Welcome back to the AI Daily Brief. Today we have a number of stories that, while seemingly disconnected at first, I actually think are part of a larger theme that's happening right now. AI competition has been fierce for some time, and despite the fact that the industry has at least thus far been pretty much a rising tide lifts all boats kind of environmental and will I think in many ways continue to be so. The competitive dynamics of the field are shifting right now in ways that feel more intense than just the past questions of who has the best frontier model. Part of that is that model is not the only vector of competition anymore, and in fact the core architectures of particularly how businesses use AI is itself in a potentially transitional period. It is in that particular cauldron, that in between moment that all of our stories operate today, the first of which is that Apple has sued OpenAI for stealing trade secrets in a lawsuit with fairly significant implications. On Friday, Apple filed a blockbuster lawsuit that alleges OpenAI had stolen hardware designs and assorted other IP. Now, despite the two companies nominally being partners, there's been rumblings about bad blood between the two for some time now, dating particularly back to OpenAI partnering with legendary Apple designer Jony I've in May of last year, many took that partnership itself as a clear indication that Sam Altman wanted OpenAI to become the next Apple and to produce a device just as revolutionary as the iPhone. What followed was a huge poaching campaign with OpenAI and Jony I've's design firm hiring more than two dozen hardware and AI specialists away from Apple. They also partnered with several Chinese companies within the current or former iPhone supply chain. In one specific example, Apple claims that OpenAI told a supplier that Apple had consented to them using the same metal finish as an iPhone, which wasn't the case. Now none of that is illegal, especially in Silicon Valley, where non competes are both illegal and culturally frowned upon. And in fact I think there are many people who would say that when it comes to their talent leaving Apple has kind of made their own bed through the actions or lack of actions they've taken around this dynamic new field. Still, what Apple is alleging goes far beyond the realm of strong competition. The lawsuit centers on an iPhone engineer named Chang Liu, who left Apple to join OpenAI early in 2025. Lou left Apple without returning his company MacBook, and also kept in touch with former colleagues that Apple claims were feeding him information. The most damning allegation is that Lou had knowledge of a software bug that allowed him to gain access to Apple's servers. In their lawsuit, Apple included a text message from Lou to a then Apple employee named Alyssa Peng. Lol, wrote Lou, I found out I can access the network storage. So funny. Apple claims that Lou used this access to download presentations, hardware designs, manufacturing details and testing procedures. While he was working at OpenAI a few months after that incident in April of last year, Peng also left Apple to join OpenAI. Apple claims that over 400 former Apple employees have joined OpenAI to date, largely to work in their burgeoning hardware division. Apple point to former iPhone design lead Tang Tan as the root of the problems. Tan had risen through the ranks to become one of Apple's top executives by the time he was thinking of moving on to join Jony I've as a co founder in his new design firm. In late 2023, Apple allowed him to stay on until early the following year, but they now allege he was already secretly working on plans with Ivan Altman. Apple alleges that Tan instigated the recruitment drive that followed. Now, at this point, you might be saying to yourself, well, yeah, it stinks for Apple that a bunch of their employees left for OpenAI, but that's just kind of what happens. What's more, you might rightly point out that with hiring 400 former Apple employees, you are going to inherently get lots of IP that's locked not in people's hard drives, but in people's minds from their experience at that company. And yet the most important claim in the lawsuit is that Apple is claiming that OpenAI encouraged, actively encouraged employees to steal IP on their way out the door, urging new hires to study confidential material before interviews or even bring hardware components and prototypes to show and tell sessions at OpenAI headquarters, writes Apple in their lawsuit. OpenAI's nascent hardware business now rests on the shakiest of foundations, rotten to its core by its illegal reliance on misappropriated trade secrets. The Wall Street Journal called this Apple taking the thermonuclear option. In their lawsuit, Apple claims that they tried to deal with this issue peacefully for months, asking OpenAI to investigate and rectify the situation. They claim they never got a response, so had little option. But the lawsuit the Journal reflected on Steve Jobs, notoriously declaring thermonuclear war on Google in 2010, calling the Android operating system a stolen product. They believe that Tim Cook, as one of his final acts of