Intelligent Machines 867 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. Paris Martineau is here. Jeff Jarvis is here. We're going to talk about the lines. They're too damn long. We're also going to talk to Ian Bogost. He is a contributing writer at the Atlantic, a professor at the Washington University in St. Louis, and he says, pay attention to the small stuff.

Leo Laporte [00:00:18]:
That's the good stuff. We'll talk about that in a lot of AI news next on Intelligent Machines, podcasts you love from people you trust. This is Twitter.

Jeff Jarvis [00:00:32]:
Wait.

Leo Laporte [00:00:35]:
This is Intelligent Machines with Jeff Jarvis and Paris Martineau. Episode 867, recorded Wednesday, April 22, 2026. The ketchup effect it's time for Intelligent Machines, the show. We cover AI, robotics and the smart little doodads and googas around your house. I think that's right. I am being corrected now by two professional writers. Paris Martineau is here, investigative journalist at Consumer Reports. Hello, Paris.

Leo Laporte [00:01:08]:
Bonjour.

Paris Martineau [00:01:09]:
Hello. We are both two professional writers and two professional write opinion havers.

Leo Laporte [00:01:13]:
Yes. No, as. As am I. I apologize because I realized last week I shouted you're wrong, which is not conducive to good conversation.

Jeff Jarvis [00:01:24]:
We'll have that conversation again.

Paris Martineau [00:01:25]:
I was about to say last week, I don't think that's the only time

Leo Laporte [00:01:28]:
you've shot it that way. I've probably done it once or twice. I'm a. I'm a little biased when it comes to AI, but anyway, we'll get that. Also with us, Mr. Jeff Jarvis. He is the emeritus professor of journalistic innovation at the Craig Newmark Graduate School of New York. Also adjunct or fellow or something or other.

Leo Laporte [00:01:49]:
Montclair State University. And he is a professor of something or other at SUNY Stony Brook. The author of the Gutenberg Parenthesis. Actually one of your books magazine was edited by our guest. Coming up, we're going to talk to Ian Bagos. Bagost. Bogost. Bogost.

Leo Laporte [00:02:07]:
Right.

Paris Martineau [00:02:07]:
By the time he's here, we'll have figured it out.

Leo Laporte [00:02:09]:
Bogost. Claude says it's Bogost and he edited a magazine. But Ian is a really interesting fellow game designer, contributing writer at the Atlantic. He's also a professor. Three things of three things. Three different departments at the Washington University of St. Louis. But he is really a fascinating guy who is a fan of AI but who says that the friction is what's important in life.

Leo Laporte [00:02:35]:
We'll talk about friction with Ian Bogust. He's not going to join us until about first. Second hour of the show. First hour. I have a surprise. I normally end the show as you do too with our picks of the week. I'm going to start the show with my pick of the week. Are you ready?

Jeff Jarvis [00:02:53]:
Well, be that way because you're in charge. So I'm in charge.

Leo Laporte [00:02:56]:
I get to see.

Paris Martineau [00:02:56]:
We have no say.

Jeff Jarvis [00:02:57]:
No, it's not my pick of the week.

Leo Laporte [00:02:58]:
This week is a little way, you see right here called Damn Lines.

Paris Martineau [00:03:02]:
Oh, I know this website.

Leo Laporte [00:03:04]:
Do you know this website?

Leo Laporte [00:03:06]:
I found out about it because one of the lines is my son, Salt Hanks, which is closed right now. So there's no line.

Jeff Jarvis [00:03:12]:
He's run out.

Paris Martineau [00:03:13]:
And even if it was open, it would be out of sandwiches at this hour.

Leo Laporte [00:03:16]:
That's right. You have to go earlier. But this site is really cool because it shows you when the next live stream's going to begin. It shows you when the peak is. Look at that. This is what happens. This is what happens. It was a 38 minute wait and then he sold out and there's no wait anymore.

Leo Laporte [00:03:30]:
And you can see where the peaks are. This is a very cool site. Right now it's just a few restaurants in New York City. Tomi, Jazz John's of Bleecker street, which conveniently is right next door to Salt Hanks. So one, one, one window does it all. And a Salt Hank clone called Breakfast by Salt's Cure. But our guest today is.

Paris Martineau [00:03:51]:
Okay, it is not a Salt Hank clone, but that's beside the point.

Leo Laporte [00:03:53]:
It's got Salt in the name. That's all that matters. That's all I care about. The guest is the creator of this site. Lucas is on the line. I said I wouldn't say anything about his. He's a little bit anonymous here. Lucas, it's great to see you.

Lucas [00:04:08]:
Likewise, thanks.

Leo Laporte [00:04:09]:
I love this idea. First of all, I gotta ask you because this is an AI show.

Jeff Jarvis [00:04:12]:
Yeah.

Leo Laporte [00:04:13]:
Vibe coded. Oh yeah, yeah.

Lucas [00:04:15]:
Me and Claude. Claude was my model of choice for this one.

Leo Laporte [00:04:20]:
Did you use the design tool, the new design tool, or did you do it all for.

Lucas [00:04:24]:
No, like, I mean like everyone's got their own like every engineer and even like those starting like to pick up engineering have their own like preferences and flavors for how they interact with AI. Like I like to audit everything it does and like see as it generates the files and whatnot.

Leo Laporte [00:04:40]:
You actually read the code.

Lucas [00:04:42]:
Well, you glance over it like you

Paris Martineau [00:04:45]:
wouldn't go so far.

Lucas [00:04:46]:
You can catch, you can catch certain like gotchas in it.

Leo Laporte [00:04:50]:
Right.

Lucas [00:04:51]:
Versus like other. Other friends of mine will have like five agents at once or ten agents at once. It's a little bit. It's a little bit riskier because some can go a little bit awol and then it's harder to track.

Leo Laporte [00:05:03]:
Yeah, yeah, it's fun. I mean, look, to me, this is the best video game ever invented. It is. I could. I play every day and for hours at a time. But let me. You did something, though, that is actually not AI because in order to get these videos of the line, what did you do to get these pictures?

Lucas [00:05:23]:
Yeah, the fun thing about this project, like, I've been. I guess I can give you a history of like, where the whole concept came from.

Leo Laporte [00:05:29]:
Yeah, please do. Yeah.

Lucas [00:05:30]:
Yeah. Okay, so I'll start with that. Years ago, when I was in my last year, university in Canada at Queen's University.

Leo Laporte [00:05:37]:
Good school.

Lucas [00:05:38]:
One of my. Yeah, it was a great school. So the issue with Queen's university is only 4 bars on campus and there's about 25,000 students. Yeah, about like 10pm ish. Come around. The lines are a kilometer long. And so for all four years of university, the biggest paradigm and annoyance that we would have across all campus was when is the optimal time to stop drinking beer at your house and to start drinking beer at the bar? Because you don't want to go too early where no one's there. You don't want to go too late where you have to wait in line.

Lucas [00:06:08]:
And it was always a guessing game and different nights, it would be a different time. You would rely on someone, some friend who went early to give you an update to. My last year, I was toying around with the idea. I had a friend move it into an apartment that had a good view of one of the bars. I put a webcam in the window. It's an IP cam. And like, an IP cam is just basically a camera that lets you route the footage over to an IP address is the gist of it. And then just put on the website, like there was a simple static front end, just had the live stream viewer and then I started.

Lucas [00:06:41]:
I put that stuff.

Leo Laporte [00:06:43]:
Did you pay the people whose window it was in?

Lucas [00:06:46]:
Yeah. And this is on campus. It's like the going rate on campus is like $50 Canadian a month. Nothing crazy. Like the New York rate now is a little bit higher.

Jeff Jarvis [00:06:55]:
Yeah, hey, yo, we know our value.

Leo Laporte [00:06:58]:
Real estate. Hey, if you have an apartment across from John's place, probably the only window

Paris Martineau [00:07:02]:
those apartments got

Lucas [00:07:06]:
one of two or one of three Betty cases. But like, the cool thing about it was when I was in university was like, I sent the URL for the website to a few group chats. And it was like a Facebook moment where within hours, like, everyone on campus explosives. Explosives. And it just. Yeah, it just went around like. There was no intentional marketing behind other than sharing.

Jeff Jarvis [00:07:25]:
So Canadians are nice. So I get that. I want to hear what happened when you went knocking as a stranger on the door on Bleecker street, saying, I want to put a camera in your window. What was that interchange like?

Lucas [00:07:38]:
Yeah, well, it's funny, I try to go door knocking first, but then like, the every residential door security gets in your way because you need to get

Leo Laporte [00:07:45]:
in and so can't even get upstairs. Yeah.

Lucas [00:07:47]:
And. And. And door knocking is hard because it's a linear timescale. Like, one door takes two minutes, et cetera. And it's not that easy. So what I did instead was if you go on, like, street Ease or any residential website, you can find listings of, like, previous apartments and whatnot. And hopefully the pictures are good enough where you can identify the view in the windows. And I just found the units of that had a good view of the street.

Lucas [00:08:11]:
And you would just find landmarks, like a tree or like the building brick across the road. And I just wrote letters to them. Like, I printed like 100 identical letters from FedEx, put them on envelopes, wrote the address on it, Snail mail.

Leo Laporte [00:08:23]:
You put us.

Lucas [00:08:24]:
Yeah, just nailed it up. And then that's the only way to go about doing it from deep, it's scalable. Like, took no more than a few hours to send out 100. And then from that, I got my first initial, like, four people who are interested who I went with, like, inbound leads from that was probably around like 10 or 12. And that way it's great because you can choose between who is the optimal apartment, who has the optimal window. Because the fun thing about this project, to answer your question before, it's like, it's both an engineering problem and it's an operations problem, and it's a hearts and minds problem. And the engineering part is easiest. Like putting a website out and running a computer vision model, that's really the easiest because it takes a little bit of a learning curve.

Lucas [00:09:10]:
And with AI now, really fast, the operations problem is something that, like, you kind of need to experiment with. And so finding out to how to get those interested to, like, help support the project. And there's a high degree of trust involved between, like, myself and these tenants. Because you're putting a camera in their window. And like, the answer is like, well, cameras have a microphone. So, like, there's a high degree of trust between me to tell them that. Okay, the audio is disabled.

Leo Laporte [00:09:39]:
Right.

Lucas [00:09:39]:
And they need to trust that likewise it's connected to their router.

Leo Laporte [00:09:43]:
It looks like you also blur everything but that restaurant. Yeah.

Lucas [00:09:48]:
Yeah, that's intentional too. No one, no one should be seeing into a person's window or money.

Ian Bogost [00:09:53]:
Right.

Leo Laporte [00:09:53]:
Good for you.

Jeff Jarvis [00:09:54]:
How did you pick. How did you pick these as your targets?

Lucas [00:09:57]:
I lived around this. I actually just moved apartments last week, but I used to live on West 4th and 6 Ave. And so these are all my favorite places. Specifically breakfast by Salts cure. Best pancakes in New York. Yeah, every weekend I would go there and it's about a 15 minute walk for a 10 minute walk for me. And it was a question. Okay, should I make the commitment, get out of my apartment, go there.

Lucas [00:10:19]:
The lines are going to be 10 minutes or it's going to be 60 minutes.

Leo Laporte [00:10:22]:
New Yorkers seem to like lines. Henry says they don't like.

Jeff Jarvis [00:10:26]:
No, we don't like lines. We just know that things are worth the effort.

Paris Martineau [00:10:30]:
There are some things that you know are worth the effort and it depends on the speed of the. Like the speed of the line is a very specific aspect of it. There's a breakfast by Salt's Cure also in Brooklyn that also has a line. And I've been there quite a few times because the pancakes are fine.

Leo Laporte [00:10:44]:
Are you lobbying Paris to have a damn lines camera placed?

Paris Martineau [00:10:49]:
They're fine, but they're extremely good when you take into account the fact that they also offer gluten free pancakes. So with my friends that are gluten free, they really.

Jeff Jarvis [00:10:57]:
Oh, how Brooklyn can you get?

Leo Laporte [00:11:00]:
Yeah, the Celia, you have what, how many right now? How many restaurants right now?

Lucas [00:11:05]:
I got five right now. I used to have cats deli.

Leo Laporte [00:11:09]:
Oh yeah.

Lucas [00:11:09]:
I had to take the cats deli one wrong, one down because the. The building didn't fit the window type.

Leo Laporte [00:11:17]:
I got into cats once because the guy that there we were waiting in line for the table and a guy had a heart attack and was taken out in the ambulance. I got his table. So that was. I don't know if you could incorporate that into damnlines.com somewhere.

Lucas [00:11:29]:
That's one way to do it. Yeah.

Jeff Jarvis [00:11:31]:
See if you see an ambulance in front of the place, then you know, you go run.

Lucas [00:11:36]:
The fun thing about this project is it had its instant product market fit because no one liked like I put this in the website footer. Like no one likes waiting in a damn line. They're annoying at the bottom in New York. They're all over the place. And if anyone can just save time, that's the instant utility. Whether that or not that translates into a revenue model, who knows? Like right now this is just like me finding this from my amex.

Jeff Jarvis [00:12:03]:
So we got to ask the standard startup question. Business model.

Lucas [00:12:07]:
I don't know, I, I, I put like a contribution button there to see if like anyone wants to like contribute. Like, I'm not calling it donations because like there's no tax. Yeah, I figured, okay, there's probably like a legal gray area there. So I'll call, I'll call contributions. No one's contributed yet, so I don't, no one.

Leo Laporte [00:12:25]:
Yo, that's the, there's a certain, a certain fella whose restaurant is on here, Salt Hanks, who, who he said, you know Surfline, which does the same thing with the surf at beaches, makes big money charging surfers for the latest surf information. So he thinks there's a business model here.

Lucas [00:12:45]:
So yeah, I, I think that's, that, that's, that's got legs too. The challenge though, it's like a kind of like a chicken, the egg. Because like in order to charge a consumer business model, you kind of need like a critical mass.

Leo Laporte [00:12:57]:
Yeah.

Lucas [00:12:57]:
Make the utility.

Jeff Jarvis [00:12:58]:
Right.

Lucas [00:12:58]:
Like five locations isn't really enough unless you live like the West Village where like you get for the West Village ones. But that's definitely an option. I mean, like I'm, I have no intention to like really make this into like the next big money making startup. This is just to serve people of New York with utility. So as long it was fun.

Leo Laporte [00:13:18]:
No, it's, it's totally fine.

Lucas [00:13:19]:
But like, and it gives me utility too. So if this covers its costs and nets zero, I am happy. Like that is all I need because I cannot subsidize it for my AMEX for too much longer.

Leo Laporte [00:13:30]:
Did Henry give you a free sandwich at least?

Lucas [00:13:32]:
No, I enjoy paying the. How much is it?

Leo Laporte [00:13:36]:
$32. I am going to talk to Henry. That young man's going to give you a free sandwich. Do restaurateurs mind these cameras or do they like them?

Lucas [00:13:45]:
Everyone. So of the four, and this is not me that's interviewed them, I've only spoken to Henry because Henry actually reached out to me. But like the New York Times did a piece on this and they interviewed and like the New York Post, of the three, the only one who had concerns was John's on Bleecker. And their concerns were valid because they were saying that the wait time estimates were too long for them because the keyword here is estimates. Like, I can only, like, estimate between, like, traffic in, traffic out and dwell time. And they were saying it was a risk of turning away business, which is fair. And so, like, for.

Jeff Jarvis [00:14:19]:
They're also jealous of the longer lines. Next door.

Lucas [00:14:21]:
Yeah, next door. Yeah. That albeit, is a fair concern. Like, I do not want a business. Business to be hurt by making people not go to the location. And so for John's, I like, did like, a special case for them where I made the. The wait time faster for them. In this case.

Jeff Jarvis [00:14:39]:
What's the hardware you have in the apartment windows?

Lucas [00:14:42]:
It's a reolink. Cameras are the ones I've been going with. They're like 150 bucks on Amazon cheap. Yeah, it's a.

Jeff Jarvis [00:14:51]:
Sorry, what is it? What is the camera tied to to get connectivity?

Leo Laporte [00:14:55]:
Do you have to use the. The routers? The people's routers?

Lucas [00:14:58]:
No, no, no. It's all WI fi. WI fi? Well, most are WI Fi. It has an Ethernet option for some of the apartments, specifically two of them. The router is significantly far away. And so when I was trying to send 4K, like, 30 FPS footage, it is good quality.

Leo Laporte [00:15:14]:
It's really good quality.

Lucas [00:15:15]:
Yeah, it was. Because you'll see sometimes, like, for. I just saw it a minute ago, like, some. And this is neat, too.

Ian Bogost [00:15:21]:
Like.

Lucas [00:15:21]:
Like one of the snapshots had, like a gray block for half of it. What that actually was was just packet loss over the Internet for that snapshot. Like, only half it got sent through, and then the other half just got lost in the ether of the Internet somewhere. And so to, like, combat that, like, yes, Ethernet's always the best. It's just. And so like, I bought a few WI FI extenders for a few of these tenants. And just, like, you plug it in right. Right next door and you plug in.

Lucas [00:15:44]:
You plug the Ethernet into this WI fi. WI FI extender just. That just increases unit costs by about 75 bucks. So always good to keep unit costs lower.

Jeff Jarvis [00:15:54]:
So many years ago, in the beginning of this thing we call the web, I created something called Burbo Cam on Bourbon street in New Orleans.

Leo Laporte [00:16:04]:
Oh.

Jeff Jarvis [00:16:04]:
From the Cat's Meow Bar out on Bourbon Street. Now, Bourbon street, you may know, is a place where people tend to get inebriated.

Lucas [00:16:10]:
Yes.

Leo Laporte [00:16:10]:
And take their shirts off.

Jeff Jarvis [00:16:12]:
Exactly. Yes. So it became incredibly popular as people came into the. Into the camera to watch people lifting their garments for the camera. And there were sites that started up where they collected the best bits as well.

Leo Laporte [00:16:26]:
Oh, Paris.

Jeff Jarvis [00:16:26]:
So I think you need performance. The restaurants.

Lucas [00:16:30]:
Yeah. Yeah.

Leo Laporte [00:16:31]:
Get some mimes. Yeah, yeah, yeah.

Lucas [00:16:34]:
It's funny. I had one of the tenants who installed an apartment, and she said, like, when she told her parents about, like, the offer she got for a camera, like, her parents were fully supportive because they're like, oh, like the camera is going to give increased security for.

Jeff Jarvis [00:16:48]:
For your building.

Lucas [00:16:48]:
Like, now there's. Now there's footage outside.

Leo Laporte [00:16:50]:
Like.

Lucas [00:16:50]:
Yeah, that's like a byproduct.

Leo Laporte [00:16:54]:
If there's a murder on the street out front, you'll have footage.

Lucas [00:16:57]:
Yeah, I mean. I mean, well, I only persist the actual video files for about 10 minutes, but it's not like, into perpetuity.

Leo Laporte [00:17:05]:
Yeah, you don't want tens, petabytes of data on your hard drive, Lucas. I just. I just. You know, I said, somebody told me about this. I sent it to Hank. He said, oh, yeah, it's blowing up. I know all about it. And I said, well, can we talk to Lucas on this show? Because I think it's really cool.

Leo Laporte [00:17:20]:
Damnlines.com. lucas, a pleasure meeting you. Thank you. I really appreciate your joining us today. Thank you, Lucas.

Paris Martineau [00:17:28]:
Thanks so much.

Leo Laporte [00:17:29]:
Damn lines. Take care. That's fun. All right, I'll tell you guys offline where he works.

Paris Martineau [00:17:35]:
Oh, I've already found him.

Leo Laporte [00:17:35]:
We saw what. How did you find out?

Jeff Jarvis [00:17:39]:
His full name was on the zoom.

Leo Laporte [00:17:41]:
And you did it. God, you guys are terrible.

Jeff Jarvis [00:17:43]:
Well, we're reporters.

