Big Companies Start Hiring Again, Anthropic's Open-Weight Position, Zuck Backs AI for All | Diet TBPN

Summary

TBPN Podcast Summary
Episode: "Big Companies Start Hiring Again, Anthropic's Open-Weight Position, Zuck Backs AI for All"
Date: July 28, 2026
Hosts: John Coogan & Jordi Hays

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Main Theme:
This episode explores recent shifts in tech industry hiring trends post-AI hype, Anthropic’s public response and proposals on open-weight AI models, the continued power moves by giants like Nvidia, and Mark Zuckerberg’s public push for a democratized AI future. The conversation blends market analysis with the hosts’ trademark humor and commentary, delivering a snapshot of the current intersection of labor, regulation, and innovation in AI.

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1. Shifting Job Market: Big Companies Begin Hiring Amidst AI Integration

Key Discussion Points:

• The Wall Street Journal reports that after a year of cautious hiring or layoffs, large companies in tech, transportation, and defense are actively increasing headcount to work alongside AI systems, contrary to prior fears of widespread replacement ([00:01–01:47]).
• The shift is characterized as Jevons Paradox: introducing AI made workflows more efficient, which ultimately increased demand for human employees.
• Prior CEO statements attributing layoffs to AI were, according to the hosts, more about management PR than actual technological replacement.

Notable Quotes:

• "Total victory for both humans and AI. We're working together. Peace is possible." – John ([00:56])
• "It was a way for CEOs and management teams to save their own ass instead of saying, hey, we over hired or the business isn't doing as well..." – Jordi ([01:47])

Context:

• Companies like Alphabet, CSX, ServiceNow, Snap-on, and Booz Allen Hamilton are hiring, especially in roles enhanced by AI productivity ([02:51]).
• The market’s approach to AI hiring is maturing: “Just because you have coding agents doesn’t mean you’re not hiring engineers.” – Sarah Franklin, Lattice CEO ([03:34])
• Discussion of offshoring entry-level tasks to AI or freelancers; shift towards using AI for supplementary, not core, functions ([04:49–05:44]).

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2. Open-Model AI Debate: Anthropic’s Public Proposal

Segment Begins: [20:16]

Overview:

• Anthropic CEO Dario Amodei issued a formal response to debates about open-weight AI models, countering claims the company supports a blanket ban.

Anthropic’s Three Main Claims:

1. No Blanket Ban: They do not support an outright ban on open-weight AI models ([20:20–22:20]).
2. National Security: Emphasizes the need for the US to outperform authoritarian regimes (e.g., China) in AI.
3. Risks of Open Models: Warns of potential misuse of powerful AI for cyber or biological attacks.

Three Proposals Outlined by Dario Amodei:

• Sanction Chips: Continue to withhold advanced chips and equipment from China to maintain the US tech lead ([22:20]).
  • "Maintaining that gap...is an advantage for the United States." – John ([22:36])
• Crack Down on Industrial-Scale Distillation: Implement policy or legal measures against large-scale model distillation operations, though it's unclear how to define and enforce these ([23:05–24:54]).
  • “A policy intervention can mean anything…from a tax, a tariff, a fine, a sternly worded letter, not getting invited to a golf tournament...” – John ([23:30])
• Mandatory Safety Testing: All capable models, open or closed, should undergo mandatory testing before release to ensure safety ([25:02–26:50]).
  • “The risk is that small companies…could get tied up in a review queue for years…” – John ([26:26])

Gray Areas & Enforcement Challenges:

• Distinguishing between legitimate model training and distillation is blurry, especially when models mix synthetic and open-source data ([24:34–25:02]).
• Enforcement could lead to innovation bottlenecks and regulatory capture by large players, reminiscent of FDA and nuclear regulation issues ([26:50–27:54]).

Notable Quote:

• “Policy interventions is all we got here, and I think it’s still too generic at this point. I want to know, like, what policy looks like." – John ([30:51])

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3. Industry News & Power Moves

a) Company Announcements & Strategic Deals

• Recursive Superintelligence: Emerged from stealth with $650M in funding; signed a massive $410M, multi-year compute deal with AWS to support open-ended, self-improving AI systems ([15:57]).
  • “Throwing safety out the window. That should be the tagline because there's already safe superintelligence. But we're just doing recursive super intelligence over here.” – John ([16:09])
• Nvidia: Leased a $50B, 1-gigawatt data center in Texas from Hut8, further demonstrating its centrality to the AI supply chain ([17:15]).
  • "Nvidia big candle today, up 3%. 5.17 trillion. Let's take a look at Apple 4.99. They crossed 5 today. They're down a little bit since they breached that, but they're neck and neck." – John ([18:56])
  • Apple, Nvidia, and Anthropic have not signed the recent open-source letter, suggesting nuanced positions on open AI ([19:13]).

b) Guerilla Marketing: The Black Sheep–Google Feud

• Black Sheep eyewear launched a 25-truck campaign around Google’s Manhattan offices, demanding the return of $80,000 lost due to a claimed search glitch post-media spotlight ([09:46–13:05]).
  • Debate around whether Google is at fault or if it’s user error in mismanaging search redirects.
• Hosts joke about the “direct-to-factory” marketing language ("I want to send some eyewear to a factory...Direct to factory!”– John, [10:46–10:59]) and the viral potential of such spectacle-based advertising.

