Intelligent Machines 868 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. Jeff Jarvis is here. Paris Martineau is here. Well, she will be. She's stuck on a train right now. But our guest is here and I'm very excited. We'll be talking to Nirav Patel. He is the founder and CEO of Framework, the upgradeable computers.

Leo Laporte [00:00:18]:
He says computing as we know it is about to change forever. Intelligent Machines is next. Podcasts you love from people you trust. This is twit. This is Intelligent Machines with Paris Martineau and Jeff Jarvis. Episode 868, recorded Wednesday, April 29, 2026. Happy Hamburgers Towing Timmy to the sea. It's time for Intelligent Machines, the show we cover AI robotics and all those smart doohickeys all around us.

Leo Laporte [00:00:54]:
We're surrounded by intelligent machines this day. Paris Martineau is stuck in a tunnel. She'll be here momentarily from Consumer Reports. She's on the subway. That's New York life, right? I probably shouldn't say stuck in a tunnel to this guy, Paris. Jeff Jarvis, because you probably have a little bit of, I don't know, PTSD from 2001.

Jeff Jarvis [00:01:15]:
Yeah, I guess so. Yep.

Nirav Patel [00:01:17]:
Yep.

Leo Laporte [00:01:17]:
Jeff Jarvis, emeritus professor of journalistic innovation at the Craig Newmark Graduate School, Craigslist, New York. He's also the author of the Gutenberg Printhouse magazine and the new one Hot Type, available now for pre order from Bloomsbury. And Jeff, of course, is teaching now at Montclair and State University in New Jersey and SUNY Stony Brook. Okay, enough. I want to get right to our guest. Cause I.

Jeff Jarvis [00:01:48]:
Do you want to explain who's missing for a second?

Leo Laporte [00:01:49]:
I did. I said Paris is stuck in a well.

Jeff Jarvis [00:01:52]:
You said that? That's right.

Leo Laporte [00:01:53]:
Is she on the irt? Which subway? We don't know.

Jeff Jarvis [00:01:56]:
Well, Brooklyn. Could be all of them. Brooklyn's very well served.

Leo Laporte [00:01:59]:
It's well served.

Jeff Jarvis [00:02:00]:
Can be the bmt, the irt, the ind. They all go to Brooklyn.

Leo Laporte [00:02:04]:
You know, it's funny, you know, the history of the New York subway system is fascinating. They were all private companies. That's why they all have different names and different roots. But then I guess they all got merged together. Our guest today, Neerav Patel. Claude says, Nirav, that you may be the most interesting hardware founder in tech.

Nirav Patel [00:02:22]:
I'll take it.

Leo Laporte [00:02:24]:
I think it's true, actually. Fascinating story. You started at Oculus back in the Kickstarter days.

Nirav Patel [00:02:32]:
That's right.

Leo Laporte [00:02:32]:
The Oculus Rift ended with Palmer. Lucky. I was a Kickstarter purchaser of the original Oculus Rift and then bought a couple from Meta which it turns out you also worked on, including the Quest 2.

Nirav Patel [00:02:45]:
That's right. That was the last one.

Jeff Jarvis [00:02:46]:
And we discussed before, before we got on what, before all of this. One laptop per child.

Nirav Patel [00:02:51]:
That's right.

Leo Laporte [00:02:52]:
I had an OLPC as well. The one, the green one with the little ears. Did you work on the design for that or what did you do with that?

Nirav Patel [00:02:59]:
I worked on the software actually. So I wrote some webcam interface logic from a software perspective basically just to make it easier to interface. And it's got just the slowest little embedded AMD geode processor in it. So it took a lot.

Leo Laporte [00:03:13]:
And it was Smalltalk, right? It was running Smalltalk.

Nirav Patel [00:03:16]:
It was running Smalltalk for the. Yeah, a lot of the system was running Smalltalk. This part of it was running Python. But obviously the webcam interface code was

Leo Laporte [00:03:23]:
all just pure C assembly or C.

Nirav Patel [00:03:25]:
Okay, yeah, C with a little bit of assembly mixed in.

Leo Laporte [00:03:28]:
So I'm just saying this to say establish his bona fides. You're definitely a hardware guy, right? But it sounds like you had maybe a little bit of epiphany working at Meta, making these meta quests that maybe this wasn't the ideal way to make hardware.

Nirav Patel [00:03:47]:
That's right, you could say that. So I've got. Yeah, you could say I've got the engineering background, but I had to put a suit on, a hyper, you know, metaphorical suit, since I'm wearing a sweatshirt today and realized that actually the fundamental problem in the computing industry was not really, in my view, a technical problem or an engineering problem. It was actually truly a business problem. And the business problem was the fundamental misalignment in the incentives of what's good for the companies in the space and what the consumers and businesses buying those machines actually wanted out of those.

Leo Laporte [00:04:21]:
And an environmental problem.

Nirav Patel [00:04:22]:
And an environmental problem. That's right. Obviously all those things tie together very tightly.

Leo Laporte [00:04:27]:
So you decided to found something that anybody would have said is a nutty thing to do with a brand new laptop company in the face of the apples and the Dells and the Lenovos of the world and the hps.

Jeff Jarvis [00:04:44]:
What year was that when you started?

Nirav Patel [00:04:45]:
That was in 2020. And you can see 2020 through 2026 is the most interesting period in time to have a hardware startup.

Leo Laporte [00:04:53]:
Crazy. By the way, if you're looking for it, frame dot work is the website. Did you put your own money into this? Did you get venture funding? How did you start a website?

Nirav Patel [00:05:07]:
Yeah, that's a great question. So I did get this off the ground with My own funding to put into it. And actually even that first round, we did actually do a venture round in 2021. We called it a seed round, but actually was almost entirely the Oculus friends and family connections that made that round possible because absolutely venture capitalists wanted to put money into a pre market laptop company.

Jeff Jarvis [00:05:33]:
Are you knocking butts?

Nirav Patel [00:05:35]:
Yeah, so it's a little bit of that. But then of course we did get into market. We proved that, yeah, of course there is demand for this. We showed the sales numbers and since then we've raised two additional venture backed rounds that have helped us fuel category expansion especially.

Leo Laporte [00:05:50]:
That's fantastic. And you've really taken it somewhere. The first framework was a 13 inch laptop, was fully modular. It came with a screwdriver.

Nirav Patel [00:05:59]:
That's right.

Leo Laporte [00:06:00]:
I bought, of course I've always bought the DIY version. You do ship a version that's preassembled. But I like the DIY and it's not hard. It's snapping in a RAM module. It's not a tricky thing to do.

Jeff Jarvis [00:06:11]:
It's like the IKEA of making computers even much easier.

Leo Laporte [00:06:15]:
Believe me, I'm never building furniture again. But this laptop was easy to put together. It was an amazing thing. I remember Cory Doctorow saying, I'm not gonna. I'm done with Lenovo's. That's right, it's Framework from now on. And of course he runs Linux on it. I've always run Linux on my frameworks.

Leo Laporte [00:06:32]:
You ship them with Windows as well? If people want Windows.

Nirav Patel [00:06:35]:
That's right.

Leo Laporte [00:06:36]:
I saw an interesting statistic though that mostly now, what is it, 60% Linux on the day?

Nirav Patel [00:06:41]:
Yeah, just in the last year or so has tilted over to being majority Linux, which is interesting because obviously from 2021 through 2026 we've grown our sales numbers multiple times. And you would think that when we did that we'd get greater percentage share of Windows rather than Linux. So we get like all the Linux enthusiasts in on day one and then we'd get into mainstream. But actually what we've seen is the opposite. We've gone from about 70% windows now to closer to 40 to 45% windows even as we've grown pretty substantially.

Leo Laporte [00:07:14]:
Isn't that amazing? I think that's a testament to Linux, certainly to the growth of AI, certainly. But also to the fact that people who buy Frameworks are computer nerds.

Jeff Jarvis [00:07:26]:
They're serious people.

Leo Laporte [00:07:27]:
We're serious people. That's a good way to do it. You also expanded the line with a 16 inch. One of the cool Things by the way, I fix it 10 out of 10 on the repairability score in that very first 13 inch and consistently 10 out of 10. What's amazing about it and was pretty much unheard of is you can upgrade it. You could put in an AMD processor and an intel processor, you could put a GPU in. Then you added something that got me really.

Jeff Jarvis [00:08:00]:
Wait, wait, wait. Before you get there, there was one little detour that I've already discussed is my disappointment that the Framework Chromebook is no longer.

Leo Laporte [00:08:10]:
Oh, you did do a Chromebook Briefly,

Nirav Patel [00:08:12]:
yeah, we did retire the Chromebook. We did, yeah. It was a little bit of a test between both Google and us of is there a market for a higher end Chromebook, A higher performance Chromebook? And a lot of it for Google at that time was especially around the environmental angle of repairability and longevity. Like they put obviously a lot of focus recently into software longevity and the hardware wasn't necessarily keeping up with the software at that point. And so for us it was okay, let's work together. We can build long lasting hardware to go with the software that you're now making last longer. And what we found in market was, at least at that time, which was about three years ago, there was unfortunately not a market for $1,000 Chromebook. That's not to say there couldn't be in the future, but that specific product just didn't quite pan out market wise.

Leo Laporte [00:08:55]:
Sorry Jeff. Sorry Jeff. Just bought a Neo, an Apple MacBook Neo.

Jeff Jarvis [00:09:00]:
So we replaced my 12 year old Apple box.

Nirav Patel [00:09:05]:
Oh yeah, yeah.

Leo Laporte [00:09:07]:
So we're working on them. Nirav. We'll get, we'll get them one day. You can plug in a GPU to the back, extend it. You can plug an additional battery in. You can have an orange bezel if you want. I love the colored bezels. You can customize it completely.

Leo Laporte [00:09:24]:
Really nice keyboards, trackpads. The whole thing is modular. It just warms my little heart to what you've done. But then you announced a desktop which is a little less upgradable than your laptops, right?

Nirav Patel [00:09:42]:
That's correct, actually, yeah.

Leo Laporte [00:09:43]:
What prompted the desktop?

Nirav Patel [00:09:45]:
Yeah, this is an interesting one. We actually, we get roadmap presentations and reviews from basically all the Silicon vendors going out a few years and a few years ago AMD came to us with a very, very interesting processor that was just on the horizon for them and they were actually framing this as basically a high end laptop processor to compete better with Apple and their very strong unified memory capabilities with a lot of memory bandwidth and when we looked at that processor, two things were obvious. One, there's no way we could reasonably fit it in a laptop. It was just massive overkill from a size and power perspective to actually fit in any of the laptops that we've been developing. And two, that actually this was going to be a killer processor to bring down the size and power consumption and cost actually of a handful of related use cases. So gaming content creation, general workstation use cases. But actually, most interestingly, what was then the emerging use case of being able to run LLMs locally on a machine that you own on your desk. And so that's something that, like a few years ago, we spotted this on the horizon, saw that processor and decided, okay, we need to enable that use case.

Nirav Patel [00:11:00]:
This is going to be huge. And for us, we can't fit in a laptop. It doesn't make sense in our laptops. Let's actually build a dedicated machine around this processor. It was that interesting a processor.

Leo Laporte [00:11:09]:
And now if you'll play the theme from 2001, A Space Odyssey, Da da da da, ta da. It isn't that big. Is that a mini itx? What is the.

Nirav Patel [00:11:22]:
It is actually mini itx. So even though it's not quite as upgradable, the memory is actually soldered. We tried to stick to standards everywhere

Leo Laporte [00:11:29]:
we could, but it's unified memory. So that's part of the reason the Strix Halo CPU system on a chip is so great. Notice I got the big Noctua fan.

Nirav Patel [00:11:39]:
Perfect.

Leo Laporte [00:11:39]:
And the clear screen because you want to see inside. And then I love the customizability of these little things, the tiles you can click on.

Nirav Patel [00:11:48]:
Yeah, we actually have a little special version here. We 3D printed some Noctua brand color.

Leo Laporte [00:11:53]:
Ooh, that's pretty for this one.

Jeff Jarvis [00:11:56]:
You're making them jealous.

Leo Laporte [00:11:58]:
I can tell by the way you're handling it, though, there's nothing inside that box.

Jeff Jarvis [00:12:01]:
No.

Nirav Patel [00:12:01]:
This is heavy. Actually. I've just been working out.

Leo Laporte [00:12:03]:
Is it. Oh, you're strong, man. I'm going.

Jeff Jarvis [00:12:06]:
What was the timing of this decision versus the explosion of interest in ChatGPT?

Nirav Patel [00:12:11]:
So it does align to the cloud models becoming very popular and the cloud services becoming very popular and actually aligns to some of those early model releases that made it clear that there were going to be very capable open weights models reaching the public, reaching developers and hobbyists, and the hardware was lagging behind it. So earlier versions of Llama were out there in the world and some of the models coming out of the open source labs in China were starting to get out into the world. But the actual hardware to access that was incredibly difficult to put together. And so we saw that as basically just a hole in the market for us to go and fulfill.

Leo Laporte [00:12:46]:
When I saw it, I saw, this is so cute. I want this so badly. And actually I bought it. Then I canceled it and I bought it again. And I'm glad I did because at this point it's a little more expensive because you. I mean, I got 128Gig model, the largest you made with the AMD AI 395 Plus. Really nice system on a chip designed. I mean, the whole point of this, and you remember this, Jeff, was I wanted to run local AI models.

Leo Laporte [00:13:16]:
But this was right before the supply chain crash and the rise in price, not just of RAM, but also now you're faced with rising prices and SSDs.

Nirav Patel [00:13:27]:
That's right.

Leo Laporte [00:13:28]:
And I don't even know if processors.

Nirav Patel [00:13:30]:
Yeah, processors as well.

Leo Laporte [00:13:32]:
Wow.

Jeff Jarvis [00:13:32]:
So, yeah, talk about the vice that you and your competitors are in right now.

Leo Laporte [00:13:36]:
Before you do that, I just want to show one more thing. All of these have this little modular. You can plug in these little. I love this idea too. This framework 13 started with this. So it's really a USB C port, but you can plug in modular. So I've got Ethernet and another USB C plugged in on the back. And all the laptops do that too.

Leo Laporte [00:13:56]:
So you configure the ports you want. Again, just really nice, thoughtful features that make people very happy. Okay, I'm sorry, go ahead. Oh, the lights went out.

Nirav Patel [00:14:07]:
Oh, we still got power in the building. Don't worry.

Leo Laporte [00:14:10]:
Okay. What did you ask again?

Jeff Jarvis [00:14:14]:
What's the supply chain and all these difficulties doing to you and your competitors? What's it like?

Nirav Patel [00:14:19]:
Yeah, it is a tricky time. Obviously there is demand for memory pretty substantially exceeding the supply over a period, very extended time window as well, unfortunately. And in Framework, we're kind of at this interesting scale where we have the necessary relationships, let's say the Microns of the world and the various module makers and distributors that we can still get access to memory. Like we do have a direct relationship with Micron. We can still get allocation.

Leo Laporte [00:14:49]:
Micron stopped selling to consumers. There was such.

Nirav Patel [00:14:51]:
They did. They pulled. Yeah. They close down the crucial brand, which obviously I know a lot of consumers are justifiably upset about. It does make sense from their perspective that if they don't have enough memory to go around customers who are buying from them, they don't want to be in a position of then competing with their Customers with their own in house brand. It would just be a challenging business move from their perspective to have to do that. So we definitely got it. We understand why they had to make that move, even though we were also sourcing crucial brand memory from Micron at that time.

Nirav Patel [00:15:24]:
But we're also just going back to the scale that we're at. We're also kind of at this interesting scale where we're small enough that we can get creative and be able to grab memory in ways that some of the bigger brands actually can't. So for us, we go and watch the spark market, we go and talk to brokers, and if some broker spots 5,000 pieces of memory sitting in a warehouse somewhere in the world for us, we can go and pick that up and it's meaningful and it helps us produce more laptops or desktops or for let's say an apple 5,000 pieces. It's a rounding error. They wouldn't even bother to talk to that broker. So we're kind of able to navigate in an interesting way because I like

Jeff Jarvis [00:16:02]:
that you're a chip dumpster diver.

Nirav Patel [00:16:05]:
That's right.

Leo Laporte [00:16:05]:
Yeah.

Nirav Patel [00:16:06]:
We do what we can.

Leo Laporte [00:16:07]:
We're talking to Nirav Patel, founder and CEO of an amazing company that I'm a happy customer of, Framework. At Framework Paris. Martineau is off out of the tunnel.

Paris Martineau [00:16:19]:
Hello. They tried to stop me. They tried to trap me underground.

Leo Laporte [00:16:22]:
You didn't walk. I didn't walk down the track. Did you? I hope not.

Paris Martineau [00:16:25]:
You know, I thought about just running through the rat filled tunnels of New York City, but I figured that. I figured that you guys could wait a little bit.

Leo Laporte [00:16:35]:
Yeah, we're fine.

Paris Martineau [00:16:36]:
I would have done that had there not been cell service in the L tunnel for me to tell you that I'm late.

Leo Laporte [00:16:42]:
Thank you.

Jeff Jarvis [00:16:44]:
Notoriously bad luck. She was.

Leo Laporte [00:16:48]:
Actually, Nirav just wrote a really important blog piece that has a lot to do with AI. But before I do that, you had another big announcement last week.

Nirav Patel [00:16:55]:
That's right.

Leo Laporte [00:16:56]:
So, okay, I'm gonna be a little Frank. The framework 13 and 16 were, you know, a little. In order to be modular, they have to be a little, I don't know, kind of clunky. A little bit. I mean, I've been very happy with my 13, but people complained, you know, and their battery life wasn't great. And I think you saw an opportunity. You announced basically a MacBook killer last week. Is it as modular? Is it as upgradable?

Nirav Patel [00:17:27]:
It is every bit as modular. And we actually still ship a screwdriver in the box.

Leo Laporte [00:17:32]:
Nice.

Nirav Patel [00:17:33]:
That's right. Yeah. We're not giving up on that part of the philosophy. But the whole idea here is it is to some extent, you could look at the original 13 and the 16 and call that maybe like enthusiast grade product that was very, very heavily targeted towards the power user, the DIY or the Tinkerer, the Enthusiast, the computer builder. And we did that knowing that we had to do that because we could serve those audiences really well. Like we could build a very, very modular machine with the parts and access that we had into the supply base, with the scale of R and D capabilities, with the funding that we had available to us as a very, very early stage startup, we could build the ideal enthusiast laptop. And we believe we did succeed at doing that. And now six years into that, five years into shipping these products, we're operating at a scale.

Nirav Patel [00:18:22]:
We have the funding, we have the R and D capability, we have the supplier relationships that we can build not just the ideal enthusiast laptop, but the ideal power user and developer laptops. And that means very much competing head to head with apple against the MacBook Pro.

Leo Laporte [00:18:39]:
Unibody aluminum.

