Thinking Machines’ First AI Model, California Loses $3.2B to Texas, TSMC Adds $100B | Diet TBPN

Summary

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TBPN Podcast Summary

Episode: Thinking Machines’ First AI Model, California Loses $3.2B to Texas, TSMC Adds $100B | Diet TBPN
Date: July 16, 2026
Host: John Coogan, Guest Host Tyler Cosgrove
Format: Live tech talk show (Best moments, under 30 min)

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Episode Overview

This lively episode features guest host Tyler Cosgrove joining John Coogan for a fast-paced discussion on three major tech and business headlines:

1. The strategic launch of Thinking Machines’ open-weight AI model "Inkling"
2. California’s $3.2B industrial loss to Texas
3. TSMC’s record $100B investment in U.S. chipmaking

Along the way, they cover the state of open vs. closed source AI, geopolitics of LLM development, the business of content creation, and key movements in tech finance and policy.

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Key Discussion Points and Insights

1. Thinking Machines Launches "Inkling" — An Open-Weight AI Model

[00:49–09:45]

• Context & Industry Reaction

  • Mir Morati’s startup (formerly OpenAI) launches its first open-weight AI model, "Inkling," designed to loosen the grip of AI giants by allowing users significant customization.

  • The model is tightly integrated with Tinker API, focusing on fine-tuning and open customization, similar to a Red Hat model for AI.

    “You can leave because we are giving you the weights of the model. Open source, you can do whatever you want with them, but keep working with us because we're helping you a bunch and we're making money in the process.”
    — John Coogan [01:49]

• Technical Details and Benchmarks

  • Inkling: 975B parameters, though only 41B are "active" at any moment — large for open-source but smaller than top closed models.

  • Designed as a broad, balanced foundation model, not the most powerful overall, but highly flexible and tailorable.

  • Early reception is positive; benchmarks place Inkling above Nemotron 3 Ultra and between Kimi K 2.5 and 2.6, but behind forthcoming Kimi K 3.

    “It's built to be fine tuned… that's the whole point.”
    — Tyler Cosgrove [03:36]

• Open-Source Pedigree & Distillation Debate

  • Some claim it's the only open-weight model not distilling from proprietary sources, but the hosts note that its training included supervised fine-tuning on synthetic data from other open-weight models — a “lightest touch” of distillation.

    “It’s not one of these scenarios where we're like, why is it identifying as Claude? Or why is it just saying that it's ChatGPT?”
    — John Coogan [05:40]

  • The term "distillation" is fuzzy; Coogan and Cosgrove debate its boundaries and implications, noting that layered distillation weakens copied features.

• Geopolitical Positioning

  • Many U.S. leaders prefer domestic open models over Chinese ones, even if quality is comparable, due to IP and alignment concerns.

  • Ongoing arms race: China moving to restrict overseas access to its top models, while Anthropic is battling widespread distillation of their models by Chinese labs.

    “Anthropic is now shutting down Distillation accounts on the order of millions of accounts per week. That is crazy scale… it's a game of whack a mole.”
    — John Coogan [08:19]

  • U.S. government exploring ways to slow Chinese model adoption globally, similar to efforts against Huawei and ZTE.

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2. Design Patterns in AI-Generated Content — The "AI Smell" Problem

[10:00–13:41]

• Grace Lee’s research found that newer models like GPT 5.6 are avoiding previous “bad AI smell” design patterns (bento box layouts, oversized hero typefaces).

• The hosts note that AI models tend to cluster around certain design patterns unless prompted with stronger references.

• Enterprises increasingly upload their own assets for internal consistency, reducing generic output.

  “You're giving the flavor of creativity… Maybe that's enough.”
  — John Coogan [12:36]

• Question: Are models really more creative now, or have they simply learned which patterns to avoid?

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3. California Loses $3.2B Shipyard to Texas

[13:42–15:46]

• The Story

  • Defense startup Saronic moves a $3.2 billion automated shipyard project ("Point Alpha"/"Port Alpha") from California Forever’s Solano County to Brownsville, Texas.

  • Main reason: California’s slow regulatory and permitting process vs. Texas’s rapid tax abatement and approval.

  • Result: ~10,000 permanent jobs to Texas, key loss for California’s industrial ambitions.