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4. The Ongoing Open AI Letter: Industry Reactions

Cloudflare, New Grads, and Hiring Sentiments:

• Matthew Prince (Cloudflare CEO) argues against dropping new grad hiring, advocating integrating them into teams for AI fluency ([07:31]).
  • "Wrong strategy to stop hiring new grads. The right strategy, hire them and insert them into legacy teams to help them better adopt AI..." – John relaying Prince's point ([07:31])

Company Positions & Signing the Letter:

• Anthropic, Amazon, and Apple have thus far not signed the Nvidia-led open AI letter, each for their own strategic reasons ([19:13–20:16]).

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5. Zuckerberg’s Manifesto: “The AI Future is for Everyone”

Segment Begins: [31:17]

Discussion Points:

• Zuckerberg's WSJ op-ed positions Meta/Facebook as a champion for democratized, decentralized AI; criticizes centralization as stifling human potential ([31:17–32:03]).
  • “History of democracy and economics has proved that centralized power stifles human potential.” – Quoting Zuckerberg ([31:17])
  • “The history of open source software has shown…full access to powerful systems will be the best way to protect safety and security over time.” – Zuckerberg, relayed by John ([32:02])
• Hosts note Zuck is filling a whitespace as the pro-open, pro-access billionaire in AI.

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6. Quick Hits and Community Banter

Apple Subscription Program ([33:31]):

• Apple launches a hardware subscription (leasing) service, with prices for iPhone, Watch, Mac, and iPad; hosts riff on how the industry has shifted from ownership to pay-by-month for both devices and other previously “owned” goods ([33:31–34:48]).

Humor & Recurring Bits ([05:35–09:46], [34:20–34:58]):

• Running jokes about hiring a full-time Celtic punk band ([05:35–05:56]).
• Banter about collectible trading cards featuring Silicon Valley’s infamous (Elizabeth Holmes, SBF, Zuckerberg) and the “canon” of business comedy ([09:15–09:33]).
• Discussion of the escalating “gong” arms race inside TVPN as a metaphor for the tech upgrade cycle ([34:18–34:58]).

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7. Memorable Quotes & Moments

• "You want a subscription gong?... There is a joy to being on the hedonic treadmill of larger gongs. Like, you don't want to jump straight to the biggest gong." – John ([34:20–34:46])
• “If you’re driving a Black Sheep truck around Manhattan today, reach out for sure, Nick. Make it happen." – John ([14:01])
• “Just because you have a data center doesn't mean you can like take an open source... Oh yeah, I open sourced Marvel...” – John ([29:24–29:32])
• “Policy interventions is all we got here, and I think it’s still too generic at this point.” – John ([30:51])

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Key Timestamps

• [00:01] — Introduction to WSJ hiring story & AI’s impact
• [03:09] — Companies signaling new hiring trends
• [07:31] — Cloudflare's approach to new grad hiring
• [09:46] — Business comedy trading card segment
• [09:51–13:38] — Black Sheep ads, marketing tactics
• [15:57] — Recursive Superintelligence–AWS deal
• [17:15] — Nvidia's $50B data center lease
• [20:16–31:16] — Anthropic’s proposals and open AI letter discussion
• [31:17] — Zuckerberg op-ed and open AI philosophy
• [33:31] — Apple launches device subscription
• [34:20–34:58] — TBPN “gong” escalation skit

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Tone & Style: Conversational, irreverent, deeply analytical but always leavened by humor and insider references; ideal for tech enthusiasts seeking both the headlines and the color commentary behind them.

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Useful for:
Anyone following hiring trends in tech, interested in the regulatory and geopolitical debate over open AI, or tracking the evolving power dynamics among Silicon Valley giants. Also recommended for fans of inside tech humor and business culture memes.

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For further updates and community news: sign up for TBPN’s newsletter at tvpn.com.

Transcript

[A]

Well, Anthropics responded, we're going to go through that proposal, the facts and the proposal for what happens next in the open, open model debate over whether or not they should be banned, restricted, tested, limited in some ways, sued. There's a whole bunch of different possible outcomes. But we'll take you all through it. The Wall Street Journal is reporting that large companies are beginning to.

[B]

They have a large white pill.

[A]

Yes, it is.

[B]

A large white pill has hit the front page of the Journal.