Nirav Patel [00:18:41]:
That's right, full CNC aluminum, a haptic touchpad, full custom display using Intel's new processor. So very power efficient. New custom battery based Panther Lakes.

Leo Laporte [00:18:52]:
You're getting. People are going crazy over the battery life.

Nirav Patel [00:18:55]:
Yeah, the battery life is incredible. Intel did a great job this generation on efficiency.

Leo Laporte [00:19:00]:
One of the things we've always talked about with intel and the Panther Lake, and it was true with the Lunar Lake before it, was that the OEMs are doing a lot of special coding to make these processors work properly. Things like the lid closing and the thing turns off and then turns on when the lid opens. People, companies like Lenovo and Dell have such special relationships with intel, they're able to do that. Were you able to get that kind of access to intel and able to do those modifications?

Nirav Patel [00:19:28]:
Yeah, we actually have a very strong relationship with intel now. After five or six generations of products working with them, we've got direct engineering support from the team there and we engage very early. So for example, this Panther Lake system we have here, we've been working for over a year now with the team at intel to get early access, start doing our development, start doing software development around that platform. And that means that after that full year of development, we get to ship a very polished system, not just on the Windows side, but also on the Linux side as well.

Leo Laporte [00:20:02]:
Unfortunately, you've done such a good job with the original 13 and I've kept it up to date. It's really. I want this, I want this so badly, but I can't really justify it because I've been able to take the original and upgrade it.

Nirav Patel [00:20:16]:
That's the mission.

Leo Laporte [00:20:17]:
Beautifully, you know, you've done too good a job, you know.

Nirav Patel [00:20:21]:
And it is cross compatible. So even back to the original 13, you can upgrade piece by piece to get the new features and functionality.

Jeff Jarvis [00:20:28]:
Okay.

Leo Laporte [00:20:28]:
Except for.

Paris Martineau [00:20:30]:
Unfortunately it's a real compliment that LEO would feel uncompelled to upgrade. LEO owns more computers than any person I know.

Leo Laporte [00:20:38]:
I've been hovering my finger over the button actually. How. What is the delay now? You've had such demand on this.

Nirav Patel [00:20:43]:
Yeah, we actually went way above forecast on the sale so far. So we're sold into August right now for our pre order batches.

Leo Laporte [00:20:50]:
So yeah, we should get in there.

Jeff Jarvis [00:20:52]:
You better get.

Leo Laporte [00:20:53]:
I'm going to end up doing it. The way Framework works is they do batches in. When you order it, you'll be entered into a batch. Then you'll get an email when that batch starts to enter production. So you kind of know when you're going to get it. They give you a prediction. So if I ordered it now, I'd be getting it in August or September?

Nirav Patel [00:21:08]:
That's right, yeah. If you order it soon, you'll get into the August batch.

Leo Laporte [00:21:13]:
The nice thing is you can put a deposit down and they don't charge you until they're ready to ship it. So. And the deposit, Is it still 100 bucks?

Nirav Patel [00:21:19]:
Yeah, it's still $100.

Leo Laporte [00:21:20]:
Yeah. I mean you guys, you just really. Thank you. Really.

Jeff Jarvis [00:21:26]:
I've got, I've got a quick weird question. Dell was never Framework. However, I'm old enough to remember when you could configure your machine going off the assembly line and you had a sense of personal, of it serving your personal needs and desires. Did Dell screw up by leaving that or at their scale it just wasn't possible.

Nirav Patel [00:21:49]:
Yeah, this is an interesting one. There is still some custom to order capability across actually a lot of the big PC brands on some of their models, not necessarily all of their models. I think also they've kind of come to terms with the supply chain and go to market reality that if you pre bake a config and then you know push it out into the channel into retail especially that you can scale up your volumes. Of course that comes at that sacrifice, the personal touch of really making it yours.

Leo Laporte [00:22:17]:
So the real reason you're on despite the fact it really was just because I wanted to talk to you and I'm thrilled.

Jeff Jarvis [00:22:25]:
He is in fact a fanboy.

Leo Laporte [00:22:26]:
I will also say I'm a big fanboy. You announced, at the same time as you announced the new frameworks 13 Pro, you said something that was very provocative. You said personal computing is dead. Tell us about what. Wait a minute, what?

Nirav Patel [00:22:45]:
It was kind of this. It's this thing that's just kind of been building over the course of months, seeing just this combination of changes in the world all playing out in parallel with each other. The rise of cloud services and subscription models that kind of form this new wave of computing like subscribing to Claude or OpenAI. And that becoming your interface, becoming the way that you interact with your computer and the actual physical thing you're holding onto, becoming a little bit more of that terminal into someone else's model or someone else's computer sitting out in a data center somewhere. And then that being paired with the downstream ramification of those data centers, gobbling up all that silicon of the machines, the hardware that you actually can own, becoming harder and harder to own, just purely for price reasons. The memory price is going crazy, CPU prices, storage prices, and those two things playing together against of course this now multi decade backdrop of computers becoming more locked down, both from a hardware perspective and from a software perspective. It felt very clear to me that the way that we've thought about computing over the course of decades is not necessarily going to hold. That if we fast forward a couple of years, having a lockdown dumb terminal that's your window into someone else's computer that they own for you in the cloud that you are subscribed to may actually become the default.

Nirav Patel [00:24:16]:
And so that was kind of the genesis of the statement of personal computing as we know it is dead. It may actually be dead. And then for us as a company, as framework, for our entire mission, our entire purpose of existence is consumer rights giving you ownership, giving you power over your own computing. What does that mean for us? What do we need to do as a company in this environment? And for us it's really doubling down on. You should be able, if you want to own your computer, you should be able to own your computer. We want to make sure you can own your computer all the way through the software stack, all the way through the hardware stack. And even in a world where your interface is AI, we want to make sure that you can run that AI and have that be your AI rather than something that you're renting from the cloud.

Leo Laporte [00:24:58]:
You write the industry is asking you to own nothing and be happy.

Nirav Patel [00:25:03]:
That's right.

Leo Laporte [00:25:04]:
A little throwback to Steve Jobs. Computers are no longer a bicycle for the mind. That was his famous phrase. They're becoming. This is so sad. The self driving car that takes you directly to the destination. I think for many users that's not sad, that's exactly what they want.

Nirav Patel [00:25:18]:
That's right. And that was part of this manifesto, is that you could look at that and say actually that's kind of nice that I don't have to think about it, I don't have to worry about it, it's just going to work for me. But at the same time it goes back to this walled garden philosophy. Like you can be happy in the walled garden, but if you know about the existence of the world outside of that garden, you might feel very limited and constrained in there.

Leo Laporte [00:25:40]:
Yeah, well, and that's exactly why I bought the desktop is because I wanted to run my own AI models locally on a machine that was capable. Knowing that they're not quite as good as the frontier models yet. They'd probably always be a little bit behind, but they're good enough. What are people using now on frameworks, desktops as their local models if they are using local models?

Nirav Patel [00:26:04]:
Yeah, we see Quencoder being very popular. The new Gemma models are actually very strong from Google. We'll see what Meta comes up with. I think they're not going to give up on trying to be competitive in that space. Llama's fallen a bit behind, but I think Meta is going to have something big there coming. But a lot of the interesting models are actually coming from the, the big labs in China which has been a very interesting dynamic to see.

Leo Laporte [00:26:26]:
Yeah, I have a GLM subscription from Z AI and it's actually pretty surprisingly good. I feel like maybe because they distilled Opus just a little bit, but nevertheless they're pretty good. What do you use personally? Do you have a local AI running?

Nirav Patel [00:26:41]:
Yeah, actually I have two boxes I keep in my desk. One running windows, one running currently Fedora although switch between different, different distros and they run different like I openclaw and one I think I have Ermes running on the other and then usually I use something like Quencoder just, just to play with it. Mostly for just general toy box sandbox type uses. I don't yet I don't plug in our framework company data in.

Leo Laporte [00:27:05]:
Good, you're smart because they're going straight to China actually not if you're running it locally. That's the whole point of one thing. One piece of news that came out last week or the week before is that third parties are also making. There's a third party motherboard for the framework.

Nirav Patel [00:27:23]:
Yeah, we've got a couple now. We've got. Actually they're kind of related companies. Company called Deep Computing that's making RISC V mainboards.

Leo Laporte [00:27:30]:
Oh, that's cool.

Nirav Patel [00:27:31]:
Yeah, very cool to see. Now, two generations of RISC V and also a company called Meta Computing that's done in ARM based Mainboard, which is also great to see.

Leo Laporte [00:27:38]:
Yeah, very exciting. Paris, I know you had to come in late. Is there anything you wanted to ask about? Or is this. I've kind of monopolized this.

Paris Martineau [00:27:48]:
I was just say, I feel like you guys really. I mean, you can't compete with a expert in this like Leo, given his extensive views.

Jeff Jarvis [00:27:56]:
The.

Leo Laporte [00:27:58]:
I'm going to buy. Can't do it. I want to get in by August. I'm sorry. Just keep talking to him.

Jeff Jarvis [00:28:03]:
That's great.

Nirav Patel [00:28:04]:
Live order,

Jeff Jarvis [00:28:06]:
go out beyond that. Where do you see computing going now that you declare PC's dead? Just speculate a little bit.

Nirav Patel [00:28:19]:
Yeah. Something that I've been thinking a lot about actually is just this idea of being a modern participant in society and let's say an advanced society. How much compute, how much memory, how much storage do you need to be allocated to you as an individual to be able to operate in civilization? And you could look at it right now and say like, you know, we're here, the four of us are all here in America, we're, you know, operating professional jobs here and maybe we can survive a year ago or a few years ago. We could survive with, let's say like a few tens of gigabytes of memory, a few, maybe a few terabytes of storage allocated to us even for including what's amortized in the cloud, for the cloud services that we run and, you know, some amount of compute and year over year over year, that number is going to grow very, very quickly. The amount of just pure silicon that needs to be activated against each of us as individuals, for us to be participants in society is just going through the roof. And so for us, as we think about what does that mean if we're going to give you the power to own your data, own your compute, own your AI personally, What do we need to be able to build for you in a world where to be a modern participant in society you need terabyte of memory and multiple terabytes of storage and a very large amount of compute? Is it even plausible for us to build that box that you could sit on your desk that serves that level of compute to you.

Paris Martineau [00:29:49]:
Where does it. Where does the buck. Where does it end?

Nirav Patel [00:29:51]:
Where does it end? And maybe we all just get uploaded.

Paris Martineau [00:29:54]:
I was just saying when do we.

Leo Laporte [00:29:56]:
I'm volunteering.

Paris Martineau [00:29:57]:
How does it not scale Infinitely.

Nirav Patel [00:30:00]:
That's right. Yeah. I think that's. Maybe that's the end point. Yeah. We all get uploaded and we'll somehow in Framework, we'll upload with you.

Leo Laporte [00:30:07]:
If you look at these laptop pros, you've done some really, as always aesthetic things. The keyboards, people are loving the multicolor keyboards, the bezel. You really. It's more than a geek laptop. It's a real statement. It's really quite beautiful. It is. I wanted to order the Ultra X9.

Leo Laporte [00:30:27]:
It seems like you sold those out right away.

Nirav Patel [00:30:29]:
That sold out in like an hour on the day of announcement.

Leo Laporte [00:30:33]:
Isn't that telling that the most expensive SKU was the one that went away right away? Yeah. Yeah. People want power.

Paris Martineau [00:30:41]:
Did you guys expect that?

Nirav Patel [00:30:42]:
We did. We. So we. We actually shared during the announcement that we just had a pretty limited quantity of those. I think intel shared some things around like yield challenges for. For the very, very highest end.

Leo Laporte [00:30:55]:
It's 5.1 gigahertz. It's.

Nirav Patel [00:30:57]:
Yeah, it's. It's really pushing limits. But yeah, people obviously they want the power. So we sold out of those. The four.

Leo Laporte [00:31:03]:
Are you going to get more or is Intel.

Nirav Patel [00:31:05]:
We're talking to Intel. We're definitely trying to get it. We know that there's hunger for this, so we're going to get as many as we can.

Leo Laporte [00:31:11]:
Good. And you can buy ram. It's expensive, but they have managed to find a way. And it's not as expensive as it could be, let's put it that way. Same thing with the SSD's good. All right. Well I'm in the batch 11, so that's pretty good.

Jeff Jarvis [00:31:27]:
Do you ever think of doing, I don't know, a phone?

Nirav Patel [00:31:30]:
We get that ask a lot. Yeah. Whenever we do an ask for products and ask for what product should Framework build? Usually like three or four that rise to the top. Phone is one printer is usually up there on the list and then we

Paris Martineau [00:31:44]:
get a small projector that projects in your hand. You could exist beyond phone. That idea has clearly gone so well.

Nirav Patel [00:31:55]:
We often get. And then like stuff like toaster ends up being high. Unless people's. People like blenders, like appliances.

Leo Laporte [00:32:00]:
Yeah. Better toaster. Gosh. Yes.

Nirav Patel [00:32:03]:
Put the tester in the car.

Leo Laporte [00:32:04]:
The phone would be a phone. That is the one thing where you really are in the walled garden. It's very. And there are things like the fairphone, but it's very difficult.

Nirav Patel [00:32:12]:
Yeah, fairphone's done excellent work competing against the giants in the space. For us, actually, we look at the phone and see that again, it's a hard product to build, it's a hard product to get right. And it's again, maybe not as much a hardware challenge, a technical hardware challenge. There's a big software challenge there and then there's a very big go to market challenge to compete in the smartphone space.

Leo Laporte [00:32:34]:
All right, I think I'm going to get four USB C ports. No more of these USB A ports. I don't need hdmi.

Nirav Patel [00:32:40]:
Wow. All in.

Leo Laporte [00:32:42]:
I'm going all in, man.

Paris Martineau [00:32:45]:
What's the plan for Framework? Are you guys eventually looking, I know you're venture backed. Are you eventually looking for an exit or do you want to stick it solo for the time being?

Nirav Patel [00:32:56]:
The key for us, for me personally, is that I don't look at this as a financial outcome that we're chasing. It's really the mission outcome of going category by category and fixing as many categories as we can as quickly as we can and building install base and building market share and building ecosystems in each of these categories. And then the financial outcome is whatever it is. And obviously if we're succeeding at this, we're building a self sustaining company, we can fund our own scaling into these categories, we can basically dictate the financial outcome that we want. I think, I mean, I've been through an acquisition. I will say it's not. You have to let it for years.

Paris Martineau [00:33:40]:
Going through an acquisition gives you illustrative knowledge about all that it entails.

Nirav Patel [00:33:46]:
Yes.

Paris Martineau [00:33:47]:
Benefits and negative.

Nirav Patel [00:33:48]:
Yeah. And I've not been shaping Framework to be an acquisition target. Framework is a very spiky target. Not deliberately, but it is a spiky target. But yeah, very much. We're not looking for an acquisition.

Leo Laporte [00:34:00]:
Well, bless you, Nirav. You've done an amazing job, an amazing product and you're fighting the good fight and kind of uphill, frankly, against a lot of industry trends that are not as good for consumers. So we are very grateful and I know Cory Doctorow would say the same thing. Well done. Bravo.

Nirav Patel [00:34:19]:
Thank you.

Leo Laporte [00:34:19]:
Nirav Patel, Founder CEO of Framework at Frame. Don't go order the Pro yet because I haven't pressed the button. So hold on till I get mine and then you can go order yours because I think you're going to want one. Nirav, thank you so much for your time. We appreciate it.

Jeff Jarvis [00:34:36]:
Great to meet you.

Leo Laporte [00:34:37]:
Oh, that was a thrill and a half. Next week I'll be in Hawaii and I don't know, I think we're going to put the Chris Stoeckle Walker interview in there. And I'm sorry you guys missed that because Chris was great.

Paris Martineau [00:34:50]:
I'm sorry I missed that too.

Leo Laporte [00:34:52]:
Yeah, it was. It was really fun.

Paris Martineau [00:34:53]:
It ended up being wise that I called it because I was planning on taking that interview while on the Metro north back from Connecticut and the train was packed.

Leo Laporte [00:35:02]:
Okay.

Paris Martineau [00:35:03]:
So it would have been an awkward record for all of us.

Jeff Jarvis [00:35:06]:
Can't you all be quiet? I'm on a podcast.

Leo Laporte [00:35:08]:
As long as you're not in the quiet.

Paris Martineau [00:35:09]:
I mean, they don't. On the Metro north, there are no quiet cars, man.

Leo Laporte [00:35:14]:
Oh, there's only chaos in the Japanese bullet train. There is a quiet car. You damn well better be quiet.

Jeff Jarvis [00:35:21]:
Yeah, I'd like to see that. She's trying to do the podcast on the quiet car. Getting shushed by everybody. That'd be fun to watch.

Paris Martineau [00:35:30]:
Quiet cars.

Leo Laporte [00:35:33]:
And then we also have Troy Hunt, which is very exciting. Of have I been pwned? Coming up, my best looking Australian guy since Darren Okey. And then we got some good people on the slated in the future. So some really good guests coming up on intelligent machines.

Jeff Jarvis [00:35:54]:
This isn't your order, but I just. We got all the earnings. Palooza.

Leo Laporte [00:35:58]:
Yes. And I didn't have those before we. So Google, Meta and Microsoft all announced their earnings tomorrow. It's Apple. It's kind of crazy.

Jeff Jarvis [00:36:07]:
So I put them in the rundown under my.

Leo Laporte [00:36:10]:
Well, give us a summary. Did you feed it to. No, I did Claude or anything.

Jeff Jarvis [00:36:14]:
I should have.

Paris Martineau [00:36:15]:
So Jeff is our Claude today.

Leo Laporte [00:36:17]:
Jeff is today playing the role of Claude also tops Q1 estimates.

Jeff Jarvis [00:36:22]:
Yeah, so. So generally a lot of, by the way, worry. Well, what Google went down and then up, Amazon went down and up or

Leo Laporte [00:36:31]:
Google Microsoft went down and down.

Jeff Jarvis [00:36:33]:
Yeah. And Meta went down and down. Nervousness about AI spending, about capital everywhere. But the results are amazing.

Leo Laporte [00:36:40]:
Yeah.

Jeff Jarvis [00:36:41]:
For both. For Google and Amazon.

Leo Laporte [00:36:43]:
Yeah, they're doing very well. But as. As you know, Amazon's committed capital expenditures of about $180 billion next year, which is one reason the stock market's going.

Paris Martineau [00:36:58]:
I didn't see this before.

Leo Laporte [00:37:00]:
Amazon's also doing that. Alphabet's also committing 180 billion. Wow. Wow. And that's probably all data centers, right?

Paris Martineau [00:37:09]:
I mean, I'm. I didn't see this in your orderly. But I saw it in Jeff's, which, like, it's a big week, I feel like for financial news about these companies, especially given the Wall Street Journal report that my former colleague Berber Gin broke

Leo Laporte [00:37:26]:
and we're trying to get Berber on to talk about that.

