Kimi K3 & AI’s Price War, What Happened To Google?, OpenAI’s Partner Trouble

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) Kimi K3's benchmark breaking results 2) How Kimi K3 fits alongside MuseSpark 1.1 and Grok 4.5 3) What are OpenAI and Anthropic's advantages today? 4) Is the price of frontier intelligence about to drop? 5) It's all about the product now 6) Satya Nadella's Reverse Information Paradox 7) What is happening at Google? 8) Is Google too focused on 'Flash' models 9) Apple's lawsuit vs. OpenAI 10) OpenAI's boneheaded espionage 11) Why does OpenAI struggle to maintain good relationships with partners? --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here’s 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  The walls are coming down for OpenAI and Anthropic as cheaper models and new open source competitors from China challenge their ability to make a profit. Google, meanwhile, delays its flagship model and seems to be spinning its wheels. And why can't OpenAI keep its partners from hating it? That's coming up on a Big Technology Podcast Friday edition, right after this. This episode is brought to you by Genesis. What does it actually take to put a Gentic AI to work across an entire enterprise? I recently spoke with Genesis chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience and what companies need to get right in the AI era. Then I sat down with Adam Mitchell, head of enterprise business solutions at Voya Financial,

• 0:43Speaker 00

  to go inside a large-scale agentic CX transformation, including the business decisions, trade-offs, and lessons along the way. You can watch both conversations now on my YouTube channel today.

• 0:56Speaker 00

  It's never been more challenging to get frontier compute. How do you know where to look, who to trust, or how much to pay? Akash is an open cloud that provides easy access, flexibility, and peace of mind. That's how companies like Razer were able to cut their inference cost by 15 times. Visit akash.network/alex for a free consultation. That's akash.network/alex for a free consultation. Welcome to Big Technology Podcast Friday edition, where we break down the news in our traditional cool-headed and nuanced format. It's the Kimi K3 episode. We're going to talk all about this new challenger from China, a 2.8 trillion parameter model

• 1:38Speaker 00

  that is taking on the frontier and beating basically every model except for Fable. So we'll get into the implications of what happens after that. And when there are price war is really getting underway, especially now that Meta and SpaceX have released cheaper models. We're also going to talk about the state of Google, what's going on there. Why is their latest model delayed? And of course, OpenAI, we didn't even get to it last week. By the time we recorded, it was, it was too early because just a few hours later, Apple would announce they've, they had sued OpenAI. So of course, today we'll talk about the lawsuit and more importantly, why OpenAI cannot hang on to its partners, at least not for long. Joining us as always on Fridays to do it is Ranjan Roy of Margins. Rajan, good to see you.

• 2:20Speaker 01

  Happy Kimi K3 day. Are you ready?

• 2:24Speaker 00

  I sure am, because this is a massive week, a potentially earth-shaking week in the AI story with the entry of Kimi K3 into the conversation. So let me just read the story from Bloomberg and then we can discuss it. Bloomberg says China's powerful new AI surprises investors, fueling a tech route. A surprise breakthrough from Chinese AI startup Moonshot rippled through global markets Friday, sending AI and semiconductor stocks sharply lower as investors drew parallels with last year's DeepSeek moment. The catalyst was Moonshot's new Kimi K3 model, which the company said rivals the strongest offerings from OpenAI and Anthropic. The launch was quickly dubbed the new Kimi moment. This is an interesting quote from Wei Cernling, who's a managing director at Union Binaquer

• 3:09Speaker 00

  Privy. He said, "People are worried that if US companies start using Chinese models more and Anthropic less, Anthropic will invest less. That means US firms will lower the CapEx and, and in the end, the chip demand will be affected." So basically, here's the story.

• 3:29Speaker 00

  OpenAI and Anthropic own the frontier, but there's a set of models that were effectively, you know, 10, 15 months behind them, that were basically jumping in and something that you could route like your lower intensity tasks to. All of a sudden, Moonshot, which has had basically released the very successful Kimi K2, comes out with this new massive 2.8 trillion parameter models, model Kimi K3. And it is right there with GPT-5.6, Sol, and Opus 4.8 on almost all the benchmarks. In fact, it even beats Kimi K3 on something called Program Bench. It beats, sorry, it beats Fable 5 on Program Bench.

• 4:10Speaker 00

  It beats Fable 5 on SWE Marathon, and it's right there in league with, you know, all the other top models on all of the benchmarks that we look to, to assess model quality. It's a big moment because it seems to show that China's open source movement is not the 10 or 15 months behind US AI, but maybe four or five months at the very, at the most, maybe even less than that. And when that happens, you know, your, your rationale for going with, you know, the closed more expensive model as opposed to one of these OpenAI model, oh, sorry, one of these open source models gets less and less. And you start to wonder, is there actually a benefit in building frontier intelligence

• 4:55Speaker 00

  if you're going to be equaled this quickly? So that is my outlook on it. Rajan, what do you think about this?

• 5:01Speaker 01

  I think this is a massive moment. I do think this is actually on par with the DeepSeek moment because it's the same principle at work again. It's the idea that, you know, like as you said, that the frontier model, why invest in it? Why is it so important? Is that truly a moat and a competitive edge versus to actually build things at work? Is there a cheaper and better way? And this reminds us, and I mean, I've been saying this for a while, like, is our frontier models required for the majority of tasks that are going to be done and become agentic? And I don't think they are. And now having a very powerful model that's just a lot more affordable and is also open

• 5:44Speaker 01

  source, I think is exactly where companies are going to go. I think, let's hold off in terms of what it means for the overall US versus China tech. I'm not going to call it a tech war, but I think before getting there, I do think this is going to already, in the last few months, so many of the conversations I've been in have shifted to model interoperability. What is the best model for the best task? And now even more so realizing that actually, why do I need Fable? Why do I need 5.6 when I can actually have all these other options? And the model gets a bit more commoditized and it becomes about the harness and the process and the data.

• 6:27Speaker 01

  I think this is, this, I don't, I don't want to say it's like a transformational moment, but I think this is actually going to be a moment where even more so the idea that frontier models are a massive moat really goes away.

• 6:44Speaker 00

  Well, here's the thing. So Kimi is not massively cheaper than any of these other models. And it also doesn't really beat, you know, the latest frontier models on these benches, on these benchmarks. So for instance, it doesn't really beat Fable in, in, you know, most benchmarks here. It beats 5.5 and 5.6 from OpenAI. It beats Opus 4.8, but it doesn't beat the others, right? It doesn't beat sort of the, the top-notch Fable models. Okay, so it's not markedly better. It's also not that much, it's not cheaper than Grok's 4.5 model or Meta's Muse Park 1.1.