[A]

Yes. And I think people have been going back and forth on this. This is a story that's, that's just getting digested by the tech folks. Like the actual AI lab leaders who had predicted crazy job losses and are now not really seeing that. They're seeing productivity boosts and different diffusion, taking time in certain places and there's new capabilities, but it's not exactly a drop in replacement for a coworker, at least in, in most scenarios. And that's what the Wall Street Journal is reporting. So let me set the table and then we can debate it a little bit. After roughly a year of cautious hiring, companies across technology, transportation, defense and other industries now say they need more employees to work alongside AI systems. Total victory for both humans and AI. We're working together. Peace is possible. It's an example of Jevons Paradox. Jevons Paradox. When a technology makes something more efficient, demand often rises enough. The use and the need for people actually increases. For roughly the past year, many companies pointed to AI while announcing layoffs. This was a huge thorn in your side. I think you hated this more than anyone else. And you were right to because it did seem like it was just PR spin, et cetera.

[B]

Yeah. It was a way for CEOs and management teams to save their own ass instead of saying, hey, we over hired or the business isn't doing as well as we would like. We need to sort of basically settle down for a second and get our mojo back.

[A]

Yeah. And there.

[B]

Obviously no one wants to say that, but I think one of my favorite posts was the. And obviously these circumstances are never great, but the new CEO of Xbox came out and just was like very honest about the situation. And I think that more of that is necessary.

[A]

Yeah. Also there's a lot of firms where they, once they get to 10,000, 20,000 employees, they might say, look, 20,000 might be the right number, but the bottom thousand people are not performing. We would like to lay them off and then bring in a new thousand people that are better fit for the company and the current trajectory that we're on the current skills that we need, maybe we need more salespeople and those

[B]

bottom people might be top 10% at another company.

[A]

Exactly, yeah. So the narrative appears to be shifting. Companies like CSX, Alphabet, ServiceNow, Snap on and consulting giant Booz Allen Hamilton have all recently signaled plans to expand hiring, particularly in areas where employees can use AI to become more productive.

[B]

Yeah, it used to be somewhat of a flex if a company was like, yeah, we put up a role and we got 2,000 applicants.

[A]

Yeah, like, well that's true. And then also it's a little bit of a sign of like, oh wow, they have a hundred openings. Like, they must be like growing so fast, you know, so. But if it's just a prompt to say, oh yeah, put up like, look at my organizational design and add five roles for everyone because why not? Why not see who comes by, you know, we don't necessarily have to interview these people. So weird, weird dynamics. But we'll dig into it. So. Meanwhile, the latest weekly US Jobless claims fell to one of the lowest levels in decades, underscoring the resilience of the labor. The shift also reflects a more realistic understanding of AI's capabilities. Sarah Franklin, CEO of HR platform Lattice, says many companies initially assumed AI agents could replace entry level workers, but are now recognizing that human, human employees remain essential. Just because you have coding agents doesn't mean you're not hiring engineers, she said, adding that Lattice is seeing renewed hiring among many of its customers, including for junior roles. Robert Half CEO M. Keith Waddle said AI's effect on employment has been more benign than some have feared, adding that hiring demand continues to improve and market conditions are increasingly more supportive of business. And so I do think there was a little bit of like a successful psyop with the, with the AI is going to be able to do everything where I do think there are some firms that were like, yeah, maybe we shouldn't hire or because like, what if we get it wrong and we hire a bunch of people and then I really does catch up and we don't need those people. That's silly. We shouldn't go through that like whipsaw effect. And so people are going back and forth on that. Bryce Roberts.

[B]

Yeah, it's interesting at least in, at least in our organization, which is unique and, and very niche and there's not that many organizations that are running, you know, a niche technology daily show. Yeah, I feel like a lot of what the value that we get out of AI would have historically been done by not super expert Level freelancers. Right. These sort of like upwork style tasks that you would do historically. Like an idea for a funny song, right? Yeah, I've paid to get a funny song made probably a decade ago online, Right. As just like joke. And now you can just go to Suno and make something like that. And then there's other things like make a funny website. Right. I historically would maybe work with freelancers.

[A]

Wait, so you're saying that I should take down the five open roles I have for Celtic punk session musicians?

[B]

Not yet.

[A]

Because I was gonna hire five Celtic punk session musicians to constantly record Dropkick Murphy's covers for us every day and then perform.

[B]

I'm not ready to say that you shouldn't do that.

[A]

I'm actually closer than, than ever to hiring a full time Celtic punk band to play music, to recreate Sonics. Yes. I'm closer than ever to doing that where that was not even on the roadmap a few years ago. Yeah, I don't know. It's a good point. Yeah. There's a lot of things that you are doing that you would never do with a full time employee that just sort of fills the cracks and allows you to do more different things in your organization. But the core stuff is still, you want a person that's responsible and then you want them using AI. I don't know, the Wall Street Journal breaks it all down, but we went through most of that. So Bryce Roberts, he's taking the other side of this. He says he shares a screenshot of a text message, says, we honestly aren't hiring a ton right now. AI backfilling, most roles. Backfilling. Is that specifically. Does that specifically refer to when someone leaves the company, you backfill them with AI. So you say, oh, someone quit. Like if there's Steve and Jim on two different. On one team and Steve quits, you say, hey, Jim, can you just, instead of hiring another person, just do twice as much work with AI? Is that what this person's articulating? I mean, obviously there's some companies that are like, yeah, we're not hiring anyone. We're going for the one person, $1 billion company. Like, I'm not going to hire anyone. I'm just going to use.