CEO, is taking a similar approach to stifling OpenAI's device. Experts have only had a few days to mull over the pleadings, and the consensus is still pretty mixed. Gene Gann, the director of legal at Saville's Singapore group, noted that California courts have rejected non competes, adding, so every allegation rests on conduct, retained devices, unauthorized access, misused documents, coached evasion in a jurisdiction where talent moves freely by design. Trade secrets law is the only legal perimeter left around institutional knowledge, and Apple has pleaded squarely inside it. Paul Simanza, the chair of the Engineering Management School at Santa Clara University, commented, getting an existing Apple employee to take the risk of bringing parts to an interview session seems more like a test of how desperate they are to work at OpenAI than anything else. Targeting Apple's supply chain is a declaration of war, and given that Apple fought Samsung for years over rounded corners, it is hardly surprising to see Apple listing metal finishes as an example of IP theft. The question here is how this gets settled, given that unlike with Samsung, Apple is unlikely to be interested in cross licensing anything from OpenAI. Now at this stage we have very little from OpenAI. Just a brief statement to the press which reads, we have no interest in other companies trade secrets. We remain focused on building innovative technology that empowers people everywhere. Now this is one where I very much want to wait to see what OpenAI files as a response before I really make up my mind on it. Googly Arose wrote, I am sometimes really surprised by how dumb very highly paid people in tech can be. 1. Leave Apple 2. Start building hardware at OpenAI 3. Access confidential Apple files on hardware from an unreturned Apple laptop 4. Expect what to get away with it I agree that this seems strange. It also feels very weird to me that OpenAI leadership would actively encourage such easy to document types of IP theft. It seems strange and desperate in a way that doesn't really comport with where OpenAI has seen themselves, but who knows, Smarter people have done dumber things. I think Ricky Ho is right when he writes that Apple's lawsuit against OpenAI is more than a dispute over trade secrets, but a signal that the AI race is entering a new phase where hardware, not just models, has become a new strategic battleground. That is really the theme right now, that it is no longer just about models, it's about the entire ecosystem around them now. One person who was not shy about commenting on this, as you might guess, was Elon Musk, who retweeted a post about it and said they sure put a lot of effort into this crime. In fact, Elon decided to use this weekend to resume his petty public feud with Sam Altman, retweeting a repost of his own post where he had said scam. Altman is super good at scamming. Elon added, he takes scamming to a whole new level. Sam Altman deciding to willfully ignore Michelle Obama's recommendation to go high when they go Low retweeted Elon Musk's post and wrote, homeboy, you're the one selling public market investors on short term space data centers. To which Elon responded, we start flying them next year. Maybe you can come see them if your parole officer approves. After stealing an open source AI charity, then you stole all of Apple's phone technology. Wow. What do you plan for an encore that's tough to beat? In a separate post, which, if we are declaring a winner in this unseemly tit for tat, has to be the victor, Altman tweeted, There are a lot of benchmarks that suggest 5, 6 SOL is the best model in the world right now, but the most reliable way to tell is that Elon is obsessed with me. Again, perhaps getting a preview of what OpenAI's tone is going to be with regard to this lawsuit when an I like Tesla's fan account tweeted, sam Altman wasn't afraid of Elon, but he is terrified of Apple. You can tell by all his posting today. Altman actually responded, I am not afraid of Apple, but I have tremendous respect for them. S tier company now, while all that was going on, the competition that is much more relevant for most of us right now is in fact the new competition between Fable 5 and GPT5.6 Seoul. Indeed, that competition seems to be potentially giving us a little bit of a reprieve at the end of the subsidy era. Over the first weekend with GPT 5.6, people were having a lot of fun discovering what the powerful new model could do. But there was one very common complaint. People were burning through all their tokens at an unbelievable pace. The problem was so severe that AI power users on X started to share tips on how to use 5.6Sol without immediately hitting the usage limit. Now, part of the problem was that this is one of the first models where you probably need to control reasoning effort rather than dialing the settings to the max. But there also seemed to be some configuration issues on OpenAI's end that contributed to excessive token burnt. Usage limits were reset several times over the weekend to compensate users, but that didn't do much to fix the underlying issues. On Saturday, Chubby commented, seriously, this has to stop. I've now set GPT5.6 from high to medium, not fast mode of course, and I'm still burning through my rates at an insane rate. My five hours are almost gone again, I've already used up all three resets. OpenAI needs to work on its efficiency. This is the biggest bottleneck on Sunday Morning, Tebow from OpenAI checked in with the Fix posting the last 48 hours of Codex and ChatGPT work have been intense. Three important updates 1 temporarily removing the 5 hour usage limit restriction for all plus business and pro plans 2 rolling out changes that will make GPT 5.6 SOL more efficient across the board and that will be reflected in less usage being used so that it can take you further exact impact to be quantified and shared. 