• 7:25Speaker 00

  Those are cheaper and those are also competitive in some benchmarks with the, with the Opus 4.8 and the GPT-5.5s.

• 7:34Speaker 01

  All right, so.

• 7:35Speaker 00

  So go ahead, go ahead. I'm just setting the table here, but go ahead.

• 7:38Speaker 01

  No, no, of course, of course. To me, the benchmark side, like the kind of like, what is that kind of final delta between, you know, on the deep SWE benchmark or the frontier? Like, to me, that really is less important than if it is in the general quality range of a 4.8 or a 5.5, you're in business. So I think on that side, the fact that on some, it actually beat Fable, on others, I love that we just actually threw in Grok 5.5. I guess they're still, he's still going for it.

• 8:13Speaker 00

  No, they are, they are. Grok 5, 4.5 actually, you know, was competitive on coding benchmarks. It's apparently more token efficient and most importantly, it's cheap. So this was also, since the, over the past eight days, we've seen Meta and Grok show up to the game, not in models that are better than let's say 4.8 and 5.5, sorry, Opus 4.8 and GPT-5.5 and 5.6. But like you said, models that are almost as good, that deliver this at 25 or 50% of the price.

• 8:42Speaker 01

  Well, so, but, but that's why I actually, what I found most fascinating about the way that this has been released is it's not massively cheaper, but it's cheaper. $3 per million token input, $15 output. It's 40% cheaper than GPT-5.6, 70% cheaper than Fable. And again, Meta's already come in hard, Grok's coming hard as well. I think this is, what makes this even more of a significant moment is a Chinese company coming in and saying, we're not going in as like significantly cheaper. We're, we're actually battling on quality and a little bit more affordable and you have more control over it, which is why I think it's very different.

• 9:26Speaker 01

  DeepSeek's whole thing was it pure price. Like, can we get something that's? Not even as good, but just in the general vicinity and far cheaper. Now, this is the first time we're actually seeing no. On actual quality, it's competitive. Again, is it better or not as good as Fable 5 or GPT 5.6? I think we'll see over time, but I mean, this is not dirt cheap stuff. This is not something you buy off Timu. This is actually good quality and reasonably affordable. And it's just making us realize that like, again, to me, the front.

• 10:08Speaker 01

  And we can get into that idea of like, is that gonna actually completely distort the investment cycle? Because Anthropic realizes Frontier is no longer the moat, so they're not gonna invest. I think we should get into that, but I think it's a big moment. Cause now more and more, you're gonna hear everyone talking about what's the most efficient and cost effective model for the task. And I'm already hearing it, but now it's, I think it's gonna be far more. Whereas six months ago, it was like, how could you not do anything on the Frontier model? It's obviously the best.

• 10:41Speaker 00

  Yeah, so there's, there's a couple of important points here. The first is that, you know, in the past, while you might think, okay, I need the best version of intelligence, so you would hot, you'd bring in Anthropic or OpenAI's forward deploy to engineers to build something for your company with their best models. This model from Kimi is gonna, from Moonshot is gonna be open weight. So what you could do is basically if you get the right people in, you could download the weights, you know, and sort of build it, build your application for yourself with it, although it is massive. So you need a lot of infrastructure to do this, right? So that's gonna be for like, let's say the governments or the JP Morgans of the world. We've already seen Apple do a version of this with Gemini, right?

• 11:23Speaker 00

  So the question is, does Apple go to Google or OpenAI or Anthropic to do something like it did in building Apple Intelligence on a really good model? And we've seen the, the progress they were able to make there. Or does it work with an open source model? The other side of it is, you're gonna get this, this model downloaded and put on all the clouds. And that's where the commoditization comes in, right? Because right now, the pricing that you listed, that's the pricing that we get from Moonshot, right? Can these clouds find a way to deliver it even more efficiently? So giving people Frontier Intelligence at an even lower price. And that's when, that's when you really get into an interesting, interesting world where

• 12:04Speaker 00

  like the, the business on the API side, the business of OpenAI and Anthropic was, we are gonna build a model that is that much better than anything else out there, and we're gonna charge you a premium to use it, right? So we will market up in a, in a massive way. And when you have these two forces coming at it, you have the Metas and the Grocks coming in with comparable models at much cheaper. And then you have the, the open source Chinese models coming in and giving you effectively the same performance as some of your better models at a price that's competitive. It does get you to a point where you start to ask, from the API side, is there profit? Does this all become a commodity?

• 12:48Speaker 01

  And then let's also recognize the fact that like Anthropic completely shifted its strategy to the enterprise and they did a very good job of that. OpenAI, it hasn't really like become as dominant in that way, but they're certainly investing very heavily and they've made significant moves around enterprise. And what you just said right there, the companies, like you and I are not gonna be cranking out our own version of Kimi K3 on my MacBook Pro. It's a pretty good MacBook Pro, but it's, I'm not, I'm not gonna be running. Yeah, exactly. So, but large enterprises will potentially, or as you said, the cloud services will be

• 13:31Speaker 01

  kind of bringing in their own offerings here. So I think OpenAI's story and their pivot gets hit harder than anyone else with this announcement, because suddenly why OpenAI becomes a much more salient question than it was just a week ago.

• 13:51Speaker 00

  Yeah, I want to read you an analysis from Gavin Baker, who's sort of, who's an investor, managing partner at Aristides Management. He's done the podcast circuit, but his analysis on this was, was actually excellent. And it kind of shows you where the challenge hits and where the benefit comes. So he says, Kimi K3 may be an important inflection point for AI, potentially negative for Anthropic and OpenAI, while being net positive for essentially every other company in the world. A world where there's only two to three dominant Frontier Labs with 90% inference margins is net negative for every other layer, while being awesome for those two to three Labs. Those Labs would become monopsonies for power, data centers, semiconductors and hyperscalers, and would obviously vertically integrate over time into all those layers, while also completely subsuming the application software layers.

• 14:36Speaker 00

  Anything that lowers the margins and increases competition at the model layer is good for every other AI layer, power, semiconductors, hyperscalers, NeoClouds, and yes, even software. I think that captures it.