[B]

Yeah, but that's rare. Usually. Usually when your business is ripping, you're like, I can't hire great people fast enough.

[A]

Yeah.

[B]

And sometimes you actually, sometimes you actually don't have time to invest into various hiring processes. But yeah, so I would read into this text, the company's just probably not like ripping. That's my. That's my takeaway.

[A]

Well, Bryce Roberts says, rip new grads. Matthew Prince over Cloudflare takes the other side. He says wrong strategy to stop hiring new grads. The right strategy, hire them and insert them into legacy teams to help them

[B]

better adopt AI in Cloudflare, of course, hired 1000.

[A]

Something like. It was a. It was a crazy number, wasn't it? Up there in, like, almost a thousand four digits. That's crazy. Let's play the latest. Good work. Real. We're just watching reels now.

[B]

This is what we got is a Bernie Madoff.

[A]

Pretty good gloves. That's from the 80s, too.

[B]

That's good. Yeah, yeah. I've seen a few of these around before. Up next, solid Sam Bankman. Fried here. That's nice. That's really nice.

[A]

I like that they actually printed these. I think he made balsa wood. This is balsa wood. The acting is so cool.

[B]

Wow. Wait, John. This is a. This is a vintage Zuckerberg. Oh, five. This is a vintage 05 Zuckerberg. Let's just check the back really quick. There it is.

[A]

That is a patch from his Fruit of the Loom boxer briefs.

[B]

You can tell by the smell.

[A]

Is that real? What is that referring to?

[B]

This is on athlete. You know, training cards. I'll put a piece of the jersey sleeve.

[A]

This one? Yeah, yeah. All right, up next. Sleeve it.

[B]

Ooh. Okay.

[A]

Nice. Elizabeth Holmes. We do have two.

[B]

I believe we have two. But a triple Holmes is what every

[A]

good collector has in their arsenal.

[B]

All right, last card.

[A]

One card left.

[B]

Three, two, one. Oh, my God.

[A]

Oh, my God.

[B]

Oh, my God.

[A]

Oh, my God.

[B]

Turn it off. Very funny.

[C]

Very funny.

[A]

It is funny how the. The, like, business comedy canon has really solidified around, like, Elizabeth Holmes, Sam Bankman, Fried Mark Zuckerberg. There's, like, a few names.

[B]

I'm surprised they didn't have an Adam Newman rookie card in there.

[A]

I don't know if Adam Newman is, like, a big enough name relative to.

[B]

That's true.

[A]

Sam Bankman. Fried and Elizabeth Holmes. It's just interesting, like, the different names that have broken out that you can do a comedy sketch that's like, you know, it goes as big as good work does because they get, you know, I think, millions and millions of views.

[B]

All right, pull up this image from Manhattan this morning. We got sent this.

[A]

We've been doing on the ground reporting

[B]

from one of our on the ground reporters in Manhattan. There's a company called Black sheep

[C]

that

[B]

got 20 trucks, and they are just driving them around. Google's Manhattan office saying, shame on you. Google return our $80,000. We had to dig in. We got very curious.

[A]

I had no idea they make sunglasses.

[B]

They make $8 sunglasses that beat $350 sunglasses in an NBC lab test.

[C]

Okay.

[A]

Are you wearing Black Sheep today?

[B]

Which I wish. I wish. So Black Sheep makes direct to factory.

[A]

Okay. Factory direct prescription eyewear stop paying for.

[B]

No, no, no, no, no. This is from their own website. They're saying direct to factory optical disruptor, which is not. This is from their website where it makes it on Black Sheep.

[A]

I'm on Black Sheep IO as well. It says factory direct. Direct to factory. Look, I want to send some eyewear to a factory.

[B]

Direct to factory.

[A]

I'll be sending it to them.

[B]

Direct to factory.

[A]

Yeah.

[B]

So this company, they say direct to factory optical disruptor. Black Sheep launches 25 truck guerrilla campaign against Google in Manhattan.

[A]

Okay.

[B]

And then they're sort of like narrating their own guerrilla campaign. A fleet of 25 minimalist LED billboard trucks surrounds Google's Chelsea headquarters after the tech giant weaponized an organic search glitch to pocket nearly 80,000 in ad spend following Black Sheep's viral NBC Today show debut. 25 LED trucks deployed. $77,000 drained in 30 hours. And then they're just continuing to market their own products. Very interesting strategy here. I think every marketer has had the experience of having a campaign go haywire. Very fascinating to take to take this route. Let's see how it works for them. If I were Google, I would say you can have your $80,000 back, but you can never advertise on Google again because I just don't know how.