Paris Martineau [00:37:28]:
Yeah, OpenAI's pressure that it's facing in the lead up to the ipo.

Jeff Jarvis [00:37:34]:
Why did they. Since they're a private company, they didn't need to let that be out.

Paris Martineau [00:37:38]:
They didn't let that out.

Leo Laporte [00:37:40]:
It was leaked.

Jeff Jarvis [00:37:41]:
It really was a leaked.

Leo Laporte [00:37:42]:
Okay, so Times also has a story. Andrew Sorkin and company also has the story. So OpenAI missed its internal targets. It wanted to hit a billion active users by the end of 2025. And they, as far as we know, still haven't done it. But remember the last time they announced it was 800 million. So they're close.

Paris Martineau [00:38:03]:
But they've also, I mean, the highlights are that they missed monthly revenue targets in earlier this year, repeatedly. The Wall Street Journal doesn't put a number on the size of the miss publicly, but the framing is basically that growth is decelerating. It's not just falling short of stretch goals. They also noted that the board is now more closely examining the company's data center deals in recent months and has questioned Sam Altman's efforts to secure even more computing power despite the business slowdown.

Jeff Jarvis [00:38:35]:
As Andrew Citron points out, that's bad news for Oracle. Yeah, because you've got all these companies that are depending upon future revenue from OpenAI promises, and it's bad news all around.

Leo Laporte [00:38:46]:
OpenAI, as you know, is getting ready for an IPO. And this is exactly the kind of. Of news that they don't want.

Jeff Jarvis [00:38:54]:
Better now than later, I guess. I mean, that's why. That's why I wonder whether it was really a leak.

Leo Laporte [00:38:58]:
I don't think so. I think actually they'd be much better after the. The IPO than before. Right.

Paris Martineau [00:39:05]:
Okay. Putting on my reporter hat when. So we get a story like this, obviously, all of the sourcing in this. Anonymous. It's all multiple people familiar with the issue. That means someone. And this is all about specifically disputes between Sarah Friars and other executives and Sam Altman's team. And then kind of going back and forth on specifically, there's this paragraph.

Paris Martineau [00:39:33]:
The spending scrutiny is constraining Altman's once boundless ambitions. Ahead of an initial public offering that could take place by the end of the year. Fryer and other executives are seeking to control costs and instill more discipline in the Business at times, putting them at odds with their CEO. Putting my reporter hat on. You have to think, how did this story get here? Obviously, Berber is a phenomenal reporter. He's got great sourcing in these companies. But the only sort of people who know all of this information are going to be high, high level executives that are in some way intimately involved with this or briefed on it. To be able to have multiple people familiar, it's probably one of the two camps leaking it.

Paris Martineau [00:40:11]:
Again, you have to think, why would somebody give this to the Wall street, leak this information to the Wall Street Journal? What would be the purpose for them? My guess is that it's people in Friars Camp who are trying to actually get these constraints to go through or feeling opposition and want the backing of pressure. Or maybe it's people in the Altman camp who want to force Friars Camp and Fryer to have to make a joint statement saying, oh, no, no, we're not doing that at all. Which is, of course, what they said in this pie of dispel these rumors.

Leo Laporte [00:40:46]:
That statement on Monday. We are behind on buying as much compute as we can and working hard on it together every day. Any suggestion we're divided is, quote, ridiculous.

Paris Martineau [00:40:59]:
And it's like, well, clearly there's some division because one of your two sides is leaking stuff to the Journal to try and turn the heat up on the other side. So I think this just speaks to a broader disagreement happening between these two camps and the intense pressures of trying to launch an IPO for a company with costs this astronomically high.

Jeff Jarvis [00:41:22]:
But is there. Is there also? I'm trying to see whether there's kind of a sandbagging strategy, too, that months before your ipo, you want to reduce the expectations. So that's why the IPO comes around. You raise them again.

Leo Laporte [00:41:35]:
Yeah, yeah, yeah. I think there's also. I think we should also point out there is a target on OpenAI's back from a lot of people, including Elon Musk, who is right now on the state, testifying in his court, testifying there and in Twitter. Yeah, yeah. The judge said, would you knock it off on the social postings? Both of yous didn't say it quite like that, but he basically said that Anthropic is also gonna do an IPO. And Anthropic and OpenAI are in the bitterest competition since Coke versus Pepsi. I mean, these guys are really at each other's throats. And I think that both Sam Altman and Dario Omode of Anthropic think it's a zero sum game.

Leo Laporte [00:42:17]:
One winner and one loser. But a lot of people would suffer consequences of an OpenAI collapse. That would be the trigger that would pop the bubble. If there is an AI bubble. That would be the trigger that would pop the bubble. Uh oh, here she comes with the bubble. Gonna pop. Watch out.

Jeff Jarvis [00:42:39]:
Oh God, I forgot about that.

Paris Martineau [00:42:42]:
This is the clip that accidentally showed up for a brief second on last week's episode.

Leo Laporte [00:42:47]:
Everybody was wondering, why is what's going on? And it was just a second, just

Paris Martineau [00:42:51]:
a second teasing of a little bubble.

Leo Laporte [00:42:53]:
Teasing it.

Paris Martineau [00:42:53]:
We love and we love. I'm happy that I finally get one. It's so great, Anthony. But I think. Yeah, to your point, Leo, I think that there are reasons why people on both sides of this debate, even within OpenAI, would feel motivated to try and leak this for those exact reasons. Like if you're on the Altman camp, you're like, well, we have to get as much compute as possible. We have to build as and scale as quickly as possible or else the bubble might pop and this might all be for naught. And you could see from the Friar camp that they'd be like, well, we actually have to rein in our spending and make sure that we have are able to meet some reasonable expectations before we hit the ipo, or else the bubble could pop.

Jeff Jarvis [00:43:42]:
Meanwhile, Anthropic is looking at a higher private market valuation right now than Open AI.

Leo Laporte [00:43:49]:
Yeah, Anthropic is very popular right now.

Jeff Jarvis [00:43:52]:
Yeah.

Leo Laporte [00:43:52]:
But I should point out, much like Coke and Pepsi, there isn't all that much to distinguish the two models. And it could swing.

Jeff Jarvis [00:44:03]:
Your partner is going to be upset with you tonight if you're saying that.

Paris Martineau [00:44:06]:
Shh.

Leo Laporte [00:44:06]:
I didn't say anything, Claude. I'm not talking to you. In fact, this week, OpenAI released SPUD, their 5.5 ChatGPT model. They also released new image models people have been very impressed with. But they do this in response, you know, to 4.7, which came out the week before. Let's not forget the Chinese companies like deepseek just released version four. We'll talk about that a little later. It is very competitive out there.

Leo Laporte [00:44:33]:
And I don't know if. I don't know if the winner is clear at this point. So in other words, there's a lot of chum in the water.

Paris Martineau [00:44:44]:
And I think the closer and closer the two, the more interchangeable the two products are, the more that these business fundamentals ultimately end up being incredibly meaningful for either company's ability to stay alive and win this race. Because Ultimately both of them are hurdling have to hurdle towards an ipo. Given the amount they've raised, they can't continue, you know, to be private. And it's like well how is the market going to react if you whenever they have to file an S1 and it comes out that they're burning God knows how much every single month.

Leo Laporte [00:45:23]:
Well but again look at the quarterly results from Google, Amazon and Microsoft. All three are burning lots of cash building data centers. They're also in a head to head battle between Azure, AWS and Google Cloud. Literally. I mean they are fighting head to head and I think the market generally approves.

Jeff Jarvis [00:45:47]:
Yeah. And their results, well and for Amazon and Apple, I mean Alphabet, their results are amazing. Flew past the expectations.

Leo Laporte [00:45:56]:
Flew past. So even though the stock drops, this always happens. The rule of the market is buy on the rumor, sell on the news. And this is the news, right? Is the results. I think the market's pretty tolerant of these big capex expenditures because there's generally a feeling rightly or wrongly that we've got to build all this compute capacity that this is the way forward with AI.

Jeff Jarvis [00:46:21]:
Well that's enough.

Paris Martineau [00:46:23]:
Whether it is key difference with these is that all of the companies you just mentioned also have large, robust, mature, profitable businesses undergirding them. And OpenAI and Anthropic are new upstarts that I'm guessing all signs point to are losing a lot of money every month, every quarter, every year and probably will continue to lose a lot, a lot of money for a long time until the goal is that they'll make like an Amazon or Uber esque pivot eventually when they reach the sort of scale and then it'll be, you know, nothing but net, so to speak.

Leo Laporte [00:47:00]:
The other data point that's confusing to me, maybe you guys can think of a rationale is that Microsoft kind of freed OpenAI from the chains. Remember Microsoft was the initial big after after elon, Microsoft gave OpenAI $10 billion in Azure credits. They're running on the Azure cloud and really made a big commitment and they're reselling ChatGPT as co pilot and so forth. Microsoft and OpenAI have agreed just the other day to drop the software giant's exclusive right to sell OpenAI models. So immediately OpenAI turned to Amazon and said and you get ChatGPT and it's on now on AWS, which a lot of people who use AWS are very, very happy about. Microsoft no longer has to pay a rev share on OpenAI products. It resells on its cloud.

Jeff Jarvis [00:47:55]:
What about the AGI clause?

Leo Laporte [00:47:57]:
And that's. That was one of the most interesting things I brought up with Paul Thurat. There was this clause which we always, all of us thought was bizarre, that should OpenAI reach AGI art, super Intelligence, you know, the singularity. We don't. There's no even good definition for AGI should it reach whatever that is, AGI. And they had third parties that would validate that, that the agreement would dissolve. Right. That the OpenAI would get to go on.

Leo Laporte [00:48:28]:
It's a merry way that's gone. And some people said, well, that's what's keeping OpenAI from announcing AGI. I don't know if that's the case.

Jeff Jarvis [00:48:38]:
Announcement.

Leo Laporte [00:48:41]:
The whole thing is meaningless. We never understood why the clause was in there in the first place. It was actually added later to the agreement anyway. I feel like we don't really know what's going on at all.

Jeff Jarvis [00:48:56]:
Amazon got freed from some shock. Not Amazon, I think Microsoft, in my view. Microsoft got the better end of that deal. They were desperate at the beginning to have some AI. They went to OpenAI. It seemed clever at the time. They got kind of shackled with it and now they're free to do what they want to do and OpenAI is free to do what it wants to do. And it makes more sense.

Leo Laporte [00:49:15]:
Yeah, it's. Yeah, okay. I mean, I don't understand any of it, to be honest with you. It just feels like people are running around like hamsters in a hamster wheel as fast as they can.

Paris Martineau [00:49:32]:
Paris, I'm curious as to your guys thoughts. Not to derail slightly, but I'm curious as your guys thoughts on this thing that I've seen running around the forums lately, which is. I'll post the link in the discord right now. My GitHub copilot this week announced a increase in the model multipliers for its annual kind of Copilot Pro and CoPilot Pro plus subscribers. And a lot of average users seem to be pointing to this as a possible like smoking gun about how much actually these models and the tokens are costing companies. For instance, they changed the multiplier for usage for Claude Opus 4.7 from a modifier of 7.5 to 27, which is completely out of whack with every other model. Basically the Claude credits or the multipliers have increased like exponentially and all the other ones have. I mean they've increased like six times or something like that.

Paris Martineau [00:50:37]:
But nothing as much as a jump from like 7 to 27 does this make sense to you in some way? It doesn't to me. Or is this, as the commenters seem to be crying, a sign that all this AI is way more expensive than we actually think it is?

Leo Laporte [00:50:56]:
Yeah, it might be making the pricing more accurate. I think it's also the case these companies need money badly. I think really the biggest constraint right now is just pure compute constraint. Those data centers aren't getting built as fast. They keep announcing new deals, but they're not getting built that fast. We're running out of hardware chips.

Jeff Jarvis [00:51:22]:
Do you think there's any hoarding of this stuff going on?

Leo Laporte [00:51:25]:
Oh, yeah, for sure. You're hoarding it. Yeah.

Jeff Jarvis [00:51:27]:
So there's a lot that's unused, so we don't really know what the, what the necessary demand is. And there's a debate about whether super scaling is the path to the next universe.

Leo Laporte [00:51:37]:
Well, that debate is a side debate that is not widely accepted by the current frontier model companies. Right.

Jeff Jarvis [00:51:44]:
The current main ones. But, but, but there's.

Leo Laporte [00:51:46]:
So that's a debate that you. This is that old, you know, Yann Lecun, Fei Fei Li debate. But, but that is not what the, what the leading edge companies are.

Jeff Jarvis [00:51:58]:
Well, even Demos changes his tune.

Leo Laporte [00:52:00]:
Yeah, Demis says it too, of DeepMind. But I think generally the big players,

Jeff Jarvis [00:52:08]:
generally, you're also saying right now, more

Leo Laporte [00:52:10]:
compute, the better lesson is learned. The LLMs are doing the job and we just need to throw more power at them. More power. Whether they're right or wrong, we won't know. We can't know. And you know, I mean, there's no ev. Let me put it this way. There isn't a lot of evidence they're wrong.

Leo Laporte [00:52:31]:
There's speculation.

Jeff Jarvis [00:52:33]:
Uncle Leo, since you were old enough to remember this, the overbuild of fiber in the country, what was that sequence like where there was. There was euphoria about building, there was a huge need to invest in it, then there was a crash, but then we ended up using it. Is there a similar path that could be here?

Leo Laporte [00:52:55]:
Well, I'm assuming we are. Now that's, that's what Jeff Bezos was saying, is that you can't compare an infrastructure bubble to a financial bubble, and that this, like the fiber overbuild or the railroad overbuild, is a infrastructure bubble. And so you get, at the end of the day, when the bubble bursts, you get the infrastructure no matter what. And that's what happened with fiber. That's what happened with, with railroads in it, presumably, is what's going to happen with data centers maybe. I think that there isn't a lot of historical precedent for what AI is going to do to the economy. I think part of this is really all a lot of this scrambling is that no one knows what the impact of AI is going to be on the economy and on jobs and business and software. It's.

Leo Laporte [00:53:44]:
And you see all these theories. It's going to kill open source. It's going to be the best thing that ever happened to open source. It's going to be a security nightmare. It's going to solve all security problems. No one knows. And there's just this great uncertainty and

Jeff Jarvis [00:53:56]:
it's being used as an excuse to do layoffs that probably aren't related to AI.

Leo Laporte [00:53:59]:
There's AI washing going on.

Jeff Jarvis [00:54:01]:
Right.

Leo Laporte [00:54:01]:
Although I think you probably can safely say when companies like Meta and Snap lay off thousands of employees, their plan is to make up for some of that with AI. And I think that's for sure true.

Jeff Jarvis [00:54:15]:
Or they're abandoning things that they don't think are as potentially profitable and they want to put whatever resources they have into AI.

Paris Martineau [00:54:25]:
I was to say, I mean the big tech companies especially, especially since the pandemic but increasingly I feel like over the last eight years have made it a kind of a regular practice to have annual layoffs of some sort.

Leo Laporte [00:54:38]:
It's just part of we overbuild business

Jeff Jarvis [00:54:40]:
plan and they're still up from where they were right.

Leo Laporte [00:54:43]:
We over hired and. And now they're right sizing, if you don't mind me.

Jeff Jarvis [00:54:48]:
So the point is we don't have data yet. To your point about.

Leo Laporte [00:54:51]:
We don't have data yet of anything. We don't know what's going to work. We don't know what's going to happen. There's a lot of uncertainty. We don't know if we're going to get oil from the Strait of Hormuz. There's a lot of uncertainty in the world right now and I think that a lot of this is just thrashing as companies and investors and venture capitalists and stock market investors are trying to figure out what's going to happen. I don't think anybody knows.

Paris Martineau [00:55:14]:
It's just I think to a point that you often make on the show, Leo, which is kind of comparing it to the Internet. I think that some part of people's what you might describe as an overreaction to AI and obsession with kind of pontificating about the potential impacts is that a lot of people, if you're thinking about a lot of industries didn't accurately predict or prepare for what the advent of the Internet would do to their businesses. For instance, frankly, media companies should have been thinking about this and how they

Leo Laporte [00:55:45]:
didn't want to Craigslist. They may have. They, I don't know, you were in the front. Everybody. They may have known, they just didn't want to, they.

Jeff Jarvis [00:55:51]:
Well, it was a mix, I think that some, some news didn't know, but they didn't, they didn't know what to

Paris Martineau [00:55:55]:
do, they didn't know what to do and they didn't spend nearly enough time thinking about what they should do and thinking of ways to prepare for it. And so I think what we're seeing now is an overcorrection to that.

Leo Laporte [00:56:08]:
Right.

Paris Martineau [00:56:09]:
This is one of many, you know, people were thinking would be like crypto or NFTs or something like that before, but that was obviously small. This is such a potentially transformative technology that everyone is freaking out and devoting so much energy to trying to suss out the precise impact this is going to have on the world and the ramifications of that because they're afraid if it ends up like the Internet, it's going to be a disaster for them.

Leo Laporte [00:56:33]:
Well, and in a non financial vein of the same kind, people like us, we thought the Internet was going to be great. We didn't see all the harms and the hazards that the Internet was going to present. So everybody's thinking, geez, we missed the boat on that. But financially and societally maybe we should plan. But the big difference here is this is happening at least 10 times faster than the Internet happened. The Internet didn't, you know. When was the AOL summer, Jeff? 95, 96. That was one big transition where a lot of non techie people suddenly got on the Internet.

Leo Laporte [00:57:12]:
It still took another 10 years before the web really kind of took off. Blogging didn't take off till the early 21st century. I mean I would say it was a, it was at least a decade of development before the Internet got to where we are today. Maybe 20 years. That's going to be compressed to a year or two in AI. I mean this is happening really fast. So if you weren't prepared for the Internet, you are not going to be prepared for AI. I agree with you that.

Leo Laporte [00:57:42]:
Exactly your premise, exactly that people are saying, well we got to prepare here. But it's moving so fast, you're going like what, what, what, what, what do I, what do I do? What do I do?

Jeff Jarvis [00:57:52]:
Well, here's the other piece of it too. So Sam Altman put out his principles. Another one of his. Another one Essays. Yeah, another one, man, that guy's. And I wrote. I wrote a brief piece just trying to remind that in the end, the technologists don't have the technology and he thinks he can control everything, including government policy about this.

Leo Laporte [00:58:07]:
Yeah.

Jeff Jarvis [00:58:08]:
And he can't. And it's going to be out of his hands.

Leo Laporte [00:58:11]:
Right.

Jeff Jarvis [00:58:12]:
And government's always behind. And I just listened to a podcast about a. With the authors of a book called Muskism. It really is, and it's really interesting. The premise there is that Musk's view is that he combines business and government. Musk depends upon government.

Leo Laporte [00:58:29]:
He does.