• 14:49Speaker 01

  Yeah, and also monopsonies, monopsony is one of my favorite words. I still remember it from under Grant, Grant Econ is where there's one dominant buyer rather than dominant seller. And I think like, it is the, I'm so curious, man, Anthropic's S1, I just wanna see it so badly. I'm sure they'll be able to tell a reasonable story, but like, again, is it, the story was 90% inference margins. Do the training, invest the money, your model becomes dominant, and then you make a ton of money. This cuts so directly into that. And I think this is why, that this makes the entire AI story completely new and brings

• 15:32Speaker 01

  in just a lot more opportunity and a lot more players. And, and like, I, I mean, the vibe shift on Twitter has been wild in terms of like, again, six to eight months ago, everyone who's just like Claude and Anthropic, there's unstoppable, greatest thing in the world. Everyone is now obsessed with what is the best model for the best task, Kimi 3, harnesses, everything like, which is good. Competition is good. This is exciting.

• 16:00Speaker 00

  Yeah, more Baker. He says, "An open source model requires the exact same amount of compute to run as a closed Frontier model of a similar size and architecture. Kimi K3 is roughly the same size as GPT 5.6 Terra on a per token basis, which actually suggests that it's less computationally efficient. That being said, lower margin at the model layer." So going back to this question of like, will the OpenAI and Anthropic not be able to, you know, command those 90% margins? What happens? Baker says, "It's more margin at every part of the infrastructure layer, and it's a godsend for software. This can happen either through open source models like K3 at the Frontier, or having vertically integrated models like Meta, SpaceX, or Google at the Frontier, which is exactly what we're talking about. We're seeing that.

• 16:45Speaker 00

  Google to come." He says, "Both outcomes result in a lower margin at the model layer, and as vertically integrated model companies don't really care where the margin comes from. This is why it was so painful for OpenAI and Anthropic was Google, when Google was right there with them from a model competitiveness perspective, and my Grok 4.5 and Muse 1.1 were just as important as Kimi K3, right? So this is all happening in conjunction at this week."

• 17:15Speaker 01

  So what do you think OpenAI and Anthropic need to do? I mean, I guess OpenAI, you make a speaker and physical devices or clouds or all these other business lines, but Anthropic, I mean, this is their business right now. This is inference margins, that's the entire game. So they start to feel even more under threat. If you're either of those companies, what do you do?

• 17:43Speaker 00

  Okay, so I'm gonna read some more Baker, cause he talks a little bit about it. And then I'm gonna give my own perspective. He goes, "The reason Kimi K3 is only potentially negative for Anthropic and OpenAI is, one, the Claude and ChatGPT products and harnesses may be more important than their models today. And two, the hypothesis that they have much more advanced model checkpoints internally that are already being used for recursive self-improvement. In the latter scenario, reaching recursive self-improvement even a few months ahead of the other Labs might be enough to cement a provenant lead." Okay, I'm gonna tackle the second one first and then the first part, okay? So basically, there's a theory that they have like, you know, self-improving AI internally already, and then therefore that will help them open up a gap, you know, far ahead of any other competitor. I don't believe that.

• 18:28Speaker 00

  And I don't believe that that's actually, you know, defensible, given how far we've seen these models, the open source models and the competitor models start to catch up, or how quickly we've seen them catch up. This is from Ryan Greenblatt, who's a researcher. He says, "I now expect an open weight AI, which is straightforwardly mythos level at cyber, in like five months, supposing Kimi and the others don't change their open weight model policy." All right, so that is how close the open source world is to the Frontier right now. And so any like, you know, sizable tech advantage or model advantage or intelligence advantage, I don't believe in. I don't believe in anymore. And it was always treading this way.

• 19:12Speaker 01

  I mean, but this is where the whole AGI, and I like that we made it this far without actually saying AGI yet, but I mean, when I've spoken with people at these companies and spoken with others, like, there still is this belief, and we debated this last week, like, all the things that you can do about model efficiency and the right model for the right task, if you just get smarter and smarter, you can just subsume the need to even think about all of that, and the model is just so good, it does everything. But I don't know, like, to me, it feels more and more, like, no one's talking about that now. Even hearing recursive self-improvement at these Labs, it's gonna give them some significant edge.

• 19:53Speaker 01

  I don't know, is that significantly different or real if Kimi's able to, or Moonshot is able to do this? I don't think it is.

• 20:01Speaker 00

  No, there's been no evidence that you could hoard that. That's the whole point, right? So Nick Clegg, who is, you know, executive at Meta, came on this show a couple of years ago, and basically said, "I don't understand why any of these companies, like, where are the profits gonna come from pursuing superintelligence, since I don't think you'll be the only company that's gonna have superintelligence when you get there." And I've never gotten a good answer in terms of what the response is on that front. So let's assume that intelligence is commoditized, right? That's sort of what this is all building, building to. If you look at what's happening with Meta, with Grok, with Kimi K3.

• 20:39Speaker 00

  As Baker put it, if you have two companies that have this, it works. If you have five companies that have this level of intelligence, it's a price war. It commoditizes. So I think we should assume, and we've talked about this on the show, that intelligence is going to commoditize.

• 20:54Speaker 01

  Well, I mean, going back to Baker's point, I actually think it is interesting that ChatGPT, I still believe the product and UI was as important as the underlying model and intelligence. Again, like I remember, this is back in 2023, feeling the difference between typing something into ChatGPT and it actually looking like it's thinking and kind of like streaming the text out versus just getting like a chunked API response as a block of text felt more intelligent and AI. And like, and we said this for a while, like OpenAI and ChatGPT was, is a great product.

• 21:36Speaker 01

  But it feels like both Anthropic and OpenAI have kind of been moving away from the product in the UI side of things. Again, like actually kind of, you know, bringing it all back down to just a command line experience only moved away from that ChatGPT, the new Mac app, they're removing more of the actual chat function, like the chat.

• 21:58Speaker 00

  They're adding some of it back. They're adding some of it back this week.

• 22:01Speaker 01

  Oh, they are?

• 22:02Speaker 00

  Yeah.

• 22:02Speaker 01

  No, because there's an outcry, but like, they have kind of like foregone the entire UI battle versus, and just focused on the model's going to be so smart. So they've given up and ceded some of that ground. And if, I think that's the right point. It's the product, it's the, I mean, okay, sorry. Of course, I think that's the right point because I've always said it's the product and the model. Yeah, I know. I like, as I was saying that out loud, I was like, oh yeah, now it feels even more real. Are you team product now over model?

