it. Yeah, Bactrim is the—

Leo Laporte [02:06:31]:
Ella Duderino says the bathroom was booked for weeks. but he says, I think I got it from Organic Girl spinach. It's completely possible. We just don't know that it comes from more than one place.

Paris Martineau [02:06:43]:
Well, so that's the thing is, it's really interesting right now because we have, every year, the US sees a rise in cyclospora infections in the summer because, like I said, it's gotta be kind of hot and wet for that sort of thing to grow. It's something that a lot of people get. I think in the last couple of years, between 2013 and 2016 and 2023, the average number of annual infections in the US was like 2,800-ish. So there's like low-level thousands. Now currently the latest count from the CDC, which is almost certainly an undercount, is like 11,000. Most of those cases are coming from a cluster kind of near Michigan that investigators say seem to be linked to lettuce, but there are quite a few other states that are experiencing kind of higher than usual numbers, and they— it is unclear whether it's linked to lettuce or something else. So there could just be, like that case we just talked about with the club member, it could just be one of the usual kind of upticks in infections, which is unfortunate, but happens. It could be lettuce-related.

Paris Martineau [02:07:48]:
It could be a different outbreak-related incident that we haven't identified the source yet.

Leo Laporte [02:07:54]:
Food-related outbreaks are actually Not uncommon. It's amazing really that our food supply is as safe as it is, I think, because we don't have enough inspectors.

Jeff Jarvis [02:08:08]:
Paris, does this job make you more weirded out about consuming food?

Paris Martineau [02:08:13]:
I feel like a crazy person shopping for food now.

Jeff Jarvis [02:08:16]:
So what do you do now?

Leo Laporte [02:08:17]:
Well, my good friend who was a master of public health, he was at the Oregon State Public Health Department, for years, college roommate. You'd go to his house for Thanksgiving and he wouldn't even handle the turkey after cooking. He used rubber gloves. He was so weirded out. He has quite famously the Outbreak Museum, a museum of famous food outbreaks.

Leo Laporte [02:08:38]:
I gotta go there.

Leo Laporte [02:08:39]:
That sounds great. Yeah, I said, this is a new museum for you, Paris.

Jeff Jarvis [02:08:43]:
So what's changed in your habits, Paris?

Paris Martineau [02:08:46]:
I mean, a lot of things have changed in my habits. habits. I'm— I, I used to walk to the grocery store with not a care in the world, not really thinking about where my food came from, what the ingredients were, and I don't do any of that anymore. I think a lot about all of my decisions in a way that's, I don't know, somewhat maddening. Um, in, in case— in the case of this though, kind of what— one of the things that, uh, kept me working for hours over the weekend is that the recall notice that Taylor Farms posted is really sparse on details. Like, normally whenever you cover, like, write up a recall notice for a foodborne illness outbreak, as I now have done a lot over the last year, they list like what are the products being recalled, where were they sold. We don't really have that. Instead, Taylor Farms listed a bunch of like abbreviations that kind of— you basically had to like guess based on what letters you thought are associated with what companies.

Paris Martineau [02:09:41]:
It was just a bit of a nightmare. I was able to confirm that the products that were called lettuce went to Walmart stores, uh, was served at Jack in the Box locations, and distributed to Sysco, which means it could go anywhere.

Leo Laporte [02:09:53]:
Oh, Sysco is every restaurant in the country.

Paris Martineau [02:09:56]:
You know, food district. So Taylor Farms said that this lettuce was distributed by it to 27 states, but we don't know whether once it went to those places it was distributed elsewhere. So kind of what our food safety experts are recommending is if you are in one of these 27 states where the lettuce— recalled lettuce ended up, discard any iceberg lettuce you have. Avoid it till we know more. If you're outside of there, the advice I've been giving people I know personally, because all of this is kind of a personal risk calculation, is like, look at your own state where you live. Are they seeing unusually high, like higher than average number of cases of cyclosporiasis? If so, so, that might be a sign that you want to take some caution.

Leo Laporte [02:10:37]:
It's mostly east of the Mississippi.