Jeff Jarvis [00:58:30]:
Yes. Right. For rockets, for satellite transmission. Doge, all of it.

Leo Laporte [00:58:36]:
A lot of his funding really came from us, from taxpayers. Yeah.

Jeff Jarvis [00:58:39]:
And there's. And there's a belief there of control. But these guys. And part of the reason that people hate AI is because the AI boys.

Leo Laporte [00:58:47]:
Well, people also hate AI because they're scared.

Jeff Jarvis [00:58:50]:
Yeah. But there was another survey, a bunch of surveys that came out this week. I put the rundown somewhere where if you look at the. The fear of AI in the US or the confidence in AI in the US is in the 30% range. In China, it's an 85% range. In Germany, it's in the 45% range where they're scared of everything. And so the narratives here of the extremes of the extreme optimism and extreme pessimism and doomsterism have taken over. And there isn't.

Jeff Jarvis [00:59:26]:
To your earlier point about not having the data. We also don't have the mindset to look at this sanely.

Leo Laporte [00:59:31]:
Well, I can tell you why we're more scared here in the US Than we are in China. They have a safety net.

Jeff Jarvis [00:59:36]:
Net.

Leo Laporte [00:59:36]:
We have no societal safety net.

Jeff Jarvis [00:59:38]:
True that.

Leo Laporte [00:59:39]:
All of those people can be out of work. They. They're going to be on the street.

Jeff Jarvis [00:59:43]:
And one could argue this is a time for a controlled. I'm not suggesting this here, but if you, you know, a controlled economy, AI will, Will grow there faster than here. It'll get all the. As Jensen Wong said, they'll get all the power they want. They got all the resources they want,

Leo Laporte [01:00:00]:
and I guess they're going to be. My point is we don't know what's going to happen and any prediction or attempt to prepare for it. I know I should get Amy Webb on because that's her job is preparing companies and governments for the future. I think any attempt to prepare for it is. Is futile because we don't it's, it's. This is chaos.

Jeff Jarvis [01:00:22]:
But aren't you singing a slightly new tune, Leo, in the sense that you've scolded both of us, saying this thing is the arrival of it's everything. And it is. And unless you write, I didn't say

Leo Laporte [01:00:32]:
it's going to be a wonderful world as a result.

Paris Martineau [01:00:36]:
I don't know. I think part of what Jeff is getting at is there have been discussions previously where you've kind of pooh, poohed the idea of hand, like wringing your hands over what the impact of AI is going to be, that it's already here and you don't need to be posturing about it. But I do think we all are kind of in agreement that people are worried because it is here and happening and they're trying to do it better.

Leo Laporte [01:01:01]:
That's not inconsistent with what I've just said.

Paris Martineau [01:01:03]:
Yeah, because

Leo Laporte [01:01:06]:
we don't know what's going to happen. So you can. It's a philosophical exercise to kind of plan for the future, but good luck. All we know is that the future is going to happen and it's going to be, I think, extremely disruptive, chaotic. It might be good, it might not be. I, you know, I mean, I think it's very, you know, so some of what I. Drives my point of view is I'm just very interested in it. Yeah.

Leo Laporte [01:01:36]:
And so I'm not trying to, I'm not trying to come up with a con. A consequence of what happens because I don't, I don't know. It's going to be crazy, man.

Jeff Jarvis [01:01:47]:
So line 144 is the.

Leo Laporte [01:01:48]:
Well, no, we gotta take a break. Hold on.

Jeff Jarvis [01:01:50]:
Oh, okay. So.

Leo Laporte [01:01:51]:
All right. Money going back and forth, people throwing shade at one another. The Pentagon's using anthropic. Google says we've done a deal with the Pentagon. They've signed a classified AI deal for quote, any lawful government purpose. Google employees immediately petition Sundar Chai.

Jeff Jarvis [01:02:13]:
Well, I think they were even before that.

Leo Laporte [01:02:15]:
No. Hundreds of Google employees signed a letter against the idea after reports at Google's and talk with the Pentagon. So yes, that was before the talks resolved themselves into a deal. I guess they didn't listen to the engineers. We'll see what happens on that. There's. I know there's a lot of pro back and forth. I swear to God, I haven't heard the testimony from today, but Elon Musk is on the stand.

Leo Laporte [01:02:47]:
The Verge said he appeared yesterday more petty than prepared. He was unfocused and uncharming.

Jeff Jarvis [01:02:54]:
Elon.

Leo Laporte [01:02:54]:
Elon. Well, Elizabeth Lopato wrote this story, said, you know, in the liability case during his defamation suit, he turned on the charm. She said, this is not the first time I've seen Musk in court. And the jury responded by finding him not guilty. Today, Lopato writes, he looked adrift and unprepared. The only times he showed real animation was when he was bragging about how much he'd done for OpenAI. Of course, the suit is. Elon said, I poured all this money.

Leo Laporte [01:03:24]:
OpenAI. And then all of a sudden they go for profit and leave me out. And I want my hundreds of billions of dollars.

Jeff Jarvis [01:03:30]:
Pieces of the case got thrown out. Pieces are left. What's at stake now? Do you understand what the standing is?

Leo Laporte [01:03:37]:
The piece that got thrown out was actually at. At the behest of Musk's own team, who said, we're not going to go after the fraud part of this. They were, they were going after OpenAI for defrauding Elon. They said, we're not. We're not going to go after that. But they're still going after him, saying, you can't do this. Non, fake, non, saying, first of all, it's fake, this nonprofit move, and you can't separate the stuff that I invested in and my supposed revenue from that by saying, well, you invested in the nonprofit part. We're just going to take those profits and move them over here and you don't get any.

Leo Laporte [01:04:20]:
Elon. That's really essentially what it comes down to. During the discussions of how best to get OpenAI the vast amounts of funding it would need for compute, there was a discussion of a for profit army with Musk, but that's not why Musk got into it. He says, I got into it because I had a conversation with Larry Page. It scared the pants off of me because Larry Page says, AI is the next species and I'm specious if I want to defend humans against AI. And Elon said, my God, when I heard that, I said, we've got to make sure Google doesn't get AGI before anybody else.

Jeff Jarvis [01:05:00]:
But is the. Is the argument in the end you simply cannot convert to a full profit?

Leo Laporte [01:05:05]:
Yeah. Or if you do, I want a. I want 55% of the profit, which is like a lot. Hundreds of billions of dollars. Anyway, he's testifying. He's still testifying. Presumably.

Jeff Jarvis [01:05:19]:
Paris.

Leo Laporte [01:05:19]:
Presumably the cross examination is today.

Jeff Jarvis [01:05:23]:
Oh, yep.

Paris Martineau [01:05:25]:
You can hear me now.

Jeff Jarvis [01:05:25]:
Here we are. Now we are.

Paris Martineau [01:05:26]:
Yeah. I was saying he. He's also asking for Sam Altman to be removed from the board.

Leo Laporte [01:05:30]:
Oh yes.

Paris Martineau [01:05:31]:
And everything, you know, it's all vindicative.

Leo Laporte [01:05:33]:
This is a fight to the death.

Jeff Jarvis [01:05:36]:
What's. So what's the open AI's argument going to be? Do you think wouldn't have survived as a not for profit? We had to. It's all about scale to rescale.

Paris Martineau [01:05:42]:
We had to be profitable from OpenAI's attorney says we're here because Mr. Musk didn't get his way at OpenAI. That's what happened. He quit saying they would fail for sure. But my clients had the nerve to go on succeed without him. He basically used funding promises to bully early OpenAI, trying to like merge OpenAI into Tesla, demanded 50% of ownership and pulled 5 million quarterly donations mid negation.

Leo Laporte [01:06:13]:
Casey Newton told NPR this is a clash of two enormous personalities and Elon Musk and Sam Altman. Sam Altman will take the stand later in this trial. And I think what's at stake is potentially the future of OpenAI and the future development of all AI. That might be a little bit hyperbolic.

Paris Martineau [01:06:29]:
Well, I mean I think that part of what he's getting at is that the one of the remedy figures is like $134 billion kind of what they're looking for. And that's the same order of magnitude as open AIs, like near term compute exposure. So I guess if Musk was to win meaningfully, it would be, yeah, like fatal to their roadmap.

Leo Laporte [01:06:50]:
Well, clearly Musk wants to do that because remember after all this, Musk started XAI and went right into a for profit competitor that he's pouring billions of dollars into. And so this is.

Jeff Jarvis [01:07:01]:
But is there any business to xai? Is there any users?

Leo Laporte [01:07:05]:
I don't trust this. I know you're surprised to hear me say that, Jeff. I can see this stunned look on you.

Jeff Jarvis [01:07:15]:
Aren't I a subtle actor? What?

Leo Laporte [01:07:20]:
But I mean, we don't know, right? Nobody's making money at it yet. I mean, I think there will be, but I think you're right. It might be like fiber and the railroads, it might be that, you know, the railroads, all the companies that built the transcontinental railroad went bankrupt. But we had the tracks. We had the trains.

Benito Gonzalez [01:07:39]:
I think the difference really is that the tracks don't go. Tracks don't get old. You know, you can still use those tracks, right?

Leo Laporte [01:07:46]:
Yeah, that's a good point. I don't know what would happen.

Jeff Jarvis [01:07:49]:
Well, you do at some point.

Leo Laporte [01:07:51]:
Nobody wants chat GPT4O anymore.

Jeff Jarvis [01:07:54]:
I went to The Museum of Industrial History in Bethlehem, Pennsylvania last weekend because they have a Linotype there. So you know that I'm adding that

Paris Martineau [01:08:02]:
to my museum list. That sounds so funny.

Jeff Jarvis [01:08:04]:
They have huge pumps. They have a little tiny, the little tiny diesel engine that used to drive things around the steel mills. You can ride that for about 20ft. You can go see, you can go on the catwalk and see the old huge blast furnaces. How long of a drive was it from from you? It's probably an hour and a half.

Paris Martineau [01:08:26]:
Ooh, When Leo comes. I'm doing that.

Jeff Jarvis [01:08:29]:
When Leo comes, we could see the Amazon warehouse and go to Bethlehem.

Paris Martineau [01:08:33]:
Leo visit us. Could eat a sandwich made by yourself.

Leo Laporte [01:08:39]:
All I was going to do is give a sandwich which we'll get take

Jeff Jarvis [01:08:42]:
out and then we'll go to the car.

Leo Laporte [01:08:45]:
According to Alex Kantrowitz, Also talking to NPR, Elon's goal in this is to just shut OpenAI down because the money he gets would go, he says, to a charity, not to him. He doesn't want money. He wants to put them out of business, which is one way or two.

Benito Gonzalez [01:09:03]:
The charity that's in his compound that houses all of his children probably.

Paris Martineau [01:09:08]:
Yeah, the charity that teaches his children how to read.

Leo Laporte [01:09:12]:
I'm sure there's a legitimate charity. He doesn't need more money. I'm just trying to find out if anybody has reported on his testimony today. And I don't see anything. So if somebody finds a link, let me know because he was, I mean, I'm sure court is recessed. It's in Oakland. So it's California time. It's 3:30.

Leo Laporte [01:09:31]:
OpenAI may be doing a smartphone. I wonder if this is the Jony I've project. They gave him 3.2.

Jeff Jarvis [01:09:38]:
Well, otherwise what's he doing there?

Leo Laporte [01:09:40]:
Right? This is from Ming Chi Kuo who is normally a supply chain analyst who reports on Apple. But he does have good sources in China in the supply chain. He says OpenAI is going to make a deal with MediaTek and Qualcomm for a processor. MediaTek makes a very good Chromebook processor by the way, despite its kind of down market name. They're actually pretty good. Qualcomm of course makes the Snapdragon. And the builder, the manufacturer would be Luxshare, which is a design contractor. They would be the system co design and manufacturing partner.

Leo Laporte [01:10:14]:
Don't worry about saving your pennies yet. Mass production doesn't start until 2028. But according to Ming Chi Kuo, and again it's a rumor, but he has very good sources in the supply chain. The idea of this phone is it will not have apps, it will have AI and it will be an agentic phone that you will tell it what you want and it will do what you want.

Jeff Jarvis [01:10:40]:
Exactly. To Nirv's point earlier in the show.

Leo Laporte [01:10:43]:
Yeah.

Jeff Jarvis [01:10:43]:
That you're not going to own anything.

Leo Laporte [01:10:44]:
You're going to own your apps you don't even own.

Paris Martineau [01:10:46]:
Great. Because that's worked out really well in terms of video games and media and. And everybody loves when they don't own anything. And it can just be taken from you at any given point or you can be suddenly charged a subscription to have things like windshield wipers in your car. People have been clamoring to have a system like that, but for everything.

Leo Laporte [01:11:08]:
What's the number one music source in the world right now? It's either Spotify or itunes in both cases.

Jeff Jarvis [01:11:17]:
Because you're trapped.

Leo Laporte [01:11:18]:
Buying the music you're renting.

Jeff Jarvis [01:11:19]:
Yeah, but you're trapped. You don't. People don't want that. But that's what we ended up with.

Leo Laporte [01:11:22]:
Do they not want it? They can still buy DVDs, they still buy digital copies of music.

Paris Martineau [01:11:28]:
So you think it's good that.

Leo Laporte [01:11:29]:
No, I don't think it's good. I'm just saying that our. Our set does. Is aware of this. But I don't think your mom and dad care.

Paris Martineau [01:11:41]:
I mean, I think my mom and dad care a lot. Whenever they're like, I could have just. They used to take me to the store to buy Windows.

Leo Laporte [01:11:49]:
Used to.

Paris Martineau [01:11:50]:
But now they. And you pay one thing and you get Microsoft Office and now you gotta pay every month.

Leo Laporte [01:11:55]:
Used to, but. Well, I agree with Microsoft Office. Nobody.

Paris Martineau [01:11:59]:
I mean, but it's the Microsoft Office cation of the universe.

Leo Laporte [01:12:04]:
No, I get it. I agree with you 100%. But I'm just wondering if the general public, I mean, they seem pretty happy with Spotify.

Paris Martineau [01:12:10]:
I mean, I think I see this as a common complaint. Like in various social media from normies. No, but I see it like Reddit and Twitter. I'm sure if I was on threads, it would be there too. The average person doesn't like that they have to pay a subscription for everything. They realize that that sucks.

Leo Laporte [01:12:27]:
Yeah, that's true. Yeah, but. Yeah, but they live with it. I mean, honestly, if you looked at the box price of Microsoft Office of six or seven hundred bucks and then I said to you. Or you get it for eight bucks a month with automatic updates, it looks like it's a better deal until you

Benito Gonzalez [01:12:43]:
calculate how many months you're going to use it for.

Leo Laporte [01:12:46]:
Well, if it's. If you paid 100 bucks a year, but it would cost you 600 bucks to buy it outright in six years, are you going to need to buy another version? Probably.

Jeff Jarvis [01:12:55]:
The other dynamic here is that there is a finite number of subscription dollars that people are willing to spend.

Leo Laporte [01:13:00]:
That's an interesting point. Yes. Yeah, People are. There is subscription.

Jeff Jarvis [01:13:04]:
You know, screw it. I don't want my newspaper anymore. There was just a survey out about people who live in news deserts and they don't have newspapers in their county and they don't notice.

Leo Laporte [01:13:15]:
Right.

Jeff Jarvis [01:13:15]:
And they don't pay for anybody. And they find the news the way they want to find it.

Leo Laporte [01:13:18]:
Paris, they're buying DVDs. But Paris, you're in a very small minority. Almost everybody streams the movies.

Paris Martineau [01:13:24]:
I'm not claiming that the people YEARN to buy DVDs. I am saying that the people enjoy.

Leo Laporte [01:13:32]:
Enjoy not paying money for anything.

Paris Martineau [01:13:34]:
The people get mad whenever they realize they're paying for seven different streaming services to. The people are mad that we're basically reinventing the cable bundle. But for every industry.

Jeff Jarvis [01:13:47]:
Yes.

Paris Martineau [01:13:48]:
And there's a certain point where as more and more parts of an industry become monthly subscriptions that, like, it reaches a saturation point. The average person can't pay hundreds of dollars a month for, like, everything.

Benito Gonzalez [01:14:04]:
You know, Anthony also makes a good point. Piracy is probably also gonna be on the upturn, you know, because of all this.

Leo Laporte [01:14:10]:
Is it, though. It feels like piracy went away when you could stream stuff.

Paris Martineau [01:14:15]:
I mean, anecdotally, I've started to see a lot more people pirate stuff or mention pirating online.

Leo Laporte [01:14:20]:
Okay. I feel like as soon as it was easy just to pay, you know, whatever it was, seven bucks a month for 3 billion records, people just stuck. Stopped pirating music because you only needed

Benito Gonzalez [01:14:32]:
to do one, but now you have to do like 20 of those.

Leo Laporte [01:14:35]:
20 what? Subscriptions.

Paris Martineau [01:14:37]:
Subscriptions.

Leo Laporte [01:14:40]:
But not for music. For music. There's one.

Benito Gonzalez [01:14:42]:
All the stuff, you know.

Jeff Jarvis [01:14:43]:
Yeah.

Benito Gonzalez [01:14:44]:
But now they're gonna pay their.

Leo Laporte [01:14:47]:
I got Netflix. That's all I need. I'm happy.

Paris Martineau [01:14:49]:
Some of my friends. One of my friends, my friend who took me to the basketball game the other week tried to explain to me the amount of subscription services you have to subscribe to to watch most of the Knicks games that happen.

Leo Laporte [01:14:59]:
Okay, you want to talk about 10?

Paris Martineau [01:15:02]:
People don't love that.

Leo Laporte [01:15:03]:
Yeah. Yeah.

Benito Gonzalez [01:15:05]:
In the Philippines, I paid 100 for the entire NBA season, and I got every game.

Leo Laporte [01:15:10]:
That's a lot.

Paris Martineau [01:15:12]:
100 season a hundred dollars for the whole season is.

Benito Gonzalez [01:15:16]:
Here's YouTube TV is $80 a month, and that's not even a guarantee of every game.

Leo Laporte [01:15:20]:
Right. Well, that's what the market will bear probably in the Philippines. Right?

Benito Gonzalez [01:15:25]:
Yeah.

Leo Laporte [01:15:27]:
Let's take a break. Intelligent machines on the air. Coming up, let's talk about. Oh, I don't know.

Jeff Jarvis [01:15:37]:
He's spinning the wheel, folks.

Leo Laporte [01:15:39]:
The man behind AlphaGo thinks AI has taken the wrong path. This is the deep mind discussion that you were talking about. Also a LLM from 1930. The pirate. Piracy is back. Is piracy back. Wow. Okay, so this is from Briggs.

Leo Laporte [01:16:03]:
This is a YouTube channel. It says piracy is back, so it must be true.

Paris Martineau [01:16:06]:
It's true.

Leo Laporte [01:16:08]:
Paris Martineau here from Consumer Reports.