    “California could not provide clear expedited approval process needed... Texas moved quickly and aggressively.”
    — John Coogan [14:46]

  • Insider admits it's a "powerful signal" about California’s competitiveness for large industrial investments.

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4. TSMC’s $100 Billion U.S. Investment and Market Reaction

[15:46–17:55]

• Announcement
  • TSMC beats earnings and raises capital expenditures, pledging an additional $100B for U.S. fabs, especially in Arizona, cementing its position atop the global chip supply chain.
• Wall Street Reacts
  • Nasdaq dropped 1% on fears of overspending, despite strong results — an odd market response.
• Long-Term View
  • TSMC is finally going all-in, timing their expansion with AI and semiconductor demand — but market skepticism remains.

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5. Media, Content, and Other Industry Notes

[17:55–19:07]

• Content + Brand Integration

  • Colin and Samir strike a first-of-its-kind creator deal: Lexus becomes their channel’s "official car," moving beyond typical ad sponsorship.
  • The aperture for creator-brand deals is widening, with deeper integration predicted across YouTube.

• Disney Acquisition Math

  • Disney has spent over $129B on major acquisitions (Marvel, Star Wars, Pixar, ESPN, Fox); total market cap is currently $169B.

  • Coogan points out the overlooked role of dividends and buybacks ($70B+ returned to shareholders) when appraising acquisition value.

    “There is a whole separate picture which is that a lot of cash has been returned to shareholders throughout this journey.”
    — John Coogan [18:38]

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6. NYC vs. Other Tech Hubs — Liveability, Policy, and Culture

[19:07–19:32]

• Sean Frank makes a tongue-in-cheek case for New York City despite high costs, taxes, and (supposed) ban on Waymo self-driving cars.
• Both hosts reflect on what makes NYC unique and compelling, despite all its practical drawbacks.

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Memorable Quotes & Notable Moments

• On AI Distillation:
  “You always think about it as like oh there's like shut down that one company or shut down that one block of IP addresses but when there's a really, really distributed attack... that is crazy scale.”
  — John Coogan [08:19]

• On Market Skepticism:
  “In a time when even TSMC, which was not a particularly AGI-pilled company for a long time... when they are finally like yes, now is the time, people are, I don't know, they're skeptical.”
  — John Coogan [16:04]

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Timestamps for Key Segments

• Thinking Machines’ Inkling Model Discussion: 00:49–09:45
• Design Patterns in AI-Generated Content: 10:00–13:41
• California Shipyard Loss to Texas: 13:42–15:46
• TSMC’s Investment and Wall Street Response: 15:46–17:55
• Creator Monetization/Disney Acquisitions: 17:55–19:07
• NYC Tech Lifestyle Banter: 19:07–19:32

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Episode Tone and Closing

A high-energy, layered conversation that mingles technical detail with frank reflections on market forces and cultural trends. The dialogue is brisk, often playful, but always grounded in the realities of the tech and business landscape.

Closing note:

"Thank you to everyone who tuned in... Let us know what you think of Tyler. Leave us a review... I think he did fantastic."
— John Coogan [19:47]

Sign-off:

“Have the best Thursday of your life!”
— Tyler Cosgrove [19:51]

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Transcript

[A]

We have a very special show for you today because we have Tyler Cosgrove guest hosting. He's here in.

[B]

Great to be here.

[A]

And I know I'm gonna make mistakes today because I always throw it over to Jordi. I gotta remember this, Tyler. It reminds me of this video from Warren Buffett. We gotta play it to show what I'm going through emotionally today without Jordi in the TVPN ultradome. Let's pull up this video of Warren Buffett. Throughout the years at the Berkshire Hathaway shareholder meetings, Warren Buffett always goes to Charlie after he gives his comment. He, he, he, he, he gives his speech and then he kicks it over to Charlie.

[B]

Charlie.

[A]

Through the years. Charlie, Charlie, Charlie. Tearjerker.

[B]

Yeah. Makes me want to cry.

[A]

It's emotional. Charlie, how do you feel? Charlie?

[B]

Me.

[A]

Charlie. Charlie. That's Greg Abel. So if that happens today, I apologize. But the first big story is of course, Thinking Machines new model has released. Miramorati's AI startup released its first model in bid to loosen AI giants grip. We're going to be talking about open source, closed source, where the frontier is national geopolitical model moves.