[A]

I don't think Google would ban them permanently for this. This is ridiculous. But you know, they're just gonna be like any other, like as a self serve platform.

[B]

But is it a good campaign?

[A]

But what, what actually happened? So they say how it unfolded. NBC Today SHOW segment airs they test the retail subscription against Black Sheep's factory direct pair. National search traffic spikes. Hundreds of Americans search Black Sheep because they're seeing it on tv. The organic listing breaks. Google search engine redirected organic brand traffic to a dead end third party 404 error page. And so with the organic route broken, users were funneled into Google's paid listings. So what is their claim? How is Google responsible for this exactly?

[B]

Sounds like user error because I mean

[A]

you do have some control over your Google search results based on the webmaster tools. You can index certain things and then also if you're noticing a 404 page. You could, like, redirect it quickly. But again, if this is happening all

[B]

very fast, they can use your error.

[A]

But I mean, it is interesting because they're probably going to get more than $77,000 worth of organic just from this. I mean, I didn't see the original campaign and I'm seeing this because this is hilarious, but this is like. Is this. They. They shared an AI image with tons of these, like, shame on you trucks. But those are real.

[B]

These are real.

[A]

And are those minimalist or maximalist? Those seem maximalist to me, but maybe they're minimal.

[B]

Minimalist, I guess, in the. In the display of the. Yeah, in the way they actually are leveraging the space on the truck.

[A]

But black and white, truly underrated surface area for stunts and advertising. This message is sort of like squabbling with Google over this sort of odd scenario. But you can imagine someone using this for something much cooler and much more positive and not like this sort of unfortunate situation for them where they're dealing with the fallout of a Google error.

[B]

Well, we want to interview the truck drivers, so if you're driving a Black Sheep truck around Manhattan today, reach out for sure, Nick. Make it happen.

[A]

Ilya said straight shot to ssi. So they better not be gearing up to release a work agent called Francois. Francois would be a very good name for. For an AI agent. I like that. I do wonder what they're going to be releasing as the SSI is going to release. Is that complete rumor? Because all. All illnesses.

[B]

They just said they would scale their research.

[A]

Scale their research. So that just means they've done a bunch of research. They have some sort of architecture that they like, some sort of flywheel, and they're going to, like, use more compute. And so that's why they're raising money. I don't think they said, like, and we're going to release it publicly. Yeah, but everyone's thinking, like, probably still LLM or something different. No one really knows.

[C]

Yeah, I mean, I think still, broadly, like, generally. LLM.

[B]

God.

[A]

Next level. There are levels to vague posting when you live a vague life. Just like your entire life is vagary. Anyway, in other news, Recursive superintelligence signs a $410 compute deal with Amazon. So funny. And it's in the TechCrunch. It's in the header too. Of course. That is a typo. It says, recursive superintelligence signs $410 million compute deal with Amazon. Congratulations to Recursive Superintelligence Throwing safety out the window. That should be the, that should be the tagline because there's already safe superintelligence. But we're just doing recursive super intelligence over here. But of course the company is doing very well. They emerged from stealth in May with 650 million in funding focused on building open ended, self improving systems and potentially compute intensive approach to AI research. This multi year deal is meant to provide flexibility as the company looks to scale up those systems. Recursive $410 million outlay represents the bulk of the company's fundraising to date. But on a call with TechCrunch.

[C]

Hey, hey.

[B]

They still have a couple hundred million left over.

[A]

Founder and CEO Richard Socher emphasized that he expected it to be the first of many such deals. So is this. I feel like normally when you see like a compute deal signed, it's always like more complicated than just like we're buying this expensive thing. Usually like we're paying that. I'm like we used to be so like anti circular deal that now I just have come to. I've been so normalized by them that I expect them every time and I'm like wait, wait, this is, there's no circularity here. I would have expected to be changing. Yeah, like Amazon's investing in you and you're buying Trainium and racking it and AWS New Campus and they're investing in this and that and you're investing in them instead. It just seems like it's a pretty vanilla deal. It's like they're just buying a lot of compute from Amazon. Great.

[B]

Seems like it.

[A]

Well, good luck to them. Very excited for what they're launching.

[B]

Yeah. Jason, VP of startups and VC at aws, says part of the agreement is that we're gonna co develop him for a purpose built for these types of companies. So fingers crossed. But it seems like we could get some circularity.