Paris Martineau [00:17:45]:
Such is the nature of our job. I was literally in the middle of texting Jeff about something related to this. That question.

Leo Laporte [00:17:53]:
That's why I didn't put his last name on the air. Wow, man. All right, let's do an ad and then. Then we'll continue. You guys are bad. You're bad. Back to the show. Steve Gibson told me to yell at you guys.

Leo Laporte [00:18:15]:
I said I already did last. You're wrong. You're wr.

Jeff Jarvis [00:18:19]:
Wrong.

Leo Laporte [00:18:20]:
I'm sorry. I apologize. Seems like every week I come back and I have to apologize for the week before. I will try. I will endeavor not to be a jerk this week. But Steve said there is no doubt now that Mythos is more than just marketing. Of course. It's.

Jeff Jarvis [00:18:35]:
We just asked. We're just reporters.

Leo Laporte [00:18:38]:
And it's a reasonable question.

Paris Martineau [00:18:39]:
The old adage is, if your mother says she loves you, check it out. And so I think it extends to if anthropic says Mythos is the end all be all of cyber security threats, you should check it out.

Jeff Jarvis [00:18:51]:
By the way, who do you check it out with? Your therapist?

Leo Laporte [00:18:54]:
No. About your mom, you mean?

Paris Martineau [00:18:56]:
Yeah, your mom and Related parties who would be.

Jeff Jarvis [00:19:01]:
If your mom's lying to you, she's lying to you.

Leo Laporte [00:19:03]:
Are you lying to.

Paris Martineau [00:19:04]:
You need to look into it with her as well as other people. People familiar with the situation.

Leo Laporte [00:19:11]:
Parties familiar with the situation. Mom does love you. Don't ask dad, though, because he doesn't know.

Lucas [00:19:20]:
He definitely doesn't.

Leo Laporte [00:19:21]:
Hello, Gizmo. Little brief.

Paris Martineau [00:19:24]:
She's, you know, trying to. Oh, gosh, don't do it, Gizmo.

Leo Laporte [00:19:29]:
So Steve quoted this paper, which is actually from the Cloud Security alliance, but it's authored by a huge number of very respectable people in the security community, including Jenner Easterly, former director of cisa. She's currently director of rsac. Bruce Schneier, we've talked about him all the time. Katie Mazuris, I've interviewed her. Just really good people and 250 other CISOs. And the paper is the AI Vulnerability Storm. Building a Mythos ready Security Program. They fundamentally accept that Mythos is what it says it is, an AI model.

Jeff Jarvis [00:20:11]:
Did they use it?

Leo Laporte [00:20:13]:
Well, I'm going to talk about some people who have used it. Some, by the way, without permission.

Jeff Jarvis [00:20:17]:
Well, there's that, but. But how do they know unless they.

Leo Laporte [00:20:20]:
I think some of them have used it, but. So they are addressing people, CISOs in business who are going to be faced with a risk spike as soon as Mythos becomes widely available, they say what will happen next. The storm of vulnerability disclosures from Project Glasswing is the first of many large waves of AI discovered vulnerabilities. By the way, that's more than just Mythos. And that's the other takeaway from this is all AIs can do this to a certain extent. All of the top frontier models are very good at finding security.

Jeff Jarvis [00:21:01]:
They will all get better as time

Leo Laporte [00:21:02]:
and they will all get better. The capabilities seen in Mythos will quickly become more widely available, dramatically increasing the number and frequency of complex and novel attacks organizations will face. Organizations are already facing this. This is a graph from that paper talking about how long it takes from the announcement of a vulnerability, what they call the CVE disclosure, to it being weaponized to there being an exploit in the wild. And a few years ago, in 2018, it would take, on average 2.3 years. Between the time the CVE came out and the time hackers reverse engineered it and were able to exploit it, that number has been going down rapidly. Last year it was 23 days. This year it's 10 hours.

Leo Laporte [00:21:50]:
10 hours from the time the exploit is announced to the time it's exploited. And I think you can directly point to AI being responsible for that. That's really the big breakthrough. This comes from a site called Zero

Jeff Jarvis [00:22:05]:
Daycare, because you're using AI to create the exploit once you have the vulnerability.

Leo Laporte [00:22:09]:
So the AI can look at the CVE and reverse, in effect, reverse engineer it, saying, okay, this is what they fixed, this is the vulnerability. And it will make, it can make a proof of concept from that CVE and then the hacker can then apply it.

Jeff Jarvis [00:22:23]:
But if things have been done responsibly, hasn't the leak been plugged?

Leo Laporte [00:22:26]:
Well, this is the. And this is why this paper was written, because it's very frequent that the patch goes out but doesn't get applied in a prompt fashion. Because partly that's because they used to have time.

Jeff Jarvis [00:22:40]:
Right?

Leo Laporte [00:22:41]:
They don't have time anymore. And so that's really part of what this paper is, is all about, is they project Zero Day Clock projects that it will be less than an hour by the end of this year and less than a minute in a couple of years because of AI. It also, just to answer your question, the percentage of exploited CVEs has been going up like crazy. It's now 72% of all CVEs get exploited on or before the day of disclosure, even though they're being patched. Patches take time, usually.

Paris Martineau [00:23:19]:
Where are they getting this data from?

Leo Laporte [00:23:22]:
I don't know. Data sources. Let me.

Paris Martineau [00:23:25]:
How do you know that?

Jeff Jarvis [00:23:26]:
How do you know that?

Leo Laporte [00:23:27]:
Places the government's CISA Volnchek, which is a very well known respected vulnerability. Commercial threat intelligence. There actually are 10 independent sources, they say, and they're all listed in the Zero day clock. So there are. Metasploit's another one. There are a lot of companies that spend, make a lot of money, in fact, charging companies for this kind of information. Threat intelligence, they call it. In fact, some of our advertisers do threat intelligence.

Leo Laporte [00:23:58]:
So anyway, I wanted to mention that. I also wanted to mention, and we talked about this last week, that Dario Omode went to the White House a week ago Friday, talked to Scott Bessant and Susie Wiles, the chief of staff, and apparently Trump has been convinced that. Well, anthropic's not so bad.

Paris Martineau [00:24:17]:
Well, you know, he's also convinced NSA spies who are using Mythos.

Leo Laporte [00:24:22]:
Yeah, they're not paying any attention to the blacklist. You know why? Cuz it's too good a tool to ignore.

Jeff Jarvis [00:24:27]:
Well, and the Trumpists want the danger. The more dangerous the tool, the more they want it, the more it's appealing.

Leo Laporte [00:24:34]:
One more data point. Mozilla shipped the latest version of Firefox, Firefox 150 yesterday and announced that they had fixed in it 271 bugs, which they found with Mythos.

Paris Martineau [00:24:49]:
However, the. That exact article says that the Mozilla team, the Firefox team, doesn't think that AI is going to upend cybersecurity long term, but that obviously software developers are going to be in for kind of a rocky transition with this.

Leo Laporte [00:25:06]:
Yeah, because they will use AI to patch as fast as the bad guys use AI to find. That's critical. I asked Steve about this. I said, well, isn't this going to be a, you know, a seesaw battle, like they're going to patch it, then the new AI will come out and find more? He said, eventually you get to stability where you don't have any bugs, you don't have any more exploits. The software is fixed, finally.

Paris Martineau [00:25:29]:
Fixed by who?

Leo Laporte [00:25:31]:
Well, and this is important to understand, we have lived in a world where software is awful, it's buggy, it's not well written.

Jeff Jarvis [00:25:37]:
But is it always a bug that's a vulnerability? Or sometimes is it part of the design that just says, oh, I didn't know it would do that. If somebody.

Leo Laporte [00:25:42]:
Yeah, often it's designed, for instance, Cisco, which makes of course, a lot of Internet hardware. You know, the government's always talking about these damn Chinese routers. Well, Cisco routers are often the most exploited routers. They're enterprise routers. And Cisco has in the past, for instance, left passwords in default passwords in the router so that you can access the interface. That's not a bug, that's just a stupid mistake. Right. So there are bugs, there are mistakes, there are unintentional, there are unique ways

Jeff Jarvis [00:26:15]:
to attack something that someone hadn't thought of. This is the problem with guardrails, too.

Leo Laporte [00:26:21]:
But AI can find, anticipate. Well, no, but that's what can't anticipate

Jeff Jarvis [00:26:26]:
every possible malign use something to it.

Leo Laporte [00:26:29]:
That's the point of this.

Paris Martineau [00:26:31]:
A couple of steps further, where suddenly we're going to be in a world where like this AI security checking is going to be an essential part of the release process for any like, new feature or that's the point of this. That's incredibly, that's incredibly expensive. How when we get a couple years down the line to where these companies are charging, let's say they're not even charging 100% of what it costs to do these tasks, they're charging only 50% which is already a lot more than what they're charging now. How is any company going to afford to do this sort of essential check for every single thing always?

Leo Laporte [00:27:10]:
Well, they better.

Jeff Jarvis [00:27:11]:
What if you're just a little app maker in the app store? What if you're just.

Paris Martineau [00:27:14]:
What if you're twit and trying to plug some sort of.

Leo Laporte [00:27:17]:
May mean. It may mean that either software gets more expensive or. Because what is also a certainty is if you are worthy of attack, the bad guys will be using these tools to attack you. So even if it's expensive because there's money to be made, and let's not forget the cost of not fixing these holes is perhaps even greater.

Jeff Jarvis [00:27:43]:
Have you taken any of the stuff

Leo Laporte [00:27:44]:
many companies are realizing that.

Jeff Jarvis [00:27:46]:
Have you taken any of the stuff you've wipe coded and put it through asking for?

Leo Laporte [00:27:48]:
Every time I do anything, I go through a security. Security check. Absolutely. And almost all these tools have skills for security checks. There are third party skills for security checks. I will run sometimes multiple ones. But the ironic thing is I'm just doing that for myself. I am not putting out commercial software.

Leo Laporte [00:28:06]:
I mean it's public because I put it on GitHub if somebody wants to see it. But I'm not putting out commercial software. And yet I still do that because I don't want to accidentally publish API key or the passwords to my house or whatever. So I always do that. I always do that. And I think that that's going to be a standard operating procedure if it's not already with every bit of software. The question that I was asking Steve, is software perfectable? And he says yes, it's deterministic, it's math. So ultimately it is possible to have perfect software.

Leo Laporte [00:28:43]:
Humans are not good at that. We, we now know humans cannot do it.

Jeff Jarvis [00:28:48]:
I'm still going to question that premise again because I'm gonna say one more time, you cannot anticipate every malign use that someone will come up with to get around something.

Paris Martineau [00:29:01]:
Well, this is kind of what the CSA paper seems to touch on is that there's basically going to be this. It says that there should be the development of like Volnops, like a permanent organizational capacity modeled on DevOps that is all about constantly trying to get ahead of this all the time. And that's a huge resource investment and just change in the way that a lot of companies are going to have to operate. And I don't think it might end

Leo Laporte [00:29:30]:
up being very expensive, but we need it because.

Paris Martineau [00:29:32]:
But I mean, is that feasible for anything Anyone outside of the top 50 or 100.

Jeff Jarvis [00:29:36]:
Does this just make the hegemony of the big guys.

Paris Martineau [00:29:38]:
Yeah.

Jeff Jarvis [00:29:39]:
More entrenched? I think Paris's point is really, really right. It's just an impact. It's not everybody's fault, but it's something.

Leo Laporte [00:29:49]:
The trend is, by the way, that these models are getting smarter and smarter at a very rapid clip, that they're getting cheaper and cheaper to run at a very rapid clip. Or the software that you run today at a certain cost will be cheaper in a year. The frontier models will always get more expensive, but the software you run today will get cheaper.

Jeff Jarvis [00:30:07]:
Not necessarily. We'll talk about that a little later.

Leo Laporte [00:30:11]:
Well, I mean, we even mentioned this. Jensen Huang has said that one of his chief goals is making these GPUs more efficient, right?

Paris Martineau [00:30:21]:
Yeah, of course. That's one of his chief goals. Practical or realistic in the next five years.

Jeff Jarvis [00:30:28]:
It's his new Moore's Law.

Leo Laporte [00:30:30]:
Absolutely, it is. You know why it is? Because we have to.

Jeff Jarvis [00:30:34]:
Because his point is that you can't increase the size of the data center that's already built. You can't put more chips in it. The only way you're going to increase the investment is by him increasing the efficiency of it. And that's why they're coming to him to do that.

Leo Laporte [00:30:49]:
Anthropic says that their most dangerous AI model, AKA Mythos, has fallen into the wrong hands. A Discord group has had access to Mythos for two weeks. This actually comes from Bloomberg.

Paris Martineau [00:31:06]:
And if a Discord group. No offense to our Discord group, but if a Discord group was able to get access to Mythos, who else has access to Mythos?

Leo Laporte [00:31:16]:
They got it through contractors.

Paris Martineau [00:31:19]:
Yeah, I know. You know who else has access to be able to do this sort of.

Leo Laporte [00:31:23]:
Well, and that's why this. I think that's why this hair on fire report from the CSA and why so many CISOs250 signed on to it, is it's gonna get out there.

Jeff Jarvis [00:31:33]:
Well, they also did it because. Because Anthropic was. Or whoever. I'm sorry, not Anthropic, but the client was sloppy because they went through the basic email structure or URL structure the

Leo Laporte [00:31:43]:
way they gave this. Right.

Jeff Jarvis [00:31:45]:
Yeah.

Leo Laporte [00:31:45]:
The unauthorized access highlights the challenges. This is from Bloomberg. Anthropic faces in fully preventing its most powerful and potentially dangerous technology from spreading. It's kind of like nuclear proliferation, isn't it?

Jeff Jarvis [00:31:58]:
Well, it's also. Mythos couldn't protect Mythos.

Leo Laporte [00:32:03]:
Okay, well, yeah, I don't know what that means. But, well, if it's.

Jeff Jarvis [00:32:08]:
Mythos isn't all powerful security aware thing and it's going to be perfect software and there's going to be no vulnerabilities.

Paris Martineau [00:32:14]:
Well, that's actually a great point. If Mythos is so good, why couldn't it protect its own?

Leo Laporte [00:32:20]:
Because Mythos is not being. It's. It's. It wasn't Mythos that was exploited. It wasn't Mythos that was exploited. So Mythos isn't like magically protecting everybody.

Paris Martineau [00:32:32]:
What I'm saying, if Mythos is so good, then how could Mythos get.

Leo Laporte [00:32:37]:
Because it isn't everywhere, but it is being used. I don't think you understand how these things are.

Paris Martineau [00:32:43]:
Mythos being deployed. Anthropic has used this.

Leo Laporte [00:32:48]:
Yeah, I don't, but it's a. It's a nonsensical question.

Jeff Jarvis [00:32:53]:
Who do you think you are, Jensen Huang with Patel?

Leo Laporte [00:32:55]:
Well, it's just. But you're asking a nonsense question. Mythos isn't sitting there protecting everybody and everything going well. Don't touch me. They.

Paris Martineau [00:33:03]:
I'm not saying that Mythos is there ready to karate chop anything, but Mythos has been deployed on the. On. All of.

Leo Laporte [00:33:12]:
Anthropic's current person had permission to access Anthropic models. Okay. They gained access from a company from which they perform contract work. Bloomberg's not naming the company for security reasons. I'm not sure how Mythos was supposed to prevent this.

Paris Martineau [00:33:32]:
Poor Mythos. We shouldn't.

Leo Laporte [00:33:34]:
You're personifying it. It's not. Okay, I'm gonna move on.

Jeff Jarvis [00:33:38]:
See, I thought when you had Lucas on.

Paris Martineau [00:33:43]:
Do we want to somebody sic their own version of Mythos to figure out exactly how many minutes and seconds it was since Leo said he's not going to tell Jeff and I that we're.

Leo Laporte [00:33:52]:
Well, I don't expect you to say so many stupid things. I'm sorry. I've tried.

Jeff Jarvis [00:33:56]:
Well, Jensen, I'm trying.

Leo Laporte [00:33:58]:
If you would just not ask dumb questions, I wouldn't have to.

Jeff Jarvis [00:34:01]:
We dare. We dare to criticize.

Leo Laporte [00:34:03]:
No, it's not a dumb question. It's just that Mythos. You're assuming that somehow Mythos is permeating everything that everybody's doing and is protecting itself from everybody. But if somebody has access to Mythos and then gives that access to somebody else, there's no Mythos in the middle. It's not sitting there going, that's not. No, no, no problem.

Paris Martineau [00:34:24]:
What happened is. That's the issue that they took. They exploited.

Leo Laporte [00:34:27]:
It wasn't a bug.

Paris Martineau [00:34:29]:
It. It Is that the.

Leo Laporte [00:34:31]:
It was a bad. It was. No, no, it wasn't a bug. It was bad policy. Mythos isn't there, staying doing.

Jeff Jarvis [00:34:37]:
You have a bad policy.

Leo Laporte [00:34:38]:
You can't do this. It's. It's. It's not. It wasn't available to. To fix that problem. And actually, that goes back to what Jeff was saying earlier, which is a legitimate point, which is there are things that can go Security, things that can go wrong that aren't bugs that an AI can't fix. If you, for instance, have.

Leo Laporte [00:35:00]:
This is why we always talk about zero trust. If you have a security policy that allows a former contractor access to your system, you're going to have a problem. And I mean, I guess you could have.

Jeff Jarvis [00:35:13]:
They could have asked Mythos. How should we put this out to our 10 contractors? Leo, I was hoping that when you had Lucas on, you wouldn't tell me what he was doing. I was hoping he was one of the guys who broke into Mythos.

Leo Laporte [00:35:25]:
I don't think those guys are going to talk to anybody.

Jeff Jarvis [00:35:27]:
No, they're not.

Leo Laporte [00:35:28]:
If I were them, I wouldn't.

Jeff Jarvis [00:35:32]:
They may be drafted into the army before you know it.

Leo Laporte [00:35:35]:
Yeah, I think it's funny because you're now ascribing to Mythos amazing capabilities beyond what Mythos can do.

Jeff Jarvis [00:35:42]:
Well, what if. What if. What if Anthropic literally had. How do we do this? Well, I don't know if.

Leo Laporte [00:35:48]:
I don't know if Mythos is.

Paris Martineau [00:35:50]:
One of the most impressive claims about. It is supposed to be that it helps anticipate a wide range of potential security risks. And this could have been one of the many things it anticipated, which is that you.

Leo Laporte [00:36:06]:
Well, I only.

Jeff Jarvis [00:36:08]:
Only with the code, not with the deployment thereof.

Leo Laporte [00:36:11]:
I guess it failed. I. I don't know. I. Maybe Anthropic hasn't run Mythos on all of its policies. I'm not sure exactly what's going on there, Darren.

Jeff Jarvis [00:36:22]:
Okay. Says rightly it's about the attack surface, which varies.

Leo Laporte [00:36:27]:
Yeah. I mean, it. It isn't a magical being that can prevent all attacks. I'm just saying it can fix bugs, software. I don't. I don't know about the rest of it. Yeah, It's. It's just.

Leo Laporte [00:36:44]:
It's a very good model and it happens to have cyber security abilities, interestingly enough, that it wasn't specifically trained in. Let us take another break. We're gonna. We're about 15 minutes away from our guest, Ian Bagost. So. Bagost. So I will practice his name.

Jeff Jarvis [00:37:06]:
Did you get a Pronunciation guide.

Leo Laporte [00:37:08]:
Claude told me it was bog ghost. Bog host.

Paris Martineau [00:37:13]:
Claude could never be wrong about anything like pronunciation. It's clearly so fun at.

Leo Laporte [00:37:18]:
We'll find out. I know it's surprising. You wouldn't expect it to be good at pronunciation, but it is apparently foghost,

Paris Martineau [00:37:24]:
according to someone who has not checked and has not been confronted with the reality of the situation.

Ian Bogost [00:37:32]:
Yes.