• 22:35Speaker 00

  I mean, my perspective was always that, and I guess my perspective was more like, kind of getting to AGI is important. Right? Because once you get there, the product experience is much better. And because they were able to improve the intelligence, they've been able to build better products. Right? But if you're going to ask me today, are they going to compete based off of building the most intelligent model? Or are they going to compete based off of the best product? I would have to say, who is they? Because, because this is where things get very interesting. If you assume that intelligence commoditizes, then does OpenAI or Anthropic have that big of an advantage

• 23:17Speaker 00

  over anybody off the street who would take these type of models to build their own product that competes with them? So basically, I think they're going to differentiate on product. But instead of it just being OpenAI and Anthropic competing to sort of corner this market on intelligence and everybody depending on them, now if intelligence is abundant and available to be accessed through multiple providers, it will come down to who builds the best product.

• 23:48Speaker 00

  And so it goes from a two-person race, right? Or a two-company or three-company race, OpenAI, Anthropic, maybe Google, to like now, in order to expect OpenAI and Anthropic to win, you basically have to expect them to be the best AI product builders in the world. And that is a much tougher bet than expecting them to be the best intelligence builders in the world.

• 24:13Speaker 01

  But then do they even make sense as a business? Like, the way these companies have structured their entire business is they have to win on intelligence. They can make some good products and, you know, like they're usable and they got some good features and they're, but like, that's not the story. That's not the, I was just, I saw some like bank analyst note that was saying Anthropic should come out at $6 trillion. Like, I mean, come on, like the absurdity of the story is all built around superintelligence or AGI at the, at a minimum versus we make some pretty good products. We're going to build a good vertically integrated company.

• 24:56Speaker 01

  We're going to be the next Google. That's not their story right now. That's not the way they're coming, gonna, supposed to be coming out to market. That's why, to me, the most interesting part of this week is, I don't want to say it's the nail in the coffin, but like, that story, I think we're both agreeing, doesn't work as well as it did certainly three months ago and even last week. So I, I'm not sure, unless OpenAI gets a really good Johnny Ive pin and suddenly they become, and launches a little bit of a NeoCloud business. I'm not sure what, what do you, do you think there is going to be some kind of story other than first AGI?

• 25:38Speaker 00

  Yeah, it's a much tougher story without being able to hoard intelligence, but it doesn't mean it's an impossible story for them. And I'll point you to two interviews I've done with folks at Anthropic over the past year that sort of shows the line for these companies to be able to make it work. Right? So last year, when I was with Dario, he agreed, he confirmed that more than 50% of Anthropic revenue was coming from the API. This year, when I was with Boris Cherny, who runs Claude Code, he would not confirm that. And in fact, he said that the Claude products have contributed meaningfully to the company's revenue. And the company's revenue has 10xed pretty much since that time that I was with Dario last year.

• 26:22Speaker 00

  So there is an advantage of being that close to the intelligence that like, you don't need to sort of guess on how it works or you can be, you can sync it into your products better than anything else. Right? So you can sort of have that integration in a way that it's going to be harder for other people to do. And you know what's coming next, so, which Anthropic has built off of. So that to me is the path here, is that there is still a way where you can be the developer of AI and then have a product sense that enables you to still be a massive company, which Anthropic is effectively doing, even though the API is still important to it. It is really made, the company's really made a lot of headway with the products that it's selling.

• 27:07Speaker 00

  And, and we're going to have Paul Kudrowski on next week. And, and basically the anticipation from him is, he's an investor and analyst, is that these companies will continue to go up market and try to, like, remember there was Cursor before there was Claude Code? Claude Code has built, Anthropic has shown that they can build a tremendous business by doing it themselves. And how many other areas are there for a company to build AI native products themselves? For a company like Anthropic or OpenAI to build AI native products themselves? And then, you know, start to profit tremendously from that direction. So I think that's still open for them.

• 27:43Speaker 01

  Okay, I will say Claude Code, even though it's just in the command line, is, was and is an incredible product. So like, and the product was effectively the harness and like, along with the model itself, but like, the experience. So even in the command line, they did create something that was dramatically different or better than everything that was out there before. One thing that that actually brings to mind though is like, I mean, I've been seeing a lot more around. I'm sure most of our listeners saw the, you know, like Figma with a plugin to Claude and then Claude Design comes in, Cursor running a lot on Anthropic models and then Claude Code coming out.

• 28:25Speaker 01

  Like, at what point do other companies actually avoid Anthropic where it becomes clear that especially if they are completely dependent on going on upmarket, creating this suite of AI native products, which they're able to do because they're being fed all of the data of these companies that are plugging into these systems, at what point do people actually just say, no, like, sorry, we see what's happening?

• 28:55Speaker 00

  It becomes a lot easier when you have a model like Kimi K3 that works just as well, that you can customize.

• 29:01Speaker 01

  Yeah, that's what I mean. That, that's exactly what I'm saying, I mean, that like, now with that option, if you have any fear that they're going to take everything that you're giving them because you're using their models and then recreate your business, you now have an option. And I think that's going to, that can slow things. Again, the speed at which they just completely replicated Figma and did it better, the speed at which Cursor was replicated and they did a very good job, probably better. I think people will start questioning that a bit more.

• 29:38Speaker 00

  Yep. We should actually, we should actually, this is a good time to just bring in quickly, or maybe not quickly, this idea of the reverse information paradox that Satya Nadella wrote about this week. He said, he said, you know, because they, Microsoft also wants to come in and offer this to its customers. Basically like, we'll protect, we will let you develop AI and we won't take your stuff. He writes, "In the age of AI, the buyer risks giving away knowledge just in order to use what they bought. You essentially pay for intelligence twice, once with money and again with something even more valuable. The proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more knowledge you have to feed it. Over time, the information asymmetry becomes increasingly skewed.

• 30:22Speaker 00

  The seller learns more and more about you as you use what you purchased, while you learn very little about what the seller is learning in return. I think of this as the reverse information paradox." Wink wink, don't buy directly from OpenAI and Anthropic.

• 30:38Speaker 01

  Yeah, I think, uh, actually, how do you feel about the Satya X and LinkedIn posts? I'm curious. This is like his second kind of, uh, do you, do you think he writes them?

• 30:50Speaker 00

  Yeah, probably with help, but yes. I mean, I'm always for, I'm always for more executive communication because like as a reporter, it like helps me at least understand the mindset here. And we could definitely understand the mindset of Microsoft here. They seem furious. I mean, they really don't like the fact, and it's interesting, like, didn't we talk about it last week or a couple of weeks ago about how OpenAI and Anthropic were like the single point of failure, uh, because only they were getting the products right? And they are the ones getting the products right, and they're the ones profiting. And what was gonna happen? Everybody was gonna come in and try to knock them down a peg. And we're watching that now. We're watching that with Meta.