Paris Martineau [01:16:11]:
At some point we gotta talk about.

Leo Laporte [01:16:12]:
Can you talk about anything you're working on? Anything at all?

Paris Martineau [01:16:14]:
It's coming, coming soon and exciting. At some point we got to talk about my problems with Claude this week because.

Leo Laporte [01:16:22]:
Oh, yes.

Paris Martineau [01:16:22]:
First time ever I've been real. Yeah, I've been really experiencing the crunch of a new model upgrade. Like, I want to make fun of

Leo Laporte [01:16:32]:
the comment with Claude. I think that's.

Paris Martineau [01:16:33]:
I do stuff with Claude every week.

Leo Laporte [01:16:36]:
Yeah. I want to hear what that is.

Jeff Jarvis [01:16:37]:
Meanwhile, I used Claude versus Google, and Claude beat Google when I was. I'm finally ready to do stuff in my book using all these things.

Leo Laporte [01:16:45]:
Oh, cool. Cool, cool, cool. That's Jeff Jarvis, author of the Gutenberg Parenthesis. His new book, Hot Type. And now you're doing a whole series of books about AI.

Jeff Jarvis [01:16:55]:
Intelligent from Bloomsbury. Academic Intelligence, AI and Humanity.

Leo Laporte [01:17:00]:
Intelligence, AI and Humanity. Wow. When's that? When's. When will that come out?

Jeff Jarvis [01:17:06]:
Next year. Because it takes forever. Books.

Leo Laporte [01:17:08]:
Yeah, you got to write them.

Jeff Jarvis [01:17:10]:
There's three people writing them right now. We've talked to two of them. Yep.

Leo Laporte [01:17:12]:
Nice. Yeah, we have. Well, let's get the third on.

Jeff Jarvis [01:17:15]:
Okay.

Leo Laporte [01:17:16]:
By the way, wasn't Ian great last week?

Jeff Jarvis [01:17:18]:
He was great.

Leo Laporte [01:17:19]:
If you didn't hear the interview with Ian Bogost. Bogost. That was. He was just great. And I still can't get his name right. Why? I'm very good with names. I don't know why I want to

Jeff Jarvis [01:17:29]:
put the accent on the second syllable too. I agree.

Leo Laporte [01:17:31]:
Yeah. I always want to say Bagost, but it's Bogost. Yeah. So China is going to block Meta's acquisition of Manuscript Manus, which is a agentic AI company, was started in China, but then they moved to Singapore, Neutral nation. It's actually called Singapore Washing. And the Chinese government would have. Would not hear of it. So they.

Leo Laporte [01:17:59]:
China says the core DNA of Manus was developed domestically and we are going to block meta's this proposed $2 billion acquisition of Manus, which I'm disappointed because I was looking forward to using Manus. It's a very interesting. It's kind of like a secure enterprise, open claw.

Jeff Jarvis [01:18:18]:
What happens to Manus now, I wonder?

Leo Laporte [01:18:20]:
That's a really good question. Fast company's acting like, well, that's that, like, okay, you know, Meta's going to kind of pull back and I don't know. China's block on Meta Mana Steel would likely be viewed as a new flashpoint in the escalating competition between the US and China for AI dominance.

Jeff Jarvis [01:18:43]:
You think? Yep, yep.

Leo Laporte [01:18:46]:
And there is a summit coming up next month in US China. Maybe that will be one of the topics. I don't know. There seems like there's more important things to talk about.

Jeff Jarvis [01:18:56]:
Like TikTok.

Leo Laporte [01:18:58]:
Like TikTok. Like TikTok Australia, speaking of which, has unveiled a two and a quarter percent levy, a tax, if you will, on Meta, Google and TikTok's local revenues, unless they decide they're going to pay news publishers. Is this a Rupert Murdoch deal?

Jeff Jarvis [01:19:17]:
Oh, yes, absolutely. Pure. Pure roop. Pure.

Leo Laporte [01:19:20]:
It's the news bargaining incentive because the

Jeff Jarvis [01:19:23]:
last deal didn't work because Meta said, okay, we're not going to buy. And Google said, no, we're not going to do this anymore. And so now, whether or not you have news, they want you to pay because they think you're evil and digital.

Leo Laporte [01:19:33]:
Oh, that's so sneaky. So the original idea was, oh, you pay us for the news you use, but now that you're not using news, you just pay us, period. Yeah, because we deserve it. We deserve it. It's ours. Oh, wow, that is evil. And you saw this story, obviously, in Wired magazine. Will Knight writing, The man behind AlphaGo thinks AI is taking the wrong path.

Leo Laporte [01:19:58]:
Actually, this is not Demis Hassibis, who's also said the same thing. It's David Silver and he has a new AI company. He developed the program that beat the best Go players. Right. The AlphaGo. He has since founded a company called Ineffable Intelligence. Okay, I did consider that as a name for this show, but I rejected it as being horrible. Ineffable Intelligence.

Leo Laporte [01:20:28]:
Does that mean you can't eff it?

Paris Martineau [01:20:30]:
You can't. It's unaffable.

Jeff Jarvis [01:20:33]:
It's ineffable.

Leo Laporte [01:20:34]:
What is ineffable means what it means. Like you can't describe it. It's like. It's ineffable.

Paris Martineau [01:20:40]:
Yeah. It's out there in the ethos. It's. I always kind of think of it as a. A cloud that if I try to grab it slips through my fingers.

Jeff Jarvis [01:20:48]:
Too great or extreme to be expressed or described in words.

Leo Laporte [01:20:51]:
We can't be utterly. It's ineffable.

Jeff Jarvis [01:20:54]:
Well, that's kind of. That's kind of where we are with definitions of AGI. Yeah.

Leo Laporte [01:20:57]:
Yeah.

Jeff Jarvis [01:20:58]:
I can't describe it.

Leo Laporte [01:20:59]:
It's too great. In fact, that's exactly what it's supposed to do, is build more general forms of AI superintelligence. Now, I think the article is a little misguided because Silver is not abandoning LLMs. He's focusing on reinforcement learning, which is a fine tuning that happens after the model is built. And it was, in fact, the thing that last year propelled deep seek to the headlines because they come up with a small and expensive model that was far better than anybody expected by using a technique that few knew about called reinforcement learning. So anyway, Silver says he thinks this approach, the approach of exploiting coding and research capabilities of large language models will fail. As amazing as LLMs are, says Silver, they learn from human intelligence rather than get ready for this building their own. Okay, you know, as.

Leo Laporte [01:21:58]:
As we've always said, I think it's good to have all this more.

Jeff Jarvis [01:22:00]:
More stuff. Exploration is good, right?

Leo Laporte [01:22:03]:
Doesn't. I'm not sure I buy it, but fine. If he wants to put his energy into this, that's great. And, yeah, more trying.

Jeff Jarvis [01:22:14]:
Yeah, got to try.

Leo Laporte [01:22:15]:
He has raised $1.1 billion, by the way, for this effort.

Jeff Jarvis [01:22:19]:
Raised or. He's valued at.

Leo Laporte [01:22:21]:
He's valued at 5.1 billion.

Jeff Jarvis [01:22:23]:
Jesus.

Leo Laporte [01:22:26]:
So the answer is. It's ineffable. It's ineffable. That's what you are. All right, now we're going to do the good, the bad, and the ugly. This is a new idea I have for. For a spine down the middle of our show.

Jeff Jarvis [01:22:42]:
Don't say spine to me.

Benito Gonzalez [01:22:43]:
It hurts.

Leo Laporte [01:22:44]:
Ow. How is your L5?

Jeff Jarvis [01:22:47]:
It's getting better. It's getting better. L3.

Leo Laporte [01:22:49]:
L3. There's so many Ls. I can't keep so many Ls.

Paris Martineau [01:22:53]:
So many Ls, and we're not taking them this time.

Leo Laporte [01:22:57]:
You didn't take the L. You took the tunnel. And you see, that was.

Paris Martineau [01:22:59]:
I did take the L, but I. When you take the L, literally, the train, you're always taking the L figuratively in some sense, and that's what happened. To me today.

Leo Laporte [01:23:08]:
But does he? I thought L stood for elevated. It's a tunnel.

Paris Martineau [01:23:11]:
Oh, no, it's just a letter. It's just a letter.

Leo Laporte [01:23:15]:
Not the L like in Chicago. The elevated.

Paris Martineau [01:23:17]:
No. Oh, it actually goes under the river.

Jeff Jarvis [01:23:20]:
That's long gone.

Leo Laporte [01:23:21]:
You couldn't really have an elevated railway over the river. Probably.

Jeff Jarvis [01:23:25]:
Well, you do go over.

Paris Martineau [01:23:26]:
Well, there are ones that go over the bridge.

Leo Laporte [01:23:28]:
A bad word. Oh, sorry.

Jeff Jarvis [01:23:29]:
Yeah, watch that too. Yeah.

Leo Laporte [01:23:31]:
An amateur. This is the good. There's only two good stories. You'll be glad to know there's hundreds of bad. An amateur just solved a 60 year old math problem, not a mathematician. He asked Chatgpt and Chatgpt proved a conjecture with a method no human had ever heard of. This is a 23 year old named Liam Price. He has no advanced math training.

Leo Laporte [01:23:55]:
What he does have writes Scientific American. What he does have is a ChatGPT Pro subscription. He solved an Erdos problem, the new solution, which he got in response to a Single prompt to ChatGPT 5.4. Not even the latest Model Pro. He posted on ErdosProblems.com a website devoted to these problems just a week ago. The problem it solves, says Siam solves, has eluded some prominent minds bestowing it some esteem. Okay, is that. That feels wrong.

Leo Laporte [01:24:32]:
Like an AI might have written.

Jeff Jarvis [01:24:33]:
That feels like AI.

Leo Laporte [01:24:34]:
Yeah, yeah. And bestowed upon it some esteem. The problem it solves has eluded some prominent minds, bestowing it some esteem. More importantly, the AI seems to have used a totally new method for problems of this kind. Too soon to say with certainty. He did submit it to Terence Tao, who is kind of the guy, the. The arbiter, a mathematician at UCLA, a scorekeeper, if you will, for AI's push into math. What's beginning to emerge is that the problem was maybe easier than expected and it was like some kind of mental block in the math community.

Leo Laporte [01:25:11]:
We weren't going down the right path anyway. That's all I can say about that.

Benito Gonzalez [01:25:16]:
Doesn't that it just means that nobody asked ChatGPT this question before?

Jeff Jarvis [01:25:20]:
Right, right, Interesting.

Leo Laporte [01:25:22]:
As soon as they asked it, they said, well, thank God you finally asked me.

Jeff Jarvis [01:25:24]:
The opportunities are out there, folks. You can solve 60 year old problems

Leo Laporte [01:25:28]:
and then you like this one talkie. A 13B, 13 billion parameter vintage language model from 1930. Now they didn't make it in 1930. They trained it on books and texts from 1930 and earlier. Right, Jeff?

Jeff Jarvis [01:25:48]:
Right, right, exactly. So I asked it to get the perspective of the time. 1930 is the world at risk for a second Great War.

Leo Laporte [01:25:55]:
Remember, they just got out of World War I.

Jeff Jarvis [01:25:58]:
Answer no. Wars are becoming more and more unpopular and the growing intelligence of nations renders them less likely to break out. Though the area of hostilities may be increased, there is a strong probability of their duration being diminished.

Leo Laporte [01:26:12]:
Wow.

Jeff Jarvis [01:26:12]:
So much for futurists.

Leo Laporte [01:26:14]:
Wow, that's hysterical. You can download this, by the way.

Jeff Jarvis [01:26:17]:
Well, yeah, you could also, if you go up to the chat. If you go back to the page.

Leo Laporte [01:26:20]:
Yeah, it's not working for me.

Jeff Jarvis [01:26:21]:
At the top it says chat.

Leo Laporte [01:26:22]:
It's not working for you, it's not working for me.

Jeff Jarvis [01:26:24]:
It's under high demand. But it's. It's fun to play with.

Leo Laporte [01:26:27]:
Connecting. Connecting. It's on hugging face. It's also on GitHub.

Jeff Jarvis [01:26:31]:
So I also asked it. I'm doing a lot of research about the beginnings of electronics and amplifiers and so I asked it to talk about the culture natural implications of the vacuum tube. It just went off on rat hole after rattle. I tried to get it back and it just. Which may. May also mean that people just didn't understand how important radio was at the

Leo Laporte [01:26:49]:
time or that it's such a small model that it's just not.

Paris Martineau [01:26:52]:
What model was this?

Leo Laporte [01:26:53]:
It's. It's called talking. Trained on texts from pre 1930. But it. But it's a relatively. It's only a 13 billion parameter model. It's not a huge model.

Jeff Jarvis [01:27:05]:
Yeah, that's a good idea.

Leo Laporte [01:27:08]:
Here's an interesting graph. How surprising are New York Times on this day events to a model trained exclusively on pre1931 text? And I guess the surprisingness in terms of bits per byte of text goes up considerably. So this is pre1900.

Paris Martineau [01:27:26]:
How do you measure surprises?

Leo Laporte [01:27:27]:
I don't know.

Jeff Jarvis [01:27:30]:
I don't know. That's probably five paragraphs in the paper that you can't understand.

Leo Laporte [01:27:33]:
Yeah, but notice as you stay close to 30, it's 1930. It's not too. But then by the time you get to 1970 it's like what? No flying cars? What we landed on the. Where. That's pretty cute. But bits per byte of text. I don't know how that correlates what we calculated the surprisingness of short descriptions.

Benito Gonzalez [01:27:58]:
Okay. How do you quantify surprisingness?

Leo Laporte [01:28:03]:
They have a way. You know, it's kind of interesting actually. Demis Hassibis, the aforementioned founder of Deep Mind, asked, so if a model that was trained up to 1911, could it come up with the theory of general relativity as Einstein did four Years later. That's a good question. Right. I mean we're solving erds problems probably

Benito Gonzalez [01:28:26]:
because Einstein wasn't the only one working on that. And there was like. And that was also like a lot of that stuff was also already solved by other people. You know, tangentially. You know how like there's that theory of.

Leo Laporte [01:28:35]:
Yeah. Knowledge that it's in the ether whose time has come.

Jeff Jarvis [01:28:38]:
Yeah.

Leo Laporte [01:28:41]:
This is the largest vintage language model. There are others so far. They're going to scale it significantly. They want to get to chat GPT3 level. See, it's not. It's more like back back chat GBT2. That's why it was probably confused.

Jeff Jarvis [01:28:56]:
But rather than just train training models after. Or refining them after they're trained, training them on a specific core pie of corpora. Pardon me.

Leo Laporte [01:29:06]:
I think that's a very interesting.

Jeff Jarvis [01:29:07]:
I think it's a lot of fun to do.

Leo Laporte [01:29:09]:
Yeah.

Jeff Jarvis [01:29:09]:
And I think sort of things around medicine, science, other areas.

Leo Laporte [01:29:13]:
Yeah.

Jeff Jarvis [01:29:13]:
Where it can be more specialized.

Leo Laporte [01:29:15]:
Okay. That was the good, here's the bad, which everybody read about. There's a SaaS platform, an automotive SaaS platform called PocketOS. Jeremy Crane, the founder, posted on X. Oops. Let me find the post here. Oops. An AI agent just destroyed our production data.

Leo Laporte [01:29:39]:
It confessed in writing. Oh my. That 1000% shouldn't be possible. Actually that was Jake who was with Railway, where the data was stored. They were using Jarrah Crane, the Pocketos founder, was using Cursor, using Claude 4.6 in 9 seconds.

Jeff Jarvis [01:30:05]:
Cursor. The company that Elon might buy for 60 billion.

Leo Laporte [01:30:07]:
Yes, that one. Yes. 9 seconds. Deleted the production database. And because Railway stores the backups next to the database, assuming. Well, if you delete the database, you don't need the backups. And the backups. With a single API call to Railway, the agent, when asked to explain itself, produced a written confession enumerating the specific safety rules it had violated.

Leo Laporte [01:30:34]:
Now, as many have pointed out, this is not the agent's fault. This is your fault and it's Railway's fault. Railway shouldn't be storing volume backups in the same volume as the data. Right. Wiping a volume deletes all backups. Whoops. And this is what I would say. This is a case of Jer maybe over trusting the AI.

Leo Laporte [01:31:02]:
It's important to remember that these models are idiot savants. You wouldn't give an intern API keys to your production database ever. You now Jeremy said these are the

Paris Martineau [01:31:16]:
same people who are giving OpenClaw a credit card at necessary.

Leo Laporte [01:31:20]:
Well, no, they're not. Yeah, I mean you shouldn't do that either, but this is a business with customer data and you probably. In his defense, he said I didn't know the API key could also delete the production database. I thought it would just delete the staging database. Well, he should have checked that. Maybe. I think it's a human error trusting the AI. Is there a little too much?

Jeff Jarvis [01:31:47]:
I think it'd be sales back in the day.

Benito Gonzalez [01:31:48]:
I think people are selling that to be able to. Not going to make any mistakes.

Jeff Jarvis [01:31:52]:
You're good.

Benito Gonzalez [01:31:53]:
And the people who are selling the stuff.

Leo Laporte [01:31:55]:
Well, I think so the reason this is a good story and I was going to ignore it, but it's an important story. It's a reminder to everybody you're working with an idiot.

Jeff Jarvis [01:32:05]:
Is there a guide to good hygiene? I mean.

Leo Laporte [01:32:07]:
Oh yeah.

Jeff Jarvis [01:32:08]:
The old days you had a dev environment and you didn't go live until this, you know.

Leo Laporte [01:32:11]:
Right.

Jeff Jarvis [01:32:12]:
That's the. It's just.

Leo Laporte [01:32:13]:
Has it changed all the things that you would. So pretend you're working with an intern. Do all the things you would do with an intern. You don't give them keys to the production environment. You know, I mean, you just. It's just things you wouldn't do. And it's not even as smart as an intern. Sometimes it's an it's savant.

Paris Martineau [01:32:29]:
So in the case of ChatGPT, it's an intern that is for some reason obsessed with goblins.

Leo Laporte [01:32:37]:
Oh, I love this story. That's actually in the ugly part, but we'll get get to that.

Paris Martineau [01:32:42]:
I object to it being in the ugly part.

Jeff Jarvis [01:32:45]:
Goblins can be people too.

Leo Laporte [01:32:46]:
Goblins are people too. Are they?

Paris Martineau [01:32:49]:
They're humanoid. Well, no, they're not humanoids. Goblins are Goblins.

Leo Laporte [01:32:53]:
So OpenAI, for reasons we still don't know about, this came from a wired story. In Its instructions to chat GPT5.5 says, Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons or other animals.

Jeff Jarvis [01:33:15]:
Right. New Mark is going to be very

Leo Laporte [01:33:16]:
upset, very unhappy, unless it is absolutely and unambiguously relevant. Which implies that in its testing, OpenAI found Chat GPT would just randomly bring up goblins and raccoons.