Leo Laporte [00:37:34]:
Somebody's saying it's like if you left your password on a sticky note on the monitor, mythos can't help you. It's, I guess, the point. It can. It. It. It has a domain that it works in, but it's not omnipotent.

Jeff Jarvis [00:37:50]:
I'm sorry, I just enjoyed the irony, that's all that.

Leo Laporte [00:37:54]:
Yeah, well, I mean, yes, Mythos is not going to. And actually this really was the point that you were making, which is that it isn't perfect every.

Jeff Jarvis [00:38:04]:
No.

Leo Laporte [00:38:05]:
Yeah. It's not going to fix all security. It's going to fix all. But potentially software bugs could be eliminated. But again, I wasn't sure about it

Jeff Jarvis [00:38:13]:
when I asked Steve. Unanticipated attack surfaces cannot be. Because they're unanticipated.

Leo Laporte [00:38:18]:
No, that just means a human didn't anticipate it. If it's in the software, presumably the AI could find it. But the AI is not going to have anything to do with a post it note on your screen with the password. It doesn't. Doesn't have that.

Paris Martineau [00:38:32]:
That is not what happened here.

Leo Laporte [00:38:34]:
It's. No, it's something very analogous to that, though.

Paris Martineau [00:38:37]:
I don't think that's accurate.

Leo Laporte [00:38:38]:
It's not through. It was not through a cve. Was not through a. I don't think

Paris Martineau [00:38:42]:
anyone's claiming that it was through a CVE.

Leo Laporte [00:38:44]:
Well, that's what Mythos fixes is CVEs. It was not through an exploit. It was through bad policy, like having a password on your monitor. Bad behavior. You see, I mean, there is a difference. It can fix bugs in software. I don't know. I'm not an expert in Mythos.

Leo Laporte [00:39:04]:
I wish someday maybe they'll release it. We could talk to somebody at Anthropic about what? Mythos.

Jeff Jarvis [00:39:09]:
Well, we're also questioning the idea that even that software can be perfect.

Leo Laporte [00:39:13]:
Yes. And I, you know, I don't claim expertise in that area. Steve, who I think is pretty sharp about this kind of stuff, believes it is perfectable. He ships, by the way he says software without bugs because he works very hard to make it bug free. He says, because it's math. The problem is humans are not very good at it. We don't do a great job with it.

Jeff Jarvis [00:39:38]:
This is Benito.

Benito Gonzalez [00:39:38]:
There's also the hardware part of it. Hardware cannot be perfected, so there's always that service.

Leo Laporte [00:39:44]:
That's true. Things like. And somebody mentioned this in the discord. Things like Rowhammer, which is an exploit which allows you to see what's going on in a parallel process on a processor, is a processor defect. And I don't. Now, Mythos probably could be applied to microcode, and I wouldn't be surprised if it could say, hey, you know what? You've got a problem here with leakage in your. In your prediction pipeline that I think Mythos probably could see, but you'd have to then know about it before you fabbed the chip. And once it's in the chip, Mythos can't fix it.

Benito Gonzalez [00:40:27]:
But it couldn't fix anything like radiation fixable in microcode. So you can't do anything about radiation or anything like that.

Leo Laporte [00:40:34]:
Yeah, okay. Yeah, yeah.

Benito Gonzalez [00:40:36]:
I'm just saying the hardware. I'm just saying the hardware. It's like there's. The hardware can never. That can't be fixed.

Leo Laporte [00:40:40]:
Yeah, okay. It is. Is not a superman, not a superhero. And I don't think Anthropic is claiming it to be omnipotent security. No, I didn't say that.

Benito Gonzalez [00:40:49]:
I didn't say they were. I was just saying that they were

Paris Martineau [00:40:50]:
all anyone is claiming that Mythos is an omnipotent superhuman. That is perfect, Leo.

Leo Laporte [00:40:57]:
Okay. Right. We will take a break and then we will talk about.

Jeff Jarvis [00:41:04]:
For Leo's blood pressure.

Leo Laporte [00:41:06]:
No, I'm fine. We will talk about the crunch that is apparently happening with a lot of companies. Your buddy Ed actually has a scoop on one of these. We will talk about that in just a bit. You're watching intelligent machines as we try to figure out what is going on in the world of AI it's not obvious. All right, we're back. And guess who. Look who's showed up.

Leo Laporte [00:41:32]:
Our special guest, Ian. Bo Ghost is here. Gosh darn it. Bo Ghost is here. Did I get that right?

Ian Bogost [00:41:42]:
You got it right this time.

Leo Laporte [00:41:43]:
Good to see you.

Ian Bogost [00:41:43]:
Oh, good to be here.

Leo Laporte [00:41:45]:
I will say something. Ian, you know this guy Jeff. Somebody told me. You know Jeff.

Jeff Jarvis [00:41:50]:
I want. Well, I have much to thank Ian for. Ian. I wrote a blurb for one of the object lessons books in the series that Ian co edits. And taking every opportunity, I said, hey, you want a book for me? And so I ended up writing magazine Magazine, which I had great fun Writing.

Ian Bogost [00:42:08]:
Do you have it there? It is always be selling.

Leo Laporte [00:42:11]:
Yeah.

Jeff Jarvis [00:42:12]:
And. And then I also said I got this book about Gutenberg. You think Bloomberg's probably might want it. And he introduced me to Harris Knockfi, who's our mutual editor and publisher. And that's led to that and my next book, Hot Type and the book series Intelligence. So I have much, much to thank Ian for.

Ian Bogost [00:42:28]:
A lot's going on. Yeah.

Leo Laporte [00:42:31]:
Introducing you is a challenge because you do so much. I was talking to Jeff before the show saying, I don't understand how Ian is so accomplished.

Jeff Jarvis [00:42:38]:
He said he hates you because you can do so much.

Leo Laporte [00:42:41]:
You make me feel like a loser.

Ian Bogost [00:42:44]:
People ask me what I do and my heart just falls out of my body.

Paris Martineau [00:42:48]:
You're like, do you have seven and a half minutes?

Leo Laporte [00:42:50]:
He's contributing writer at the Atlantic and that's where I know you from. I read your stuff. I love it. It's fantastic.

Ian Bogost [00:42:56]:
Thank you so much.

Leo Laporte [00:42:57]:
Is also a game designer. In fact, you might know the game. He did a few about 15, 16 years ago called Cow Clicker.

Ian Bogost [00:43:06]:
Cow Clicker. That's right.

Leo Laporte [00:43:07]:
On Facebook, which was a parody. It satirized the exploitation of Facebook and its games. But it became so big

Ian Bogost [00:43:19]:
that you

Leo Laporte [00:43:20]:
actually had to have a rapture.

Ian Bogost [00:43:22]:
Yeah, I had to get rid of all the cows.

Paris Martineau [00:43:25]:
How many cows did you murder?

Ian Bogost [00:43:27]:
That's the question. A lot of cows. I have never counted the number of cows. I wouldn't think of me as murdering them. They were mysterious.

Paris Martineau [00:43:34]:
You delivered them to cow heaven.

Ian Bogost [00:43:35]:
That's right.

Leo Laporte [00:43:36]:
Well, they got raptured. I think they got raptured from the point of view of the cow. A good thing.

Paris Martineau [00:43:41]:
Well, we don't know what sort of sins those cows committed.

Ian Bogost [00:43:43]:
The cows were innocent.

Leo Laporte [00:43:45]:
They were 100% raptured. Not one cow was left behind. So he's also a professor in kind of multidisciplinary professor at Washington University in St. Louis. The Barbara and David Thomas Distinguished Professor, Co executive director of the Office of Public Scholarship, Provost Fellow in Interdisciplinary Initiatives.

Ian Bogost [00:44:06]:
This is too much, isn't it?

Leo Laporte [00:44:07]:
I know it's too much for one person. His portfolio focuses on AI plus design. He's also assistant vice president. Provost. Because, you know, you had a little free time, I guess. Founding partner at an indie game studio called Pervasive Games, which has consulted for 2K games, Activision, Disney, Nintendo, Sony, the Tetris company.

Jeff Jarvis [00:44:29]:
And how many books has he had written?

Leo Laporte [00:44:30]:
Eleven, according to Claude. Claude could be lying.

Ian Bogost [00:44:33]:
This is my 11th.

Leo Laporte [00:44:35]:
11th book.

Ian Bogost [00:44:36]:
It's an odd number. I need to write a 12th.

Jeff Jarvis [00:44:39]:
I want to talk to you about that later.

Leo Laporte [00:44:40]:
And that's a very bad number.

Paris Martineau [00:44:42]:
Well, no, you've got a baker's dozen. That's a perfect number.

Leo Laporte [00:44:44]:
Well, the good news is I only wrote, like, couple. The rest were ghosts.

Ian Bogost [00:44:47]:
The rest, Claude wrote they were bogos.

Paris Martineau [00:44:51]:
Yeah.

Leo Laporte [00:44:52]:
Actually, the thing that really interests me most about Ian particularly is your notion that. And I'm going to misstate this so you can kind of restate it, but friction is important to our humanity.

Ian Bogost [00:45:08]:
Yeah, I've been. You know what? This. This book, this new book, the small stuff, is about gratification. And like, at this. At the same time as I was working on the book, this idea of friction got really popular. You hear this a lot now, that we need to reintroduce friction. There was just a New Yorker story about this just a couple days ago.

Paris Martineau [00:45:29]:
It was good.

Ian Bogost [00:45:30]:
It was a good story. Right. And I think what I'm saying is related, but different because. So to me, this. This idea of gratification is all about the sensory enchantment of everyday life. It's about your. Your constant sensory encounters with the world and how you can derive, you know, small amounts of little pleasures from them all the time. And that's a little different, isn't it, from friction? It's not about making it harder in some ways, it's about making it easier.

Ian Bogost [00:45:56]:
So that's. That's an interesting idea that I've been. I've been thinking about since we, you know, since. Since we started promoting the book and since I've started thinking about it in the context of today. Have conversations about technology today, where this idea of friction has suddenly become quite popular.

Leo Laporte [00:46:13]:
Well, it's also germane to the topic of AI because one of the things AI seems to do is smooth all the edges. Right. And AI pros in particular is.

Ian Bogost [00:46:22]:
Oh, yeah, I think that's true. But I've also been thinking about the ways that AI pushes me. least I don't know that it does this generally. I'm starting to see evidence that AI is pushing people back into the world rather than removing them from it.

Paris Martineau [00:46:41]:
And what sense?

Ian Bogost [00:46:42]:
Well, here's an example that just happened to me this week. So it's the springtime, thank gosh. I mean, golly, it's like, been so cold all winter and finally spring, and I need to water my lawn because it's spring again, and I live in a place where it freezes, so you have to turn on the irrigation system, and there's like a leak in my Backflow, my irrigation backflow, which is something we don't need to talk about today, but it's the thing that you have to have in your irrigation system. And so I talked to AI and I'm like, help me, help me figure out how to fix this. Right. So in that sense, I'm not generating text. AI is pushing me back out into the world where I'm taking on these really material tasks that I might not have done otherwise. So I think it's complicated.

Ian Bogost [00:47:28]:
I think the smoothing over is happening for sure. But there's also this, like, these kind of rough edges that AI is revealing, including for me, really, like inviting me to engage with the physical world in ways that I might not have chosen to previously.

Jeff Jarvis [00:47:46]:
Is there a linkage to the fact that you edit the book series called Object Lessons?

Ian Bogost [00:47:50]:
Well, certainly, when we. So Object Lessons, which is delightful book series, we've done about 100 books with Bloomsbury and they're all about the secret life of ordinary things is the tagline. We've done so many books. Taco and Phone Booth and Jeff did magazine and. And so I've been interested in things for a very long time. Ordinary things, toasters and stuff. You know, that's just an obsession of mine for forever. And people sometimes sneer at you when you think when they find out that you're interested in toasters, they're like, why? Like, that's not important.

Ian Bogost [00:48:23]:
And one of the things that Object Lessons was meant to do was to say, yes, it is. It is important to tell those stories. And then we tried to make the books themselves. Jeff held one up at the start, like really delightful, delightful objects. They've got French flaps and, you know, we do pantone printing on them and they're the covers.

Jeff Jarvis [00:48:44]:
Wonderful.

Ian Bogost [00:48:45]:
So I do think it's related to, you know, that this is a project. This is a long standing project for me that really touches a lot of things that I've done over the years, even if I didn't realize at the time how they were contributing to this, this kind of discovery of gratification as a topic of interest.

Jeff Jarvis [00:49:02]:
It's a very academic thing to do, to abstract those common things in life and ask what else is there about this? And to learn lessons from that. And I haven't read your book yet, but I'm suspecting that there's a through line to that.

Ian Bogost [00:49:21]:
There is the through line. I mean, for me personally, you asked what's the story with all these things that you've done? And as a game designer, I was always thinking about the games are absurd. Games are ridiculous, and there's no purpose to them. There's no reason to play Candy Crush or even Scrabble. But we do it and we enjoy it.

Leo Laporte [00:49:47]:
And that's unless Paris is playing against me, and then I don't enjoy it at all.

Jeff Jarvis [00:49:52]:
She smashes him.

Ian Bogost [00:49:53]:
You could even enjoy being, you know, like. Like whooped, right? Defeated at a. At a game. There's something about it that, like, that's part of the deal is. Is the pain of play. And so I. One of the things that. It was always eating at me when I was writing about games, making games, studying games, teaching about games, I was like, why? Why is this miserable, weird, useless, purposeless thing so compelling? And one reason I think it's compelling is because games invite us to engage with something that doesn't matter, that doesn't need to exist, that almost shouldn't.

Ian Bogost [00:50:26]:
That's pure excess. And if you. If you look at the world, it's full of all that kind of stuff, too, that, you know, like, I can. I can feel the. The smoothness. I have this walnut desk in front of me, and I can feel the smoothness of the wood under my hands. And sometimes I just. I just do that.

Ian Bogost [00:50:45]:
And that's gratification. That's. That's delight, that sensory delight. It doesn't do anything for me. But if I. If I didn't do that, if I didn't accept the gift of that sensory encounter, would my life be better? No, it wouldn't. I would be missing out on that little moment that's free. And so it may not seem that that has anything to do with games, but I really did come to some of those observations through, you know, my experience with games and then later, you know, with.

Ian Bogost [00:51:11]:
With the philosophy of objects in the way that Jeff kind of hinted at.

Jeff Jarvis [00:51:15]:
So AI De. Objectifies things. Everything is an abstraction in AI.

Ian Bogost [00:51:20]:
AI is complicated. I think what AI is doing is. Is giving us a very easy to use window. Into answers are simulated answers to lots of questions, which means that we ask a lot more questions, and that's qualitatively different than Google. I think partly because it's quantitatively different. It happens faster, but that makes it qualitatively different. Like the story I told about the irrigation fix. Why wouldn't I have done that just by going to YouTube or Reddit? And the answer is pretty clear, isn't it? It's because I wouldn't have been able to find the answer on YouTube.

Ian Bogost [00:51:57]:
I would have stumbled into some. Some channel that Had a bunch of ads and pre roll, and I would have had to find the part of the video where it was correct, or I would have had to wade through all the arguments on Reddit about someone had already asked and answered this question eight years ago. And the AI just tells you, it's like, oh, I can take a picture of this apparatus. And it's like, okay, here's what you do. And it's not always right. And I know that people worry about that, and I worry about it too, but it's often right. And in my case, in this example, it was right. And it helped me not just fix something in my life, but engage physically with a part of the world, a part of my home that I had never touched, not really.

Ian Bogost [00:52:39]:
And that is. I think that's kind of magical. And it's a different story than the one that I've heard told about AI

Leo Laporte [00:52:46]:
you famously said you were glad that AI ingested your books.

Ian Bogost [00:52:52]:
I did, yeah. Yeah. Someone noticed this, I guess I was wondering if anyone had noticed that I wrote that.

Leo Laporte [00:52:56]:
I agree with it. In fact, I've said the same thing.

Paris Martineau [00:52:59]:
What was your argument for it?

Ian Bogost [00:53:01]:
When you make something as a creator, it is no longer yours. It lives in the world. Isn't that what all of us want? You write a book, or you make a piece of art and you want it to travel. It's no longer connected to my intention and what I might do with it. And anyone can consume it and they can misinterpret it, or they can reinterpret it, or they can throw it away, or they can crumple it up, or whatever it is that they do with it. That is. That is what it means to be a creative person and to disseminate work in the world. And I'm disturbed in a way by this, this.

Ian Bogost [00:53:33]:
This idea that we ever had control of our work. And yes, I realized that AI I mean, it was like stealing the books, like the digital files for the books. That's like a slightly different topic than a computer reading them. Who would have ever thought when I wrote, you know, these books 20 years ago, that someday a computer would read and understand them and make new sense of them? Oh, my God. That isn't. That is certainly something that I don't want to. I don't want to squelch. I don't want to say, well, you know, that's not what I meant when I wrote the book.

Ian Bogost [00:54:05]:
Because we don't get to mean how our work is interpreted.

Leo Laporte [00:54:09]:
It's another form of dissemination. It's another way to give your. What you're giving, what gives it.

Jeff Jarvis [00:54:14]:
Readers are the ones who give books meaning. And it's another way to give meaning.

Ian Bogost [00:54:19]:
And the funny thing about this is this idea of dissemination, this idea that when you make something, it enters the world and is no longer yours. This is like, you know, 50, 60 years old in literary criticism and philosophy. This is not a new concept, but somehow we kind of forgot about it. I think the Internet made people. It made people feel as though they had more control and they deserved more control than they ever did before. And now it suddenly seemed like you could talk to celebrities or you could repost when someone misinterpreted you or you perceived that they did. And every article I write now, I have to deal with people responding to it online and thinking that I should engage in conversation with them about it. It kind of changed our worldview about how work enters the world.

Leo Laporte [00:55:07]:
In 2022, you wrote a book, a great piece called. Which I remember vividly, ChatGPT is dumber than you think. And basically you said, it's a toy.

Lucas [00:55:17]:
Yeah.

Leo Laporte [00:55:18]:
Not a tool, but a toy.

Ian Bogost [00:55:19]:
Yeah.

Leo Laporte [00:55:20]:
Now here we are four years later, things have changed a little bit.

Ian Bogost [00:55:24]:
Yeah. I mean, it was always going to become a tool because that's the. The thing that we make when we make computer systems. But it's also a toy. And. And what I mean by that toy is like, it's something you just do for its own sake, you know, like, you manipulate it and you mess around with it. It's an entertainment vehicle, too. Like, sometimes I'll just have ChatGPT, like, you know, write me heart Crane poems about Diet Coke or whatever.

Ian Bogost [00:55:49]:
Like, what's the point of that? It's not in order that I can have the Hard Crane poem. It's in order that I can kind of explore two things that I love, that poet and Diet Coke, in a different way. And I think that that persists as a use of AI, that usage still persists. And sometimes I'll just kind of hang out with one of these machines and spend a little time with it, not personifying it, but just exploring it in the same way that would click through Wikipedia articles or in the same way that I would hold. I have a Rubik's Cube over here. When you play with this thing, sometimes it's just about holding it in your hand. Hands and kind of feeling what it's like. For the.

Leo Laporte [00:56:31]:
For me, it is because I can solve it.

Jeff Jarvis [00:56:33]:
Oh, I can't.

Ian Bogost [00:56:34]:
I can't solve it either.

Leo Laporte [00:56:37]:
That's an interesting point. It's a game that you can't solve, but it's still pleasant.

Ian Bogost [00:56:43]:
Right. And some of the things that we love about, about games and toys and objects is, is not that they're useful, but that they can be manipulated. I don't mean manipulated like, like used in, in indiscriminate ways. I mean, like just, just physically touched.

Leo Laporte [00:56:57]:
That's the game is playing. That's what play is.

Ian Bogost [00:57:00]:
That's right, yeah.