[B]

And some people had an idea this was going to happen. Some inkling.

[A]

Oh, they had an inkling that.

[B]

Yeah. That they did they.

[A]

I didn't have an inkling that they were going to jump into the open source.

[B]

I think it's actually, I think it makes a lot of sense given the Tinker API. Right. The whole business is, is, you know, you're doing fine tuning on open source models.

[A]

Yeah.

[B]

It makes a lot of sense that they're going to have their own.

[A]

Yeah.

[B]

That, you know, you can easily.

[A]

It's sort of like they are set up as a business to launch an open source model without it degrading any other piece of their business. Because the Tinker API, that fine tuning, that they do, that integration with the customers that they have actually benefits from open source.

[B]

Yeah.

[A]

And then they can go to their clients and say, look, you know, it's the Red Hat model. At any time you can leave because we are giving you the weights of the model. Open source, you can do whatever you want with them, but keep working with us because we're helping you a bunch and we're making money in the process. So Thinking Machines lab first. The first model is an open weights model designed to chip away at the lead of OpenAI and Anthropic, says the Wall Street Journal. Former OpenAI technology chief Mir Murati is betting on more customizable artificial intelligence models to Chip away at the lead. The Frontier Labs, such as her former employer, hold over the technology. Tml, a company led by Marathi, released its AI model Wednesday and did it with open weights, meaning that others can modify it with their data. Called Inkling, the model has 975 billion total parameters, making it far smaller than estimates of the most advanced closed source models.

[B]

So only I think the number is 41 billion of those are actually like

[A]

active at any moment.

[B]

Yeah. So this is definitely on the bigger side of open source models. Sure.

[A]

Yeah.

[B]

But like that number, it's not. These aren't like dense models like what you traditionally think of.

[A]

Sure.

[B]

The model is like four years ago.

[A]

Yeah, yeah. Muradi told the Journal. We trained it to be a broad, balanced foundation model, strong across many domains, flexible enough to adapt. Inkling is not the strongest overall model available today, open or closed, which is a different frame of reference for many of these model launches. Everyone's been jockeying for the Frontier, even if they're not world class at everything. Usually when they launch they say, oh well, we're best at something or we're best at this. But different tone, different communication strategy and I think it's being well received. I think people are having fun with it.

[B]

The reaction, yeah, I mean, I think the main picture is that this model is like uniquely set up for the Tynker API. It's built to be fine tuned.

[A]

Sure, sure.

[B]

That's the whole point.

[A]

Got it. DD DAS says Thinking Machines just dropped the best open weight AI model outside of China. And obviously that is a big topic of conversation as business leaders in the United States have some policies and some reticence about using Chinese open source models. Even if they're not worried about the dystopian, you know, Manchurian Candidate hidden inside the weights. Maybe they just want to be aligned with a US based company. For a variety of reasons. Inkling beats Nemotron 3 Ultra and benchmarks put it between Kimi K 2.5 and 2.6. Of course, there's also news today that Kimik3 will be launching is another jump forward, but there's back and forth between some AI researchers around what's going on there, how long that strategy will continue. So Dee Dee says many were contending to this throne, but Thinky has come out on top, really solid release and will pair well with Tynker. So there are some benchmarks that you can go and dig into if that's your thing. There's another very bullish take from Jack Morris of Engram Labs. He says people Are under are underestimating what a big deal this is. This is the only open weight model that that's trained without distilling for OpenAI from OpenAI or anthropic Kimi distills, GLM distills, Quen distills, Nemo Tron distills, Kimi and Deep Seq which count basically a fully different tech stack. The first pure open frontier coding model. Very exciting. And there's a community note on this. Can you break down exactly like where are they standing on the shoulders of giants, where are they not?

[B]

So I think this tweet is not exactly true. In the blog post, they say to bootstrap post training, we ran an initial supervised fine tuning on synthetic data generated by open weight models including Kimi K 2.5.

[A]

Okay.

[B]

So I think that's like generally how people think of like distillation, that they mean something related to this. So I think that is not that different than what people like, you know, Nvidia with Nematron did.

[A]

Sure.