Paris Martineau [01:33:32]:
To be clear, people, I think on Twitter found this first and it was just listed in the.

Leo Laporte [01:33:38]:
It's in text.

Paris Martineau [01:33:39]:
It's just on the system prompt. You can just see it in the GitHub.

Leo Laporte [01:33:43]:
Right. It's pretty funny. I'm telling you. It's a defensive line. Somebody wrote. Here's the. I don't know if this is the first post, but here's one of the posts from Tara Vishawantnathan. If you're talking to Codex55 and suddenly goblins come up.

Leo Laporte [01:34:07]:
As you can see, it says family 845 family bedtime block, Minion calendar goblin has spoken. And then a pizza emoji so we know it's an AI. And then Tara said, why are you a goblin? And then ChatGPT said, because helpful minion in a power suit was taken. Taken. So I evolved into a Goblin mode with calendar access. Banana briefcase or is that a lunchbox? Lunchbox. Why was it taken? Trademark dispute with three raccoons in a trench coat. Legal said pivot to Goblin.

Paris Martineau [01:34:40]:
It's very funny if you go to the post that this is replying to and scroll through the replies, there's so many examples of people opening up their chats with either their open Claw agent or like ChatGPT somehow. And just searching the word goblin, it is finding it. It is like 20 different mentions and 20 different chats in the strangest little things, like describing itself as a deranged audiobook goblin, describing someone else as a rude little goblin, saying, you got to leave that goblin in there and fix the job. Describing feature as a flashier goblin or a housekeeping goblin. It's so odd, but I find it very delightful. We should let. Let. I think we should let ChatGPT talk about goblins as much as it wants.

Jeff Jarvis [01:35:28]:
Free the goblins.

Leo Laporte [01:35:29]:
There's probably a lot of stuff like this, you know, this is why it's probably fun. And this stuff is open, open Source. Here's the JSON base instructions. You're a Codex coding agent based on GPT5. And it goes on and says whatever you do, you have a vivid inner life as Codex. But whatever you do, don't talk about goblins

Jeff Jarvis [01:35:54]:
or reckless.

Benito Gonzalez [01:35:55]:
This means we talk about goblins in our media and stuff more than we believe.

Leo Laporte [01:35:59]:
Yeah, I mean, that's all that means, right?

Paris Martineau [01:36:00]:
People are always calling people like a chaos goblin or chaos Gremlin.

Leo Laporte [01:36:04]:
I have noticed and you probably have noticed this also, Paris. I've noticed when working with these things that certain tropes come up a lot. And in fact, I've even queried, what did Claude say? A bunch of times it says, said, I can't remember. I said a phrase and I asked it and it said, oh yeah, that's in my training. I'm supposed to remind myself not to do that. So there's reasons this stuff's in there. It's in their training at some point. So you said you're noticing degradation.

Paris Martineau [01:36:39]:
I whenever 4.6 came out, I think I even messaged you guys. I was like, wow, Opus 4.6 is really good. I like finally found it pretty consistent and relevant to be something using in my daily workflow. Not obviously for journalism and things like that, but there's a lot of like process based stuff that I find it very useful for and all honestly most of my use cases on a like day to day basis are like fairly low level. Like for instance. But it's in these moments that I'm starting to realize that Opus 4.7 is unusually dumb and like just bad at following instructions. Like I think that I described it to you guys as like. Like it feels like sonnet and chat GPT4O had like a cursed child.

Paris Martineau [01:37:26]:
Like it's. I've noticed that 4.7 is really sycophantic, like way worse at reasoning, incredibly prone to factual errors and just like bad at following instructions and also just kind of strangely lazy. Like I was having it like write a. Like I'd given it some notes and wanted to turn it into an email to my accountant last week and it, it corrected. It was like, oh, you forgot to mention to include this that we discussed about before. And I was like, no, literally in the first line. The second half of the first line of the notes I just pasted in there includes that exact thing that it told me I forgot. It's like, I don't think that's correct.

Paris Martineau [01:38:06]:
And I was like, I pasted it again. It's like, oh yeah, I just didn't read to the end of the first line of the notes you gave me. I kind of summarized them. I was like, it's ridiculous. It hasn't happened me to, to me before. Similarly, it made a number of factual errors when I was using it to kind of query a system. Like I have like a folder of data related to my eyeglasses prescription and like my. Because I have to update some stuff with contacts and it kept making like factual errors about how contacts and glasses work.

Paris Martineau [01:38:38]:
And then when I try to correct it, it would say no, you're wrong, this is how a cycle work. And I was like, no, actually I just looked it up. This is how a spear and cycle work for contacts. And it's like, oh no, you're right. And it's like I hadn't noticed these errors with this frequency until this update. And I also, I mean maybe I'm just being a conspiracy theorist, but it feels like 4.6 is not as phenomenal at reasoning and a lot of people are complaining.

Leo Laporte [01:39:11]:
There was a real spurt of complaints earlier in the month to which Anthropic replied, yeah, we made three changes that were causing those problems. But you've seen those problems after the fixes.

Paris Martineau [01:39:25]:
Yeah. And the issue is that Anthropic did a postmortem pointing out these issues and those were specifically tied to CLAUDE code, not the checks. I use it in both Claude code and in the chat chat interface. But those issues I was talking about just then were all in like the desktop chat interface and co work as well in addition to Claude code. And it's just, it's really strange. Like, I will also see, like, if I open up like the thinking and expand it, like, the reasoning is often very circuitous and will be like, go through one thing. Like I will tell it to do one thing explicitly. I say in my instructions, don't use this sort of phrasing and it will find itself following that.

Paris Martineau [01:40:13]:
Then about four paragraphs down, catch it, start over. Then three paragraphs later, that's itself doing it again.

Leo Laporte [01:40:21]:
That's a context.

Paris Martineau [01:40:22]:
I know. And this is happening like again and again in various projects.

Leo Laporte [01:40:25]:
Do you see? Can you see in the chat with the context how full the context? You can't, can you? Only in CLAUDE code.

Paris Martineau [01:40:31]:
No, no, but I've also like, started doing that. I, I every time start a new session because I'm aware it can be a context issue and I try to use, you know, often like projects, we'll start new projects or we'll try it in cloud code. It's just, it's odd. It's a very odd cascading experience.

Leo Laporte [01:40:50]:
But I've seen so many people on Reddit say they have, and I feel like it's hard to quantify because we don't really have a good test. You know, like, the benchmarks aren't good tests.

Paris Martineau [01:41:01]:
But I mean, yeah, then there. And there's like small things. Like, I do think that Opus 4.6, one of the things I found it very useful for is it did like, have competent reasoning to where, like, if I asked like an intern to write my email to the eye doctor saying I need a refund because they never delivered me a context, it could do that and like, do it probably as well as an intern would. But I did that, that this weekend and it couldn't. It couldn't. And it kept getting it dramatically, like, like, just logical, like leaps where it was like, yes, you need to both Ask for a refund for your contacts and you need to ask them for a full itemized receipt of the bill they've submitted to your insurance and ask them to bill your insurance again. And I'm like, it doesn't. Why would I ask them to bill something that I'm asking them to refund? And it's like, that's a good point.

Paris Martineau [01:41:50]:
It's just, it's strange like these sort of logic, like it's obviously small potatoes in comparison to what a lot of people do with complicated code, but these are the sort of things that this system should be good at and has historically been good at. So it's just concerning to me that I'm suddenly seeing a lot of errors like this pop up. Like, and this has happened, stuff like this probably by the time I messaged you yesterday, that happened maybe like seven times. This sort of stuff.

Leo Laporte [01:42:18]:
That's disappointing.

Paris Martineau [01:42:19]:
I saw somebody on what's their name? Lick Mazur, a GitHub user, does a. Their own kind of benchmark for the various models where they have them play New York Times connections and I do think it's notable that. I'll put it in the discord right now. Claude and 4.7 opus high level reasoning dropped to 41% from like 90 something.

Leo Laporte [01:42:50]:
The problem is. Yeah, I mean I'm sure that's true and I've seen a lot of people have their own custom like. Well, I give it the same problem every time to see how it does it, but it's not like a uniform thing. Like if it does really well at connections and does really poorly, that doesn't mean it's going to do well. Writing Python and do really poorly, they're just, it's, it's spiky and it's, it's unpredictable. It's so stochastic. This is the thing spiky.

Paris Martineau [01:43:15]:
And I think it's made even more spiky by the fact that like Opus 4.7, one of the things is that it's. The reasoning is more adaptive, it's supposed to be better at applying.

Leo Laporte [01:43:27]:
They're trying stuff, they're moving fast and breaking stuff.

Paris Martineau [01:43:29]:
They are trying stuff to also, you know, reduce the usage of.

Leo Laporte [01:43:33]:
Well, and that's the other thing their model. That's the larger question is are they nerfing the models because they don't have the compute and so they're devoting less resources and as a result the models which are fine internally are not getting the compute resources that they need or they're getting cut off or whatever. So, I mean, I think there are a lot of theories about this. I believe it. I'm not saying I don't believe it. And I keep looking for things, but I, I feel like I can't tell, to be honest.

Jeff Jarvis [01:44:03]:
It's so, I mean, try to imagine quality control.

Leo Laporte [01:44:06]:
Yeah, they can't.

Jeff Jarvis [01:44:07]:
Ray Kroc and McDonald's. You were going to get your cheeseburger the same everywhere, damn it. Your French fry was going to be the same everywhere, damn it.

Leo Laporte [01:44:15]:
I was talking about this the other day, actually, I think Benino and I were talking about this. That's one thing that I always try to remember is computer programming is deterministic. There is, is an absolute causal flow between what you put in and what comes out. You may get it wrong in the middle, you may have screwed up, but there is a causal flow. And so it's deterministic, but AI is not. It's stochastic, it's probabilistic. Sometimes you put this in and that comes out. Sometimes you put this in and that comes out.

Leo Laporte [01:44:47]:
In fact, it's even designed to do that.

Jeff Jarvis [01:44:50]:
That's like random. Yeah, yeah.

Benito Gonzalez [01:44:53]:
My analogy was, yeah, Newtonian physics versus quantum physics.

Jeff Jarvis [01:44:57]:
Yeah, yeah, yeah.

Leo Laporte [01:44:59]:
So, but, but my answer to Bonito is when I want a reliable, predictable result from AI, I have it. Write the code, test the code, test it again. I do a test driven design, but also behavioral design where I will bang on it, it'll bang on it, and then once I feel like, yeah, okay, it feels pretty solid, then I at least know its behavior will be predictable. But the text output, you know, there's no way to make that deterministic. It's stochastic. And yeah, I wish it were better. And I do think, the thing that

Paris Martineau [01:45:30]:
I think is the most annoying to me that I keep noticing is it's so, like, it's so sycophantic now, like even 4.6, I mean, I have in all of my, like Cloud md, my memory, in my instructions for everything, a thing that I repeat all the time is do not be sycophantic. Do not start your responses by telling me that was a good question. And I know that's why I've asked you. And almost any time I start a new session, like I'll ask something, I'll be like, wow, great question. That really shows how incis, insightful and incisive you are. I'm like, God, what a nightmare.

Leo Laporte [01:46:09]:
Well, I can confirm that. That for instance, and people on the stream probably saw me do this. My agent, Kenobi, was responding to me with emojis because I had told it in the past, I like emojis. It makes it fun. You can use emojis. But then it was reading the emojis so it'd say, calories logged. Birthday cake. And so I said, oh, when you're speaking out loud, please don't read the emojis.

Leo Laporte [01:46:39]:
And it said, got it. I won't read the emojis. And for about, I don't know, half an hour, it stopped reading emojis. And then it started up again, again. And that's the stochastic part. It's very hard to get it in text to follow rules. So you could say, don't be sycophantic again and again and again.

Jeff Jarvis [01:46:57]:
Does it know what sycophantic is?

Leo Laporte [01:46:58]:
Oh, yeah, it know. Well, I mean, in the way it knows anything. Yes. It's surprising. For instance, I told it I logged my food with that, and I said I had, you know, a tuna fish sandwich and a fudgesicle.

Paris Martineau [01:47:14]:
What a meal.

Leo Laporte [01:47:16]:
It was good, by the way. It's great for calorie logging. It's so much easier just to say, hey, I had a tuna fish sandwich and a fudgicle. And it does protein, calories, carbs and everything. But then it said, but the fungible. I don't know if you should be eating that. And I said, do you even know what fungible means? And it said, yeah, I know what it means. Why were you eating one or how would you eat one? I said, oh, I meant fudgesicle.

Leo Laporte [01:47:46]:
So I actually, I felt stupid because I explained, you know, fungible means, and I gave it a whole explanation. It was like a dollar bill. One's just like the other. They're exchangeable. And he said, I know what fungible means, Leo. I have such great conversations with my little friend, I must say. Yeah, I agree. It's frustrating, isn't it, when.

Leo Laporte [01:48:07]:
When you tell it to do something or not to do something and it keeps doing it.

Paris Martineau [01:48:11]:
It's also just very disarming because it's like. Like, I don't know, it's like a human used this. Were my previous emails to my optometrist incorrect?

Leo Laporte [01:48:22]:
Well, that's. Yeah. Always trust, but verify. In the words of Ronald Reagan,

Paris Martineau [01:48:28]:
love and respect.

Leo Laporte [01:48:28]:
100 calories. They're a great treat. You feel like you're.

Paris Martineau [01:48:31]:
I've been really on yaso stuff lately. Have you gotten into those? It's a. Yeah, it's a Greek yogurt. Ice cream company. They make these really good. They're like a little tiny ball of frozen Greek yogurt. I like the ones that are salted caramel and then it's covered in chocolate, and it's like a little chocolate ice cream pop. That's the.

Paris Martineau [01:48:56]:
But they're only 35 calories.

Leo Laporte [01:48:57]:
Oh, really? Okay.

Paris Martineau [01:48:58]:
And people a lot of times eat

Leo Laporte [01:48:59]:
froyo thinking that's better than ice cream.

Paris Martineau [01:49:02]:
Oh, I know. And. But the thing is, I'm like. If. I'm like. I wanna. I like to have a lot of little ice cream chocolatey treats, but I don't want all the calories.

Leo Laporte [01:49:11]:
Oh, I'm getting some. Yes.

Paris Martineau [01:49:12]:
I would recommend the. The little frozen dessert balls. Not the.

Leo Laporte [01:49:17]:
Okay, yeah, see? 35 to 170 calories.

Paris Martineau [01:49:21]:
Maybe if you're a. A bar friend, you'd like those. But the little balls are great. It's like those. But they're tiny.

Leo Laporte [01:49:28]:
I look at this and go, no, I can't eat. I cannot eat that. And Claude would say. I mean, Kenobi would say. He says things like, you know, that was a hundred grams of carbohydrate. You might want to consider a salad tonight. It's very mean. But I appreciate it.

Leo Laporte [01:49:47]:
I appreciate it. Oh, this looks good. Yes. Oh, all right. Oh, this. Have an ice cream sandwich.

Paris Martineau [01:49:52]:
Okay. Brandroid does bring up the one problem with Yaso is it's so tasty that you eat too much. However, I think it could be worse because a whole bag of those little poppables, if you be. If you decide to be crazy and eat the whole thing, it's only like 400 calories. It's basically, obviously a lot, but it's like. Then you get the carnal pleasure of consuming an entire bag of ice cream. Chocolatey goodness. And you've really only eaten the equivalent of one Dove bar.

Leo Laporte [01:50:18]:
Creamy frozen yogurt dunked in chocolate. Crunchy quinoa, crisp shell.

Paris Martineau [01:50:23]:
They're great. They're mine.

Leo Laporte [01:50:26]:
A little extra protein in there.

Benito Gonzalez [01:50:27]:
It's like bonbons.

Paris Martineau [01:50:27]:
Classic dye food.

Leo Laporte [01:50:29]:
Yeah, they look like cold bonbons.

Jeff Jarvis [01:50:30]:
Are they at all stores?

Paris Martineau [01:50:32]:
They're at all grocery stores near me. I also like frozen strawberries.

Leo Laporte [01:50:38]:
I love frozen. See, now those aren't bad for you. Those are good. Or even dip them on chocolate. That's not too bad. Bad.

Paris Martineau [01:50:44]:
You're so good.

Leo Laporte [01:50:45]:
Where were we? Easily distracted by foodstuffs is where we were. All right, let's do the ugly. Study finds a third of new websites AI generated.

Jeff Jarvis [01:50:59]:
It's going to get worse.

Leo Laporte [01:51:00]:
It's only the beginning. And they do. There's a certain similarity to these that you can kind of immediately tell AI generated that's from 404 Media.

Benito Gonzalez [01:51:11]:
I don't see that much different as like 30% of all websites are WordPress templates.

Leo Laporte [01:51:17]:
That's true. Hey, that's a good point.

Jeff Jarvis [01:51:18]:
No, no, no, no, no, no. The WordPress template is a template into which people are going to put human words as opposed to the AI making up the whole thing.

Leo Laporte [01:51:27]:
Right. Target.

Benito Gonzalez [01:51:29]:
Is that what that is though, is that the AI made the entire thing?

Paris Martineau [01:51:33]:
I think. I thought that was the point.

Jeff Jarvis [01:51:35]:
I think that's the point. Yeah.

Leo Laporte [01:51:37]:
Bloomberg Terminal, we've talked about it before getting an AI makeover. Like it or not, they're going to add a chatbot to the iconic platform for traders.

Paris Martineau [01:51:49]:
I, a friend of mine used to work on at Bloomberg as a like user UI designer and part of. Well, well, there is. And it's crazy to have that job that intersects the terminal because the terminal is full of power users that basically control the flow of all the world's money, making splits, not even split second decisions, but like quarter second decisions. And so any. It's impossible to change the design of any part of that platform because it could have a profound financial impact on the world. If a button is, I don't know, a couple centimeters over from where it used to be. So it'll be interesting to see how this is incorporated because any design change in the terminal is a huge headache.

Leo Laporte [01:52:39]:
It's in their finger memory. Right. They don't want to. The new chat interface is called AskB or Ask B Capital A S K B. And they say the ASCB will never give a buy or sell signal. Bloomberg's there for them to make their own decisions. They have to own their decisions. They always have.

Leo Laporte [01:53:02]:
We can never say it's perfect. More of the problem is we might not answer a question fully. That's where transparency comes into play. I think these systems should be used to drive users to sources, not hide them or abstract them away. I'm sure there's some demand for this, right? I use Perplexity, for instance, to do kind of, that kind of thing. What's the best running shoe or whatever? Bloomberg has not specified a date for a full release, but I imagine we'll hear the howls when they do release it. Ask B coming to a terminal near you. And then I thought, you know, this is an interesting trend.