• 31:26Speaker 01

  I mean, not just knock down a peg. I think this is like, kind of fundamentally pushing against the entire. I mean, I, I, I can tell you, so at Writer where I work, like, we have our own foundation models. They're trained on synthetic data. And we have seen when you're not, and we will like be ingesting all the data of the users, it does change the entire trajectory of how models, the advances in the training. And I mean, I think Anthropic and OpenAI are very open that all non-enterprise data, at least in theory, is not, is used for training. And that is one of the biggest advantages, and it's kind of that flywheel. And I think Satya is certainly making it clear.

• 32:12Speaker 01

  Again, I, I can say this, like, a few months, maybe six months ago, everyone stopped caring about these companies training on your data, and now everyone is talking about it again. And it's, again, like, the vibe shifts are so wild right now, like, it literally just how much the conversation changes. But, I mean, Satya is completely right. Like, it's completely right on this.

• 32:36Speaker 00

  Yeah, I mean, this is sort of this, by the way, this is like, this is normal business cycle, right? It's like companies get ahead to certain advantages.

• 32:42Speaker 01

  No, no, come on, this, this stuff is compressed to like, uh...

• 32:45Speaker 00

  But, but compressed, but compressed. I agree, compressed, like, things that would typically take years are now taking weeks. So it's, it's very, very interesting. Okay.

• 32:55Speaker 00

  Couple more interesting things. First of all, it is interesting that even with the restrictions, I don't think we should gloss over this point, China has been able to catch up the way they have. This is from a user named Matt on Twitter, who I'm sure is not a Chinese bot.

• 33:07Speaker 01

  This was my favorite, this was my favorite.

• 33:09Speaker 00

  Since, uh, his, his handle is Matt503EA5SF9Z5, doesn't sound body anymore, but, but body, bot E, but anyway. He wrote, "How is Kimi running on a bunch of 14 nanometer Huawei toasters beating SpaceX AI with multiple data centers of Blackwell chips?"

• 33:32Speaker 01

  That was my favorite, uh, thing I saw, I think, on Twitter this week. But I think, again, like, what do you think this means for the, not just US versus China, but also within even the US? Like, actually, going back to, you had made, you'd kind of read this at the very beginning around, like, this worry that Anthropic invests because they believe frontier models are gonna be the battle, and that powers so much of the current trade or the US, and I don't want to say the entire US economy, but the whole AI ecosystem. So it's technically bad if they don't believe that, which I, I find that ridiculous.

• 34:16Speaker 01

  I find that like crazy.

• 34:18Speaker 00

  Yeah, I don't agree with that. Well, here's my perspective is, all right, let's say, okay, let's say Anthropic and OpenAI go to zero, but like, the industry, whatever, achieves AGI or something close to it, right? So what happens is Amazon, Google, Microsoft, they buy all the data centers, and they buy all the compute that these companies have. In fact, a lot of the compute that these companies have are already effectively, you know, kind of paid for in conjunction with these companies, right? Like, Amazon.

• 34:47Speaker 01

  Not just paid, they are paid, paid to these companies, accounted as revenue that invested in by, come on, let's not forget our circular financing.

• 34:57Speaker 00

  No, you're right, our circular financing laws. All right, I'm Andy Jassy, um, and I have, uh, and I'm running Amazon, and all of a sudden Anthropic goes to zero, and now, like, as a big shareholder, I get to collect and basically own at 100% these data centers.

• 35:14Speaker 00

  Or I don't have to meet, like, commitments to compute that I would previously for Anthropic. But my customers can use Kimi K17, uh, and get AGI-like performance out of them. Um, and I just get paid by delivering the infrastructure. So that would encourage me to invest even more, you know, in AI infrastructure, even though Anthropic and OpenAI aren't hoarding it anymore.

• 35:37Speaker 01

  It's rare that I will ever look at Amazon as the company that tells a good story about a competitive economy, but you just did, and I agree with it. I think, that was a good Andy Jassy impression. I think that's like, uh, that, that is like a very logical way that, and I don't want to say likely, but logical way this can play out and would play out in this case.

• 36:05Speaker 00

  Yeah, it's one possibility. All right, let's talk about it quickly before we move on from the US government perspective. David Sacks, all-in podcast host and erstwhile AI czar from the US government, who was sort of instrumental in making sure that this Fable ban happened when it happened.

• 36:24Speaker 00

  He writes, "This is concerning. For the first time, a Chinese model, Kimi K3, has taken number one on the front-end code arena and is scoring at or near frontier on other benchmarks. Meanwhile, America is tying itself in knots. Politicians and bureaucrats are banning new data centers, piling on state regulations, and pushing for new federal agencies to pre-approve frontier models. This is how you lose the AI race. The rest of the world won't play by our rules if we bog ourselves down. Permissionless innovation is how America won the internet and became the technical, technological envy of the world. We can do it again with AI."

• 37:02Speaker 00

  I, I appreciate a lot of what David Sacks has to say, and I've invited him on the show. But this is like hilarious and so rich and ironic that he, he being part of the Trump administration, which did like the most interventionalist policy to ban Fable, is now saying we need permissionless innovation to beat China. I mean, come on.

• 37:24Speaker 01

  And let's not forget, like, regulatory capture was kind of the entire business, or that, like, that was this project, Stargate, and whatever else that he helped coordinate. Maybe he was kind of resistant to a lot of this stuff early on, but, you know, Oracle, Stargate, all of these things, which, I mean, the Trump administration, I think, uh, it is rich. It's ironic, it's, uh, I don't, I agree that, or actually, do you think we are over-regulating at the current state and that that is a danger and competitively against China?

• 38:05Speaker 00

  Yeah, I think so. I mean...

• 38:08Speaker 01

  Why?

• 38:09Speaker 00

  I don't think, well, we, Stamos explained it to us at the summit. It wasn't like Fable had cyber capabilities beyond, that weren't available, you know, from like Opus 408.

• 38:19Speaker 01

  But Fable wasn't, again, rich and ironic, the Fable ban felt as much political as it did...

• 38:27Speaker 00

  Yes. That's my point. Yeah. You asked me for over-regulating. That is like a pure case of poorly thought out over-regulation.

• 38:36Speaker 01

  Okay, I guess, I differentiate, I'm still thinking of like over-regulation around actual safety concerns and like, are we too concerned with, like, well-thought-out, but potentially overly aggressive things around we should not release models purely from the safety side versus Dario's beefing with, uh, someone at the secretary, or the Defense Department? Like, to me, let's ignore that. Let's ignore the pure political, no, because I mean, that's just, that's not good in any situation. I'm talking about, like, should the US be versus China more of a leader in terms of we are going to have safe, equitable, regulated AI like, like Europe?