Jeff Jarvis [00:57:02]:
Ian, I'm eager to hear your thoughts on AI and education. Not the obvious, not the, the everybody has blue books.

Lucas [00:57:09]:
Right.

Jeff Jarvis [00:57:10]:
But the, but calling on what you said earlier about the machine reading your books, you now have a machine that not only speaks our language, but it supposedly learns.

Ian Bogost [00:57:18]:
Right.

Jeff Jarvis [00:57:19]:
And does this, does this, does this affect. At a high level, does it, does this affect your view, your perspective on learning generally? And then because of everything you do in education? I'm curious about your view of education in the class, AI in the classroom.

Leo Laporte [00:57:34]:
Yeah. You're on the front lines.

Ian Bogost [00:57:36]:
I am. And I've written about this extensively. And you know, I've tried my best in my writing on AI and education. And I focused on higher education because that's where I live. I've tried to, to give everyone voice, you know, the students, the faculty, the administrators, the AI companies even. And I feel like it's complicated. These things are here and we can't deny that. And what is it, what does it mean in terms of learning? I do think that this, this ability, like think, think about the irrigation story.

Ian Bogost [00:58:08]:
Like this ability that I have to try something out, like relatively easily, fairly consequence free. This is related to a concept in the learning sciences of which I'm not an expert, but I do know, and I've loved this concept for many years called performance before competence. Have you ever heard of this? The idea is it's generally good for learning if you get kind of thrown into the deep end. You don't quite know what you're doing. And instead of ratcheting up from the basics, at least all the time, by pretending that you're an expert, really kind of jumping in with both feet, you can learn in a different way. Some kinds of learning you want, like skill and drill basics. Sometimes you want to learn fundamentals and build up. You need to learn color theory or something before you can paint.

Ian Bogost [00:58:59]:
And then in other cases, especially complex situations, performance is performance before competence really works. So you get a new job and you don't really know what you're doing, and you kind of figure it out by being in the environment of work and talking to people. People. And then you work it out relatively quickly, partly because you have to and partly because you're fully embodied in that situation. And AI seems like particularly potentially good at this. I don't know that it's actually good at this. It's very, very, very good at it for computer programming, which is something that interests me. I don't know if it's so great for writing argumentative essays, but I think it has a lot of potential.

Ian Bogost [00:59:38]:
And I also think it rubs against the standard practices we've used in classrooms for a long time, which are not like that. We don't really trust the students to learn in that way. And we haven't set up the learning environment for them to learn in that way most of the time. That said, I worry about. It's so easy. It's so easy and so tempting when you have a problem solving machine like this, just to have it solve problems. And what I see among the students, they are pulled in so many directions. They're full of anxiety.

Ian Bogost [01:00:17]:
They are facing a difficult and a difficult job market that seems to be becoming ever more difficult. They have spent their whole lives worrying about performance and trying to get to the next thing in order that they can then get to the next thing. And they don't even know why they're doing things sometimes. And so they're like wired to just accomplish. And they don't even know why they're accomplishing things sometimes. And so you put AI in front of them and what do you expect to happen? It's like, well, the moment I need a release valve, there it is. And it will give you the answer. I teach this class.

Ian Bogost [01:00:52]:
We just had the last meeting just this afternoon. I teach this class on Atari 2600 programming where we make Atari games.

Leo Laporte [01:00:59]:
I love it.

Ian Bogost [01:01:00]:
Yeah.

Leo Laporte [01:01:01]:
Oh, the Mosfet two years ago when I teach.

Ian Bogost [01:01:06]:
Oh yeah, Sprites and you know, I mean, it's. It's a really challenging machine to program. You have to write it all in 6502 assembly. And it doesn't have any video ram. And it's a. It's very, very weird. And I love it. I love the thing.

Ian Bogost [01:01:18]:
I've been teaching and writing about it and making games for it for a long time.

Leo Laporte [01:01:21]:
Oh, man, I wish I had. Class is like that.

Ian Bogost [01:01:23]:
Yeah. No, it's. I mean, I can't believe I get to do this. So a couple years ago, you know, when AI started, I was like, look, guys, like, you can't use AI to Program the Atari. Like, trust me, it just, it's just gonna. And now you kind of can. You kind of can.

Leo Laporte [01:01:36]:
Okay, really?

Ian Bogost [01:01:37]:
You kind of can.

Leo Laporte [01:01:37]:
There's enough 6502 code out there.

Ian Bogost [01:01:40]:
It under, it understands it well enough now. It doesn't mean that the students understand what they're doing. And if they want to go in and modify, it's a very tightly, you know, wounded up system. And the time.

Leo Laporte [01:01:49]:
You only have 16k, you've got. Yeah, it's very limited.

Ian Bogost [01:01:52]:
We have 4k, we got 4k ROMs, 128 bytes of RAM. And anyway, so I have some students, you know, this, even this term and you know, they would submit code and I'd be like, I know that they wrote this with AI. It's totally different than the code that I was showing them. And when I talk to them about it, you know, they're trying to solve the problem of their lives. They're like, well, look, I've got a million other things going on. I was trying to get a handle on how to do this. I thought I'd ask it and it was giving me the answers. They're not cheating.

Ian Bogost [01:02:20]:
I mean, they are cheating, but that's not the way that they perceive it and it's not the way that I perceive it either. It's rather that the whole world has been wound so tight in this watch spring like way that what are you going to do? And I think that is the thing I think about most with education. Where do you learn these when you have to learn fundamentals? How do we guarantee that it happens when it's so easy to shortcut or short circuit the process?

Leo Laporte [01:02:54]:
I love your idea of games being the analogy you used of a playground, which is a series of rules that a kid can go into and because of the rules can be free.

Ian Bogost [01:03:08]:
And yeah, this is the weirdest thing about, about games and play. There's this paradox that the way that play becomes more interesting is becoming. By becoming more constricted rather than less so. So you think, you know, play sounds like, do anything you want. It's freedom. Go out and play. But that's, that's not right.

Leo Laporte [01:03:29]:
It's not fun.

Ian Bogost [01:03:30]:
Yeah, what you need. And if you watch children who are better at everything than adults are, if you watch children negotiate play, they do this instantly. You know, they're like, okay, here's what we're going to do. You can't go. You can only watch steps in this direction. Right. You can't go past the line of the door. If you sneeze, you're out, whatever it is.

Ian Bogost [01:03:49]:
They're always, you know, assigning these new constraints on the system. And broadly speaking, in your life, if you're missing meaning or if, you know, if something feels like it's just no good anymore and you want to get out, you're always just like, oh, if I could just escape from this, then I would finally be free and happy again. It's usually the opposite. It's that you need some, some set of constraints to, to work, to work under.

Leo Laporte [01:04:13]:
Maybe that's what this book is all about, is recovering that sense, that childlike sense. It's very Zen.

Ian Bogost [01:04:20]:
There is a, there is a. Yeah, there is a child. I mean, there is, there's some lessons from, from children in it. Yeah. I think that kids are curious. Okay. Children have not encountered things before.

Leo Laporte [01:04:34]:
Right.

Ian Bogost [01:04:34]:
Like the reason a baby will put stuff into its mouth is because it wants to sense it. And that's. There's like so much sensation in your mouth. And you know, if you think about what makes like a three year old really irritating, it's that they're always asking questions and it's because they don't know anything. They don't know what anything is. And like, what is this thing? There's a telephone pole here. What's that about? What's a telephone pole pole? And if you think about that curiosity and that openness, we lose it over time or our lives get busy, but also we have to tune out the noise or we'll go crazy. And part of what I'm interested in this book is letting back in the stuff that we shut out.

Leo Laporte [01:05:19]:
I guess that's what Object Lessons was about too. I just love the idea of 111 books about, not just magazines, remote controls, golf balls.

Ian Bogost [01:05:27]:
Yeah.

Leo Laporte [01:05:28]:
Drones, driver's licenses, driver's license.

Paris Martineau [01:05:31]:
Is there any one that really surprised you?

Ian Bogost [01:05:34]:
Oh, so many of them have surprised us. You know, when we silence the one that's on the screen right there by just an amazing writer friend, John Bigonet. People were like, you can't do an Object Lessons book on silence. Silence isn't an object. And I was like, well, yeah, who says? Like all I mean by object is like an entity in the world, you know, I just mean like a noun.

Jeff Jarvis [01:05:57]:
A noun, yeah.

Ian Bogost [01:05:58]:
And you know, it's funny the way that that rubs people the wrong way. So that was one that was surprising. That was. And we've learned a lot about books, you know, like the, like it turns out that golfers spend a lot of money on, on Golfing, but not a lot of money on books. Whereas baseball. Baseball, they'll spend money on. On books. So that was interesting.

Ian Bogost [01:06:15]:
Didn't really have anything to do with the object text, but that was something.

Jeff Jarvis [01:06:18]:
It's so much fun to. I mean, just having written one of them and I've got five more. I want to.

Leo Laporte [01:06:23]:
I want to buy all 111.

Jeff Jarvis [01:06:24]:
It's so much fun to write too, because you look at something differently. It's.

Leo Laporte [01:06:28]:
Yes, it's focusing very skull. Yeah.

Ian Bogost [01:06:31]:
There is this, this concept in philosophy, the TST question. It's from Greek. It means what is it? Tst. What is it? What is its nature? And it's the. It's the first question that you ask when you're thinking about existence or something existing. And you can kind of live your whole life in that question about anything. You could spend the whole rest of your life asking, what is a phone booth actually? And you would be happy with that life, I think, because there's so much to learn and to observe about everything in the world. And this attitude of mine, I mean, it's really been one that I've cultivated.

Ian Bogost [01:07:07]:
I just want to share it. I feel. I feel so compelled to share it because I. I am not perfect and I haven't figured it all out, but I feel like this attitude has been so helpful to me and it's so different from the attitude of big stuff, happiness thinking, which is like, I have to accomplish more. My life needs. I have to have more wealth, my relationships have to be this way instead of that way. Whereas I'm going to just allow the crunch of the twig under my foot or the sensation of the hot mug in my hands. Just.

Ian Bogost [01:07:36]:
I'm going to accept that, that I'm going to let that happen to me right now and accept it, and then I'm going to move on to the next thing. That's such a different way of thinking about contentment.

Leo Laporte [01:07:46]:
The whole world in a drop of water. It's kind of Taoist, actually, come to think of it.

Ian Bogost [01:07:52]:
There is a kind of Eastern perspective that's represented here and in a couple of my books. Now I've kind of taken the Western adoption of.

Paris Martineau [01:08:03]:
Of.

Ian Bogost [01:08:03]:
Of kind of Buddhist style, you know, Zen mindfulness to task. Because I think that mostly what it's done is giving people a. It's like I need to take a break from achieving so that I can

Leo Laporte [01:08:15]:
recharge, so I can achieve more.

Paris Martineau [01:08:17]:
Yeah.

Ian Bogost [01:08:18]:
And that's. That's not what the Buddhist meant at all. You know, that's all about letting go. And so in the, in the. In the Small Stuff book, you know, one of the things that I did this podcast at the Atlantic, we had Oliver Berkman on, and Oliver Berkman's in the Book too, this sort of story from the podcast. And he did this great book called 4000 Weeks, about how you're immortal and you actually have less time than you think. And we were talking about some of these themes.

Jeff Jarvis [01:08:45]:
Tell us about it. Yeah.

Ian Bogost [01:08:47]:
And he said on this show of ours, he was like, I find it getting back to the senses is one way that you can just kind of live your life in the moment. But I find it really hard to get in this mindset. He said something like that. And that really caught me dead in my tracks because I was like, well, what do you mean? Like, you don't have to have a mindset for experiencing your senses at all. I'm not talking about your mind. I'm talking about your body. I'm talking about your fingertips and your nose. And it's just amazing to me that in the west especially, we've tied ourselves in these knots where we feel like we can't.

Ian Bogost [01:09:21]:
We won't accept that we can just sense things, we can just feel and see and smell and be in the world, that somehow we have to practice that. That's kind of bananas, actually, isn't it? And if you let go of that idea and you just let it happen to you, then the whole. The whole universe unlocks and every moment is available to you as this kind of easy opportunity for. For this. This sensory enchantment, this thing I call gratification.

Jeff Jarvis [01:09:48]:
Do you have a related view on

Leo Laporte [01:09:51]:
the

Jeff Jarvis [01:09:53]:
move by some folks, Yann lacone and company, toward world models, trying to imagine AI to have that experience of the world like a toddler experiencing it and understand learning from it, or a cat.

Ian Bogost [01:10:07]:
Yeah. I mean, the thing that I think about the most in this topic is like, what is the difference between being embodied and not being embodied?

Benito Gonzalez [01:10:16]:
Okay.

Ian Bogost [01:10:17]:
And as I've become so interested in embodied experience and as AI has been on the rise and AI is fundamentally disembodied and like, let's set aside our matrix conspiracy theories, right? Like, you might say to me, well, bogus. Like, maybe we live in a simulation anyway, and you're not embodied, you're just. It's just a simulation of embodiment. But I feel like I'm embodied, and that's enough for me for now. You know, what's the difference between understanding something by having read everything on The Internet and being able to predict what word comes next and give me information about how to engage with that world and feeling it for real. And maybe that is helpful because we can, can't we have it both ways? You know, we could, we could do the world modeling thing and have a sim. I think it's like I have all this experience with simulations, right? And back in the day when I started working on simulations, I did a lot of stuff for like science and politics and education and corporate learning. And in the world of simulations, we always knew that they were representations.

Ian Bogost [01:11:23]:
And then somehow we stopped, we started thinking, no, they're not. They're just the world. The world and the representation of the world are indistinguishable, which is very odd to me. So even a world model in this advanced Yann Lecun kind of way is still a representation of the. Of the world. And if, if we can agree on that, then I'm totally on board. And what that gives us is that gives us this incredible distance between what the AI knows and can do and what we as human beings know and can do. And yeah, you can wire it up to a robot and you can do all that kind of stuff, but it will still be a differently embodied entity.

Ian Bogost [01:11:57]:
It won't be you or me. And the thing that we share as human beings in the world, which should give us comfort, I think.

Leo Laporte [01:12:05]:
Ian Bogost, his book is the small stuff. It'll be out in July. You can pre order it now from a variety of places if you go to the website. Are you doing the audiobook, Ian?

Ian Bogost [01:12:20]:
So this is under discussion. I want to do it because I have a chapter in the book about asmr.

Leo Laporte [01:12:29]:
Yeah, you sound. You could do a.

Jeff Jarvis [01:12:31]:
You have a great voice.

Ian Bogost [01:12:31]:
I have a good voice for it. Yeah, yeah, yeah, yeah. We've been, we've been debating this back and forth. Like currently the plan is that there is an audiobook and we have a professional. And. And I'm still like a little bit jealous, you know, I really kind of want. I want to speak the words, but I also would love it. I'd love to share that experience.

Ian Bogost [01:12:51]:
But like, there will be an audiobook, no matter. And you'll be.

Jeff Jarvis [01:12:53]:
I should know this and I don't. Did you record early. Your early books?

Ian Bogost [01:12:56]:
No, no, I didn't do it.

Jeff Jarvis [01:12:58]:
I have never recorded a book.

Ian Bogost [01:12:59]:
I have a previous life as I had a small publishing company many years ago. And so I've overseen audiobook production, but I've never recorded one. It's a lot of work. I know this torture.

Jeff Jarvis [01:13:10]:
It's an exquisite torture.

Ian Bogost [01:13:11]:
No, it's.

Jeff Jarvis [01:13:11]:
It's.

Ian Bogost [01:13:12]:
I know how I've been on the other side of the board in the studio with it.

Jeff Jarvis [01:13:16]:
Oh, you definitely should do it.

Ian Bogost [01:13:18]:
Well, I'm. I'm glad.

Jeff Jarvis [01:13:20]:
Let us convince you.

Ian Bogost [01:13:21]:
Yeah.

Leo Laporte [01:13:21]:
The small stuff, how to Lead a More Gratifying Life, read by Ian Magos, I think would be a best seller. I would listen to it all the time. You got disconnected from the physical world, but you can reclaim the sensory enchantment of everyday life. I guess there is a thread leading through a lot of your work.

Ian Bogost [01:13:42]:
There really is. People ask me all the time. They're like, how did you get from where you started to where you are? And it's like, well, one day at a time. I think the difference between me and some people is that this is going to sound haughty. I don't mean it to, like. I've really learned from the things I've been. I've had the opportunity to do, and I've changed my mind a lot. And so I am on this random walk through life, taking those lessons and trying to find new things to describe and tell people about.

Ian Bogost [01:14:15]:
And I'm just so grateful to have had that opportunity.

Leo Laporte [01:14:18]:
Yeah, we're great. And I hope you come back when

Ian Bogost [01:14:23]:
the book comes out. And I'll be back when the book comes out.

Leo Laporte [01:14:24]:
Good. We would love that. And meanwhile, everybody read Ian's writing in the Atlantic. Get his books. I want to get all of these object lessons books. These are so cool. It's such a great idea to honor these individuals.

Jeff Jarvis [01:14:41]:
They're a little addictive. 100 books on the shelf.

Ian Bogost [01:14:43]:
Yeah, they look good together on the shelf, too.

Leo Laporte [01:14:46]:
I might. There's even one about the bookshelf.

Ian Bogost [01:14:48]:
There is one about the bookshelf.

Leo Laporte [01:14:49]:
So it's kind of a meta. A meta experience.

Ian Bogost [01:14:55]:
And they all have their own take on things, by the way. It's not like, let me tell you everything about bread or the cigarette light.

Leo Laporte [01:15:00]:
Right?

Ian Bogost [01:15:01]:
Like, they're all very particular.

Leo Laporte [01:15:03]:
Right. Neat. What a great idea. Thank you for your time, Ian.

Jeff Jarvis [01:15:08]:
Thank you.

Leo Laporte [01:15:08]:
I feel very fortunate.

Jeff Jarvis [01:15:09]:
Thank you for everyone.

Leo Laporte [01:15:10]:
Thank you. And have a great day. All right, take care. We will have more with intelligent machines. But now, no more fighting. Just peace. Oh, no.

Jeff Jarvis [01:15:20]:
I'm gonna bring up y' all in the cone in a few minutes.

Paris Martineau [01:15:23]:
We'll always be fighting.

Leo Laporte [01:15:24]:
I was waiting for Ian to just destroy you on that, but okay.

Jeff Jarvis [01:15:28]:
Nope, nope.

Leo Laporte [01:15:28]:
Couldn't get him to do it. You tried. Thank you, Ian. You can hang up now. He's looking for the button. I can see him. I know there's a button here to get rid of.

Jeff Jarvis [01:15:37]:
Get out of here.

Leo Laporte [01:15:39]:
We'll have more intelligent machines in just a bit. With Paris and Jeff, I was boy, he's great. I why haven't you pushed to get him on before? Jeff, this is. You're muted.

Jeff Jarvis [01:15:51]:
I put him on the list sometimes

Leo Laporte [01:15:53]:
I think, I think, well, I'm glad

Jeff Jarvis [01:15:54]:
we finally got brilliant. He's amazing.

Leo Laporte [01:15:56]:
Yeah. Barbara and David Thomas, Distinguished professor at Washington University in St. Louis, contributing right here at the Atlantic.

Jeff Jarvis [01:16:02]:
As I said in our best voice

Paris Martineau [01:16:04]:
we've had in the podcast.

Jeff Jarvis [01:16:05]:
Isn't it?

Leo Laporte [01:16:07]:
It's very peaceful. Yeah. I think the ASMR version of his book would be fantastic.

Jeff Jarvis [01:16:12]:
Yeah.

Paris Martineau [01:16:14]:
So I mean, yeah, if he just wanted to record a version of him reading every single one of the object lesson books, people all around the world would be falling asleep to that. In a complimentary way.

Jeff Jarvis [01:16:25]:
In a complimentary, very good way. Yes. In an enjoyable way. With a smile on the face.

Paris Martineau [01:16:29]:
Yes.