Paris Martineau [02:10:39]:
It is. Like, for instance, California officials— like, with you saying that, Leo— like, California officials have been like, yeah, we've got not as many cases this year as we saw last year, so we seem to be unimpacted.

Jeff Jarvis [02:10:51]:
41 states doesn't leave many out.

Paris Martineau [02:10:53]:
No, I know.

Leo Laporte [02:10:55]:
I will point you to the International Outbreak Museum, which is at outbreakmuseum.org. They have all sorts of— I think you'd enjoy this, Paris. All sorts of features, exhibits like this 2014 Florida staphylococcus outbreak at a holiday buffet.

Jeff Jarvis [02:11:14]:
Where is this?

Jeff Jarvis [02:11:14]:
Physically?

Leo Laporte [02:11:15]:
This is my old college roommate, Bill Keane.

Paris Martineau [02:11:17]:
No, I know, but physically, is this a physical museum?

Leo Laporte [02:11:19]:
It's in Oregon. It's in Oregon.

Paris Martineau [02:11:22]:
I wish I had known about this.

Leo Laporte [02:11:23]:
Yeah, they have many exhibits like the famous Will Smith and leather spray exhibit, or the Jack in the Box E. coli, or the venison jerky. He investigated—

Nate B. Jones [02:11:33]:
this was his—

Leo Laporte [02:11:33]:
he was the most famous investigator of foodborne outbreaks in America.

Jeff Jarvis [02:11:38]:
I think it's a business.

Paris Martineau [02:11:39]:
How did I not know this when I was in Portland?

Jeff Jarvis [02:11:42]:
This is my guy.

Leo Laporte [02:11:42]:
Oh my God, you missed out. You missed out on the diaper-changing Satyan norovirus, the Pennsylvania raw milk Campylobacter jejuni breakout. The Listeria soft cheese breakout. Unfortunately, it ends in 2016 when Bill ended. But yeah, he passed away, not of a foodborne illness, I might add. But this was his office. He had all of this in his office. That's so cool.

Leo Laporte [02:12:10]:
He was very— he was a wild man. So yeah, I guess that's another connection we have besides saunas and and pour-over coffee is foodborne illness. He sold t-shirts. His most famous one had a fry cook on the front, was him with his beard, you know, holding the spatula saying, how do you want your eggs today? And in the back it had all these parasite egg.

Paris Martineau [02:12:37]:
That would be great to mix with my flaming rat t-shirt from the American Museum of Torture.

Leo Laporte [02:12:42]:
There you go.

Leo Laporte [02:12:43]:
There you go.

Leo Laporte [02:12:44]:
They should bring it all back. Jeff, pick of the week.

Jeff Jarvis [02:12:49]:
All right, so last week we were discussing, uh, Jensen Huang's jacket, and in the meantime, one sold at auction.

Leo Laporte [02:12:56]:
Oh, so these are the beautiful leather jackets.

Jeff Jarvis [02:12:59]:
Very beautiful, designed by Tom Ford. One sold at auction for $960,000.

Leo Laporte [02:13:05]:
What?

Jeff Jarvis [02:13:06]:
It was intended to be— the estimate was $60,000. It was a charity event.

Leo Laporte [02:13:10]:
Oh, okay.

Jeff Jarvis [02:13:11]:
But there were 45 collectors bid on the jacket, and it sold for $960,000.

Leo Laporte [02:13:17]:
He doesn't wear the same one twice though, right? I mean, there's a—

Jeff Jarvis [02:13:20]:
Well, I think he might wear more than one, but there are many.

Leo Laporte [02:13:22]:
Yes. Every keynote he has a different one.

Jeff Jarvis [02:13:26]:
Some are like—

Paris Martineau [02:13:26]:
That's so many leather jackets. That's actually really—

Leo Laporte [02:13:30]:
No matter what the price on these is, not cheap.

Leo Laporte [02:13:32]:
It ain't a million bucks.

Jeff Jarvis [02:13:32]:
In the middle of August, he's wearing the leather jacket because it is his trademark.

Leo Laporte [02:13:35]:
Yeah, it's his black turtleneck.