• 39:22Speaker 00

  I mean, I don't know what it save equitable regulated.

• 39:25Speaker 01

  I don't know. I don't even know what that means. I was trying to think of what like just smartly regulated AI, but it's not free for all, anything goes purely permissionless innovation.

• 39:39Speaker 00

  Here's my perspective. If you have a model that is going to cause cybersecurity problems for companies, if it's released to the public right away, and not just companies, companies, academic institutions, governmental agencies, if you know, if you can see and you're testing that it's going to cause these issues, if it's released to everybody right away, I would try to release it in a somewhat controlled way in the early going and then release it to everyone. Like, I think the Fable initial launch of Fable made sense. Same with GPT 5.6, but I don't want the, I don't think the way the government has been involved recently has been smart because it has been largely political.

• 40:21Speaker 01

  Wait, so you're a Glasswing guy.

• 40:24Speaker 00

  You're a. I'm a Glasswing guy. I've always been.

• 40:26Speaker 01

  All right, all right.

• 40:27Speaker 00

  I'm a Glasswing.

• 40:28Speaker 01

  Hold on, but you just said that the rollout was good. So what don't you agree with in terms of the rollout?

• 40:37Speaker 00

  The government banning the model for no reason.

• 40:41Speaker 01

  Oh, yeah, I guess after.

• 40:43Speaker 00

  Forgot about that?

• 40:44Speaker 01

  Yeah. Oh, that whole, I don't even remember last week, man.

• 40:48Speaker 00

  Yeah, it's crazy. All right, let's take a break. I want to come back, talk a little bit about Google, and then we can end with OpenAI beefing with Apple and all of its partners. We'll be back right after this. This episode is brought to you by App Point. Everyone's racing to roll out AI right now. Co-pilots, chatbots, agents doing real work. But here's the part nobody loves talking about. All that AI runs on your data, and most teams have no single way to see it, secure it, and prove it's under control. That's exactly what App Point does. For 25 years, they've been the trusted layer beneath the world's most demanding data, now extended across your entire AI estate, your data, your cloud, and the agents acting on your behalf.

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• 43:00Speaker 00

  And we're back here on Big Technology Podcast Friday Edition. We come to you amid a rapid, a rapid deployment of AI models. Of course, we have the latest models coming out from Anthropic with Fable and OpenAI with 5.6, and Meta with MuseSpark 1.1, and SpaceX with Grok 4.5, and China with Kimi K3, and Google with... ...dot, dot, dot. This is from Bloomberg. "Google Gemini launched delayed as tech falls short of internal goals." What's going on at this company? "Apple links Google is months behind schedule on delivering Gemini 3.5 Pro,

• 43:42Speaker 00

  its most powerful flagship AI model, because the company has been taking time to try to improve its capabilities, particularly in coding. The delay has been a source of frustration for Google engineers, AI researchers, and managers, many of whom are concerned the company risks losing an edge in the market as rivals Anthropic and OpenAI produce models that exceed Google's capabilities. Google has multiple layers of stakeholders involved in preparing models for release, working to weave AI across a vast product portfolio, including search, maps, and YouTube, which can cause delays.

• 44:17Speaker 00

  Both OpenAI and Meta platforms recently released new models that further outpace Google's current offerings in AI for writing code. Late last month, Google updated the data being used to train Gemini in an attempt to improve these skills, but the results were disappointing. Shares slipped as much as 3.2% on Thursday." Oh, this is, this is, I mean, we've known that Google has been behind for a while, but this is like getting to the point of embarrassing. What do you think about this?

• 44:46Speaker 01

  See, I actually, I was just looking up Gemini 3 was launched November 18, 2025. Let's not forget, there was a few months where everyone's like, they're back. We were like, they're back, that.

• 45:01Speaker 00

  Yeah, they were back.

• 45:02Speaker 01

  And they were back. Yes. Okay, they were back. And like, it was on par with everything else, and it just stopped. And I genuinely wonder what's going on because they caught up, they felt maybe they could even be ahead, and they have distribution like no other. And suddenly, like Gemini itself, even the standard consumer version, like, has just kind of gotten a little bit, maybe not worse, but everything else is getting so much better. You can feel the difference. Nothing in the last seven or eight months feels like it's significantly improved. I, though, except for AI overviews, I have found myself again, and I always feel very basic,

• 45:46Speaker 01

  using them more and more and actually doing a Google search and following on with the, and maybe they're just going to go all in on that and make a ton of money. But in terms of like the actual frontier battles, they feel like they're, they're out.

• 46:01Speaker 00

  Yeah. So here's a theory. I mean, you know, the world's perspective on AI seems to, seemed to shift last, last year, January or February, when DeepSeek came out, right? And there was a perspective that if you can deliver intelligence that was on par with the intelligence that existed then, which was pretty smart, at a cheaper price, more people would use your models, and you would be like the beneficiary of the Jevon's paradox. And for Google, which had, you know, not just a model, but cloud services to sell, it figured maybe if I bundle the smaller flash models with the cloud services, I will enable people to do more.

• 46:41Speaker 00

  Then the world shifted, and the bigger models began to do this coding autonomously, starting in December, January this year, right? So a year later, and a big company moves slowly, right? So Google just took a long time to catch up. And this idea perhaps that, you know, a big model is all you need, and we see the problem of developing these big models, maybe didn't really, you know, catch on within Google. And, you know, instead, it might have just like, instead of training these, these like, unifying to train these big models, it might have just decided smaller flash models is going to be the way to sort of make our, make, make the most out of this.

• 47:22Speaker 00

  And it's also helpful for our products, which could use these sort of smaller, purpose-built AIs to enhance what they're doing.

• 47:33Speaker 01

  Actually, you can even feel that big company under, like in the same article, it talked about Google co-founder Sergey Brin and others were advocating for Google to move faster to seize opportunities in AI coding, but slowed by competing factions, two former employees said. Both cloud computing unit Google Cloud, research lab Google DeepMind, and the team between, behind the Android operating system were all building AI coding tools. So you can picture, I guess I can, I mean, that's a mess. And like, again, you have developers who have the opportunity to build their developer tools.

• 48:12Speaker 01

  They're gonna do it, but to try to do that in a unified fashion, that just, that feels like old school Google. Not, not the lean fighting machine that Sundar just somehow reorged into. This is back to like Google Chat Hangout, whatever the product names, whenever they all just were ridiculous and kind of like stacked on top of each other. This feels like that Google.

