The AI Daily Brief: Artificial Intelligence News and Analysis - How the Escalating AI Wars Benefit You
Episode Date: July 13, 2026Apple’s lawsuit against OpenAI signals an AI race expanding beyond models into hardware, efficiency and control. NLW explains how the escalating competition is producing better models, higher usage ...limits and lower costs for users—and why the opportunity may not last. In the headlines: the White House weighs action on Chinese open-source AI and the UAE gains greater access to advanced US chips.Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at kpmg.com/us/SophisticatedHyperagent - Hire a fleet of always-on agents. New users get $1,000 in inference. hyperagent.com/aidailybriefRetool - Secure your vibecoded apps. New enterprise customers get up to $10,000 in AI credits per year. retool.com/aidaily Rackspace Technology- One accountable partner to build, operate and run your full enterprise AI stack https://www.rackspace.com/Section - Section turns AI investment into workforce transformation and ROI - https://www.sectionai.com/Scrunch - The AI customer experience platform - https://scrunch.com/Blitzy - Want to accelerate enterprise software development velocity by 5x? https://blitzy.com/AssemblyAI - The best way to build Voice AI apps - https://www.assemblyai.com/briefRobots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Our Newsletter is BACK: https://aidailybrief.beehiiv.com/Interested in sponsoring the show? sponsors@aidailybrief.ai
Transcript
Discussion (0)
Today on the AI Daily Brief, Apple sues Open AI, and tensions are ratcheting up as the AI competition shifts.
We're going to discuss what happened and how it potentially benefits you.
Before that in the headlines, reports suggest the Trump administration could be thinking about a new AI executive order focused on open source.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive in.
First of all, thank you to today's sponsors, KPMG, Blitzy, Retool, and Airtable.
To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe
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at AIdailybrief.a. Finally, for those of you who have been Jonzing, for some summer learning
activities, keep an ear out. We are going to be announcing some fun things soon. Your AI adventure awaits.
For now, though, let's talk about this new potential executive order.
Now, the theme of our main episode, as you will see, is the increasing intensity of AI competition.
galvanized by this liminal in-between period where there are major questions about which types of
models are going to have value accrued at them, whether alternative architectures will change the
entire shape of the AI business, and surrounding all of that is a geopolitical dimension, of course,
which has made everything much more acute. Now, last week, we explored some reports that China was
potentially considering ways to restrict or limit Western access to leading open source models. Now, however,
there are rumblings that the Trump administration is itself considering another executive order
to deal with what they perceive as the threat of Chinese open source AI models.
In a Politico newsletter, journalists claim the White House is working on another EO to tackle the issue.
Writes Politico, nine people familiar with the subject said the administration officials
appear to be holding at least early stage discussions of how to deal with open source AI,
a technology that poses potential security risks that existing U.S. policies are ill-equipped to handle.
Now, officials denied this executive order is in the works.
But reading the tea leaves, it would not be at all surprising to see the admin heading in this direction.
During the short period last month where Mythos and Fable were offline, we had tons of headlines
about GLM 5.2 and China creeping back up on frontier level performance.
Now, of course, for those who are deep in the weeds of AI, we can understand how GLM 5.2
could be extremely valuable without it actually being at Mythos level, but it's fairly unlikely
that senior White House officials at this point are running their own benchmarks to test model quality
or much to their detriment listening to the AI Daily Brief, rather than simply reading
headlines like this one from Fortune, which read, buckle up, the bad guys now have an
AI model as powerful as Mythos. As an aside for what it's worth, even the ZAI CEO, Xi Tang,
said that they are not there yet, although they do expect to have an open source model at Mythos
level by the end of the year. Additionally, there's been some chatter that the administration's
AI policy isn't going as well as they'd hoped. Last week, Politico reported on an AI infrastructure
export program that received a pretty tepid response, embarrassing commerce officials. The report noted
that Chinese firms are successful in, quote, turning out low-cost open-source models that developing
countries are increasingly adopting, and there are some indications that this administration is
interested in pushing U.S. models and infrastructure out into the world, viewing Chinese models as threatening
that strategy. This is the flip side of the export control debate that we've been having forever in the U.S.,
which is do you, one, restrict access to the most frontier models and the infrastructure to build them,
or two, do you try to get models everywhere and use models themselves as the sphere of influence?
And although most of our U.S. policy has so far focused on the restriction side of things,
it seems that some are interested in open source diplomacy.
Now, ultimately, at this stage, all of this is just rumors.
Andrew Curran commented,
it's not clear if the executive order would target Chinese open source model specifically
or apply more broadly to open source AI in general,
but something is probably under discussion.
And indeed, that plausibility seems to be the general tone.
Adam Tierer from the R Street Institute said,
I would not be surprised if this admin eventually sounds off about governmental use of open source AI
and even potentially limits agency use of various open source tools.
Some open source advocates are certainly wary,
with interconnects Nathan Lambert writing a piece called Six Months to Live for Open Models,
with the subheader saying it all,
staring down the barrel of policy action that could make open models a permanent second-class
citizen. This is certainly something we will keep an eye on, but in terms of policy that is here
right now, the Trump administration has eased export controls for the UAE, paving the way for AI megaclusters
in the Middle East. In a rule change posted on Friday, the Commerce Department wrote that the
UAE government and approved companies will now be able to access advanced AI chips without a
license. The notice, which also enabled military exports cited new technology protection measures
under the export deal signed in May of last year. That deal also contained domestic investment
pledges that would see Emirati groups accelerate foreign direct investments in the U.S.