Jeff Jarvis [02:13:38]:
So the other one was a story that has nothing to do with AI but amused me. I giggled About this. Wall Street Journal— rarely do I giggle at the Wall Street Journal. Everyone gets lost at the Pitbull concert. Pitbull is a, um, singer who is bald, and so everybody who goes to the Pitbull concert wears bald caps and sunglasses. And when people go off—

Leo Laporte [02:14:01]:
Mr. Rogen and I are the same.

Jeff Jarvis [02:14:03]:
And come back, they can't find their friends because all their friends look the same.

Leo Laporte [02:14:09]:
Okay.

Leo Laporte [02:14:09]:
I thought that was amusing.

Paris Martineau [02:14:10]:
I love this. This is a great version of the Wall Street Journal's A-head.

Jeff Jarvis [02:14:15]:
Yeah.

Nate B. Jones [02:14:17]:
Wow.

Leo Laporte [02:14:18]:
And they— it's not just a bald head and the glasses. White shirts, black ties.

Jeff Jarvis [02:14:21]:
Yep.

Leo Laporte [02:14:22]:
There's a look.

Paris Martineau [02:14:23]:
It's so great.

Jeff Jarvis [02:14:25]:
Isn't it?

Leo Laporte [02:14:27]:
It's too bad it's Pitbull, but okay. You know, I guess. Are you a Pitbull fan? He is from Florida.

Paris Martineau [02:14:34]:
No, I just, you know, you start walking off with the wrong people. At the London show, he and other— and over 222,000 attendees set the world— the Guinness World Record for the largest gathering of people wearing bald caps.

Jeff Jarvis [02:14:52]:
Wow.

Jeff Jarvis [02:14:52]:
I'm walking and I'm like, oh, I'm with Denise. And no, I'm not. I'm with Dave. I don't know Dave.

Leo Laporte [02:14:59]:
Uh, I have, uh, My— it's not a pick, but I do want to end the show with a mention that my dear friend, the guy who started me in this business— I was a broadcaster, but I wasn't known for my technology expertise, even though behind the scenes I was writing articles for computer magazines and playing with this stuff. It was in 1992 that I started doing a radio show with John C. Dvorak, who at the time was the most prolific computer columnist in the world Wrote many, many columns, most famously the Inside Track column for PC Magazine. We learned just a few hours ago that John passed away Monday at the age of 80. He had a heart attack in March, and according to Scott Mace, who is also a longtime computer journalist, a friend, posted this on our TWiT forums. Scott says he succumbed to complications following that double bypass surgery he got back in the spring there.

Jeff Jarvis [02:15:54]:
Yeah.

Leo Laporte [02:15:54]:
got with John. And of course, if you want to post here your memories of John, you can. There's been some beautiful pictures. And I wasn't at first convinced, but I did go to the No Agenda website. That's the podcast he did with Adam Curry and confirmed this in their chat room. And then I saw the newsletter, which came out just a little bit ago, confirming his passing. He was quite the character. He was a character is a good word.

Jeff Jarvis [02:16:20]:
How did you start with him? Tell the audience.

Leo Laporte [02:16:23]:
a talk show host on KNBR in San Francisco, a station I'm sure you know, Jeff.

Leo Laporte [02:16:27]:
Mm-hmm.

Leo Laporte [02:16:28]:
And it was an NBC station. It was a very famous radio station. I was doing the mid-days, and every once in a while I'd have John on to talk about computers, 'cause I was into it. This was in the late '80s when it was still pretty new. And at one point, about 1991, the program director came to me and said, well, I got some bad news for you, Leo. there's this up-and-coming talk show host out of Sacramento. Uh, we're going to replace your show with his. His name is Rush Limbaugh.

Leo Laporte [02:16:57]:
I wasn't too happy about it, but he said, we're not going to fire you, we're just going to put you on the weekends, and you will do 10 hours of programming every Saturday and Sunday.

Jeff Jarvis [02:17:07]:
Geez.

Leo Laporte [02:17:07]:
In 2-hour chunks.

Jeff Jarvis [02:17:09]:
No wonder you can do what you do to this day.