[A]

Yeah, let's hope so. Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite to deploy web app services and more. While Railway automatically takes care of scaling, monitoring and security. Fingers crossed. Well, well here's, here's a deal that's somewhat circular. We got Nvidia revealed as a tenant for a $50 billion data center that will use its chips. So they're the tenant of the data center that uses its chips. We'll talk to take him about this. CEO Jensen Wong deploys balance sheet to backstop growth of AI computing market Nvidia signed leases worth up to $50 billion for a massive Texas data center. That's very, very big. That's very, very big for a single site. A previously undisclosed commitment that shines a new spotlight on the chips. On the chip group's growing role in financing AI. The nearly $5 trillion company is leasing the entire 1 gigawatt facility that developer Hut8 is building, which will house hundreds of thousands of Nvidia graphics processing units. So you have to imagine that once they have these, they serve something or wind up selling them. These things change hands so many times. There's a lot of different ways that this could play out ultimately. But in the. Can we pull up the Nvidia chart? Yeah, there we go. Nvidia big candle today, up 3%. 5.17 trillion. Let's take a look at Apple 4.99. They crossed 5 today. They're down a little bit since they, since they breached that, but they're neck and neck. Google is sitting at 4.

[B]

Apple running the do nothing win strategy. Jensen doing thousands of deals.

[A]

They didn't even sign the open letter. There are three companies that still, I believe, still haven't signed the open letter.

[B]

Only three companies on the entire surface of the earth.

[A]

There are three. There are three major companies that haven't signed that Nvidia open letter about banning open source and. Or not banning open source. Amazon, Apple and Anthropic. Anthropic put out a post yesterday, very, very clear response, sort of outlining their view on open source, their stance. Apple and Amazon haven't signed and they both have like very physical elements in the world in the sense that they're not. They're sort of unslappable, like, you can't vibe code an Amazon warehouse, you can't vibe code an iPhone. There are threats to those businesses, of course. And of course Apple should benefit from open source and so should Amazon because they'll be able to serve open models across aws. But it's just potentially interesting. I think the Apple standing, standing back is more just like, look, we're not jumping on with this crazy open letter that everyone is signing. Like, we just have our own brand, we're thinking different, we're doing well.

[B]

And based on other Apple AI timelines, I would expect them to sign it in maybe a year or two,

[A]

potentially. These glasses have changed you. They turned you into a beast. Let me run through the three anthropic proposals because it's an important response. So Dario Amadeh, Anthropic CEO, responded directly to that letter summarizing supporting open weight models that circulated over the weekend. So he makes three claims just to sort of clarify things that I think are important. One, he says Anthropic has never advocated for a ban on open weight models. Now that's a blanket ban. There's obviously like defining what a ban is and what an open weight model, what a distilled model, what a foreign model is. These things all matter. But he has, he has come out and said, look, we never advocated for a total ban on open weight models. Two, he says undergirding all of this is the US must beat authoritarian governments in the AI race. He points to China, but he identifies any authoritarian government. If they get really powerful AI, they, they'll come over here and steamroll us and you won't be free to do whatever you want to do in America. Three, powerful AI models may be misused to carry out cyber attacks or biological attacks. There are risks to having really, really powerful AI open source systems just running around. So he's worried about those three things, clarifying those three points. But he makes three recommended actions. He makes three proposals. First he says let's continue to sanction chips, let's not sell chips to China. He says we should not sell powerful chips or chip making equipment to China. So this has been debated for years, like going back to the Biden chip controls. Everyone knows every different angle on this, the basics. I mean there is a pretty good argument for chip controls even on purely geo economic competitive grounds. Like even if you don't believe in the risk of authoritarian governments having powerful AI, even if you just think it's like, you know, fancy autocomplete, it's like, well it's the engine of our economy and if you can slow down a rival economy, that's beneficial to you. Right. And so, and there also seems to be basically unlimited demand for chips in America. So by restricting sales to China, that shouldn't actually hurt American chip companies all that much.

[B]

But yes, well they just like their argument would be we fully lose the Chinese market, which is second largest computing market in the world.

[A]

No, no.

[B]

Right, so, so I think, but, but you're the counterpoint to that is you were going to lose it anyways.

[A]

Yeah. And a lot of that stems from the fact that China has been building an indigenous chip supply for decades. We've talked about going back to a whole bunch of their, you know, state led, state funded chip and fab processes. They've always been a few years behind. And so maintaining that gap, all else equal, is an advantage for the United States. The second point Dario makes is he says we should crack down on industrial scale distillation operations. This seems totally reasonable. Companies can set their terms of service and they have a right to maintain intellectual property with proper legal consequences for violations. Anthropic's been fighting distillation attacks, but according to them, it's not that effective. Dario proposes policy interventions to deter this behavior. And this is where I'm still not clear on what, where that goes next. Like, what is the correct policy intervention? There's a policy intervention is a very, very broad thing. It can mean anything from like a tax, a tariff, a fine, a sternly worded letter, not getting invited to a golf tournament. Like, there's so many different things that policy like, covers these days. Right. Where, where does this actually go? He says he doesn't want a blanket ban on open weight models, but it does seem like one possible policy intervention would be to sort of like ban, restrict or pressure open weights models that can be reasonably shown to have been distilled. So if there's someone who's just a perfect distillation, it just gets. It just doesn't quite feel right. It's hard to quantify these things. We don't have a binary where you run some sort of algorithm. You say, yes, this was distilled because you can distill half on Opus 5 and then throw in a little GPT 5.6 and then mix in some mistral and just be distilling from all over the place. Fine tune stuff, change the flavor, change the RL environment. There's so many different pieces of it. And Tyler, you were making a point about tynker or inkling.