[B]

So this is not like very new

[A]

I think, but it's sort of like the lightest touch of distillation that could happen because it's just one piece of the pipeline, one small amount of data. It's not one of these scenarios where we're like why is it identifying as Claude? Or why is it, why is it just saying that it's ChatGPT?

[B]

But it is funny because you can kind of say like, oh well, if this is like kind of distilled on Kimi and Kimi's kind of distilled on closed source.

[A]

Yep.

[B]

Well then maybe you get some kind

[A]

of two layer distillation, this sort of round trip loop. But at the same time there's probably something to be said for the more layers of abstraction, the more ingredients you pour in, the distillation becomes weaker and weaker.

[B]

Yeah, and I think there's also an important question of like, well, okay, they're doing some level of distillation. Like why? Because you can either be like, well they're just doing it to save time, whatever. Like obviously they have these capabilities, but there's no point in, you know, doing everything over again. You might as well just use what's out there already. Or is it because these capabilities that they get from this, this distillation, light, whatever it is, are those actually super imperative to the model, like being good

[A]

and grim says our founder Jack Morris recently issued some unfounded claims that got community noted. We deeply apologize for the confusion caused by his original post, the follow up post and the follow up to the follow up post. Nevertheless, we stand by his conviction in his own takes and in strong open source models like inkling. And there is a question of like distillation is a vague term where it's not a binary thing and if it's not in the pre training data, does it count?

[B]

I think it's also very much this mean. People love to talk about Onx. Yeah, they like to kind of, you know, scapegoat. Oh you know, it's all distillation. That's the only reason Chinese models are good.

[A]

Yep.

[B]

Is that actually true?

[A]

Probably. I mean Anthropic's head of National Security Policy Taran chabra, accused Zpuz AI of distilling both Claude and OpenAI models for GLM 5.2 at the Aspen Security Forum earlier this week. This is from Vincent Chow, senior AI reporter at scmp. He said it's the first time that they've named ZHIPU specifically after previously calling out Deep Seek, Alibaba, Moonshot and Minimax. Join the Join the club at this point also accused, they also accused Deepseek of continuing its adversarial campaign of distillation. Anthropic is now shutting down Distillation accounts on the order of millions accounts of per week. That is crazy scale. You have to, I mean you always think about it as like oh there's like shut down that one company or shut down that one block of IP addresses but when there's a really, really distributed attack. We've even heard about whole companies that just like resell Claude tokens or GPT 5.6 tokens and that looks like a reasonable business because it's just a wrapper company. Of course you want to work with them but then you don't realize that on the other side who are their customers? Why did they get to 100 million run rate so quickly? Well maybe it's a lab that's trying to distill through this pass through entity and of course it's hard to like watermark the tokens once they go out the API and they get passed through some other system and they can go through other countries, all sorts of things. So millions per week. That is crazy. That's gotta be really difficult to. It's a game of whack a mole. They say GLM is quote probably the most advanced Chinese model on the market now, which poses significant cybersecurity challenges. They hinted that Anthropic will expand access to Mythos to ensure fair fight for cyber defenders. And they said that Distillation challenge is real in shrinking US lead in AI, suggesting that the US government could do more to clamp down on Chinese model adoption globally by working with allies similar to trusted telecom efforts like Huawei and zte. So obviously a hot topic and people will be debating how, how, how exactly how heavy of a hand the government should be.

[B]

Yeah, I think this, this release is also makes a lot of sense and I think it was a week ago there was that article about like Beijing is looking at curbing overseas access to Chinese top AI models.

[A]

Yeah.

[B]

Right. So you're not gonna be able to access the Chinese open source. Right. It makes a lot of sense to start doing American open source, Western open source.

[A]

Yeah, it really does feel like there's

[B]

a pretty feel very well timed.