Leo Laporte [02:17:10]:
It will be food and wine, it'll be home improvement, it'll be cars, it will be real estate. I mean, literally, there were— it was every subject. And, uh, I was announcer boy on those shows, you know, so they'd have an expert come in and I would read the commercials and ask the questions and we'd take calls. And I said, well, I'll be glad to do that, but can I just— I love computers and this friend of mine, John, is great.

Jeff Jarvis [02:17:31]:
He's been on my show. And we're in San Francisco.

Leo Laporte [02:17:33]:
We are in San Francisco. The guy says, Leo, nobody cares about computers. I said, please, you know, this is just as a— this Rush Limbaugh has taken my job Just for, for me. So they let me do 2 hours every Saturday with John. We got to know each other, and John, to his credit, did not treat me like an answer boy. He realized fairly quickly I did know a little bit about technology, let me start answering questions with him. We later syndicated the show as Dvorak on Computers. We stayed good friends.

Leo Laporte [02:18:00]:
In fact, he was one of the first people on our podcast network. He was on many, many Twitch shows, and we always enjoyed having him on, even though he always got got up into trouble. He would steal gaffer's tape from the studio. Once he found out how valuable it was, he would take— every time he would take a roll of gaffer's tape. He always used to take mugs from our cupboard. Um, I, I always invited him back, but at some point, you know, we kind of had a parting of the ways. Uh, he kind of got into right-wing conspiracy theories, but more it was that he started asking $5,000 an episode.

Jeff Jarvis [02:18:34]:
Whoa.

Leo Laporte [02:18:35]:
And I couldn't really afford that. So, uh, we stopped having him on maybe 10, 15 years ago. He didn't stop podcasting. He worked with me at TechTV. He's host of the Silicon Spin Show, which was very much like our Twitch show, a news roundtable. Then took that to the internet with Cranky Geeks, which I know a lot of you watched and loved. He was the original cranky geek.

Jeff Jarvis [02:18:57]:
Cranky he was.

Leo Laporte [02:18:57]:
Partnered up with Adam Curry, former MTV VJ, an early podcast adherent. In fact, he is credited a little bit with inventing podcasts.

Jeff Jarvis [02:19:05]:
He and Dave Weiner.

Leo Laporte [02:19:06]:
With Dave Weiner. He went to Dave and said, you know, if you just would give us in your RSS feed, because Dave invented RSS, if you just do an audio enclosure in there, I could, I could put shows in there. Dave did it. Adam actually wrote the first podcast app. Anyway, he and Adam worked together at Mevio, which was a podcast company that Adam started, took over Cranky Geeks, and eventually he and Adam for many years have been doing a show called No Agenda.

Leo Laporte [02:19:33]:
No Agenda.

Leo Laporte [02:19:35]:
which was kind of a crank conspiracy show. They used to call— Adam was Crackpot. What did they call him? It was Crackpot and— oh, they had nicknames I've forgotten for each other. The chat room will tell me.

Jeff Jarvis [02:19:52]:
But—

Jeff Jarvis [02:19:52]:
What I remember about John from his last show— Buzzkill.

Leo Laporte [02:19:55]:
Crackpot and Buzzkill. Yeah. John never had spare I get no spam was his famous line.

Jeff Jarvis [02:20:03]:
Yep.

Leo Laporte [02:20:04]:
Uh, his other line was, you'll find out more at dvorek.org/blog. He never passed up a chance to plug his blog. Uh, I love John. He was just a character, a wild man, very funny. He used to come and say, oh, you got the new iPhone, let me take a look at that. And he would change the language to Chinese and give it back, which is a good prank because Because it's— if you don't know Chinese, pretty hard to find the settings to change the language back. It took me a while.

Jeff Jarvis [02:20:34]:
Before Google Translate.

Leo Laporte [02:20:35]:
Yeah, yeah, no, we didn't have it back in the day. John, we will miss you dearly. I have a handful of recordings of John that I, you know, saved from his appearances on the show. I'll play a couple for you, just for those of you who don't know John, just so you You can kind of hear what, what he sounds like because he had a pretty distinctive sound. He had a— he was the original, the one and only cranky geek, right? This is one that I played earlier on Windows Weekly.

Leo Laporte [02:21:11]:
The search engine needs work.

Leo Laporte [02:21:13]:
Congratulations anyway. I'm glad you got a job.