[C]

So the inkling model from Thing machines, it used some synthetic data that was created with, I think, Kimi K 2.5.

[A]

Yes.

[C]

So like, does that count as like distillation? Like, probably not when people usually talk about it, but like, it definitely benefited from Chinese open source models. Yeah, So I wouldn't call that downstream of.

[A]

Yeah, I wouldn't call that industrial scale distillation. Yeah, sort of downstream.

[C]

There is like some big gray area where, like, how do you actually define this?

[A]

Yes. And so defining that is going to be what that's going to be the conversation that plays out in, in D.C. like behind the scenes on the basis of this. And that's where the actual negotiation is going to happen between, you know, the position of Nvidia and everyone that signed the letter versus the position of Anthropic and everyone who didn't sign the letter, they're going to sort of decide, okay, well if you can prove this, this and this, and you can show us that your API was getting hit by these different things, and you have a really solid report of what happened. And then the model also, you know, sort of, you know, checks these boxes quantitatively. When we do this eval, then maybe we will pressure it. And then what does that actually mean? You could go after the lab that committed the distillation attack with lawsuits, but that seems really difficult given the international nature of these attacks. So we're sort of back to where we started. Like, what. What can the government do that the lab can't? Like, the lab should be looking at every customer and saying, oh, this seems like someone who's trying to distill. They keep asking for basically what looks like a lot of training data. They're not acting like a normal user, just being like, build me a website. Okay. Third, he says all sufficiently capable models, open and closed, should go through mandatory safety testing. So this was recently outlined by Demis Hassabis over at Google DeepMind as well. And it seems like the two companies are in alignment on this in particular. Particular. And it's a somewhat reasonable position, although the risk is that small companies who have safe models could, that aren't distilled could get tied up in a review queue for years before they can release. Like, that would be very, very annoying if you're recursive super intelligence, for example, and you don't have a Washington D.C. office and you're like, hey, we want to release our new model. And they're like, yeah, totally. Like, you got to go through the, the review process, get in line. And then it's like every, you know, every trillion dollar company is there with a ton of lobbyists being like, well, review our model first, because we want to get out a week before the small startup. And that's the frustration of biotech, the fda, anything that goes through approval. We've talked about this with the nuclear stuff, it gets very tricky. And so you want to avoid that and you don't want to wind up slowing down innovation that's happening on small scales and decreasing competition. Dario does do a good job of like, acknowledging up front that he says it would protect us AI companies from competition. But that's never been my goal with anything that he's saying here. And so it's still worth working through what happens in a really adversarial situation. Like, what if a foreign lab distills a bunch of frontier models? They're the most aggressive, they're just distilling everything. Then they Jump forward a bunch in capability, they get a bunch of smuggled chips, they take all the restrictions off of cyber, all the restrictions off of bio and then they just drop the weights on like a torrent or they put them up on hugging face and hugging face is like this is really crazy. No one likes this. There's a lot of pressure to take it down. I don't know but it's out there. Like what does the government actually do? Like the government probably pressures or bans like hosting the weights, maybe serving the model, you maybe won't be able to run it in American data centers. You go to the Neo cloud and say like hey, this thing is actually bad. And I think people are divided on this because they see the current models not as actually dangerous which is totally reasonable to assess that. Yeah, it's not that bad but like if there was a model that was like yeah, it's actually just like the killing machine, like I think most people would be like yes, I'm democratically voting to not serve that because it's just like it's an annoyance at best and like actually bad.

[B]

It works. And the other big question is like how much computer do you actually need for it to be dangerous?

[A]

Yeah, totally.

[B]

This is like having some GPUs in the back shed going to be enough maybe for sufficiently advanced model. Yes. Or do you need access to a ton of racks? Yeah, ton of power. And then you do need to work with a Neo cloud in that case.

[A]

And as soon as you're a US based company with a real data center with a bunch of NVL 72s in there, you probably have registration and you know, all sorts of just like business registrations where the government can reach out to you and say hey, we're actually really worried about this. Just like there are other things you can't host in a data center. There's all sorts of stuff that's illegal even if it's just intellectual property.

[B]

Yeah, exactly. Yeah, that's like you can't even, just,

[A]

just because you have a data center doesn't mean that you can like take an open source, you know you can't

[B]

as a data center.