Leo Laporte [01:16:30]:
So we have so, so much news. I don't know exactly what to do here. There's no way I knew that we wouldn't get through it all, but I really now we've only gotten through one segment, two interviews in one segment, I guess one of the stories and we can kind of take a bunch of data points and squeeze it down to the story which is I think COMPUTE has become really a precious resource. Has become.

Paris Martineau [01:17:00]:
It was always. We just weren't aware of it.

Jeff Jarvis [01:17:02]:
Yeah.

Paris Martineau [01:17:03]:
We weren't as con as it wasn't as top of mind. But it's always been a precious reason.

Jeff Jarvis [01:17:07]:
It was like VC money back in

Paris Martineau [01:17:09]:
the I would say it's we're now getting to a point where these companies are realizing they have to be more explicit with their efforts to ration it.

Jeff Jarvis [01:17:17]:
Yes.

Paris Martineau [01:17:18]:
As consumers are using more and more of it.

Leo Laporte [01:17:21]:
Well, that's why it wasn't constrained until now because consumers weren't using as much. But they've wrapped up very, very, very rapidly and data centers can't be built fast enough. Anthropic has now decided that they're no longer Ed Zittran had this scoop going to allow you to use Claude code not only from the free Claude, but from the $20 a month Pro subscription. You have to be a Max subscriber,

Paris Martineau [01:17:47]:
100 or 200 subscribers. That's not exactly they Anthropic. What happened was a lot of people on Reddit and Twitter over the weekend or maybe it was Monday noticed that Claude code was removed from the $20 a month pro plan on some of the pricing pages on the Claude website. And people started asking around, being like, well, I could still see it and use it on my Pro subscription. What's going on? Anthropic's head of growth, Amal of a SAR claimed that it was a quote, small test of 2% of new pro consumer signups. However, Ed, some other Claude users view that statement suspicion because they were wondering why support documents like that. But that has since been reversed all

Leo Laporte [01:18:41]:
the time because the immediate response from OpenAI was to say, oh, and guess what? You can use Codex in the free program. So have at it. I, you know, I think the theory is this was a come on, always was a. It was always subsidized, it was a come on to get people to try it. But ultimately they really want you to move not just to the MAX plans, because I think they still lose, and Ed's been saying this too, that they still lose money in the MAX plans. That I mean, they lose money on all the plans.

Jeff Jarvis [01:19:07]:
All the plans.

Leo Laporte [01:19:08]:
The MAX plans were designed to get your data in for training and that they really want you to start using their API tokens, where you pay as you go. And in fact, now they are saying to enterprises, that's the only way you can use us. You have to pay for tokens, pay as you go. Which I don't. It's not demonstrated that they lose money on that, by the way, I think.

Paris Martineau [01:19:32]:
No. Similarly, there's absolutely no evidence that they don't lose money on it. And all, you know, anecdotal understanding of how much these sort of things cost suggests otherwise. Like if, if Anthropic was making money on any of its subscriptions, I'd hope that it'd be shouting that from the rooftops, because it'd be an extraordinarily rare and unique thing that they'd be using to raise money on. Important context here is that during all of this, Amal Avsar, the head of growth, tweeted, when we launched MAX a year ago, it didn't include COD code, cowork didn't exist, and agents that run for hours weren't a thing.

Leo Laporte [01:20:11]:
Right.

Paris Martineau [01:20:11]:
MAX was designed for heavy chat usage. That's it. And I think this kind of goes up against what we're all talking about. Talking about the way that users are using Anthropic's monthly subscription products is there has really changed rapidly over the last couple of years as more and more companies and more and More people are becoming Claude code power users and using an immense amount of resources for $20 or 100 something dollars a month.

Jeff Jarvis [01:20:41]:
You also have to get to the point of rationalizing the business. It's. It reminds me of the early days of the web when VC money was used to create content cheaply and more importantly to market and get audiences inexpensively. And it was marketing dollars and in a sense usage is marketing it convinced people this is valuable they spread was an investment but at some point it's not rationalized on a P and L basis.

Leo Laporte [01:21:07]:
Microsoft doing something similar GitHub has stopped accepting new copilot individual subscriptions because they are having trouble meeting their service commitments and so no new subscriptions at all. They've also changed the. They've adjusted the usage limits as has Anthropic. I think this is a general problem

Jeff Jarvis [01:21:30]:
going on Turning away customers is not a great business strategy.

Leo Laporte [01:21:34]:
Well, yeah, I get it but worst strategy would be to take customers you cannot serve.

Jeff Jarvis [01:21:39]:
Yes.

Leo Laporte [01:21:40]:
And I think that that's what they're up against and that's why I say it's not a financial crunch, it's a capacity crunch and it's going to be an issue. It absolutely is going to be an issue. Although Michael Dell has something interesting to say about this. He says the demand for tokens is proof that we are not going to have an AI bubble that there is demand for this, that businesses have accepted that it is valuable and something they want. The demand for tokens is in excess of the supply by a lot. He said this was at the Semaphore World Economy Summit yesterday. It would be hard for there to be a bubble right now just because there's not enough supply at this price point.

Jeff Jarvis [01:22:23]:
We'll see when you get to Paris point. If you get to the real cost, will that continue to be true?

Leo Laporte [01:22:28]:
I would push back on that. I don't think we know what the real cost is.

Paris Martineau [01:22:31]:
So yeah, that's the underlying.

Leo Laporte [01:22:33]:
But you're making an assumption that the real cost that there's doing this at a loss. It's not at all clear.

Paris Martineau [01:22:38]:
Well, we've had a lot of. There's been no evidence that none of these large AI companies have reported making a profit on any aspect of their business because of the compute costs.

Leo Laporte [01:22:54]:
Well, they're not public so they don't report first of all.

Paris Martineau [01:22:57]:
Second of all they have not been sorry in conversation.

Leo Laporte [01:23:03]:
Okay, but you don't know what the costs are because remember they're also.

Paris Martineau [01:23:05]:
Are you genuinely arguing that you think that it's pro, the claude selling access to CLAUDE code. You're making a profitable at $20 a month.

Leo Laporte [01:23:12]:
Well, no, no, it's not at 20. That's why they're stuck.

Paris Martineau [01:23:14]:
What about 100? What about.

Leo Laporte [01:23:15]:
It's not at either of those. It's at it. The token cost is considerably higher. Most enterprises are playing tens of thousands of dollars. But you're asserting that that's losing the money as well. And I'm not saying that may not be. That's why they're moving people this way. I mean, we may.

Leo Laporte [01:23:29]:
I just don't think we know. And because they're not public companies, we don't have that information. Plus, the costs that they face are more than providing inference. The costs are buying all those GPUs and building data centers and so forth.

Jeff Jarvis [01:23:43]:
Settling copyright suits.

Leo Laporte [01:23:44]:
Yeah, settling. That's not an insignificant cost either. Anthropic is doing something interesting with regards to Amazon. They are expanding their partnership with Amazon. They're setting up 5 gigawatts of new compute. 5 gigawatts is pretty significant. That's probably a couple of data centers. And Amazon is committed to a further investment of up to $25 billion in anthropic.

Leo Laporte [01:24:13]:
But Anthropic saying, and yeah, in return we're going to buy $100 billion worth of AWS. So I think that's kind of interesting. That's building on the 8 billion Amazon's already invested. So they put 5 billion in today, an additional 20 billion in the future and they've already put in 8 billion.

Jeff Jarvis [01:24:31]:
So I listened to the now infamous interview with Patel, Rohit Patel, with Jason Wong, because I am a student of Jason Wong and listen to all of his performances.

Leo Laporte [01:24:42]:
Dwarkesh actually did a very good job. And I, I know you think that Jensen was prickly.

Jeff Jarvis [01:24:47]:
No, I don't think.

Leo Laporte [01:24:48]:
I think he appreciated the chance to defend this.

Jeff Jarvis [01:24:50]:
He said, he said he enjoyed it. And I think that, that I think Dwarkish, yes, he tried, but I think that Jensen, in the end, I think won the day.

Leo Laporte [01:25:02]:
Yes, because he knew the most interesting one. Jensen said. And I thought this was really interesting and I'm not sure how I feel about it, is it is foolish to hold back chips from China. Now, obviously Nvidia would love to sell every one of its chips if it had. Actually, I don't know if Nvidia needs to sell any more chips. I think they're sold out.

Jeff Jarvis [01:25:21]:
But it wants Cuda to be everywhere. He made that very clear.

Leo Laporte [01:25:25]:
And I think this was his point. Which I think is a very good point, that if you create a supply constraint to China, they're going to invent their own way and it's not going to end up being a universal capability. It's going to be restricted to China and it's going to hurt America, it's going to hurt enterprise, because China will have its own better way. The best thing is for us to top chips. They don't need it. We should all. So it's a little self serving because Cuda is his and is proprietary. His chips are his and proprietary.

Leo Laporte [01:25:55]:
But at the same time it makes an interesting point.

Jeff Jarvis [01:25:57]:
He also argues though that they don't need the top chips because they have unlimited power. This is to what Paris was saying earlier is that what Nvidia has to do to prove its value to its customers here in finite data centers with finite gigawatts of power, is that they've got to constantly increase the value you get for that power. He said in China they have unlimited power, they control it all, they can do it all. And so they don't need the top chips, they don't need that level of efficiency and they can compete with the US and he said, why would we give up this huge market?

Leo Laporte [01:26:31]:
Right.

Jeff Jarvis [01:26:32]:
The other thing I didn't get, and it's just a bit of history that you probably know that I don't Dorkish was asking him about the early days of Anthropic and how Nvidia would have done more with them but couldn't at the time. Did you understand that part at all?

Leo Laporte [01:26:50]:
No.

Jeff Jarvis [01:26:50]:
Okay, never mind. But I thought it was a very interesting interview. It was very interesting to see the debate squad. Jensen Wong, I think he's a brilliant communicator. I think it's a presenter.

Leo Laporte [01:27:04]:
Jensen got in a situation where somebody challenged him, was smart enough to challenge him. And I think that Jensen, I think

Jeff Jarvis [01:27:09]:
he did very well. Yeah, I think he's a great debater too.

Leo Laporte [01:27:11]:
Yeah, yeah.

Jeff Jarvis [01:27:12]:
And, and it's, and it's just fascinating to watch him in operation.

Leo Laporte [01:27:15]:
This is the problem with things like the Tech Bros. Podcast network and others is their softball throwers. And so these guys and I, I know that CEOs like softballs, but I think Jensen's one of those guys who might prefer every once in a while something a little juicy to across.

Jeff Jarvis [01:27:30]:
Well, we kind of heard that from Stephen Witt who wrote the book on Jensen Huang here on the podcast.

Leo Laporte [01:27:34]:
Yeah, he's combative.

Jeff Jarvis [01:27:35]:
Yeah, yeah, yeah.

Leo Laporte [01:27:37]:
SpaceX has struck a deal. This is a wild deal. Talking about deals with Cursor saying we'll either buy you for 60 billion. Cursor is a very popular vibe coding platform. It's kind of an IDE plus as we found out recently. Claude code in the background. A little Cursor doesn't admit that 60 billion or if we don't buy you 10 billion for working together, not sure what's going on there. A lot of these AI deals.

Jeff Jarvis [01:28:05]:
Interesting 2 cursor people left for X which explains the bridge to this. But I wonder, given that if OpenAI has been out there buying stuff, others have been buying stuff. If your cursor is musk where you want, is that the best place to put your chips? Yeah.

Paris Martineau [01:28:26]:
How did this deal come together?

Leo Laporte [01:28:29]:
I think this is personally opinion. I think Cursor is really laggard. They don't have their own models. It's just a harness.

Jeff Jarvis [01:28:42]:
It's the perplexity of vibe coding.

Leo Laporte [01:28:44]:
Yeah. OpenAI and Anthropic have their harnesses. There are many, many open source third party harnesses like OpenCord and or in PI. And I just think Cursor is rapidly losing its moat or has no moat at all. And so I'd take the money and run if I were them personally and I wouldn't care who's giving it to me.

Jeff Jarvis [01:29:03]:
I remember when that old company long ago that had the screensaver was an information. I can't remember the name of it. When your machine went to a screensaver this very early Internet and Rupert Murdoch offered them $400 million.

Leo Laporte [01:29:17]:
Yeah, yeah.

Jeff Jarvis [01:29:19]:
It's far more valuable than that.

Leo Laporte [01:29:21]:
Yeah. No, you always take the money and run. If there's any lesson we've learned from the Internet era, take the money and run. Google right now is doing its next conference and man, were there a lot of announcements out of Google and I don't know if we want to call cover all of them but one of the biggest is the 8th generation change log.

Jeff Jarvis [01:29:41]:
Change log.

Leo Laporte [01:29:43]:
The Google changelog. Do we have that still? I don't know.

Jeff Jarvis [01:29:49]:
Long gone really.

Leo Laporte [01:29:51]:
Oh, sorry. Thank God. Google has announced its 8th generation of TPUs. These are the chips Google makes in competition with Nvidia's.

Jeff Jarvis [01:30:02]:
How do they compare in terms of.

Leo Laporte [01:30:05]:
I think a lot of people use them. In fact I think that's what Amazon's using. I may be wrong on that.

Jeff Jarvis [01:30:11]:
Well, I think they all have to use all of them because again, cuda shortage. I mean doesn't Google's hosting offers, Nvidia chips included?

Leo Laporte [01:30:20]:
Yeah.

Ian Bogost [01:30:20]:
Have to.

Leo Laporte [01:30:21]:
Oh, I don't know. Yeah, maybe they do have some. So Cloud Next introducing the 8th generation of their custom Tensor processor unit. I'm not expert enough to know. I mean, I think generally the consensus is that the Nvidia chips are the superior, partly because they own Cuda. Right. There's a certain advantage there. But I don't think, I would think it'd be premature to write Google off in any of this.

Jeff Jarvis [01:30:49]:
And Google just. We think Rumor did a deal with Marvel to produce more chips.

Leo Laporte [01:30:56]:
Right.

Jeff Jarvis [01:30:57]:
And I think more inference chips. Again, inference chips.

Leo Laporte [01:31:01]:
This is what Dell is saying, I think, is that there is such demand that it's, you know, if it's a bubble, we're not at the end of it by any means. Also, to answer the efficiency question, these TPUs are designed to be much more efficient. The seventh generation TPUs were two to four times faster and 30% lower. I'm sorry, the eighth generation are two to four times faster and 30 percent lower. And this is unclear than what. Thank you. The seventh are better than the sixth and I guess the eighth are even better. Yeah, but they're going for efficiency.

Leo Laporte [01:31:41]:
In other words, that's the metric. And this single TPU superpod has 9,600 chips. Two petabytes of shared high bandwidth meta memory. Wonder where they're getting the memory chips with double the interchip bandwidth of the previous generation. 121 exaflops of compute. So these are very powerful machines. It's funny how Cuda really has become a moat for Nvidia. The software, not the hardware.

Leo Laporte [01:32:08]:
They announced a Gemini enterprise agent platform and developer tool built on Vertex. They said, maybe this is interesting. 75%. This is Sundar Pichai talking. 75% of the company's new code is AI generated. 75%. I wonder though, if they're using Claude or if they're using Gemini. There's a whole.

Paris Martineau [01:32:37]:
I'm wondering if they're going to have a come to Jesus moment like Amazon did. When was it?

Leo Laporte [01:32:42]:
A couple weeks ago, right over there

Paris Martineau [01:32:43]:
where they're like, yeah, actually all of our code has been AI generated.

Leo Laporte [01:32:47]:
And it's a real problem that it's a problem with engineering because the DeepMind has access to Claude and uses Claude, the competitor and everybody else at Google is forced to use Gemini. And Yeggi says it's been a real problem in engineering at Google. Google is at great pains to deny it. When I asked Christina Warren, who used to work at DeepMind, she's now one of the hosts on MacBreak weekly, she said, no, that's not been my experience that's not accurate. But Yegi says, oh no, I'm hearing from a lot of people at Google is very distraught that they forced to use Gemini. And in fact Google, he says, tried to take Claude away from DeepMind. And DeepMind said, you take it away from us, we're walking, we're out of here. Let's see.

Leo Laporte [01:33:32]:
I'm running through these really quickly, trying to get at least some of these big stories out. YouTube is making its deep fake detection tool to anyone at high risk of having their likeness abused, not just public officials and politicians.

Jeff Jarvis [01:33:45]:
Good.

Leo Laporte [01:33:46]:
Yeah, there are a bunch of new models. We kind of hinted at this. There's Claude Design.

Jeff Jarvis [01:33:52]:
This is the changelog.

Leo Laporte [01:33:53]:
Yeah, this is the Changelog. Claude Design from Anthropic Labs is a design tool, aims straight at the heart of figma. ChatGPT has announced images 2.0. Everybody's using images. They say they can even pull information from the web to create your images. Salesforce has launched Headless 360 to turn its entire platform, all that business information into infrastructure for AI agents.

Jeff Jarvis [01:34:20]:
They're running a bit scared, I think.

Leo Laporte [01:34:22]:
Two big new Chinese models. Alibaba's Quen 3.6 agentic coding power. It's open weight, but you need a pretty hefty machine to run it. I can't run it on my framework, that's for sure. You need probably a few 50 90s at least.

Benito Gonzalez [01:34:42]:
Is there a system requirement? Is there a system requirement, Doc?

Leo Laporte [01:34:46]:
Probably. When I was looking around to see if I could run it, I asked Claude, can I run it? And it laughed at me. It said, no, but it is a fully open source. You don't have enough RAM, man. I have under 28 gigs. It's not enough, man. Fully open source. MOE model, mixture of experts.

Leo Laporte [01:35:05]:
Which does mean it can be smaller because all the models aren't. All of the model isn't running at the same time. Alibaba is saying, exceptional agentic coding capability, competitive with much larger models, strong multimodal perception and reasoning ability. You know, but you can run this on other places. You know, Ollama has a subscription. There are a number of places, open code subscriptions. Kimi 2.6 has also come out. Not open weight, but a very powerful Chinese model, Kimi 2.6.

Leo Laporte [01:35:40]:
And I've heard coders say some very good things about this. So everybody's chasing Anthropics, Claude and Codex 5.4. Very, very hard. And I think this is good. Competition is always good. Right? Did we talk about this last week? I think not Sam Altman's World. You know the iris scanning thing?

Jeff Jarvis [01:36:02]:
We didn't talk about it.

Leo Laporte [01:36:04]:
Well, now Tinder is going to use them to make sure that you're a human, not a bot. When you're asking for dates. I'm not sure how this is going to be implemented, but Tinder users can use a. Can put a digital badge in their profiles signaling this is wired writing to potential suitors they're a real boy or real girl.

Paris Martineau [01:36:31]:
Provided apps already have this, but they just use kind of like a Yodi right thing.

Leo Laporte [01:36:36]:
This is. This is like your eyes are getting. Your irises are getting.

Paris Martineau [01:36:40]:
Do you still get the World Coin?

Leo Laporte [01:36:42]:
I don't know. Probably. Although I think you don't get as much World coin in the US as you would get in other places. World says 18 million people have been verified with an orbit, so the dating pool is wide. Yep. But it's not just Tinder. Zoom is going to use it to verify humans in meetings. This is Sam Altman's company is one of his side bets.

Leo Laporte [01:37:10]:
This is not OpenAI, DocuSign, Okta, Shopify and Vaneck all signing deals with World to verify humanity. One thing humans are good at is bipedal motion. But they are no longer the world record holder for bipedal half marathons. A robot has now the new world record. 50 minutes and some seconds in a half marathon. Look how fast that guy's going.

Jeff Jarvis [01:37:44]:
John Henry.

Paris Martineau [01:37:45]:
Woo.

Leo Laporte [01:37:46]:
It is. It's like John Henry in the locomotive. I don't know what it means that

Paris Martineau [01:37:49]:
a deep stance, that robot.