Leo Laporte [02:21:16]:
Yeah, I needed one. You know, we got the deli, we got to get going.

Leo Laporte [02:21:19]:
The deli?

Jeff Jarvis [02:21:19]:
I'm going to sleep at this point.

Leo Laporte [02:21:21]:
I mean, what are you going to sell?

Paris Martineau [02:21:22]:
We have like 14 columns. Cranky Geeks, you participate in—

Leo Laporte [02:21:27]:
I got time on my hands, believe it. I'm a columnist savant. The columns don't take that long to do.

Leo Laporte [02:21:33]:
Hey, columnist savant, I like it. Yeah, a lot of people would make something else savant, but that's another story. All right, well anyway, I don't know what it means, but—

Leo Laporte [02:21:42]:
And I have to say that now I can say for a fact that my—

Leo Laporte [02:21:46]:
Oh, let me play this one.

Leo Laporte [02:21:46]:
I have to say that, and I have to say that now I think that my My pulled or chopped pork is as good as anything in North Carolina. Really?

Nate B. Jones [02:21:56]:
Absolutely.

Leo Laporte [02:21:56]:
Are you making some right now?

Leo Laporte [02:21:57]:
I've been working on this for years, and I finally got the whole formula down where I can make it. It's just a stunner.

Leo Laporte [02:22:01]:
Now, you said pulled or chopped. Which is it?

Leo Laporte [02:22:04]:
Well, you can— it depends. You can take— the way I make it with shoulder is that you can take and mash it up with a fork and it becomes kind of pulled. It has its— it's got a stringier quality. Or you can take the whole thing and then chop it, and it has a slightly different, more chunky quality, but essentially the difference is minor. The North Carolina— North Carolinians, they like to chop it, and the Georgians, when they make this type of pork, they like to pull it.

Leo Laporte [02:22:27]:
He was—

Leo Laporte [02:22:27]:
But in fact, it's kind of mashed.

Leo Laporte [02:22:29]:
He was going to write a book about how he makes his own vinegar. He was, uh, he was working on a multi-volume history of the Civil War. He was really smart, a great writer, and a very odd person. but his trademark was being kind of the, the opposite guy, right? The, the naysayer. I learned from him you can really rarely, especially in technology, rarely go wrong by saying a new technology is crap. Like this.

Leo Laporte [02:22:56]:
It doesn't make any sense to me that Macintosh has evolved. I think it's the actual hardware. I think there's something shoddy about Macintosh laptops.

Jeff Jarvis [02:23:04]:
What?

Jeff Jarvis [02:23:07]:
You, you and your Apple baiting. Isn't he great?

Leo Laporte [02:23:12]:
Ladies and gentlemen, you're hearing John C. Dvorak in his prime.

Leo Laporte [02:23:15]:
This is bull. I'm not trying to put down Apple. I was playing with one of these shoddy—

Leo Laporte [02:23:21]:
it's nothing.

Leo Laporte [02:23:22]:
It has a shoddy quality, like the push-down buttons and stuff.

Nate B. Jones [02:23:25]:
They're like offset.

Leo Laporte [02:23:26]:
They're kind of crooked.

Paris Martineau [02:23:27]:
He wasn't wrong about the keyboard, the butterfly keyboard.

Leo Laporte [02:23:30]:
No, no, this is way beyond that.

Paris Martineau [02:23:32]:
I know. No, I'm just saying, you know, if you take a long enough world—

Leo Laporte [02:23:36]:
He often said the mouse will never take off. Nobody wants to use a mouse. Um, he called the first colorful Apple laptop, he says, looks like a toilet seat. He was great. No, I will miss him terribly. Uh, we're sorry to lose John C. Dvorak, uh, at the age of 80. RIP.

Leo Laporte [02:23:56]:
Uh, and if you are a No Agenda listener, even if you're not, noagendashow.com, we'll do a tribute to John tomorrow. I'm not sure I have the highest hopes. Adam is kind of notoriously, um, uh, uncomfortable with this kind of thing, but we'll see. We'll see what happens. Uh, and we will of course talk more about John on TWiT on Sunday. I'm gonna try to get some people who know John, uh, as well or better than I do on the show. Thank you everybody for joining us. We appreciate your patronage.