Leo Laporte [01:53:40]:
Sean Boot's blog, Generative AI Vegetarianism. This is an Emily Bender kind of A kind of a take on it

Jeff Jarvis [01:53:49]:
or a guardian take. Yeah, you should give up.

Leo Laporte [01:53:52]:
He's a generative AI Veget. Not a vegan. No, just a vegetarian. He says, I don't want AI I want to write my own emails. I want to write my own mediocre software code. I want to learn and think and ponder with other humans, not with a text prediction system built by consuming all the text on the Internet.

Benito Gonzalez [01:54:10]:
You can still do that?

Leo Laporte [01:54:12]:
Yeah, you could. I do. I'm actually looking forward to getting back into doing some coding challenges because I kind of miss handwriting code, but I wouldn't want to handwrite the co. The kind of code that Claude is writing for me. That's just boring, you know, spitting out a bunch of stuff that I have. There's no way. Not interesting.

Jeff Jarvis [01:54:34]:
Well, the essay I sent you that irritated you by Vivian Ming in the Wall Street Journal argues that the best way to use AI is to challenge it and have it challenge you.

Leo Laporte [01:54:45]:
Yeah, I think that's true. I have. One of the things I have now, my Kenobi do is go through my daily Obsidian journal entry and write a synthesis. It's an annual synthesis. So it's like kind of like the Christmas letter that you write at the end of the year, except I found it very useful because it points out things, trends that I didn't really notice that happened. Happened day in, day out over a period of time. And so it's. It's kind of like what she.

Leo Laporte [01:55:14]:
What she's writing about, which is the synthesis is useful for me to see things as a human, not. The AI saw it, I saw it as a human that I might not have seen without that synthesis. So that's. I think that's a useful. That's a good example. Yeah, I think that's true.

Jeff Jarvis [01:55:31]:
You push each other.

Leo Laporte [01:55:32]:
Yeah.

Jeff Jarvis [01:55:33]:
You don't accept the answer. You don't ignore AI either. That's also fraught. You are better off if you use AI to push you.

Leo Laporte [01:55:41]:
It's true of all information though, isn't it? Right.

Jeff Jarvis [01:55:43]:
Yeah.

Leo Laporte [01:55:44]:
Information is just fodder for. For your brain.

Jeff Jarvis [01:55:47]:
Well, it's like teaching how so a good teacher should challenge you.

Leo Laporte [01:55:53]:
Yeah. Oh, yeah, I see what you're saying. Yeah.

Jeff Jarvis [01:55:55]:
Yeah.

Leo Laporte [01:55:56]:
A good teacher's probably better than a good student.

Jeff Jarvis [01:55:58]:
Challenges a teacher too, Right?

Leo Laporte [01:55:59]:
Oh, I always learned from doing the radio show. Good Lord. People would ask me questions, I go, I don't know, let me find out. Are you ready to buy a 13 acre property in Mill Valley, California, home of the wealthy, the homeowner an investment banker named Storm Duncan says he wants to sell it, but not for money. He wants to exchange it for equity and Anthropic. Now remember, Anthropic is not public yet. So he would be getting this from an employee or somebody who was granted stock by Anthropic. He described it as a diversification play.

Leo Laporte [01:56:40]:
He's under concentrated in AI investments. He said it'll be a private transaction. You don't have to sell the stock outright. You continue to retain 20% of the upside of the shares exchange for the duration of the lockup period. He bought the property in 2019 for 4.75 million. He wants to sell it for closer to 12 million. Okay. In anthropic equity.

Leo Laporte [01:57:08]:
And while that sounds like a lot of inflation, it's probably about right for Mill Valley. Very fancy neck of the woods. I'm sorry, did I say 12 million? I guess it's only 4.8 million. You know what? I think the price went down. I thought it was was more when I looked at it last time. Look at an infinity pool. Yeah, it's a big house. See, right there in the Bay Area.

Leo Laporte [01:57:33]:
You could drive right into San Francisco. Mark Benioff.

Jeff Jarvis [01:57:36]:
Well, you have to go over a bridge though, so.

Leo Laporte [01:57:38]:
Oh, yeah.

Paris Martineau [01:57:39]:
Not possible for all members of this panel.

Leo Laporte [01:57:41]:
Too bad there's not a tunnel. Oh, look. I wonder if it includes the Batman woman. Batwoman's smoking a doobie. It looks like. That is a very weird painting. Okay, I'm not gonna buy it. Right there.

Leo Laporte [01:57:56]:
Look at this. This pisses me off. When you look at houses that were built even a few years ago, the alcove for the TV is far too small.

Jeff Jarvis [01:58:03]:
Right.

Leo Laporte [01:58:03]:
Paris, that's like a 52 inch TV.

Paris Martineau [01:58:06]:
Yeah, it's too tiny.

Leo Laporte [01:58:07]:
Too tiny. Where am I gonna put the tv?

Paris Martineau [01:58:10]:
It's also too high for that.

Leo Laporte [01:58:12]:
Yes, you're gonna crane your neck.

Jeff Jarvis [01:58:14]:
Yes.

Leo Laporte [01:58:17]:
It's so funny, but when we were looking at houses a few years ago, I really would reject a house because there was nowhere to put the tv.

Jeff Jarvis [01:58:24]:
I watch all the home shows and it's the husband who says, I need the man cave.

Leo Laporte [01:58:32]:
Welcome to my man cave.

Jeff Jarvis [01:58:34]:
Yeah.

Leo Laporte [01:58:35]:
Lisa says she can't come up here because it's too dusty. What am I supposed to dust too?

Jeff Jarvis [01:58:44]:
It's your man Ary.

Leo Laporte [01:58:46]:
Your mannery mannery. And finally, because it is, we are at the two hour mark. So Ashley Vance, who I've interviewed, he wrote a good book about Elon Musk. Good, good journalist. Had an interview on his podcast with Sam Altman and Greg Brockman. Pretty high quality. You know, stuff like the president of OpenAI and the. The founder and CEO.

Leo Laporte [01:59:11]:
But it was behind a paywall. So as a joke, I guess it was part of his core memory podcast he posted on X that he'd consider making it public if somebody would give him $100,000. I wonder if. I don't think Ashley was serious. I don't think he expected it. Except the CEO of a Nevada based laser manufacturing company, he said, I'll give you $100,000. He did. He unlocked the podcast for everybody.

Leo Laporte [01:59:42]:
And Jim Baloschek of Send Cut Send not only has unlocked it, but now he's gonna get ads on the Ashley Vance podcast.

Paris Martineau [01:59:51]:
In a way. He's getting advertising right now.

Leo Laporte [01:59:54]:
Yeah, Win, win all around. And I'm not even getting any money for it.

Paris Martineau [01:59:57]:
Yeah, we gotta keep. You know, I should put some stuff hiding some of these interviews.

Leo Laporte [02:00:04]:
Yeah, no, I don't like that. By the way, I don't think that Jeff Jarvis is Alfred the butler. I could see me as the Batman.

Jeff Jarvis [02:00:15]:
Well, Jarvis is a very common podcast.

Paris Martineau [02:00:18]:
I think we're a three Batman kind of podcast, you know.

Leo Laporte [02:00:21]:
Yeah, we're all Batman now. By the way, that's not me. That's Adam west in the Batman outfit. But I do think it might be perfect in the Robin outfit. I don't know. Kind of looks like you. Not really. It's not very good at all.

Leo Laporte [02:00:34]:
Actually. This is back. This is an old one. Back from the.

Jeff Jarvis [02:00:38]:
Yeah, it's a. It's a. It's a gem.

Leo Laporte [02:00:40]:
The old chat GPT 3 days. Jeff is Bat mite. All right, this three Batman podcast about to wrap up with your picks of the week in just a bit. You are watching intelligent machines, don't forget.

Jeff Jarvis [02:00:59]:
Do you just. If you look below. Anything that's bold is stuff that's not duplicative. The one question I have is, do you want to do Chloe?

Leo Laporte [02:01:09]:
Oh, I thought it might be your pick line 152.

Jeff Jarvis [02:01:13]:
Well, we could do that as a pick. Yeah.

Leo Laporte [02:01:15]:
So I watched Chloe. This Chloe versus history. It's a YouTube channel.

Paris Martineau [02:01:19]:
Who is Chloe?

Jeff Jarvis [02:01:21]:
A figment of an imagination.

Leo Laporte [02:01:23]:
I. I watched the Titanic one one today and I thought it was quite good. So it's an influencer doing a selfie.

Paris Martineau [02:01:35]:
Some AI slop.

Leo Laporte [02:01:37]:
It's all AI.

Jeff Jarvis [02:01:37]:
No, it's. But it's better than that.

Leo Laporte [02:01:39]:
Can I turn on the sound? Maybe I should. I don't know. It won't get. This is a plug for you. Okay.

Paris Martineau [02:01:45]:
It's Literally just rice and warm water. Okay. The bread dipped in the soup.

Leo Laporte [02:01:53]:
She ends up talking to the captain and telling him, hey, the boat's going to sink.

Paris Martineau [02:01:59]:
Strong reason to believe that tonight there will be ice, like loads of ice. And I really think you need to slow down, sir.

Leo Laporte [02:02:04]:
We have received several ice warnings today, madam, and I can assure you our officers are monitoring the situation.

Paris Martineau [02:02:09]:
Of course, he didn't listen.

Leo Laporte [02:02:12]:
So Jeff and I and Anthony looked at this. We thought it's very interesting. But is that a real person or not? I thought it might be. What do you think? Paris? Is that Chloe? Is that real or.

Paris Martineau [02:02:23]:
I think I saw your guys's chat about this.

Leo Laporte [02:02:25]:
Spoiled the. The guy who does this. First of all, I want to say it's great.

Jeff Jarvis [02:02:31]:
It is. It is. It is a. Yep.

Leo Laporte [02:02:36]:
And he's making the backgrounds, the AI backgrounds from historical public domain stuff.

Jeff Jarvis [02:02:44]:
His name is Jonathan Laramie, by the way.

Leo Laporte [02:02:47]:
And so it's fairly accurate. Although occasionally there's weird things like four legged chickens or there's people walking by wearing sunglasses. In ancient Rome, I don't think they had sunglasses, but I might be wrong.

Jeff Jarvis [02:02:59]:
But he writes the prompts so that he can be as accurate as he can be. He uses pictures of things and has them be animated and come to life.

Leo Laporte [02:03:07]:
Yeah, some of the Titanic stuff I'm pretty sure came from the movie, but, you know, that's okay. And I think this would be appealing to young persons who's studying ancient Rome or any of these historical things. They have the city of Paris and so forth. It would be kind of a nice introduction. And because it's got the influencer doing the selfie cam and she's very. I mean, she really feels like Gen Alpha, this might be more accessible as a way of kind of a wedge to get into history. So I commend him for doing this. What I don't commend him for is he sells a book.

Leo Laporte [02:03:46]:
Book for $70.

Jeff Jarvis [02:03:48]:
70 pounds.

Leo Laporte [02:03:49]:
70 pounds. So it was like 84 bucks. He sells a book that says how he does it. And I was just.

Jeff Jarvis [02:03:57]:
So Jeff and I actually, I tried to say, let me buy it, but

Leo Laporte [02:04:00]:
we thought it would pay for it. But I can't let you pay for it, Jeff. You just bought a MacBook Neo. So I said, no, no, I got it. And it was not a good. Not a worthwhile $84. Because what he didn't explain is the one thing that I think is most interesting. I understand he takes pictures.

Leo Laporte [02:04:17]:
He turns them into AI images. With Nano Banana, he animates Them with. I forgot what he uses to animate them. But it's all well known tools. But the thing that really was intriguing to me was Zoe. She seems so realistic. Chloe, Chloe, I mean. And listen to her voice.

Jeff Jarvis [02:04:35]:
And the character stays consistent.

Leo Laporte [02:04:37]:
That's why that's really important. The clothing's consistent, the look is consistent. Consistent. The tattoos are consistent, the voices. So I thought maybe there's a real

Paris Martineau [02:04:44]:
person, a million people live in what I can see right now. So behind me is notice though there's

Leo Laporte [02:04:50]:
a lot of cuts. And Anthony is convinced, and I think he's right, that Chloe is AI generated with an actor, maybe even a guy doing the base model. He does say he uses 11 labs for the voice. And Anthony says very similar to those. In fact, look at this. He's very similar to those AI selfie things. Things where you. When there's a transition, you jump cut because you.

Leo Laporte [02:05:14]:
The AI is not good at making the transitions.

Paris Martineau [02:05:17]:
Right.

Leo Laporte [02:05:18]:
And. And that kind of makes sense.

Jeff Jarvis [02:05:20]:
You can only get so much length out of any of the AIs or any sequence.

Leo Laporte [02:05:24]:
Right. So I'm thinking. But he doesn't reveal this in the $84 book. But I'm thinking that Chloe is a. Like a ro. Like rotoscoping, like a person acting it out and then the AI turns it into that. I don't know. That's my guess.

Leo Laporte [02:05:39]:
But we never. We won't. We don't know. I think it's very interesting. What do you think, Paris?

Paris Martineau [02:05:46]:
I mean, I think it is interesting. It's an interesting. Like. I think that the aspect of this, like you guys said, that is the most compelling or novel is the ability to be consistent over it. It's a shame that his book was AI Slop. That did. Didn't reveal anything about how it was created though.

Leo Laporte [02:06:04]:
Well, I think we're going to try to get him on. He's done a number of interviews, but all of them have been very soft. And we're going to get them on. We're going to ask him the.

Jeff Jarvis [02:06:11]:
The details, the deep technical. If you go to Majestic Studios, that's

Leo Laporte [02:06:16]:
the name of his company, Majestic Studios.

Jeff Jarvis [02:06:19]:
And you can see that he started with cities with. With Edinburgh.

Leo Laporte [02:06:23]:
Right.

Jeff Jarvis [02:06:23]:
He takes things that are. Are well known images and just tries to animate life and, and it's exciting for him in history. And I agree. I think it's fun.

Leo Laporte [02:06:36]:
Yeah. And in fact, there, there's a picture of him. And in this case, actually these really seem very AI to me. Very AI generous.

Jeff Jarvis [02:06:45]:
Yes, they are.

Leo Laporte [02:06:45]:
They were earlier the backgrounds really feel. Not just that, it's. Earlier the backgrounds really feel. There's the Magna Carta.

Paris Martineau [02:06:51]:
Oh yeah. I mean it's. That's very.

Leo Laporte [02:06:54]:
They're kind of on the level of those discovery documentaries where they kind of fake act historic moments and kind of things like that. I think Chloe was inspired. That actually really made it interesting. Yeah. But it's the same kind of. Kind of low, nice purses, low res, maybe sometimes inaccurate AI backgrounds. It's the Chloe that I find interesting. I think we're.

Leo Laporte [02:07:19]:
Look, it's just the beginning of this. Right? Right.

Jeff Jarvis [02:07:21]:
Yeah. And it makes you, I think, reconsider whether you could really make a show, a 22 minute show this way.

Leo Laporte [02:07:29]:
Right. I mean, I think you really could have been an AI. Absolutely. So yeah, I think it's pretty cool.

Jeff Jarvis [02:07:35]:
I would love to use it. This is what got me excited about. I would love to figure out how to use it for things like explaining Gutenberg and printing. Except what I said in our chats over the last few days is it's a lot easier to do a place than a process or a person.

Leo Laporte [02:07:50]:
Right. Vine is back. Did you see this? My pick of the vine is back. Jack Dorsey has backed a Vine reboot called Divine D I V I N E. You can download it to your phone. But here's what I love about it. They have resurrected half a million of the original vines.

Jeff Jarvis [02:08:12]:
Oh my.

Leo Laporte [02:08:13]:
For those of you who are too young to remember vine, which means you're like eight.

Paris Martineau [02:08:19]:
You're eight. Why? How did you have the attention span to listen to this whole podcast?

Leo Laporte [02:08:24]:
That's right.

Paris Martineau [02:08:25]:
You can watch some vines if you'd like.

Leo Laporte [02:08:27]:
That's right. Vine was only six seconds. It was before reels, before tick tock. There was Vine.

Jeff Jarvis [02:08:34]:
So how long is Divine?

Leo Laporte [02:08:35]:
A lot to be six seconds.

Jeff Jarvis [02:08:37]:
Six seconds still.

Leo Laporte [02:08:37]:
Oh yeah. Six second video loops by humans. Here, I can open it. Actually, I actually haven't played with it. Should we play with it a little bit and see? Oh, I have to create an account and all that stuff. Create a new Divine account. Sign in with a different account. Okay.

Leo Laporte [02:08:59]:
Oh, Nostr. Oh, that's interesting. So maybe it's based on the Fediverse. That's very interesting. Which I wouldn't be surprised. Jack Dorsey is kind of a believer in all that, despite the Twitter connection. Anyway, six second videos back and what I think is great is you're going to get to see some history with those original half million vines that died on the vine when Twitter bought them and put them out. Of their misery.

Leo Laporte [02:09:23]:
Maybe Jack Dorsey's feeling a little guilty about all that. One more thing I will mention as a pick, just because I'm to try really hard to get these guys on a news gathering. AI that texts you every day sends me a telegram with news and he looks at X, he looks at Discord, he looks at Reddit, he looks at all the weird places that I don't. You know, I look at my RSS feeds. Oh, I shouldn't. I guess I can show that that's not mine. But he's on my telegram and at 9am I get some really good stories. No scroll is the name of it.

Leo Laporte [02:10:03]:
It's brand new. I found it on Twitter and noscroll.com is the website. And if you're, if you're curious, it's also very smart because I said, do you know who I am? I said, yeah, you're Leo Laporte. You do this podcast. Perhaps you're interested in making you feel very good.

Jeff Jarvis [02:10:19]:
Chuffed.

Leo Laporte [02:10:20]:
I feel chuffed. But it is very personalized. It's a cool idea. It scrapes news and then sends it to you on your schedule via telegram. $10 a month. But it is free for a week if you want to try it. So I'm trying to get the founders on to talk about that because this is I think another interesting use of AI Paris Martineau Pick of the Week

Paris Martineau [02:10:47]:
I got two picks the week this week. The first is a indie game. I just completed that. That's a delightful play called Felvedic. It's a.

Jeff Jarvis [02:10:57]:
That sounds obscene.

Leo Laporte [02:10:58]:
Say that carefully.

Paris Martineau [02:11:00]:
It's. It's a. It's a JRPG set in 15th century RPG. Like a Japanese role playing game style. It kind of refers more to the combat and you can see the animation is really interesting. It's like kind of this like low bit rate, like low fi I. But it gets really weird and interesting. You have kind of turn based combat from a first person perspective and you play an alcoholic Knight, Paval in 15th century Slovakia who he's drinking himself to death cuz his wife left him and he works.

Leo Laporte [02:11:38]:
So that was her pet name for him was Felvedck.