Leo Laporte [01:37:51]:
Oh, yes. It runs low to the ground. The better videos of the robots falling over. Yeah, that's more smashing into a little. Here's a little one. Show some of these video. There's a little one going by. Oh, little robot fell down.

Leo Laporte [01:38:05]:
Sometimes when they fall down, they burst into a thousand pieces. I'm trying not to laugh because I know this is all being. Whoa. All being recorded. This is via Reuters. Thank you, Reuters. Don't take a step. Last year, the winning robot had two hours at 40 minutes.

Leo Laporte [01:38:24]:
This year, 50 minutes. But again, I. What have we accomplished here?

Benito Gonzalez [01:38:30]:
It just means the robot police are going to be able to catch you no matter what.

Leo Laporte [01:38:33]:
Catch you.

Jeff Jarvis [01:38:34]:
How about in Ukraine?

Leo Laporte [01:38:38]:
How about a beanie designed to read your thoughts?

Ian Bogost [01:38:40]:
Yeah.

Leo Laporte [01:38:40]:
Ukraine's using robots to scare Russians.

Paris Martineau [01:38:42]:
Come on. How many of these sort of stories. Stories we had, and none of them are real. We've gone over multiple things that are supposed to read your thoughts, but they don't does this one just also read your thoughts by reading what you mouth with your lips closed? That's what the last one did.

Leo Laporte [01:38:58]:
Well, remember neuralink you actually have to have it surgically implanted. This one is sitting in a little beanie on your head. It's a little chip. It's reading EEGs, electroencephalograms. So it is reading more than just your lips moving. I don't know if you can get speech out of an eeg. Maybe in time.

Jeff Jarvis [01:39:19]:
There's experimentation, but it's very.

Leo Laporte [01:39:21]:
Maybe in time. But you know what? That's what. These are the steps you have to take. You know who doesn't have to read your mind? Dairy Queen. They're now using an AI to take your order at dq. You probably could also get it to do math. Did you see McDonald's chatbot? There's their customer service chatbot on their website. Somebody in between asking, well, what's in a Big Mac? Asked him and can you write a Python script for reversing a list? And it happened, like gave him the Python code and then said, what else do you want to know about Big Macs?

Benito Gonzalez [01:39:59]:
It spoke the Python code?

Leo Laporte [01:40:01]:
No, it's a text chatbot. But it was code. It was real code. TSMC more bullish than ever. They expect revenue to grow by more than 30%. They're the company that makes many of the chips, including Nvidia's GPUs. They expect to grow revenue 30 revenue 30% year over year. More than 30% actually.

Leo Laporte [01:40:27]:
They have a 66% profit margin for the first quarter. That's the highest in 20 years. So demand is high and when demand is high, prices are high.

Jeff Jarvis [01:40:36]:
It's a single point of failure if there's an invasion.

Leo Laporte [01:40:39]:
Actually, no, they're very actively building. They have a plant already up in Arizona. They're really actively trying to diversify, which is pretty important. And I think they're getting a lot of support from the US government doing that. AI traffic to. According to Adobe, AI traffic to US retailers went up almost 400% in the first quarter. This confirms what you've been saying, Jeff, that you're dumb to exclude yourself from AI search results.

Jeff Jarvis [01:41:07]:
Well, certainly brands are going to be out there and marketers. The other interesting thing though is that, and there are some arguments, I didn't put this stuff in there. Huge projections for OpenAI's advertising opportunity, but so far chatbots do not perform well.

Leo Laporte [01:41:25]:
Oh, interesting.

Jeff Jarvis [01:41:26]:
For advertising. I think we have to get to an agent to agent world before it

Leo Laporte [01:41:29]:
starts to really work well. And that's my new. This is the drum I'm beating from now on is that if you are making a website, if you're making a tool, a product operating system, an app, you darn well better have a agentic facing ui, an API or something that an agent can interface with because I think people are just not going to look at you if you don't. If you can't be controlled by AI, if you can't be controlled by an agent, if you can't be searched by an agent, you will not exist. And that's true for retail.

Jeff Jarvis [01:42:00]:
Aio.

Leo Laporte [01:42:02]:
Aio, that's what they call it, not SEO. Stanford's AI index finds China has nearly closed the performance gap with the US. This is related to Kimmy and Quinn, despite spending 23 times less. Maybe this is the what you were talking about, Jeff. The unlimited power China has. They lead in AI patents 69% of global findings publications, industrial robot installations, nine times the US rate. And Jeff, energy infrastructure and their the brain drain has slowed considerably. AI talent migration to the US has dropped 89% since 2017.

Jeff Jarvis [01:42:43]:
That's the huge harm. And that's another thing Justin Wong said is the half the best AI scientists are Chinese and now we're shoving them away.

Leo Laporte [01:42:52]:
We dominate with private AI investment because we've got the venture capitalists. China investing 12.4 billion in 2025, we invested a whopping $285.9 billion in AI. California alone, 218 billion of that, more than 75% of the US total.

Jeff Jarvis [01:43:13]:
You know, I recently read a history of the Bell Labs and it really struck me how history could have turned out differently that so much of the great innovation, including especially the transistor, happened at Bell Labs in New Jersey and the serendipity of how California ended up being the place instead of Jersey. Man, Jersey should have been the Valley.

Leo Laporte [01:43:35]:
Really?

Jeff Jarvis [01:43:37]:
Yeah. There was so much happening here on the East Coast.

Leo Laporte [01:43:40]:
Oh, it was really because of collapse.

Jeff Jarvis [01:43:42]:
Yeah, it was. Well, I also just read it. I recommend this right now. I was going to do it as a take. I just finished a wonderful book. Hold on here. Conquering the Electron by Derek Chung and Eric Jason Morton.

Leo Laporte [01:43:56]:
Is this about the transistor or.

Jeff Jarvis [01:43:58]:
It starts with the Edison effect. It goes all the way through. Chung worked in chip making and so there's more of that stuff at the end.

Leo Laporte [01:44:08]:
This is a Jeff Jarvis subtitle. The geniuses, visionaries, egomaniacs and scoundrels who built our electronic age.

Jeff Jarvis [01:44:16]:
Yeah, so it's 12 years old. But it's really.

Leo Laporte [01:44:19]:
Sounds good.

Jeff Jarvis [01:44:20]:
It's very educational.

Leo Laporte [01:44:20]:
I have to read it. Yeah.

Jeff Jarvis [01:44:22]:
And it. So was. It was the fact that Shockley went to California. He was a horrible manager for Bell Labs, but he. But. And a credit hound.

Leo Laporte [01:44:36]:
And then not a great person in any way.

Jeff Jarvis [01:44:38]:
Turns out bad stuff. But he hired the best people. And there was the so called Traitorous8 who went and created Fairchild and then from Fairchild created Intel and so on and so forth. And it was really that seed that created Silicon Valley.

Leo Laporte [01:44:51]:
Yep. Well, it's all. You know, Hewlett Packard always gets credit because that was the first garage in the 30s. So there. And Stanford gets some credit because there was a lot of stuff going on at Stanford at the time. All right, a couple more bad things. AI Bad things. I don't know if this is a good thing.

Leo Laporte [01:45:08]:
The first movie with a fully AI generated performance approved by the actor Val Kilmer, who's passed away, will be AI generated.

Paris Martineau [01:45:21]:
How did he approve it if he's

Leo Laporte [01:45:22]:
passed before he died?

Jeff Jarvis [01:45:23]:
Family did his estate. I don't know.

Leo Laporte [01:45:27]:
I don't know. I bet he. I wouldn't be. They had to capture him, right? Oh yeah.

Paris Martineau [01:45:31]:
I almost have enough footage of Kilmer.

Jeff Jarvis [01:45:35]:
Yeah.

Leo Laporte [01:45:35]:
Kilmer's family blessed the use of his likeness.

Paris Martineau [01:45:38]:
Oh, I don't like that.

Leo Laporte [01:45:39]:
He. He died at the age of six after a lengthy battle with cancer. Yeah, but I don't know. Let's.

Jeff Jarvis [01:45:46]:
On the other hand, let's honor dead dad and have him live on.

Leo Laporte [01:45:49]:
See if I can find project he cared about. The pictures of Val. It looked like. It kind of looked like him.

Paris Martineau [01:45:55]:
Well, yeah, that's kind of the whole point. Right.

Leo Laporte [01:45:57]:
Well, sometimes these things look kind of fake. Yeah. Oh, that looks pretty good. Well, it's only shortened, showing little short bits of Val. So. Yeah, I don't know.

Jeff Jarvis [01:46:08]:
We'll see.

Leo Laporte [01:46:09]:
I don't know. This could be a watershed moment. Or not.

Paris Martineau [01:46:17]:
He's seen for around an hour of the film's running time.

Leo Laporte [01:46:21]:
It's amazing. It's not just because we've seen that before, like in Star Wars, Carrie Fisher and stuff, but. But this is like he's actually fully performance.

Jeff Jarvis [01:46:30]:
You're gonna keep on counting fingers the whole time.

Leo Laporte [01:46:33]:
Yeah, that's the problem. You highlighted this as well. Andon Labs. We gave an AI a three year retail lease in San Francisco and asked him to make a profit.

Jeff Jarvis [01:46:45]:
That's selling weird stuff.

Leo Laporte [01:46:47]:
In fact, people are trying to game it to get it to sell stuff they're interested in. In the comments Section, they're saying, you know, this is a really great place if they would only sell sugar free gummy worms. Because sugar free gummy worms are really a great thing to have in any store. Sugar free gummy worms are a must. And I don't know if it's working. These agents, they're kind of soft brained. It's easy to influence. This is like what Joanna Stern did with the Wall street journal.

Jeff Jarvis [01:47:17]:
Yeah. Vending machine.

Leo Laporte [01:47:18]:
Yeah. Finally.

Jeff Jarvis [01:47:25]:
No, you're not done yet. I got a few.

Leo Laporte [01:47:27]:
Oh, you got a few.

Jeff Jarvis [01:47:28]:
I got a few.

Leo Laporte [01:47:29]:
We're at two hours. This pasta sauce wants to record your family. Prego pasta sauce is now selling a screen free voice recorder that you're supposed to put on the dinner table as the family talks. It's the prego connection keeper, created in collaboration with StoryCorps, which is a nonprofit preserving StoryCorps.

Paris Martineau [01:47:54]:
Cool.

Leo Laporte [01:47:55]:
Yeah, they're preserving the stories of Americans in the library of Congress at the folklife center. There's no AI Wi, Fi, or Bluetooth, so it isn't really an AI story. But you can upload the recordings to StoryCorps website to make it easier to share.

Paris Martineau [01:48:07]:
What is the difference between this and just having a recorder on your table or just opening up your phone and hitting record every time you sit down?

Leo Laporte [01:48:14]:
Well, here's the difference. It's $20. But you get a jar of prego spaghetti sauce.

Jeff Jarvis [01:48:18]:
There you go.

Leo Laporte [01:48:19]:
And spaghetti noodles. And a deck of cards featuring conversation prompts and ideas.

Paris Martineau [01:48:24]:
If they really cared about making this a good stunt piece, they would have found a way to get the recorder inside the jar of pray. Like a toy or the lid.

Benito Gonzalez [01:48:36]:
The lid should be the recorder or something.

Leo Laporte [01:48:38]:
You know what? It's totally what I thought it was when I first saw this story. Oh, it's the lid.

Jeff Jarvis [01:48:42]:
What was the. What was the spaghetti sauce commercial? It's in there.

Leo Laporte [01:48:45]:
It's in there. It's your recorder in the sauce. There's a recorder in the sauce. All right, you guys, you get to pick some stories. Go ahead.

Jeff Jarvis [01:48:53]:
All right, I got one to drive you angry, and then I want one. I want to hear.

Leo Laporte [01:48:56]:
I was just calming. My blood pressure was just getting to normal.

Jeff Jarvis [01:49:00]:
So line 108 is the world model.

Leo Laporte [01:49:06]:
And this is another one of those Yann Lecun things.

Jeff Jarvis [01:49:09]:
It's Yann Lecun, and the paper is hard to understand. But below that is a very good explanation. And I also asked Gemini for an explanation, and it was similar. So if you go to the next slide, what's interesting about this is the role models have a problem, a representation collapse. They kind of consider everything the same and they get distracted by things like a light bulb and don't understand what's what. Attention must be paid. But for reasons, ways that I cannot explain, I'm not capable of explaining, they came up with ways to get it to pay attention to the important stuff and a cleaner model. The efficiency.

Jeff Jarvis [01:49:42]:
This is what got me. The efficiency gains are striking. The model has around 15 million parameters, trains on a single GPU in a few hours and can plan up to 45, 48 times faster than larger foundation model based world models. And so you start to see development here in the world model side of things. And this doesn't say anything against LLMs, it doesn't say anything against the scale world, but it is a competitive worldview which I think is really important that we get research going into other areas.

Leo Laporte [01:50:12]:
It's a little deceptive because I mean I can train a model, I have been training models here. You can train small constrained models easily on simple model.

Jeff Jarvis [01:50:22]:
These are trained on video, these are trained not on text, but on video to understand.

Leo Laporte [01:50:25]:
So what I'm training is of I don't want to have to say Alexa or any of those words to talk to my agent. I want to say hey Kenobi. So I was going to go hey Obi Wan. Or actually I want to go help me Obi Wan Kenobi. But it said that's not, it's not good. And that we actually tried it. And what we did is we generated thousands of, with speech synthesis, thousands of audio files and trained on that plus some audio files that were similar but not it. So that would have what to reject.

Leo Laporte [01:51:02]:
But I think it was a bad phrase and I wasn't using, I was using a model text to speech model called Piper that wasn't very good. So I'm going to move to a better model that one I use called Kokoro and I'm going to make it. Hey Kenobi chat. Claude and I went back and forth on this and said, you know, you need some, you know, fricatives and some consonants in there. Be better if you started with something called fricative. A fricative. You need a fricative.

Jeff Jarvis [01:51:27]:
I like that. Hey fricative.

Leo Laporte [01:51:29]:
And so it's, I said what about hey Kenobi? And he said that's really good because of the K and the Kenobi, the B and the B and the hey. And it's, it said that's going to be really good. So I haven't done it. I said, you know, would it be better if we use a synthetic model? Or if I said it. It said well you're going to have to say it 200 times and you're going to have to say it another 200 times of things that are close but not the same. I said it's worth it. If it works, it's worth it. It said, you know, if you used Alexa it'd be a lot better.

Leo Laporte [01:52:00]:
I said no, I don't want to use Alexa. So in other words, if it's a constraint, if you're doing something constrained, you don't need a thousand GPUs and 8,8 trillion parameters because you're not in training on the giant universe, you're training a constrained universe. And so that's I'm sure what's going on here. These world models are simpler models. It's not a universal world model where it's like well you now know everything that happened in physics. We've had physics models for years. Games have them. So I think Jan's trying has something he wants to sell.

Leo Laporte [01:52:37]:
I'm not against it it.

Jeff Jarvis [01:52:39]:
I think it's fine. And Fei, Fei Lee I think it's, it's a competitive view. I wanted to get Paris's view. Paris on the Peter Thiel backed startup called Objection. Did you see this?

Paris Martineau [01:52:52]:
Oh vaguely. I mean this is a startup that you can pay inordinate sums of money.

Jeff Jarvis [01:53:00]:
Well starts at $2,000.

Paris Martineau [01:53:01]:
Yes, yes to basically I think it's a mix of. They claim it's a mix of AI and humans that then will do research to disprove or investigate a claim you set it to. And some of the arguments or case studies that they're putting out there is things like basically trying to correct the record if you believe an article is false. Which I just think is very laughable and speaks to these sort of people not really understanding how journalism works exactly.

Jeff Jarvis [01:53:34]:
Or, or facts. Yeah think thinking that oh if we, if we. It degrades anything that comes from a not named source. So all investigative journalism goes away and it only it most trusts official documents. Well we know how well that works and then the AI is going to be the, the tribunal of truth in the end having been presented with, with this, this information and, and the idea is that it replaces both journalism and

Paris Martineau [01:54:03]:
the courts and part of it is you're able to sign truth scores to every single reporter or outlet and your truth score will go down if you do terrible things like ignoring objections from. Objection.

Benito Gonzalez [01:54:21]:
So there's no objective truth Then, Right, so that's just whatever it says. There's no objective truth.

Leo Laporte [01:54:26]:
So here's a sample honor index for a fake journalist named Sarah chen. She is 810% trusted out of no, 81% trusted. Top 18 of tracked authors. And this is her score. Corrections. Well, you know, that's one good thing, that retractions are issued within 48 hours, so they probably publish corrections.

Jeff Jarvis [01:54:51]:
Yeah, there's something called the trust project.

Paris Martineau [01:54:53]:
Yes. But to do that, that's different than three objections ignored for over 30 days takes your score down negative 24 points, while correcting one published error and doing a retraction within 48 hours only takes it up 12 points.

Jeff Jarvis [01:55:15]:
G. Do you think you could game this?

Paris Martineau [01:55:18]:
Yeah.

Jeff Jarvis [01:55:18]:
Yeah. So it's. It's ignorance.

Leo Laporte [01:55:22]:
Is the. Is the principle wrong, though? I think the principle is wrong. Right, Yeah.

Paris Martineau [01:55:27]:
I mean, everything about it is.

Jeff Jarvis [01:55:28]:
Well, it's what. It's what Benito was trying to say. There's context, there's framing, there's nuance, and this erases all of that.

Benito Gonzalez [01:55:40]:
Two plus two is four, no matter what anybody says.

Leo Laporte [01:55:42]:
And this facts is facts.

Paris Martineau [01:55:45]:
And I mean, it gets to something that Ian was touched on a little bit in our interview earlier, which is one downside of our increasingly interconnected world is that when you put anything out into the world, especially if it's journalism or something, suddenly, or even if it's just a post, suddenly, there's this whole class of people who believe that that means they have a right to be in your inbox or at you on things and demand an. An answer and a response and your time. And I don't want to conflate this statement with saying like, oh, people who publish things, or journalists or quasi public figures have no obligation to the readers. Obviously that's not true, but I worry that if something like this were to take off, one of the downsides is you'd suddenly publish an article that's maybe a bit controversial. You, instead of being flooded with, you know, spam and hate emails, you'll be flooded with the spam and hate emails and hundreds of objections that if you do not respond, must respond on every single fact in your article, your credibility is taken down. It's just silly.

Leo Laporte [01:56:58]:
It's totally weaponizable. In other words.

Jeff Jarvis [01:57:00]:
Yes, exactly.

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

Jeff Jarvis [01:57:02]:
One other quick one, real quick. I found this amazing line133. A Tokyo court ruled that somebody who put who. Who published a movie and anime spoiler articles that it was a copyright infringement to say how something ended, number one. And number two, it's criminal got jailed.

Leo Laporte [01:57:21]:
What Spoilers go to jail.

Paris Martineau [01:57:26]:
This is an example of all the things I hate.

Jeff Jarvis [01:57:30]:
Yes.

Paris Martineau [01:57:30]:
I don't under. I mean, listen, I don't understand how maniacal spoiler culture or anti spoiler culture has gotten lately. I understand not wanting to be spoiled about things things. But it has also gotten to the point where people on say, you know, Reddit will get mad at like 48 or 72 hours after, say, the winner of Drag Race was announced that they're like, I go on the subreddit, I open up Reddit and suddenly I see posts spoiling the winner of Drag Race. I'm like, I'm sorry, baby, that that happened.

Jeff Jarvis [01:58:03]:
Have you heard of the watercolor?

Paris Martineau [01:58:05]:
Have you heard of.

Benito Gonzalez [01:58:08]:
Why are you on Reddit? Why are you on Reddit then? If you don't want to know this

Paris Martineau [01:58:10]:
information, why are you on the Internet?

Leo Laporte [01:58:13]:
It's. Why are you not complaining? It's another thing to go send somebody to jail for a year and a half. Yeah, that's insane for publishing Spoiler.