Leo Laporte [02:24:27]:
We do this show every Wednesday right after Windows Weekly, 2 PM Pacific, 5 PM Eastern. That's 2100 UTC. You can find us, uh, if you want to watch live, you can, uh, on YouTube, Twitch, X, Facebook, LinkedIn, and Kick. Of course, club members, they, they get special treatment. They get to watch in the club Twit Discord. After the fact, on-demand versions of the show available at the website twit.tv/iam. Or you can go to YouTube. There's a video link there for all of our shows.

Leo Laporte [02:25:03]:
Great way to share shows with you. And best way to get it, of course, with all our shows is subscribe in your favorite podcast client. It's easy enough to do. It's free and you'll get it automatically the minute it's done, audio or video. Next week we're joined by— tell us who Henry Blodgett is, Jeff Draper. Oh, Henry.

Jeff Jarvis [02:25:25]:
Paris might be able to tell them too. So Henry Blodgett's an amazing character. He was a financial analyst who was— what was he convicted of, Paris?

Paris Martineau [02:25:34]:
Do you remember? Securities fraud.

Jeff Jarvis [02:25:38]:
Securities fraud.

Jeff Jarvis [02:25:39]:
Yeah.

Jeff Jarvis [02:25:40]:
And then remade himself as a— that's not Henry.

Leo Laporte [02:25:44]:
Oh, that's the link I had. It sure doesn't look like him, does it?

Jeff Jarvis [02:25:48]:
That's how he looks, like a journalist. And he started Business Insider. And under Henry, Business Insider was a tremendous success. It was the original aggregator along with Huffington Post. And frankly, you could go— it was more than Google was in the day. You could go to Business Insider and they already had all the headlines you wanted from all around. They rewrote everybody, pissed off everybody, but it was terribly convenient. Then they tried to make special content, then they got bought by Axel Springer.

Jeff Jarvis [02:26:16]:
they tried to do paywalls, and they got too big for their britches, and they become Insider and all that.

Paris Martineau [02:26:21]:
And they became Insider, and they moved back to being Business Insider.

Jeff Jarvis [02:26:25]:
Exactly.

Paris Martineau [02:26:25]:
Now they're run by a former Wall Street Journal head honcho. And now they're trying to not do aggregation. And I think they had a recent report that 80% of their stories are non-aggregated. But Henry— but Henry Blodgett's uninvolved with the rest of that.

Jeff Jarvis [02:26:41]:
No.

Jeff Jarvis [02:26:41]:
Yeah. So he's left. And now he— we tried to have him on some months ago, uh, because he was using AI to write newsletters or some sort of thing. And now he has somehow a novel involved with Henry. Henry's just a character.

Leo Laporte [02:26:53]:
He has a newsletter called Regenerator on, uh, on Substack.

Paris Martineau [02:26:56]:
And doesn't he— it's a comp— at some point he wrote a blog at Regenerator being like, it's a company of one, me, and a bunch of agents.

Leo Laporte [02:27:04]:
Yeah.

Jeff Jarvis [02:27:05]:
Yep, yep. So I figured he's a character. Uh, uh, this is obnoxious, but I would always see Henry in Davos. He knew all the rich folks. He is the sort of person you would see at Davos. Exactly, exactly. But he's, he's a nice guy.

Leo Laporte [02:27:20]:
So we will talk AI with Henry Blodgett. That'll be fun next week.

Jeff Jarvis [02:27:24]:
Who knows what comes of it? We have no idea.

Leo Laporte [02:27:26]:
You'll find Paris Martineau and her great pieces on diarrhea and more at Consumer Reports. Her website, paris.nyc.

Jeff Jarvis [02:27:35]:
Explodes the news.

Leo Laporte [02:27:37]:
I feel like you picked a good time to go to Consumer Reports and write about food safety.

Paris Martineau [02:27:42]:
Like, it's my 1-year anniversary this week.

Leo Laporte [02:27:47]:
Congratulations.

Paris Martineau [02:27:48]:
It has been a good year.