[A]

Yeah, there's, it seems like there's a pretty wide gap with, between at least what's reported preferences from Beijing from the actual government and the companies. The companies are like, yeah, send us all the Nvidia chips, let's distill everything, let's. And then let's open source these models and compete internationally. And Beijing's like, maybe we need like, you know, an indigenous supply chain here. Maybe we need to you know, lock down these models, keep our lead over here, go work internally. I don't know. This was an interesting post from Grace Lee. She, she asked the question, how did OpenAI Soul finally learn design taste? She projected 1000 websites by GPT 5.6 Soul into a design manifold and discovered big holes. These holes were where GPT 5.5 previously generated outputs, outputs with quote, bad AI smell. So there were, you know, there's these tells in any AI model that you. It's not this, it's that the EM dash, once people start identifying those as ah, we don't like that. It's too AI, it's too generic. One way it appears to actually sort of beat that out of the model is to actively avoid those specific things. And then she calls out three particular areas that have been avoided as anti patterns. One, the bento box layout in dashboards. Two, large typefaces and hero images. I did realize that sometimes you would ask for a website and you would just get a massive block of huge text. And that's just not the way when you land on a beautiful website, it's usually there's more wordsmithing, there's more slang.

[B]

Well, you know, you make your first website with five, six, old, whatever and it looks really good.

[A]

Yeah.

[B]

And then you make 10 and they're like, oh, okay, there's Actually, a lot of patterns I'm seeing.

[A]

Totally.

[B]

And you can start clocking them, like, everywhere. You see a lot of, like, cloudisms, whatever.

[A]

Yeah.

[B]

General design, especially.

[A]

Yeah, especially if you don't come with,

[B]

you know, it's like the, you know, high border radius on the edges. There's a little color on the side.

[A]

Yeah. Yeah, especially if you don't come with, like, an opinion. If you come like. We made a whole vibe coded website in Codex for just the latest episode of Nick Bostrom on Joe Rogan. And I wanted it to look like a UFC fight card and a fight promotional website. And it doesn't look like any normal AI slop. I mean, there's still AI generated images. It looks like AI, but it doesn't look like, oh, yes, that's the bento box layout, or that's the offset layout or that's the purple, or it's stealing from linear. It's a completely different style. So if you at least inject one reference point, you'll usually land somewhere.

[B]

Yeah. It is interesting, though. This makes it seem like the new model is not necessarily. It doesn't have higher variance with outputs. It gives, but it's. We basically just found, like, oh, there's certain examples that people really don't like. Let's just remove those. But you're not necessarily making the model more creative by removing these patterns. It always comes to you.

[A]

Yeah, well, you're giving the flavor of creativity and maybe that's.

[B]

Yeah, but you can imagine if we kind of keep the same model for six months, we'll just notice new patterns.

[A]

Totally.

[B]

And you'll have this kind of problem.

[A]

But at the same time, like, midjourney had, like, a very distinct look, and people like that look. At least some people. And so if you can quickly personalize and customize and land in a place where someone whose job is designing dashboards is happy every time with the layout. Like, there is somewhat of a platonic ideal for some of these design patterns. And at the same time, if you're working on certain. So, like, there are certain designs that are just, like, solved. Like, you know, make the call to action. Green, blue, not red, Right.

[B]

Yeah.

[A]

And so some of those, like, do need to be consistent. And then also I imagine that many folks who are using these tools, like, in enterprises are doing, even if it's not a fine tune, they're uploading a reference for everything that they're designing. So it's consistent with the brand that they've designed.

[B]

Yeah.

[A]

Anyway, California Forever lost a $3.2 billion shipyard project from defense startup Saronic after the company chose the port of Brownsville, Texas over Solano County. Oh no, you're not supposed to clap for that. We got a Texan in the studio who's happy about that. This is bad news for California. We want California have a whole bunch of amazing stuff. Brandon Corral, who wrote the newsletter tppn.com today, was very disappointed about this. The automated ship shipyard known as Point Alpha Port Alpha is expected to create roughly 10,000 permanent jobs, along with thousands of union construction jobs. Supporters say California's lengthy approval process ultimately cost the state one of the first marquee tenants that California Forever had pointed to as evidence its planned city could anchor a new era of American shipbuilding. Joshua, executive director for the California alliance for Jobs, said California failed to move with the urgency the product required required quote while Texas moved quickly and aggressively. Thank you Jackson. California could not provide clear expedited approval process needed, he said, calling the decision an enormous loss for Solano County, California workers and our state's manufacturing economy. Earlier this year, California forever signed a 40 year construction labor agreement covering 70,000 acres and labor groups later backed legislation to fast track environmental review and permitting for the proposed shipyard. The legislation has yet to advance. Instead, Texas approved a $211 million tax abatement package in June to secure Sironics investment at Brownsville, roughly 20 miles from Starbase. Labor leaders said they warned that without expedited approvals, the project would leave the state. And that is exactly what happened. A project insider told the San Francisco Chronicle that California Forever itself remains on track, but acknowledged that losing a major defense contractor sends a powerful signal about the state's to ability ability to compete for large industrial investments. Very disappointing. But I like Yan. I like the California Fair project and I'm excited for where he takes it next. I'm sure he's on the hunt for the next major tenant.