[A]

Oh yeah, I open sourced Marvel like

[B]

they'll be, or even, even a, you know a CRM company can't knowingly support like a organized cartel, global cartel that is like trafficking narcotics. Right. You have, you'd have to imagine like

[A]

that they have, they have to buy

[B]

their own balances

[C]

maybe.

[A]

So, so, so what's interesting is like what is the next step of that. So if there is a bad model and everyone agrees, like, okay, yeah, we got to not host this, not distribute this. Like, yeah, the weights are out there. People are trying to, like, sort of run it a little bit. But does it go offshore? Do we wind up in, like, the crypto scenario where there's like, these offshore things and people are using VPNs to get access to it? Like, what level of aggression do you see from the US Government in that scenario? It probably should be proportionate to, like, the danger imposed by the model. Like, if it's just a model that's like, that's like, annoying or like, slightly IP infringes, but, like, no one's really being like, I'm not. I'm canceling my Disney subscription because this new model will generate me Disney ip. Like, that's probably not like, okay, put up a crazy firewall. But if it is like the ultimate hack machine that's like stealing everyone's money from the banks, then, yeah, you are going to put up the firewall and sort of be much more aggressive. So I think the response will be in reaction to whatever the power of the models are. But it'll be interesting to go back and forth anyway. All in all, the letter clarifies a lot about the anthropic position. So I think it's good that it came out, but it's still worth working through the game theory of, like, what happens down the line. Policy interventions is all we got here, and I think it's still too generic at this point. I want to know, like, what policy looks like. I want to predict that. I want to understand what's actually being proposed, what people like, what people don't like. And so I think we'll learn more about this in the coming days.

[B]

Mark Zuckerberg is in the Wall Street Journal opinion section with a new piece, the AI Future is for Everyone. He says the history of democracy and economics has proved that centralized power stifles human potential. And it's quite long ago. Let you guys read it. But let's head into the comment section. Let's get it. Let's get a quick reaction. Let's get a quick reaction.

[A]

This is the Wall Street Journal.

[B]

I think it'll be, you know, it looks relatively tame.

[A]

It'll be.

[B]

But yet making a, you know, a clear effort to position to. To be the overtly. There was a white space for a guy investing hundreds of billions of dollars a year in AI that is like, says, hey, this is going to be really great for everyone.

[A]

Yeah.

[B]

And I'm going to help us get there.

[A]

It is, it is interesting. Like, Facebook does have some monopolies, but like, the competition for attention is constant and there are always sources outside. Like, they've never had a full monopoly on social media, even with TikTok and Snapchat and LinkedIn and Twitch and YouTube and Netflix and the podcast feed and SMS and iMessage. Like, there are so many other platforms for disseminating information. Like, I don't know. I. It's hard to jump straight to a critique here, but the key quote that Andrew Curran pulled out was that he said in most cases, like cybersecurity, the history of open source software has shown that giving everyone full access to powerful systems will be the best way to protect safety and security over time. So he's firmly on the side of democratizing powerful AI. And he is yet another one. I imagine that they signed the letter. I've lost track at this point, but you can imagine that he did. Anyway, thank you so much for tuning in. The other piece of news is that Apple is launching Apple Upgrade next week. Then iPhone, iPad, Mac and Apple Watch leasing subscription program. They said you will own and you will be happy.

[B]

We're launching our new program. You will own nothing and be happy.

[A]

It's partnering with Klarna to launch in the United States at online and retail stores. It's now official leasing prices start as low as $20 or $17.99 per month for iPhone, $11.99 for Apple Watch, $24.99 for Mac and $11.99 for iPad. So interesting. I mean, a lot of people are saying this is a direct reaction to. To increased prices for memory, increased prices for products. There was a time when an iPhone was a couple hundred dollars and there were incentives to jump on a Verizon plan. And you sort of amortize the cost over that. Those days are gone. Like, we're in the world of like a $2,000 iPhone.

[B]

It's a significant same thing with our gong for people. Honestly.

[A]

You want a subscription gong?

[B]

No, I'm just saying there was a time when a TVPN gong was $200.

[A]

Yeah.

[B]

Now it's in the tens of thousands of dollars.

[A]

It's actually so expensive. Somebody, a friend of mine, texted me and was like, where do we get the gongs? I need a gong. And I was like, I think you should start small. And this is not like you can't handle the big gong. I was more saying that, like, there is a joy to being on the hedonic treadmill of larger gongs. Like, you don't want to jump straight to the biggest gong. You want to start with a small

[B]

gong and work your way up.

[A]

Work your way up. Because every gong that we've added has been been so electric. When we get.

[B]

I think it's time for a new one.

[A]

You want an even bigger gong or.

[B]

Yeah, I want. I want one that's hanging from the rafters.

[A]

Leave us five stars on Apple podcasts and Spotify.

[C]

Money never sleeps. You shouldn't either. Call me back.

[A]

Sign up for the [e-mail] and we will see you tomorrow at 11am Pacific. Goodbye.

[B]

Cheers.

[A]

Flashbang.