Jeff Jarvis [01:58:22]:
This is copyright gone mad.

Leo Laporte [01:58:23]:
But, you know, I think Japanese courts are very aggressive about copyright. I think about Nintendo, which is extremely litigious and always seems to win. I think this is not. This is something typical of Japan. But that's ridiculous.

Benito Gonzalez [01:58:39]:
Yeah, it feels like there's something cultural going on here.

Leo Laporte [01:58:42]:
It's cultural in the movie Godzilla -1, which came out, by the way, in 2023. The Godzilla article, 3,000 Japanese characters in length, was a complete detailed plot summary of the movie. The. The makers of the movie sued Toho, largest studio in Japan. They're famous, apparently for stringent trademark protection. Ah, interesting. Went after him. He also wrote an article about the anime overlord that aired in 2018.

Leo Laporte [01:59:21]:
So it's not even like recent stuff. When does. When does the spoiler.

Paris Martineau [01:59:26]:
The thing that apparently ended up up being the smoking gun for prosecution is the fact that the website ran ads. These spoiler articles, therefore, were not only stealing copywritten work, but earning money through it. But the fascinating bit this writer at Hassan Nassir at a Tom's Hardware writes the fascinating bit is that these pieces were all written by outside contributors. Takauchi simply operated the site, though he did earn revenue from it. But he's still the one that is has gone to jail over this.

Leo Laporte [02:00:03]:
So this is an interesting question. This actually applies to this whole question of copyright with AI if I read a book and then write a summary of it, because I think spoilers might be kind of not a good way to describe this because we Think of spoilers as like telling you about the plot twist. He wrote detailed plot summaries. You know, more like classic comics or Cliff Notes. We don't think that's a copyright violation, but it is kind of what an AI does, right? It's not recreating the. The book, it's summarizing it in its head so that it can use that information.

Jeff Jarvis [02:00:39]:
Which is why I argue that. That it has a right to learn the same way we do.

Leo Laporte [02:00:43]:
Yeah, apparently not in Japan. I wonder.

Jeff Jarvis [02:00:48]:
Yeah. So, Paris, you had something too.

Paris Martineau [02:00:51]:
Oh, my last thing is just I don't know if you guys saw this week that Reuters broke a story that Meta is now going to be recording all of its employees, clicks and keystrokes on its computers to turn all of that into AI training data. And of course, the Metamates are up in arms about this. That their precious keystrokes and clicks could be. Suddenly everything happening on their computer screen is going to be logged by their employer and used to train on. Which is, well, are they mad about

Leo Laporte [02:01:24]:
the training or that it's recorded? Because there's a historic right to record everything. Every employer has the right to record everything.

Paris Martineau [02:01:30]:
I mean, yeah, I think they're mad about the fact that suddenly everything they do on their computer is being recorded and logged somewhere.

Leo Laporte [02:01:38]:
Chances are it's being recorded and logged at every.

Paris Martineau [02:01:41]:
No, because I believe part of this is they have to. To are having to install new software on all this. A lot of I'm sure what is going on in their community.

Leo Laporte [02:01:49]:
Almost all businesses, I have, I have to tell you, almost all businesses do this because they're liable for what's done on their premises with their hardware on their Internet connection. And so almost all businesses record what you do on their computers.

Paris Martineau [02:02:01]:
Well, they are installing new tracking software on their computers to track mouse movements and keystrokes in order to train AI agents.

Leo Laporte [02:02:10]:
So that's the question. Are they mad about the AI training or are they mad about being recorded?

Jeff Jarvis [02:02:15]:
Good question.

Paris Martineau [02:02:15]:
They are mad about being recorded and I think some of them are also mad about that bad news.

Leo Laporte [02:02:19]:
I bet you anything Met has always recorded it. Almost all companies do that. Big companies all do that. You know, you go down the hall to it, they can look at what's on any screen in the premises at any time. They have to. They're protecting themselves.

Paris Martineau [02:02:35]:
When you're doing that, something pops up on your screen that is you're suddenly being remote accessed. I think people are.

Leo Laporte [02:02:43]:
No, no, there's no requirement. The law absolutely is clear on this.

Paris Martineau [02:02:46]:
Courts I mean, I'm not saying that they're legally required to. I'm saying that the general practice employee will see when you work at one of these large companies is something pops up in your screen to show remote X. That has happened at, at Conde Nast. That's what they did.

Leo Laporte [02:03:02]:
They're being very good about it.

Paris Martineau [02:03:04]:
That's what it was.

Leo Laporte [02:03:04]:
Because I talked about this a lot on the radio show for years because people were up in arms about it. The courts have been very clear. It's nice if you put it in your policy and tell people you have no requirement to do so.

Benito Gonzalez [02:03:17]:
I mean, I think people have always assumed they were being recorded. I think the difference here is that now it can be queried and now you can like find out.

Leo Laporte [02:03:23]:
It could always be what people are doing.

Benito Gonzalez [02:03:25]:
No, but like always.

Leo Laporte [02:03:26]:
That's always been the case. That's always been the case.

Benito Gonzalez [02:03:30]:
And now it's being.

Leo Laporte [02:03:31]:
And especially at a company like Facebook,

Paris Martineau [02:03:32]:
I'm sure it seems like there's something new going on here because they are,

Leo Laporte [02:03:36]:
by the way, we don't have.

Paris Martineau [02:03:37]:
They are putting new software on.

Leo Laporte [02:03:39]:
We've never done this at Twit. Reporting is we're small enough, we didn't really probably have to. But many big companies, very common practice. It's actually very nice of Conde to warn you because they don't even have to put it in their post war you.

Paris Martineau [02:03:53]:
It's just what pops up on the top right bar.

Benito Gonzalez [02:03:58]:
You should just always only do work on your work computer anyway. Like that was never a good idea to do anything other than work on your work computer.

Leo Laporte [02:04:04]:
That was always the message that I took people on the radio show is you should never do anything personal on your company phone, your company computer, or at work or with the company Internet because they have the absolute right to spy on you. What's funny is the law says if you're on a company phone and they listen in on the phone call and they hear you having a private conversation, they're required to hang up. They're not allowed to listen to a private conversation on the phone. That's because older laws protected privacy on phones. Those laws never applied to digital technology. They never got around to making those laws. So unless something's changed, which I don't think it has, I used to talk about this all the time because people would always call up saying, hey, I got in trouble for this. It's like, dude.

Leo Laporte [02:04:50]:
And I always said it would be really good if the company told you. But they don't have to. They Absolutely don't have to. And I bet you knowing Meta that that's always, that's what they've done. Always. And it's their full Right. Right. To do that and to train AI with it.

Leo Laporte [02:05:13]:
That's your work product.

Lucas [02:05:15]:
Yeah.

Benito Gonzalez [02:05:16]:
I think that the employees are probably, you know, thinking like yeah, you're training, you're training the AI to replace you. That's exactly what's happening.

Leo Laporte [02:05:22]:
It's like that's their right as well.

Jeff Jarvis [02:05:24]:
It's a new. I think it's a new implication of what's possible because they have it.

Leo Laporte [02:05:29]:
Yeah, I mean I look, I don't blame them. I wouldn't be happy about it either

Paris Martineau [02:05:34]:
because people in the chat seem to think I'm an idiot. I in no way saying that you should have personal and private access to your work computer. Work computers are obviously work computers and are owned by your employer and the things you do on them are monitored as almost any one of the corporate job has a pop up that says that when you're logging in.

Leo Laporte [02:05:58]:
Right.

Jeff Jarvis [02:05:59]:
Darren Okey has a funny noting that

Paris Martineau [02:06:02]:
there was an article this week, Reuters said that.

Leo Laporte [02:06:05]:
Well that's what I was curious about is what the people were upset about. Was it the AI training or the spying or both? Because the AI training is new. But again I think it's probably the

Benito Gonzalez [02:06:16]:
moment too also like you know, we always assume that we're being spied on by our company but like being told explicitly that we're spying on you is also different. It's better.

Leo Laporte [02:06:26]:
It is better.

Jeff Jarvis [02:06:27]:
Better to be told.

Leo Laporte [02:06:27]:
I think so. I think you're conscious of it than companies Paris. That told you because I don't think a lot of companies do. I really don't. I think a lot of companies just spy on you. Well anyway, I hope somebody has learned something here today and they now know that they should stop buying drugs while they're at work.

Paris Martineau [02:06:52]:
Yeah. Wait till 5:30, get home, use your

Leo Laporte [02:06:57]:
phone, not your company phone. Do you have a company phone and a private phone? Right Paris, I think you said that.

Paris Martineau [02:07:04]:
I mean I have a work phone number and a personal phone number paid phone for by me because I don't want to miss any. I want my to be able to take my work phone number with me wherever I go.

Leo Laporte [02:07:19]:
Right.

Jeff Jarvis [02:07:19]:
Ah, ergo signal.

Leo Laporte [02:07:23]:
You're watching intelligent machines. Guess what's next Picks of the week. Before we wrap things up, Paris Martineau from the very ethical Consumer Reports who I'm sure would tell you if they were spying on you. Right, right, of course it Would. I'm happy to hear that. Conde does that. That's good.

Jeff Jarvis [02:07:39]:
Even Conde.

Leo Laporte [02:07:40]:
Yeah. And Jeff Jarvis, whose personal emails are incredibly dull. So spy away. Right.

Jeff Jarvis [02:07:48]:
My life is an open blog.

Leo Laporte [02:07:52]:
Author of many wonderful books like the Gutenberg Parenthesis. I didn't realize magazine was part of that 111 book. Object Lessons. What an interesting idea that is.

Jeff Jarvis [02:08:02]:
It really is. And the ideas they come up with. There's others. I'm dying to write. I've got an extra book to get out, but then there's others. It's such a fun format to work in.

Leo Laporte [02:08:10]:
What's the retail price of Magazine 22.

Jeff Jarvis [02:08:13]:
But you can buy it online for $11, I think.

Leo Laporte [02:08:15]:
11. So it would be $1121 to buy all 111 of those. Because I would love that on the bookshelf with.

Benito Gonzalez [02:08:27]:
There's no bundle. There must be a bundle, right?

Jeff Jarvis [02:08:30]:
Well, no, it's. It's 111 bookstores is hard. They can't get the whole series in the bookstores, which is difficult. I got a London magazine store to carry the book. Like. Hello.

Leo Laporte [02:08:41]:
Yeah, it's about magazines.

Jeff Jarvis [02:08:44]:
As a professor, I like to watch.

Paris Martineau [02:08:45]:
You gotta have one.

Jeff Jarvis [02:08:46]:
Eileen Giselle. I don't know how to pronounce it. G apostrophe, S E L L. She just put did one on a lipstick and she's been on a. She put herself on a national tour promoting it. It's been fun seeing where all she's

Leo Laporte [02:08:57]:
talking about it actually related to what we were talking about. I forgot. This is one of the stories I had. Defunct startups are liquidating their Slack archives, Jira tickets and email threads by selling them to AI and finding a whole new revenue stream.

Paris Martineau [02:09:17]:
Oh my God.

Leo Laporte [02:09:19]:
So that's exactly everything you wrote every email you wrote, every Slack, you wrote, every JIRA ticket. The company Simple Closure. When Shanna Johnson was winding down CLO24 Cielo24, the transcription and captioning company she ran as CEO, she discovered an unexpected asset. This is from Forbes. Its operational exhaust, the digital leftovers that piled up across years of work and collaboration. She sold to Simple Closure. Everything. Everything on every.

Leo Laporte [02:09:58]:
On the hard drive. Every slack. 13 years of slack jokes, Jira tickets, emails, multi terabyte Google Drive as training data. And she got hundreds of thousands of dollars for it.

Benito Gonzalez [02:10:14]:
This is brilliant.

Paris Martineau [02:10:15]:
Hundreds of thousands of dollars is actually impressive. I thought it would have been much less.

Leo Laporte [02:10:19]:
It's worth something. You know, I'm just thinking our Google Drive is more than 100 terabytes.

Benito Gonzalez [02:10:26]:
No, I'm thinking not Selling our data. We even broker deals between. You'd be a middleman between selling this data from defunct companies.

Leo Laporte [02:10:35]:
See, he's already thinking about a business.

Jeff Jarvis [02:10:38]:
Why wait to be defunct?

Leo Laporte [02:10:40]:
You know what it really is? They've run out of all the public data. There's nothing more to ingest. They ingested it all and now they need something. Something new. That's what Ilya Sutskever says.

Jeff Jarvis [02:10:57]:
That's just to inspire synthetic data.

Leo Laporte [02:11:00]:
Yeah. Paris pick of the week.

Paris Martineau [02:11:04]:
This weekend I went to Depths of Wikipedia live show.

Leo Laporte [02:11:09]:
What?

Paris Martineau [02:11:10]:
Which was a great show put on by Annie. I guess I should have remembered her last name. Annie Raul Ruda. She is. She runs the fantastic accounts called Depths of Wikipedia, which you may have seen on Twitter, Blue Sky, Instagram. And it's this. Was this really funny live show all about kind of the wonders of Wikipedia and has fantastic guests. They still have a show going on, I think in Los Angeles next month.

Paris Martineau [02:11:44]:
So if you're around there and interested in any sort of nerdom or Wikipedia, I'd really recommend it.

Leo Laporte [02:11:50]:
So it's a comedy show?

Paris Martineau [02:11:52]:
Kind of. Yeah, it's a bit of a comedy show. She goes through like a presentation and then interviews people about just incredible fun facts and deep dives into Wikipedia. And it's about also the culture of Wikipedia editing. Some of the interesting time, like the interesting minutia in terms of, let's say like Wikipedia editor on Wikipedia editor violence or the various sort of drama going on in the sub.

Leo Laporte [02:12:25]:
This is very enterprising of her to do this.

Paris Martineau [02:12:28]:
Fantastic.

Leo Laporte [02:12:28]:
Cool.

Ian Bogost [02:12:29]:
She's.

Paris Martineau [02:12:29]:
I mean, it was a package packed house. It was a packed house at the Gramercy Theater. They were so sold out they had to have two different shows.

Leo Laporte [02:12:37]:
She organized a perpetual stool stew.

Paris Martineau [02:12:40]:
Yes.

Leo Laporte [02:12:41]:
In a Brooklyn park.

Paris Martineau [02:12:42]:
The famously organized a perpetual stew. There was a couple of signs up saying perpetual stew this Bushwick Park. And she didn't expect many people to show up, but suddenly I believe there were hundreds, if not more. And there was a New York Times article written about it. She's very funny. She had a couple different guests up for the show I was at, including the woman who is the voice of the New York City subway.

Leo Laporte [02:13:09]:
Oh, that's cool.

Paris Martineau [02:13:11]:
Next stop.

Leo Laporte [02:13:14]:
Did you recognize. Did you go that's her?

Paris Martineau [02:13:16]:
Yes. She sits down. Everyone's like, huh, who's this? And then she goes into the voice and everybody screams.

Leo Laporte [02:13:23]:
The next train is a C train. Yeah.

Ian Bogost [02:13:26]:
Wow.

Paris Martineau [02:13:27]:
Brooklyn bound 4 train. Next stop. Yeah.

Ian Bogost [02:13:31]:
Wow.

Paris Martineau [02:13:33]:
But I'm excited to see. And they're at Great Merch as well. I got a good shirt.

Leo Laporte [02:13:38]:
There's only one more show. It's in Los Angeles, May 9th at Hollywood Forever. She's done Seattle, San Francisco, a bunch of shows in New York, Chicago, Philly.

Paris Martineau [02:13:48]:
And if you have no idea what I'm talking about, I'd highly recommend that you follow her her on Instagram or Twitter or wherever you are, because her accounts are so funny. It's called Depths of Wikipedia and it is just. Let's see if it'll come up here.

Leo Laporte [02:14:05]:
I love it. That ciabatta was invented in 1982 as a rival for baguettes.

Paris Martineau [02:14:13]:
She will post just some of the most interesting tidbits of lore that you could ever imagine about things you.

Leo Laporte [02:14:21]:
It's wild.

Paris Martineau [02:14:22]:
Never, ever even thought of this.

Leo Laporte [02:14:24]:
Clearly that she has massive fan base. I mean, does she have a podcast or just an Instagram?

Paris Martineau [02:14:29]:
No, it's just this. I mean, her Instagram has 1.6 million followers already, which is.

Leo Laporte [02:14:34]:
Wow.

Jeff Jarvis [02:14:36]:
It's brilliant. This. This is. This is the. This is.

Paris Martineau [02:14:38]:
And she's a fantastic Wikipedia editor as well. So.

Leo Laporte [02:14:42]:
Yeah. One of their most famous Wikipedia.

Jeff Jarvis [02:14:45]:
Is there an AI angle we can get her on?

Leo Laporte [02:14:47]:
I think we should just get her on just because it's hysterical.

Paris Martineau [02:14:50]:
I mean, we should. It was fantastic. Yeah.

Jeff Jarvis [02:14:53]:
How did you learn about it? Paris? You already followed her?

Paris Martineau [02:14:55]:
I've. I followed her on multiple platforms for potentially years, and I don't really know when it started or what it didn't, but I just. I love her posts. They're all so funny.

Leo Laporte [02:15:08]:
She's only 26. I mean, she's a young person who's just hit on something crazy.

Paris Martineau [02:15:16]:
Yeah. And she runs a great live show.

Leo Laporte [02:15:19]:
Brilliant. Yeah. You know what? This is. This is why the modern world is so interesting and the Internet is so interesting.

Jeff Jarvis [02:15:26]:
This would not have made it through the gauntlet of Basketia.

Leo Laporte [02:15:29]:
No.

Paris Martineau [02:15:30]:
I mean, one of the anecdotes she told during it is if you look up the Wikipedia article for humans, or I guess, human, there was a lot of back and forth over what photo should be chosen to be on the Wikipedia page for human. And there was also just a lot of internal conflict within the Wikipedia editor community because normally you're not allowed to edit any article that you have any potential relation to all by definition, Wikipedia editors can't edit human because they are human. So once they got around that, they were like, well, what photo should we use? And they ended up using a photo of a AKA couple in Northern Thailand. And she, After, I think the Wikipedia editor conference in Singapore a couple of years ago, ended up flying to Thailand and tracking them down, or ended up tracking their children down because they've since passed. And it showed them that. Yeah, she said basically, Google the word human, click on Wikipedia. And they were like, oh, my God, that's my parents.

Leo Laporte [02:16:40]:
That's very funny. They are the quintessential humans. Her Instagram is depthsofwikipedia. And that's also where tickets are.

Jeff Jarvis [02:16:49]:
Also on Wiki on Blue Sky.

Leo Laporte [02:16:51]:
And I see that Micah already follows her, of course.

Paris Martineau [02:16:54]:
Yep.

Leo Laporte [02:16:56]:
You all know each other. There's Paris also following. That's great. And Megan Maroney follows her. Very nice. Oh, and my favorite, Worcester Terrariums.

Jeff Jarvis [02:17:08]:
She has lots of good followers, including aoc.

Paris Martineau [02:17:11]:
Yeah, it's a big screen.

Jeff Jarvis [02:17:13]:
Jamel Bowie.

Leo Laporte [02:17:14]:
Amazing.

Jeff Jarvis [02:17:15]:
Brandy is a Drozney. Amazing.

Paris Martineau [02:17:23]:
What are you laughing at?

Leo Laporte [02:17:24]:
I'm looking at the Wikipedia entry for ketchup effect. The ketchup effect is when nothing comes then way too much, very fast. That's it. That's the whole article.

Jeff Jarvis [02:17:35]:
Ketchup effect on Swedish Wikipedia.

Leo Laporte [02:17:38]:
Yeah, ketchup effect.

Paris Martineau [02:17:42]:
I mean, that's the thing is the whole account is just little things like this that are just flavorful.