[B]

Got to talk about tsmc.

[A]

Yes, tsmc. TSMC both beat earnings and raised their capex guy. They're spending a lot more money and

[B]

pledged to invest an additional 100 billion in the U.S. yes, plans to spend spend a record amount cementing its position atop the global semiconductor supply chain.

[A]

Yes, but. And yeah and they're investing another 100 billion in Arizona Fabs. But people are worried about overspending. The news is that the Nasdaq dropped 1% on TSMC's spending plans, offset by strong results. Very, very odd story that in a time when even tsmc, which was not a particularly AGI pilled company for A long time since they'd been through the smartphone boom, the so many booms and busts, so many cyclical build out cycles that when they are finally like yes, now is the time, people are, I don't know, they're skeptical. In creator world, there is some news from Colin Samir. Lexus is now the official car of Colin and Samir. What does that actually mean? They made four ads for them that roll across the. Roll out across YouTube. They're sponsoring four videos on their channel. It's the first of its kind deal that represents broader shift taking place in media. The aperture of what it means for a brand to work with the creator is changing quickly. It's very cool to see because obviously They've been on YouTube for a long time. They've done a lot of like host red ads mid roll ads. But this is a much deeper integration and something that I think will be hopefully replicated all over YouTube and be a new source of revenue for creators of all kinds. So I was excited to see this. In other entertainment news, Jake from economic says this is almost hard to believe. Disney spent $129 billion acquiring Marvel, Star Wars, Pixar, ESPN and Fox, which is 182 billion in today's dollars. Throw in all their legacy assets in the entire company's market cap today is $169 billion. Do you know what this picture is missing?

[B]

Which, what do you mean?

[A]

So they're saying they acquired all these assets and the company's only worth $169 billion. What's missing from this analysis? The cash that's been returned to shareholders. Disney across dividends and buybacks has returned like 70 billion, maybe more to shareholders, which is, I don't know, I just thought. And it is an interesting angle because they have spent a lot acquiring and the company is not worth more than what they acquired. So there's this question of like were those, were those acquisitions accretive or destructive or dilutive. But there is a whole separate picture which is that a lot of cash has been returned to shareholders throughout this journey.

[B]

Yeah. Also, I mean that's the mechanism with which those acquisitions were funded also.

[A]

Yeah, yeah. Matters a lot. I don't know. It was sort of interesting. Sean Frank has a pitch. He says you should move to New York City, bro. You got to move to nyc. The weather horrible hundred degrees, easy AC F that taxes so high. Rent highest in the country. Air quality some of the worst in America. Tech bro. We banned. Do they really ban Waymo in New York?

[B]

I believe so. Yeah, they know Waymos.

[A]

Wow. That's very wild. Yeah. If you can make it here, you can make it anywhere. So I don't know. Do you ever have aspirations to move to New York City?

[B]

At some point, it seems I've been

[A]

to New York City, yeah. What do you think? It's a nice city. That's the thing, is that all of this is true and it's still a great city to hang out in. It's so fun, so dense. You can see. See so many people walk around. It's beautiful. It's just like. I don't know, it's unlike anything else. Still great, but. Yeah.

[B]

You never lived in New York City?

[A]

I've never lived in New York City, but I've spent a lot of time there, so I've had a good time. Thank you to everyone who tuned in in the chat. Thank you for positive reviews of Tyler. Let us know what you think of Tyler. Leave us a review on Apple Podcasts and Spotify. Write us an email, tell us how he did. I think he did fantastic.

[B]

Have the best Thursday of your life.

[A]

Yes. There you go. That's a good impression. That's a good impression. But thank you. Sign up for a [e-mail] and we will see you on Monday.

[B]

See you.

[A]

Goodbye. Oh, we got the flashbang. There we go.