• 48:39Speaker 00

  Yeah, there's some crazy stuff in here in this Bloomberg story. Efforts to win that coding have also been up against some engineers at Google with the more purist stance who believe that all important code should be human-written to adhere to Google standards.

• 48:53Speaker 00

  I mean, obviously, you don't want AI to write like the core Google software, but to have these purists who are like, it must be handwritten, where like, nobody's writing handwritten code anymore is sort of where you get into trouble.

• 49:07Speaker 01

  Yeah, this, that actually, I mean, they're a giant organization. It is funny though, because remember Sundar, I think, said like 95% of code is written by AI?

• 49:18Speaker 00

  75%.

• 49:19Speaker 01

  75%. Okay, all right, I guess the, the AI holdouts are still handcrafting their code, but yeah. It's, do you, do you think they're going to come back? Do you think?

• 49:31Speaker 00

  Of course they'll come back. Yeah.

• 49:33Speaker 01

  Gemini 4 is going to blow us all away and.

• 49:37Speaker 00

  Google, don't we know, like, Google will inevitably come back. So they, I mean, they have, they have the talent and they have the compute. But the one thing that I can't understand here is, for the life of me, if you're Google, you should never run out of compute, right? The fact that they've run out of compute, by the way, they're licensing a lot of their compute in their cloud business, where maybe, I mean, the cloud business is doing great, but maybe that should be going to your AI development if you think this is the most important technology in history, or one of them, and Sundar certainly does, comparing it to Fire. So I don't get how you-

• 50:08Speaker 01

  Yeah, but that's like a perfect-

• 50:10Speaker 00

  That just seems like poor management.

• 50:12Speaker 01

  No, no, but that's a perfect example of like, Google Cloud, I can't, I mean, it's one of the fastest growing businesses in the last 15 years. It's gigantic. It's run very separately from the rest of Google. So like, that idea that you can reallocate resources without any massive complexity and internal politics, I can only imagine how difficult that would be. And that's a perfect example of like, trying to move stuff around to where it's most effectively allocated is gotta be difficult.

• 50:46Speaker 00

  Yeah, but that's your job, right? When you're running a company like this, that is your job.

• 50:51Speaker 01

  Come on, Sundar.

• 50:51Speaker 00

  You gotta make decisions.

• 50:52Speaker 01

  McKinsey-ify this once again. Let's reorg.

• 50:57Speaker 00

  They'll see it. I mean, they've, they've shown that when they get the whole company focused on a goal, they can accomplish it. But, I mean, it is crazy watching them to go, watching them go from unfocused to focused and effective to whatever this is now. It's not good.

• 51:10Speaker 01

  I'll say, I'll give them credit that still on like multimodality image and video, they still kind of own it right now. And everyone kind of puts them far in a way, like I do, I really never hear that much about ChatGPT Image 2 or any of these others. Like, out of the big players, they still kind of own multimodality. So they're still doing good there, but the rest of it, they're definitely, something is up.

• 51:38Speaker 00

  Right. Okay, we can't leave today without talking about what's going on with Apple and OpenAI. So if you listen to this show, you've already heard that Apple sued OpenAI for stealing trade secrets from it. And if you've done any of the reading, or if you've watched any of the coverage, you know that this is the most boneheaded corporate espionage attempt maybe in history, where the Apple employees on Apple issued laptops were discussing plans to exfiltrate Apple data, to bring Apple parts into interviews, to, you know, access through a bug, but like Apple's roadmap and future plans. And then Apple caught them red-handed. So, I don't know, like, I'm just gonna turn to you quickly on that, Ron

• 52:22Speaker 00

  John, like, this is, do you agree with me that this is like one of the, like legitimately dumbest moments in corporate espionage history?

• 52:31Speaker 01

  I mean, if you are going to an employer's whose goal is super intelligence, don't do something this dumb. I mean, come on, like, I still cannot believe, I, yes, I would firmly agree, this is one of the dumbest corporate espionage things I've ever seen, even though, even the Uber Waymo stuff back in the day had a little bit more, like cloak and dagger elements to it. Like this, it's literally like you're on Slack or whatever other chat, just, hey, how do we steal information from our employer?

• 53:08Speaker 00

  Right, but you're not just on Slack, you're on Slack on Apple's, you know-

• 53:11Speaker 01

  Yeah, no, no, that's what I mean.

• 53:12Speaker 00

  On Apple's computers, stupid.

• 53:15Speaker 01

  Yeah, yeah.

• 53:16Speaker 00

  Anyway, Apple, go ahead.

• 53:18Speaker 01

  Do you think, like, these are career technologists? Like, how do you end up here or thinking this way? Seriously?

• 53:28Speaker 00

  Some people are really smart in some ways and really not smart in other ways.

• 53:32Speaker 01

  Okay, you know what? The one bright side I'll say is, it's probably clear they had not stolen information or participated in corporate espionage prior to this. So that's, that's what I'll give them. That's the good side.

• 53:45Speaker 00

  When you make a career and potentially company ruining moment, like blunder, and you start this blunder with LOL, I think you're, you're just like-

• 53:57Speaker 01

  Explain that one?

• 53:57Speaker 00

  Completely out of your depth, right? Like, one of the people at OpenAI, apparently on the, in the chat, said, like, LOL, I found all the network files. Like, oh, so stupid.

• 54:09Speaker 01

  So stupid. Come on, guys, up your espionage.

• 54:12Speaker 00

  So the latest is that Apple has now sent dozens of OpenAI employees legal letters asking them to, to preserve their documents. And Apple has also said that this, they only found the tip of the iceberg. And the AI lab said that while it had, OpenAI had said, while it had taken the allegation seriously, it was not aware of any evidence that the complaint has merit. So that's where it goes next, is Apple's gonna take OpenAI into discovery, you would imagine, not settle, and just get about as much information as it can. And this is probably gonna look much worse when all is said and done.

• 54:47Speaker 01

  Well, I mean, 40 employees is a lot. And I think OpenAI has probably got like seven or 8,000. I mean-

• 54:54Speaker 00

  Oh, they have 400 from Apple, so.

• 54:57Speaker 01

  Yeah, but if 10% of those employees were engaged in something like this, and that's the tip of the iceberg, that's actually, that's wild. That's wild. Like, if, if it's 400 from Apple and 40 have already been, you know, like, directly receiving some kind of communication around this, this is, this is gonna get fun. This is gonna get very fun.

• 55:19Speaker 00

  Not for OpenAI, not for OpenAI. And if you're OpenAI, you have to think like, what, what am I doing that makes my partners my enemies? Elon Musk, you know, founder of OpenAI, now an open-

• 55:33Speaker 01

  This is what you're doing?