Leo Laporte [02:27:50]:
Yeah, that's— yeah, no kidding, a good year for food poisoning. Yeah.

Jeff Jarvis [02:27:54]:
Is there anything you won't buy now?

Leo Laporte [02:27:57]:
I think Little Debbie— no, Hostess donuts are probably right up on the list.

Paris Martineau [02:28:02]:
She bought them anyway before I mean, yeah, I mean, protein powder, I guess.

Jeff Jarvis [02:28:08]:
Or—

Paris Martineau [02:28:08]:
okay, so, but I mean, I just get my protein from other places. Everything with food is a personal decision. I don't want to give any prescriptions for folks, but I probably am not— I'm not buying iceberg lettuce right now.

Leo Laporte [02:28:22]:
Is romaine okay?

Paris Martineau [02:28:25]:
I mean, all this is a personal decision right now. The only— there's no broad— there's no data supporting of avoiding fruits and vegetables generally, and the only source identified by federal investigators has been iceberg lettuce in a handful of states.

Jeff Jarvis [02:28:44]:
Okay, so do we trust—

Leo Laporte [02:28:45]:
because it's peach season and I have a peach with my name on it.

Paris Martineau [02:28:48]:
I was gonna say, someone asked me about peach. I did a Reddit AMA yesterday where— and oh good, where we answered a lot of these questions. And so I did some peach research, and peaches I think are almost certainly I mean, from Cyclospora at the very least.

Leo Laporte [02:29:01]:
It's my favorite type.

Paris Martineau [02:29:02]:
Because they grow on a tree.

Leo Laporte [02:29:03]:
They're on trees. Nobody can poop on them.

Paris Martineau [02:29:05]:
They're on trees. You're not gonna get poop water up there on top of a tree.

Jeff Jarvis [02:29:10]:
Poop water?

Paris Martineau [02:29:10]:
That's the technical term for it.

Leo Laporte [02:29:14]:
Jeff Jarvis, uh, they water them on the ground. Besides being a brilliant professor at Montclair State University in New Jersey and SUNY Stony Brook in the state of the Great State of New York, the Empire State as they call it, is also the author of many wonderful books like The Gutenberg Parenthesis, The Web We Weave magazine, and his newest, Hot Type, comes out next month. You can get any or all at jeffjarvis.com. I do recommend Hot Type. Uh, it is a great read, fascinating story about the linotype, the magnificent machine.

Jeff Jarvis [02:29:45]:
Did I send it to you yet, Paris?

Paris Martineau [02:29:47]:
You did. Send it to me again though.

Jeff Jarvis [02:29:50]:
I'll read it.

Leo Laporte [02:29:51]:
Send it to me again. You, you threw it out?

Paris Martineau [02:29:55]:
No, no, he sent, sent me the PDF he's talking about.

Leo Laporte [02:29:59]:
Okay. Yeah, I guess it's— I have pre-ordered.

Paris Martineau [02:30:02]:
I've pre-ordered the book.

Leo Laporte [02:30:04]:
I haven't received it.

Paris Martineau [02:30:06]:
But are you gonna do like a little launch party sort of thing in New York or anything? Come on, I'd be there.

Leo Laporte [02:30:13]:
I have an editorial question. Uh, should we have Jeremy Rifkin He's got a new book, Rescuing the Future: Reimagining Artificial Intelligence in a World on the Edge.

Paris Martineau [02:30:30]:
Hmm. I don't know enough to be able to answer that question.

Leo Laporte [02:30:34]:
I think he's a— he's like John C. Dvorak. He's an interesting character. He's, you know, we seem to be having some, you know, I mean, Henry Blodgett, same thing. I think characters are They make it fun. Anyway, I will think about it and I'll take your votes. Go to the Twit forums.

Jeff Jarvis [02:30:53]:
But it's not a democracy.

Paris Martineau [02:30:55]:
It's not.

Leo Laporte [02:30:56]:
No, I will consider your votes. I will weigh them in my decision. Thank you, everybody. We'll see you next time on Intelligent Machines. Bye-bye.

Paris Martineau [02:31:06]:
I'm not a human being, not into this animal scene.

Leo Laporte [02:31:12]:
I'm an intelligent machine.