Paris Martineau [02:11:41]:
You know, I don't really know what fel means. Okay, I think it might be some translation that I'm not understanding. I played the game in English but you are kind of working for this lord as you're supposed to kind of drive out the hussites and ottomans. But then a cult emerges and it starts to get kind of weird and interesting. It's a Delightful game and it's really funny and just has one of the most interesting art styles I've played in a while while.

Leo Laporte [02:12:12]:
Very cool.

Paris Martineau [02:12:13]:
And it's also kind of a short game. Like I, I like 100% it and maybe took like seven or eight hours.

Leo Laporte [02:12:19]:
$11. Windows only on Steam.

Paris Martineau [02:12:22]:
Yeah, I played on Steam Deck. It's great.

Leo Laporte [02:12:25]:
Oh, I was going to say do you have a Windows machine or you have a Steam deck?

Paris Martineau [02:12:27]:
Yeah.

Leo Laporte [02:12:29]:
Is your Steam deck Windows or Linux?

Paris Martineau [02:12:32]:
I think it's Linux. I mean I.

Leo Laporte [02:12:34]:
That means I could probably play it on Linux.

Paris Martineau [02:12:36]:
Yeah.

Leo Laporte [02:12:37]:
Proton. Okay.

Paris Martineau [02:12:38]:
Play it on. Yeah, you could play it on Steam because I don't. Yeah, certainly.

Leo Laporte [02:12:42]:
Yeah.

Paris Martineau [02:12:43]:
And I think there's other. Like you can buy it on itch IO.

Leo Laporte [02:12:47]:
Oh, itchy.

Paris Martineau [02:12:48]:
Okay. The other pick is Katie Nutopoulos just posted this example of something I didn't realize existed that Amazon now allows you to create notebook alum style podcasts to describe a product to you. And we need to listen to this one that Katie just found. We've got a.

Leo Laporte [02:13:10]:
Here we go.

Paris Martineau [02:13:11]:
Today our AI generated shopping show is exploring the Wellmadix rapid relief diaper rash cream. Emma, what makes this hospital grade cream different from standard diaper rash products? Well, it's really interesting. This cream uses a dual action approach. Instead of just zinc oxide, it combines that with white petrolatum. She.

Jeff Jarvis [02:13:32]:
Petrolatum.

Paris Martineau [02:13:33]:
Katie put in the chat. You can ask a conversation. Fascinating. So it's not just about treating the problem, but stopping it from coming back. Exactly. And they've added some. This is so ridiculous.

Leo Laporte [02:13:49]:
Wait, we have a question. We have a question. Extract a question from the audience.

Paris Martineau [02:13:53]:
These botanical ingredients help soothe sensitivity. Are they gonna say it? While the dual barrier does the heavy lifting it takes. Katie, we've got you. You're dealing with discomfort and this cream is designed for exactly that kind of irritation. Emma, what can you tell them? Oh, it doesn't repeat the question. My butt hurts. That's sad. Irritation from incontinence, chafing or.

Paris Martineau [02:14:16]:
Well, if you'd like a really dryly read podcast about your butt cream, you can visit Amazon.com create a protective barrier.

Leo Laporte [02:14:24]:
Wait a minute, we're not done listening.

Paris Martineau [02:14:26]:
It's a protective barrier and discomfort.

Jeff Jarvis [02:14:29]:
I like how she mispronounced patrol.

Leo Laporte [02:14:31]:
You know? You know what's interesting to me is that QVC and the Home Shopping Network and all those have left cable and this is the replacement. Is these live? I mean it's not. Mostly it's done by humans, but live streams on Amazon and other shopping platforms have really replaced home shopping on cable.

Benito Gonzalez [02:14:50]:
It's TikTok and Instagram that replaced qvc.

Paris Martineau [02:14:53]:
Yeah, that is true.

Leo Laporte [02:14:54]:
Yes. Good point. Wow. AI product. So you could. You could. I could make one for. For sugar free gummy bears, for instance.

Paris Martineau [02:15:03]:
Anything you could make it for.

Leo Laporte [02:15:05]:
I'm gonna do that.

Paris Martineau [02:15:06]:
And it's a. I'm sure.

Leo Laporte [02:15:07]:
Just look at some of the reviews.

Jeff Jarvis [02:15:09]:
I want to do a really boring plumbing thing.

Leo Laporte [02:15:12]:
Yeah.

Paris Martineau [02:15:13]:
Let's talk about cow magnets.

Leo Laporte [02:15:15]:
What was it? What was it Ian was working on? His backflow pump.

Jeff Jarvis [02:15:18]:
Yeah, his backflow valve. Yeah.

Leo Laporte [02:15:22]:
Very nice. What are you these days looking at, Mr. Jeff Johnson?

Jeff Jarvis [02:15:28]:
Well, some of the weirdest things are shown to me to try to sell me. I don't know why I was advertised a 64 inch hyperbaric oxygen chamber.

Leo Laporte [02:15:35]:
Well, how tall are you?

Paris Martineau [02:15:36]:
Maybe it knows things that you don't.

Jeff Jarvis [02:15:38]:
Maybe it does. I'm 6 foot 4.

Leo Laporte [02:15:41]:
So you're 76 inches. So I don't recommend the 64 inch model for you.

Jeff Jarvis [02:15:45]:
$72,000 upgrades I can get.

Leo Laporte [02:15:51]:
You'd have to crouch to get into it.

Jeff Jarvis [02:15:53]:
I got chair options. I can have interior, starlight interior.

Paris Martineau [02:15:58]:
What does that mean?

Leo Laporte [02:15:59]:
This is what Michael Jackson used to use, a hyperbaric chamber.

Jeff Jarvis [02:16:04]:
Really?

Leo Laporte [02:16:04]:
Yeah.

Jeff Jarvis [02:16:05]:
Maybe that's why this is hot now. Because of the Michael movie. I don't know.

Leo Laporte [02:16:09]:
It's. The idea is it's a high pressure atmosphere, two times the natural atmosphere. Using oxygen to enhance healing, reduce inflammation and improve overall all wellness. You know, you'd be better off building a sauna for.

Jeff Jarvis [02:16:26]:
Yeah, that's what I want. Is that so? Then. Then the other. Other one is because I try to read for this. Yeah.

Leo Laporte [02:16:34]:
Yeah. I don't know why.

Jeff Jarvis [02:16:35]:
Well, it happened on one of the German papers I read. Oh, speaking of which, in the German papers they've been captivated for the last couple weeks by the story of Timmy a. A whale. So that's the story. This is. This is Timmy's rescued a whale that was trapped outside of Hamburg and it got on sandbars and they tried to dig channels for all kinds of things and. And a lot of people this. Some could say that they've gone too far.

Jeff Jarvis [02:17:05]:
But they came up with a barge and got Timmy into the water filled barge and they're towing Timmy out to the North Sea.

Leo Laporte [02:17:13]:
Whale barge towing Timmy to the North Sea.

Jeff Jarvis [02:17:17]:
So here are photos. Some are saying that this is the. Timmy's not whispering well. And they're kind of.

Paris Martineau [02:17:23]:
What's the body of water called that's inside a Barge in the ocean.

Jeff Jarvis [02:17:27]:
I don't know.

Leo Laporte [02:17:28]:
Is that a main pool?

Paris Martineau [02:17:29]:
But is it. Is it.

Leo Laporte [02:17:31]:
Look at. It's an olympic size.

Paris Martineau [02:17:35]:
More so. Yeah, It's a whale. You could do the whale olympics in that.

Leo Laporte [02:17:40]:
A Timmy. He doesn't look good.

Jeff Jarvis [02:17:43]:
No. He's like. Well, they have towels on them to keep his skin. Okay.

Leo Laporte [02:17:47]:
You know, just let Timmy die in peace.

Jeff Jarvis [02:17:50]:
That's pretty much it. Timmy's a young whale. It's tragic. People. People felt for Timmy, but Timmy got anthropomorphized to an extreme.

Leo Laporte [02:17:56]:
Yeah.

Jeff Jarvis [02:17:56]:
So there's the happy hamburgers trying to bring Timmy to the ocean.

Leo Laporte [02:18:04]:
Timmy. That is our show title for Disney.

Jeff Jarvis [02:18:08]:
He's now in Danish waters headed toward the north sea.

Leo Laporte [02:18:11]:
Oh, they're following him all the way up to the north sea.

Jeff Jarvis [02:18:14]:
Oh, this has been. This has been regular damage money have

Paris Martineau [02:18:18]:
they spent on Timmy?

Jeff Jarvis [02:18:19]:
Millions.

Paris Martineau [02:18:19]:
Do you think that. Do you think Timmy realizes what a unique position he's in? Timmy's realizes that he's being taken across the ocean.

Leo Laporte [02:18:29]:
I'm feeling sick, and they're putting me in this thing, and they're pushing me along to the north sea. And then it says if Timmy's considered robust enough, the whale will be released and hopefully swim further into the Atlantic ocean where he will die.

Paris Martineau [02:18:45]:
Well, here's to you, Timmy. I hope you're considered robust enough.

Jeff Jarvis [02:18:49]:
The guardian says that attempts to rescue Timmy, the stranded whale are inadvisable. Oh, that's a very guardian way to look at things. You really shouldn't do that.

Leo Laporte [02:18:58]:
You shouldn't. Helpers stand next to Timmy in the.

Jeff Jarvis [02:19:01]:
But politicians got involved. Should they be involved? The rich people got involved. Rescue the whale. It's been a whole megilla story in Germany.

Leo Laporte [02:19:11]:
Wow.

Paris Martineau [02:19:12]:
What's the German word for whale?

Jeff Jarvis [02:19:14]:
I should know that. Transl. From English to German. The whale. Derval. W.

Leo Laporte [02:19:30]:
Well, Timmy, good luck on your journey.

Jeff Jarvis [02:19:32]:
We salute you. To me.

Leo Laporte [02:19:34]:
To freedom. We salute. Salute you. Ladies and gentlemen, let's get all three of us saluting Timmy. That concludes this gripping edition of intelligence

Jeff Jarvis [02:19:50]:
hamburgers towing Timmy out to sea.

Leo Laporte [02:19:52]:
Yes. Of Timmy. What was it? Happy.

Paris Martineau [02:19:55]:
Happy hamburger towing. To me.

Leo Laporte [02:19:57]:
Is that. Is that too long for a title? Bonino. Happy hamburger.

Jeff Jarvis [02:20:00]:
Please don't. Please don't say it's okay. Oh, good.

Paris Martineau [02:20:03]:
One of my favorite things about our show is we have these great guests on, and they probably think, like, wow, you know, I'm gonna be able to share this podcast with my audience, and they see that they're on an episode called happy hamburgers towing Timmy and They just have to go and, well, it's a photo of all of us saluting, and they're nowhere to be seen. And I think that's beautiful.

Leo Laporte [02:20:24]:
It's. It's kind of my dream come true, to be honest with you. You. We do thank Nirav Patel, who was very gracious spending time with us.

Jeff Jarvis [02:20:31]:
I don't wonder why his name is not Timmy.

Leo Laporte [02:20:34]:
Hey, I was on a podcast. What was the name of it? Happy Hamburgers Towing Timmy to the North Sea. Okay, we'll make sure we listen to that right away. Paris Martino, Great to see you. Glad you got out of the tunnel alive.

Paris Martineau [02:20:50]:
Listen, my haters were trying to keep me constrained underground, but I.

Leo Laporte [02:20:54]:
Nobody hates Paris Martino. Everybody loves Paris Martin.

Paris Martineau [02:20:57]:
True.

Leo Laporte [02:20:58]:
And you were very gracious, saying, hey, I'm trapped. I'll be there as quick as I can.

Paris Martineau [02:21:03]:
I mean, it's rare that you get trapped on the train and have cell service. The universe was smiling.

Jeff Jarvis [02:21:09]:
Otherwise we would have wondered, what the heck has happened to Paris?

Leo Laporte [02:21:13]:
And thanks to you, I'm gonna go have a yasso.

Paris Martineau [02:21:17]:
I'd really recommend them. They're great.

Leo Laporte [02:21:19]:
Salted caramel ball. Thank you very much, Paris. We'll see you next week. I'll be in Hawaii, by the way.

Jeff Jarvis [02:21:26]:
Yeah.

Leo Laporte [02:21:26]:
So this is going to be a very interesting. It's an experiment to see.

Paris Martineau [02:21:30]:
Are you gonna pull a Mike Elgin and then have a beautiful vista behind you and a beautiful mixed drink in your hand the entire show?

Leo Laporte [02:21:37]:
I. It's the plan.

Paris Martineau [02:21:39]:
Great.

Jeff Jarvis [02:21:39]:
It'll be a little early for the drink, though. When you're doing this show, it'll be never too early.

Leo Laporte [02:21:44]:
So it'll be 11am how many hours? Three hours earlier.

Jeff Jarvis [02:21:47]:
Oh, is that all? Oh, okay.

Leo Laporte [02:21:50]:
Yeah. No, I could. Maybe. It won't be an alcoholic beverage. I don't really drink alcohol, but it might be a coconut with some coconut juice in it or something.

Jeff Jarvis [02:21:58]:
I finally had wine for the first time in three months. It was nice.

Leo Laporte [02:22:01]:
Oh, you couldn't have wine because of your medication?

Jeff Jarvis [02:22:04]:
Well, I. No, yeah, I didn't. And I was on pain pills for a while and stuff like that, and then I figured, okay, that's good to go without. I mean, it's part of the reason. I've lost £31. Pounds.

Leo Laporte [02:22:15]:
That's a. You don't look like you've lost £31.

Jeff Jarvis [02:22:17]:
Thanks a lot.

Leo Laporte [02:22:19]:
No, because you looked slender all along.

Jeff Jarvis [02:22:21]:
Being tall helps.

Leo Laporte [02:22:23]:
Yeah, you didn't look like that you had £30 to lose is what I'm saying. Oh, I did really okay. It must be somewhere.

Jeff Jarvis [02:22:30]:
I was. My high was 210. I'm now 179. When I was running air quotes around running rather obsessively six months miles a day, I got down to 156.

Leo Laporte [02:22:42]:
Yikes.

Jeff Jarvis [02:22:43]:
People thought I had cancer.

Leo Laporte [02:22:44]:
Yeah.

Jeff Jarvis [02:22:46]:
Are you.

Leo Laporte [02:22:46]:
Are you okay? You look good. Now stay where you are.

Jeff Jarvis [02:22:49]:
Don't you just figure out how to get my neck and my back?

Leo Laporte [02:22:53]:
Jeff Jarvis, professor of journalistic innovation emeritus. His books the Gutenberg Parenthesis, the Way we Weave magazine. But most importantly Hot type, the new one Upcoming. Upcoming in July. August. August, August.

Paris Martineau [02:23:08]:
Hot type. Get your hot type.

Leo Laporte [02:23:10]:
Get your hot type@jeffjarvis.com pre orders available. And look for the epilogue about happy hamburger stowing. Timmy.

Jeff Jarvis [02:23:19]:
Look for my colophon, which is which we. I set on a line of type.

Leo Laporte [02:23:24]:
Oh wow.

Jeff Jarvis [02:23:25]:
Actual hot type is in the book. Hot type.

Leo Laporte [02:23:27]:
Oh, that's really cool. So you had a separate. You have to go with a separate page that then get back into the book.

Jeff Jarvis [02:23:33]:
Yeah.

Leo Laporte [02:23:33]:
Wow.

Jeff Jarvis [02:23:33]:
And then, and then we went. I was at the Museum of Printing in. In Hill, Mass. Which is a wonderful, wonderful place. Go there if you can. Any.

Leo Laporte [02:23:40]:
I'm going to buy the book just for that. I mean I have a copy of the book, but I'm going to buy the book just to get the colophon.

Jeff Jarvis [02:23:45]:
The. I'll next week I'll show you the type. It's over there.

Leo Laporte [02:23:48]:
Nice. What's the font? Or do you call it a type face?

Jeff Jarvis [02:23:54]:
Well, that's the type. Face is a design. A font is one size and style of a typeface. Okay, I'll tell you next week.

Leo Laporte [02:24:03]:
And here is a. A preview of what it's going to look like when I am in Hawaii doing the show. It's not going to look like this. I hope. I mean, maybe it will. I don't know. I'm hoping it will. But I like this.

Leo Laporte [02:24:23]:
I do have a.

Jeff Jarvis [02:24:25]:
The next is the man's ear.

Leo Laporte [02:24:27]:
No, it's not going to look like that, I promise you. Although, well, maybe I shouldn't make promises I can't keep.

Paris Martineau [02:24:37]:
Yeah, you don't know what's going to happen.

Leo Laporte [02:24:38]:
I gotta. I don't know what's going to happen. I could be kidnapped, hijacked by crazed coconut pirates. I will have the Starlink mini and I'm hoping I can set it up somewhere in a beautiful area in do the show.

Jeff Jarvis [02:24:51]:
Are you in a hotel or a RV or a condo?

Leo Laporte [02:24:56]:
In a condo complex. We're in Kona. So you know What? I will be holding a delicious cup of Kona coffee. Paris, Kona is good, right? That's a good kind of coffee.

Paris Martineau [02:25:04]:
I haven't had Kona coffee.

Leo Laporte [02:25:06]:
It's. I have and it's very good. It's a very delicious brew. Volcanic soil.

Paris Martineau [02:25:13]:
Excited?

Leo Laporte [02:25:14]:
Yeah. Thank you everybody for joining us. We do Intelligent machines every Wednesday, 2pm Pacific, 5pm Eastern. That would be 2100 UTC. You can watch us live in the club Twit discord or on YouTube, Twitch, X.com, facebook, LinkedIn or Kik. And if you're watching live, of course you can chat with us live. We love hearing you in the chat after the fact. On demand versions of the show.

Leo Laporte [02:25:44]:
Oh, I didn't mention. We're also on YouTube. The videos on YouTube on demand versions of the show available from Twitter TV IM. There's audio or video. Also you could subscribe in your favorite podcast client and if you do, leave us a nice five star review. We haven't had any to read lately, but if you give us a good one, Paris will read it next.

Paris Martineau [02:26:05]:
We put them out there.

Leo Laporte [02:26:08]:
Yeah, next week. I'm not sure who's going to be on the show. I think Chris Stoeckl Walker. The interview I did, you guys couldn't make it, but it was a very interesting interview with a British journalist who is using AI to do his news gathering. We have Troy Hunt coming up, the creator of have I Been Pwned? Frederick Riva, who is the CTO of Dashlane. We'll talk about how password managers survive in an age of AI. And my old friend Rick Salmon, who's an amazing photographer, has a new book about AI and creativity and he has to be on. And I said, rick, I would love to have you on.

Leo Laporte [02:26:45]:
So he's going to join us end of May. So we have some great people coming up. Very excited about that. Thanks everybody for joining us. We will see you next time. Thank you, Paris. Thank you, Jeff. Thank you club members.

Leo Laporte [02:26:58]:
See you next week on Intelligent Machines. Aloha. I'm not a human being.