• 55:35Speaker 00

  Dario, Dario, an early OpenAI employee, now an OpenAI enemy. Microsoft, biggest funder of OpenAI, for a long time at least, and the champion of this company. Now, we just read what Satya said, an OpenAI enemy. Apple, a partner with OpenAI to build ChatGPT into Apple intelligence, now an OpenAI enemy. I'll just say this one thing, I'm gonna turn to you. In tech, you need friends to win. You can't do it yourself. You need friends. Look at Apple and Google. They should be enemies. Google helped Apple save its business by putting Gemini into Siri, to a degree. I don't want to overstate things. OpenAI's

• 56:17Speaker 00

  loss of these friends over time is going to add up to something really bad. Who knows what that exactly is, but there's gonna come a time where OpenAI is gonna need Satya, or it will need John Turnis, or it will need Elon. And they won't be there for them.

• 56:33Speaker 01

  So I, I keep thinking right now, who do you think, is it Tim Cook, or is it Turnis who's gonna be the one, could this be like Tim Cook's final act? Just the head of Sam Altman in his hands, like, or is this Turnis coming in like killer turnus? Who, who's gonna be spearheading this effort?

• 56:56Speaker 00

  Great question. So it's gotta be Turnis, right? Because Cook is gonna step down, this case will like last for a long time after he leaves. And from, what I would have guessed is that Cook brought this to Turnis and said, John, we got a problem.

• 57:10Speaker 01

  John, we got a problem.

• 57:12Speaker 00

  A number of your former employees, including people that reported to you stole our shit.

• 57:17Speaker 01

  Oh, wait, did they report to Turnis even?

• 57:20Speaker 00

  At least one reported to Turnis, but he did, he ran hardware engineering. These people are stealing from hardware engineering.

• 57:26Speaker 01

  Oh, man. Oh, he's gonna come strong. This is, oh, he's coming strong on this one.

• 57:32Speaker 00

  And Cook probably said, we want to do this. And the thing is, this may take up a lot of energy as you get your, as you get going. But ultimately, it's sort of up to you in terms of whether we should sue OpenAI. And Turnis probably looked at him and said, Timmy boy, sic the lawyers on these assholes.

• 57:55Speaker 01

  The betrayal, the betrayal. All right, this is, okay, this is, this is now becoming one of my favorite stories of that, to see what happened. Forget, forget Kimmy K3 and the entire future of the AI ecosystem and economy. I just want to see what Turnis is gonna do to OpenAI right now.

• 58:15Speaker 00

  I just want to be clear, I'm not the one saying that OpenAI folks are assholes. I'm just saying that that's probably what John Turnis would have said.

• 58:26Speaker 01

  I think John Turnis doesn't swear. He's-

• 58:28Speaker 00

  John Turnis definitely swears.

• 58:30Speaker 01

  He's a very polite, upstanding citizen.

• 58:33Speaker 00

  No. Do you, do you think, okay, well, we'll end on this. Do you think that there's any of the folks at the top ranks of these companies who doesn't curse during the day?

• 58:45Speaker 01

  Uh, no, but this is a good-

• 58:47Speaker 00

  There's so much stress involved in these jobs. You almost need swear words as a, as a way to, you know, let off some steam.

• 58:54Speaker 01

  I would like to say, as the parent of a seven-year-old child, I do feel, and as someone who has sworn many, many times in my life proudly, I still feel really weird how normalized it's become with adults swearing in like very public communications and forums, obviously, the president and others. And like, it's just become very normalized and it's weird to me. Like, they're still, they're still bad words. We should own them. And Turnis should be dropping F-bombs left and right, but not in front of the kids. That's all I'm asking.

• 59:30Speaker 00

  Let's take a moment to reprimand John Turnis.

• 59:32Speaker 01

  Yeah, swearing in front of kids, apparently, you scandal.

• 59:38Speaker 00

  A imagined fanfiction version of you swore on this show is deeply upsetting to us and our listeners. And you should, you should really think twice before using that sort of language.

• 59:49Speaker 01

  I think the good thing, the good thing, if I am to swear on this show, I think the population of seven-year-olds listening to the Big Technology Podcast is one of our smaller, if nonexistent, demographics.

• 1:00:02Speaker 00

  Well, it's definitely not nonexistent. That's why I try to keep it as clean as I can, because I know that parents play it in the car. And honestly, I commend those parents. You know, we're here, you know-

• 1:00:13Speaker 01

  All right, in the interest of that.

• 1:00:15Speaker 00

  As an educational endeavor to make sure that the youth of the world knows what the AI industry is gonna look like when they grow up.

• 1:00:25Speaker 01

  And not to mess with John Turnis. Do not mess with John Turnis.

• 1:00:29Speaker 00

  And one of those lessons is, yeah, stay out of the, stay out of the bad side of John Turnis, because you never know what he'll do. It's gonna be a running joke that will just have bad John.

• 1:00:39Speaker 01

  Well, I think I know so little about his personality that I can only create extended fanfiction around it. So, sorry, John, get ready.

• 1:00:51Speaker 00

  Okay. Well, this is, this is a new thread for us, and it's a new meme. So, we're gonna, we'll run with it. I guess that's it for this week.

• 1:01:04Speaker 01

  That's it.

• 1:01:05Speaker 00

  Kimmy K3 episode, ending with a meditation on language, as we typically do here on Big Technology Podcast. We leave you with that to think about. Thank you, Ron John. Great to-

• 1:01:15Speaker 01

  All right.

• 1:01:16Speaker 00

  See you as always. And thanks to all of you listeners and viewers. We'll see you next time on Big Technology Podcast.

• 1:01:24Speaker 02

  Now, more than ever, we need someone on our side. But Rob Whitman? Whitman's votes drove up costs, cut Medicaid, and risked 350,000 Virginians' health care to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes, and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the HouseMajorityPac.com. Not authorized by any candidate or candidate's committee.

• 1:01:53Speaker 03

  In this life, you can't win.

• 1:01:55Speaker 04

  When the world gets you down.

• 1:01:57Speaker 03

  No!

• 1:01:57Speaker 04

  Escape to Pluto TV.

• 1:01:59Speaker 03

  This is objectively fantastic.

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• 1:02:07Speaker 01

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  Watch School of Rock, Crazy Ex Girlfriend, Anchorman: The Legend of Ron Burgundy, The X-Files, Wayne's World, and so much more.

• 1:02:14Speaker 00

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• 1:02:16Speaker 04

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