3 We hit 6 million active users and are landing a usage reset in the next hour. Go do things According to early reports, some of the changes do seem to be helping and OpenAI said they'll continue to work on token efficiency tweaks. Now heading into the release of GPT5.6, many thought OpenAI would use the model released to poach users from Anthropic. The model was expected to land just as the trial period for Fable expired and Anthropic subscribers would be forced to pay full price. Of course, that's not how it played out with Anthropic extending the trial period until Sunday just as GPT5.6 was released. Then on Sunday they extended it again, including Fable in the subscription for another week and keeping Claude code limits 50% higher. Developer ECAS wrote, Capacity wars between labs are one of the best things that can happen to us who build with this. And while indeed this is an unambiguous short term win for the power users and really, what are you even doing listening to me right now? Go use this subscription subsidy while it lasts, because you do have to wonder how sustainable this price war will be. Semi Analysis recently updated their understanding of the size of token subsidies and and found the subscriptions are still a ludicrously good deal. The $20 a month tier still allow $400 of usage for Anthropic or 700 from OpenAI, while the $200 a month tier are now running at 8,000 in max tokens from Anthropic or a staggering 14,000 in tokens from OpenAI. Now obviously the average user isn't actually getting this much value from their subscription, but on a weekend with multiple usage resets from OpenAI and anthropic extending their Fable subsidies, there is very clearly going to be a price war that, at least for a while, we can all take great advantage of. And yet we know the frontier isn't going to be subsidized forever, even if we are getting a temporary reprieve. I do believe that it is temporary and I think that the race to find alternative architectures is going to do nothing but continue as we heard in the headlines today and in a main episode last week, the one answer of simply turning to cheaper Chinese models looks more in jeopardy than it has in the past. Interestingly, the founder of Chinese AI lab Zhipu, also known as Z AI, recently wrote a note imploring why frontier AI should stay open to all. He wrote. Recently we released GLM 5.2, our most capable open source model to date. It supports a genuinely practical context window of 1 million tokens, continues to lead in long horizon tasks, and is available to all users. It will also be officially open sourced under the highly permissive MIT license. Anyone will be able to download it, deploy it, and use it commercially with no restrictions based on the type of user or organization. This is the company's firm position expressed through the form of its product we choose to believe in a different path Frontier intelligence should not belong only to a select few, nor should access to it be withdrawn at any moment by a small group of rulemakers. It should be open, usable and buildable, and it should serve every developer. With one hand we reach upward to challenge the limits of intelligence. With the other, we build roads downward, making the most advanced capabilities as open and broadly accessible as possible. The heights we reach belong to all humanity, and the roads we build belong to everyone. And of course, it's not just the Chinese labs that are trying to own a different narrative around AI. Microsoft CEO Satya Nadella once again took the X to write a blog post further articulating the new vision for AI that they're starting to promote. In it, he argues that consumers and businesses right now, quote, 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 of that knowledge you have to feed it. He basically talks about how the frontier model providers get richer from usage models. He writes, learn from exhaust the prompts people write, the tools agents use, and especially the corrections people make when the model is wrong. Every correction is distilled into institutional know how. It's the kind of knowledge a competitor could never buy, and the kind that leaks almost imperceptibly, trace by trace, correction by correction, eval by eval. In consuming intelligence, you are creating intelligence, and what you create should belong to you. And here's his subtle declaration of war. While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation and to reserve the right to learn from customer usage and interaction data. If learning flows in only one direction, economic value converges towards the owner of the learning infrastructure rather than the creators of the knowledge itself. Therefore, it's imperative that we distribute the learning infrastructure to every firm so that they can control their own learning loop. He then refers to a recent interview with Palantir CEO Alex Karp, who said, what the technical customers want is control over their compute, their models, their data stack and their alpha. They want to know they own the means of production and it's not being transferred to someone else. The current regime, Nadella says, does precisely the transfer Karp and companies fear. So what should enterprises do? Well, Vercel CEO Guillermo Rush sums it up by saying, make the model a cog in a machine you own. Startups and enterprises must own their data evals Model choices Software layer don't outsource your brain CNBC's Deirdre Boso summed up some of the changes going on right now in a piece called the AI race is shifting from bigger models to cheaper, smarter systems, which is of course exactly the shift that we've been charting on this show. It's also one that markets are paying attention to. Big Shorter Michael Burry retweeted the CNBC piece, affirming that this is what he's been hearing from his contacts in Silicon Valley around where the AI race is shifting from bigger models to cheaper and smarter systems. Now, for some like Burry, this is how an AI bubble comes crashing. In short, if people don't want to buy anthropic and OpenAI tokens anymore, all the infrastructure deals around them crumble and everyone goes home a loser. Gavin Baker, on the other hand, thinks that this represents a big opportunity. Retweeting Michael Burry, he wrote the mega bull case for AI infrastructure would be if market share shifted away from certain frontier labs with 90% plus inference margins towards cheaper models, whether open source or closed. It would increase the ROI on AI spend for end customers by increasing intelligence per dollar, which would drive incremental token demand. Margin dollars would effectively get redistributed from the frontier labs to AI infrastructure providers. The infra winners would be those with the lowest per token cost, and the winners at the model layer would be those with the highest token efficiency. There are many reasons Jensen is so focused on open source, but this is likely the most important one. Lower margin percentage at the model layer equals more margin dollars at the infra layer. All else being equal now, Baker points out, this is not happening yet. Cheap, mostly open source tokens are likely the majority of volume today, but the majority of economic value is still accruing to the most intelligent models. Might change though. We will see. It's beyond the scope of this show, but one thing that I will explore in future episodes is what I find as a faulty assumption that even if this is the shift in buying behavior that happens, that somehow the leading Frontier Labs just aren't going to participate, all the evidence suggests that that's not going to be the case. And if you need evidence of that, just look at the announcement for GPT 5. 6. The cheaper versions of that model, I. E. Terra and Luna, were basically better than GLM performance for lower than GLM costs. If you think that OpenAI and Anthropic are just going to roll over and let the market shift away from them, you're nuts. I also think that the speed at which these sort of changes are going to happen are wildly overstated. Most firms are still trying to get their employees to use their CLAUDE subscriptions, not thinking about advanced model architectures even if they should be. And then of course I haven't even mentioned Google, who are off cooking something and have already released a lot of products that show that they're paying attention to the efficiency and cost side of the market. This might be an opportunity for them to be a leader in a really important market segment, even if their leading Gemini model at the moment can't match up with Fable and GPT 5.6. And still, for all that being said, there is no doubt that the tectonic plates of AI competition are shifting. I think a big reason for the intensity that you saw at the beginning of this episode, the growing public spats and acrimony, is that no one has a handle on exactly how things are going to shift next. Those unstable foundations create lots of anxiety and stress and tension even for companies that are doing really, really well now. What we see from these subsidy extensions is that at least in the short term, this sort of competition is really good for all of us. And so if you take away nothing else for this in between period, at least take advantage of the competitive upheaval because if you're smart, you can probably as an individual benefit from it pretty mightily. Anyways guys, for now, that's going to do it for today's AI Daily Brief. Appreciate you listening or watching as always. And until next time, peace.
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