Leo Laporte [02:17:48]:
That's fantastic. Oh, my goodness. Let's see. My pick of the week. I had a couple. I've forgotten completely what they were. One of them is because we were talking about how Claude now has Claude design. Anthropic has Claude design.

Leo Laporte [02:18:06]:
And then Google, which has Stitch, which does kind of the same thing, lets you design your own, you know, design stuff with AI. Somebody at Google said, you know, you know how we could. We could trump Anthropic's Claude design? Let's just give them all our prompts for Google Stitch, and they can run it in Claude code. And they don't even need Claude design. So this is on GitHub, Google Labs Code Design MD. It's the prompts you need to basically turn Claude code into Google design, which is probably something very close to what Anthropic did to create Google Design. I think that was kind of a nice little competitive jab from Google. And then the other one is maybe a little bit more important.

Leo Laporte [02:18:54]:
And it's something we were talking about is your website agentready at. Let me see, what's the isagentready.com so you put in your website here. Why don't we put your website Paris, NYC and just see how. How ready for Agentic AI it is for mcp, for markdown negotiation, for agent skills. It'll do a Scan will it? Oh, yours is better than mine.

Paris Martineau [02:19:28]:
I was about to say it. It scans to paris martineau@parismartner.com, right?

Leo Laporte [02:19:35]:
Oh, it did. It's it automatically redirected.

Paris Martineau [02:19:37]:
Mine's better than yours.

Leo Laporte [02:19:38]:
Yeah, mine is only 17. Yours is 25 out of 100. I make no attempts to make it compatible.

Paris Martineau [02:19:47]:
I mean, I've made no attempts to make it compatible.

Leo Laporte [02:19:49]:
Oh, you have bought access control set on yours. That's I think the big difference. I don't know, maybe you're a host to it.

Paris Martineau [02:19:56]:
What is this website?

Leo Laporte [02:19:58]:
Is this is kind of a terrible URL?

Jeff Jarvis [02:20:00]:
Is it agentready?

Leo Laporte [02:20:02]:
Is it agentready.com?

Jeff Jarvis [02:20:04]:
what was Paris's score?

Leo Laporte [02:20:06]:
25.

Jeff Jarvis [02:20:07]:
I got 33@jeffjarvis.com.

Leo Laporte [02:20:09]:
nice. Twit gets a lowly 17 as well, and as does BLO FM. So Paris, you beat Twit and me. Jeff, you beat Paris and Twit and me. But probably this is more seriously to the whole thing we were talking about, which is I think everything has to be. What did you call it? Aioa.

Jeff Jarvis [02:20:32]:
AIO is. Well, there's one, it was called Geo Generative Engine Optimization. But you know, in some schools that's over Liam.

Leo Laporte [02:20:41]:
So AI Optimization. Optimization.

Jeff Jarvis [02:20:42]:
A optimization, yeah.

Leo Laporte [02:20:44]:
And Jeff, you used up a bunch of picks. Are there any left?

Jeff Jarvis [02:20:46]:
Oh, I, I, I want to come. I have a happy ending to my long saga, okay. On getting Ask Gemini into my browser, on my Google Chrome, on my Google Chrome, on my Google workspace. So there was another story about more features that are added. But once a month I go to my admin settings and I say, surely there's been be something left out, something new. I'm going to go through all of them. I go through all of them, I find nothing. I have said yes to everything.

Jeff Jarvis [02:21:13]:
I am my administrator. I am the entire site. I am it. But now there was a new feature. There was, you can use Gemini on the admin site to get help with admin. So I thought, okay, I put my complaint in. I say, hello, I'm. This is this, this and I don't have it on my browser.

Jeff Jarvis [02:21:31]:
And it comes back and it says, we need to set this, this and this. And I went back and I said, I have. And I said, it's still not working. And it came back and it said, no, no, no, if you do this, this, this, it'll work. And I said, I have your wrong. No, I still don't have it. Third time it said, oh, try this setting that you would never find. And I'd Gone through everything about.

Jeff Jarvis [02:21:57]:
About. You think it'd be in the Gemini part? No. You think it'd be in the Apps part? No. Hidden three layers into the user. There was a special thing where you had to set defaults to. Okay. Now mind you, I shouldn't have gotten AskGemini on anything on Gmail or anything by this. I got it on everything except Chrome in my Chromebook.

Jeff Jarvis [02:22:20]:
The one thing you wanted three boxes. And now I have it. Wow. Now what I do with that I have. I used it it.

Leo Laporte [02:22:28]:
No, I actually you don't really want it. But I took.

Jeff Jarvis [02:22:30]:
Well, the only thing I've done so far is when I read tried to read the Yann Lecun the World bottle.

Leo Laporte [02:22:35]:
Oh, it's good for that. Yeah.

Jeff Jarvis [02:22:36]:
I said explain this to me. It did a good job. It did a very good job. I now have it. So I'm not going to say all is forgiven because I begged here a hundred times and no one told me.

Paris Martineau [02:22:46]:
It's true.

Jeff Jarvis [02:22:48]:
I bored the world.

Leo Laporte [02:22:49]:
Three check boxes and you're in, Jeff.

Jeff Jarvis [02:22:52]:
I'm in. Meanwhile, one more line. 152 bonito. Are you going to show your loyalty and get one of these with Leo on it?

Leo Laporte [02:23:00]:
Oh, now I'm worried.

Benito Gonzalez [02:23:03]:
Me too.

Leo Laporte [02:23:05]:
Must have item in Silicon Valley. The $178 sweater with the CEO's face on it.

Paris Martineau [02:23:12]:
Leo, when are you going to get ones of this with for all of us? Yeah. Be a great.

Leo Laporte [02:23:17]:
That's a jet skit. No, I have not sufficient ego. I know you don't believe me when I say this, but I do not have sufficient ego to send you all sweaters with my picture on it. That would be appalling.

Jeff Jarvis [02:23:30]:
Alex Karp has his on a T shirt.

Leo Laporte [02:23:33]:
What a surprise.

Paris Martineau [02:23:34]:
I think that's even. I. I don't know.

Leo Laporte [02:23:36]:
What do you think?

Paris Martineau [02:23:37]:
More appalling sweater. Okay. Yeah. The fact that the T shirt says dominate. Yeah, that's.

Jeff Jarvis [02:23:42]:
That's.

Leo Laporte [02:23:44]:
Wow. Now, I don't mind the Hawaiian shirts that Anduril sells based on Palmer Lucky's Hawaiian shirts.

Benito Gonzalez [02:23:56]:
The guy who makes your T shirts. You should get them to make a Twit one or a Leo.

Jeff Jarvis [02:23:59]:
Yeah, yeah. Somehow to incorporate the Twit logo into it.

Paris Martineau [02:24:04]:
Wait. Yeah, can you get someone.

Benito Gonzalez [02:24:06]:
So it's in that guy's house.

Paris Martineau [02:24:06]:
Make a version of your colorful Hawaiian shirts, but with your own face on it.

Leo Laporte [02:24:15]:
Paris, don't mock me. I know you would not wear anything that had my face on it.

Paris Martineau [02:24:19]:
I would wear it for this show.

Leo Laporte [02:24:21]:
Just for this show?

Paris Martineau [02:24:22]:
For an episode.

Leo Laporte [02:24:23]:
Well, Twit TV store. Nothing has my face on it, but there's one. Yes.

Jeff Jarvis [02:24:30]:
We need a Hawaiian shirt.

Leo Laporte [02:24:31]:
Oh, wait a minute. It does have something with my face.

Paris Martineau [02:24:34]:
Just scroll up. You just scroll down your own face. Yeah. Yes, go up.

Leo Laporte [02:24:37]:
Oh, my God. Right there. I think we may.

Jeff Jarvis [02:24:45]:
Well. I would never do that. I don't have much of an ego. Not only is his face, but Chief.

Benito Gonzalez [02:24:51]:
Chief, Chief, Chief Twitter saga.

Leo Laporte [02:24:55]:
We did it when Elon took the name Chief Twitter, and I had nothing to do with it. I just want to tell you, I didn't say, smithers, make a T shirt with my face on it. Call it Chief Twit. Okay, I take it back. I guess. I guess you can buy that Twit TV store.

Jeff Jarvis [02:25:14]:
And.

Leo Laporte [02:25:14]:
Yeah, you should buy it now, Paris, you have to retract that you want it because otherwise you're gonna get it for Christmas.

Paris Martineau [02:25:21]:
Yeah, I mean, that's what I was thinking about.

Leo Laporte [02:25:24]:
No, yeah, I know. I know it's not what you were thinking.

Paris Martineau [02:25:26]:
You know, I was hoping there'd be

Leo Laporte [02:25:27]:
some wine shirt would be better. Yeah.

Jeff Jarvis [02:25:29]:
The guy who makes.

Leo Laporte [02:25:30]:
We are going to Hawaii. We used to have a lot of the twit hoodies that we used to sell were really great. These are not quite as nice as the ones we used to sell. You know, the reason is you just make no money on these. And. And we'd have to. We have to charge so much for these to make even a dollar that

Benito Gonzalez [02:25:49]:
it's, you know, to do collabs and limited time drops.

Paris Martineau [02:25:53]:
Yeah, we got a this week in Google sticker.

Leo Laporte [02:25:56]:
Yeah. Isn't that funny? But there's nothing for intelligent machines, is there?

Paris Martineau [02:26:00]:
There is a lot of stuff for intelligent.

Leo Laporte [02:26:02]:
Oh, is there? Oh, good. There's homeware.

Paris Martineau [02:26:05]:
There's intelligent machines.

Leo Laporte [02:26:06]:
Totes holiday. I don't know what that is. Ceramic ornament for your tree. Somebody's having. Oh, there, look. There is an intelligent machines Die cuts. Oh, yeah, look at that. That's nice.

Leo Laporte [02:26:20]:
Pets. What do we have for pets? An ask the tech guy's pet T shirt and you can get a mug. Intelligent Machine's mug. That's fun. I think Anthony does this when he's feeling like a little bored. Bored. Puts these together. All right.

Jeff Jarvis [02:26:40]:
Get your twig merch before it goes. It's a gone away from collector's item.

Leo Laporte [02:26:46]:
Hey, by the way, I should mention, Jeff, I forgot to mention this. Google is apparently working on a Pixel laptop. Yeah, Pixel glow lights. Because you can see apparently something in the latest beta releases of Android. Android 17 beta reference to a feature called Orbit.

Jeff Jarvis [02:27:09]:
What are some light animations? Might be the aluminum laptop Pixel Glow. Guess what I bought this week.

Leo Laporte [02:27:17]:
A new Mac by a Neo.

Jeff Jarvis [02:27:20]:
But a Neo.

Leo Laporte [02:27:21]:
Oh, cassette is the bill.

Jeff Jarvis [02:27:23]:
No, no, no, no, no, no. Let me, let me complain though.

Paris Martineau [02:27:26]:
Are you going to be using the Neo for this? Can the Neo even support stream?

Leo Laporte [02:27:30]:
Oh, totally. Yeah, yeah, yeah. I'm on a 12 year old Mac, Intel Mac mini.

Jeff Jarvis [02:27:37]:
12 years old? Yeah, and it works fine.

Leo Laporte [02:27:40]:
I'm using an M1 Mac mini that probably has 8 gigs of RAM to do the show right now. Benino's using something a little heavier duty.

Jeff Jarvis [02:27:48]:
So I go in the store and I say, I want to buy a Neo. I want the blue one. I want this education.

Leo Laporte [02:27:54]:
Good choice, right?

Jeff Jarvis [02:27:56]:
Oh, no. Well, I'll sign you up for a specialist. Go sit over there in my, My cane. Incredibly uncomfortable. Drives me nuts. Used to be in the day, if they were busy, anybody would. Oh, I can write that up for you now. No, no, no, no, no.

Jeff Jarvis [02:28:10]:
I sat there for more than a half an hour.

Leo Laporte [02:28:14]:
Oh, for the privilege. Giving your money.

Jeff Jarvis [02:28:17]:
I. I left. I left, I said, and I'm walking out the scheduler. I went to the scheduler at some point. I said, come on, man, I know what I want to buy. Just sell it to me. There's no way to run a store.

Paris Martineau [02:28:25]:
No way to run a store.

Leo Laporte [02:28:26]:
No way to run a store.

Jeff Jarvis [02:28:28]:
Yeah, they didn't like that. So I walk out, I say goodbye, and he didn't catch the nuance of my voice and said goodbye.

Paris Martineau [02:28:35]:
Or maybe he did, but is used.

Jeff Jarvis [02:28:36]:
Maybe he did, but I don't think Apple people would have that much irony. So I go home and I order.

Leo Laporte [02:28:41]:
Did you shake your cane at him when you said, that's no way to run a store?

Jeff Jarvis [02:28:45]:
I should have. Meanwhile. Meanwhile, my Chromebook died.

Leo Laporte [02:28:49]:
Oh, how did. It's brand new.

Paris Martineau [02:28:52]:
Was it before or after you got Gemini on it?

Jeff Jarvis [02:28:58]:
Good question. Before

Leo Laporte [02:29:01]:
it died, before you got Gemini on it. Now I question that.

Jeff Jarvis [02:29:04]:
It went black and it couldn't, it couldn't, couldn't boot. So there's some hardware problems. So it's now slowly, FedEx is very slow. I got it to FedEx on Sunday. It's supposed to be delivered to the place on Thursday. Then it's seven to 10 days to do it and then time to get it back. So I decided, okay, there's no way

Leo Laporte [02:29:21]:
to run a store. So did you mail order a Neo?

Jeff Jarvis [02:29:25]:
No. No. Because actually, no, you couldn't get the Neos until midday. Oh, they happened to have it at my local store.

Leo Laporte [02:29:31]:
Well, the other stores go online. You buy it online and you say, I want to pick it up at the store.

Jeff Jarvis [02:29:35]:
Exactly, yeah. Or I go in and. That was nice. Nice and efficient. That was easy.

Leo Laporte [02:29:39]:
Yeah, that's very efficient. They just give it to you.

Paris Martineau [02:29:41]:
Did you get one in a fun color?

Jeff Jarvis [02:29:43]:
Blue? I like the blue. No, I didn't get the greeny one. No, the blue's nice.

Leo Laporte [02:29:47]:
The blue's nice. I think we all agreed on Mac pretty quickly. That's the.

Jeff Jarvis [02:29:50]:
There's nothing. I, I should not, I should not move any, anything over from the 12 year old Mac Mini.

Leo Laporte [02:29:56]:
Probably not.

Jeff Jarvis [02:29:57]:
No.

Leo Laporte [02:29:59]:
Yeah, because those will all be intel programs. Don't don't even, don't even. Just download a new copy of Zoom and you'll be fine. Yeah, yeah. Well, thank you, Jeff, for your commitment to the show. I appreciate that. That's very nice of you. And we would buy that for you if you want.

Jeff Jarvis [02:30:13]:
No, no, no, no, no, no, no, no, no, no. I've used this one for 12 years.

Leo Laporte [02:30:16]:
If we buy it for you, though, you understand we will use all clicks, all documents.

Jeff Jarvis [02:30:21]:
Yes. And sell it to.

Leo Laporte [02:30:23]:
And send it to Grok. Yes, we'll send it to Grok.

Paris Martineau [02:30:27]:
Yeah. Actually, if they buy it for you, they're going to put Bad Rudy on your computer.

Leo Laporte [02:30:33]:
Bad Rudy's good. Thank you, everybody, for joining us. Thank you. Paris Martineau. You'll find her at Consumer Reports. You're still on, on Deadline, are you,

Ian Bogost [02:30:42]:
Are you working on this?

Paris Martineau [02:30:42]:
No, I just, you know, we got a lot of things going on and I am the person who has to solve all of those problems. But a story will come out of it. I do love it.

Leo Laporte [02:30:52]:
You love it. This is.

Paris Martineau [02:30:53]:
And tomorrow, if you happen to be a retiree in Westport, Connecticut, it. I'm going to be speaking to you.

Jeff Jarvis [02:31:00]:
Really?

Paris Martineau [02:31:01]:
Me and some of my colleagues are doing a food safety discussion for the wise men of Westport tomorrow.

Leo Laporte [02:31:09]:
You're talking to the wise men of Westport now?

Paris Martineau [02:31:12]:
We think it's the letter Y at the Y could be discussing. It should be at the men May or may not be wise. It's not at the Y either.

Leo Laporte [02:31:22]:
The wise men at Bridgeport.

Jeff Jarvis [02:31:25]:
So. So it's don't leave fish in the refrigerator for two weeks. Is that what, what you're doing?

Paris Martineau [02:31:30]:
No, actually, we're talking about kind of an inside look at how Consumer Reports, like three pillars, the testing, the testing team, reporting, and our advocacy teams kind of work together. And they are particularly interested in our Food safety coverage, specifically the protein powders investigation. And in my reporting on radioactive shrimp, of course, taking them through it by, like, kind of a deep dive into protein powders.

Jeff Jarvis [02:31:58]:
Well, if I. If I weren't going to my wife getting an award tomorrow, I would call up to Westport as a retired man.

Paris Martineau [02:32:03]:
Congrats.

Leo Laporte [02:32:04]:
So bring your cane and your food safety questions.

Paris Martineau [02:32:08]:
Yes, true.

Leo Laporte [02:32:09]:
For the wise men of Bridgeport. Well, they're very fortunate to have that. That's lovely.

Jeff Jarvis [02:32:15]:
How are you going to get the Bridgeport?

Paris Martineau [02:32:17]:
Well, I'm getting to West. It's Westport. I'm getting there by taking the train very early tomorrow and then going to be picked up at the Westport train station. As you deserve, content officer.

Leo Laporte [02:32:30]:
Nice. We'll have a wonderful talk.

Paris Martineau [02:32:33]:
Yeah, I shall.

Leo Laporte [02:32:34]:
Yay.

Paris Martineau [02:32:35]:
I was gonna say everybody was. We were all discussing this week, like, oh, do you guys need to prep and stuff? I'm like, I. I can talk.

Leo Laporte [02:32:44]:
I have some practice. Just let me go. Nice.

Jeff Jarvis [02:32:49]:
Put a mic in front of me. And.

Leo Laporte [02:32:51]:
Nice.

Jeff Jarvis [02:32:51]:
And by the way, should we note the dulcet tones remained the entire show? Did not. Did they not?

Leo Laporte [02:32:58]:
They did.

Paris Martineau [02:32:58]:
There was a brief moment where we thought we were flickering, but they have remained. And Gizmo is currently laying on top of the scarlet. And so I would expect that would be impacting it, but it isn't.

Jeff Jarvis [02:33:12]:
I think.

Leo Laporte [02:33:12]:
She always do that.

Paris Martineau [02:33:14]:
No, because I usually pick her up, but I didn't.

Leo Laporte [02:33:18]:
Overheating could explain it.

Paris Martineau [02:33:20]:
It's not. She's not on top of it. It's just she, like lays in front of it and definitely touches it.

Leo Laporte [02:33:26]:
I think it's doing it now, by the way.

Paris Martineau [02:33:29]:
Well, it could have been because I was wrestling a cat as I said that.

Leo Laporte [02:33:37]:
Okay, my friends, thank you. Jeff Jarvis. Don't forget his new book, Hot Type, available now@jeffjarvis.com for pre order. It comes out the same time as Ian's book.

Jeff Jarvis [02:33:48]:
No, it actually comes out in now in August because they were going to come out. It was supposed to come out in June. Then they moved it for production reasons to July. And I said, I'm not gonna say this to Ian, but July's dead time. So they moved. It's now an early fall book.

Leo Laporte [02:34:03]:
Okay. You'll still get it if you order it now.

Jeff Jarvis [02:34:06]:
Yeah, if you order it now.

Leo Laporte [02:34:07]:
It'll make me happy, it'll make Jeff happy, and that's our goal in life. Thank you, everybody. You've made us happy by joining us. We'll see you next week on Intelligent Machines. Bye. Bye. I'M not a human being.