The Commerce Department also cited cooperation from the Emirati government in the conflict with Iran.
The Commerce Department said that they plan to favorably review applications from
Emeraldi investment firms G42 and MGX, allowing them to shortly begin chip exports.
It's unclear exactly how large the data centers plan for the UAE will end up being.
Last year's deal mentioned 500,000 chips, but once MGX and G42 are approved, there's effectively
no limit. Now, this is a fairly big development in terms of geopolitical precedent. The ability to
import controlled goods without a license has previously been restricted to countries that are signed
on to multilateral export control regimes. Generally, NATO countries are members of other formal
alliances. By way of example, other friendly nations in the region, including Saudi Arabia and
Israel do not enjoy this benefit and need to go through the formal licensing process before getting
access to U.S. tech. Even the Commerce Department acknowledges that this is a significant step,
writing that it would, quote, significantly upgrade the status of the UAE in recognition of their
status as a U.S. major defense partner and its support in advancing U.S. national security interests.
Unsurprisingly, the move is very controversial.
Senator Elizabeth Warren blasted the deal as, in her words, corrupt due to President
Trump's outside dealings with MGX through his family's crypto business.
Warren claimed the president received a $263 million windfall from the deal.
Meanwhile, Chris McGuire, a noted China Hawk from the Council on Foreign Relations and former
Commerce Department official also had deep concerns over this policy change. He said,
now it is likely that the world's largest data centers will be in the UAE instead of the United
States and will be operated by firms that will provide back-door access to China. There is only
one explanation for why commerce made this change. The UAE paid for it. Ryan Fetisioch from the
American Enterprise Institute differed, however, commenting, I'm not sure this was the right decision,
but with respect, I think some of these concerns are either overblown or fail to account
for where the world is heading. He acknowledged concerns of transshipment of chips to China,
remote access to training clusters and overall technology leakage, but continued, it is clear
we are moving closer toward a world where the Gulf is an essential node in a globally distributed
network of hubs running USAI inference workloads. I don't see an alternative to that future.
And so, if there is some upside to this decision, it is that exporting large quantities of chips
with less supervision will bring forward this reality sooner than later. We are living through an
essential window where China's advanced chipmaking capabilities are still in their infancy.
To drive down AI inference costs, win new customers, and remain the preferred partner for
global software developers, the United States needs to be using this time to install chips
and sockets as quickly as possible. I do agree with Ryan that whatever else is going on,
there has clearly and rightly or wrongly been a shift towards viewing the Gulf as a key ally
in the AI geopolitical era, and so I would expect more, not less of this type of policy.
Moving over to markets, S.K. Heenik stock surged after completing the largest ever U.S. IPO for a foreign
company, bucking the broader downtrend and semiconductors. The South Korean Memory Maker raised
26.5 billion on Friday in their NASDAQ debut. The company has already been public in South Korea since
1996, but this listing makes the stock far easier for U.S. investors to access. The offering was slightly
larger than Alibaba's 2014 IPO, which raised 25 million, and not quite as large as the $29.4 billion raised by
Saudi Aramco in their 2019 IPO, but that wasn't a U.S. listing. The NASDAQ version of S.K.
Heinex jumped by 13% on Friday, driven entirely by a massive IPO pop to begin the day.
Now, this was an especially strong result given that semiconductors are in the midst of a pretty
significant correction, with the sector's main index down 9% so far this month.
Now, in many ways, this IPO is where some of those geopolitical discussions we were just having
started to meet the markets. Coming into the IPO, Commerce Secretary Howard Lutnik
urged S.K. Hynix and their South Korean competitor, Samsung, to build more capacity in the U.S.
The two chipmakers recently announced a $550 billion long-term construction plan to expand capacity,
but at this stage, the buildout will be entirely within South Korea.
Lutnik's comments were actually made during an event hosted by Micron, the largest U.S.-based memory supplier.
Referring to the micron CEO, Lettick said,
You know, he won't like it, but I want to bring his competitors, Samsung and S.K. Hynix
Here to America to build.
Meanwhile, S.K. Hynek's chairman, Che Tai Wan, was in town for the IPO.
and although he didn't commit to building capacity in the U.S., he did push back on the idea that new
facilities would lead to oversupply. S.K. Heinex has committed to doubling capacity over the next five years,
but Teyuan commented, all my customers said that, well, that's not enough, man, and, well, we need more.
Referring to a possible collapse in AI-focused high bandwidth memory, the chairman doesn't think it's likely.
The demand, he said, is enormous, exponential, so I don't really see it.
The AI agent, physical AI robot, all that needs a lot of memory chips.
Taiwan also reiterated his previous view that supply issues will continue to get worse, commenting,
We expect 2027 to be the worst year in terms of memory supply shortage.
Lastly, one little feature update from a story from last week.
Meta has rolled back a controversial feature on their new image model after just a few days.
Last week, you might remember Meta released their impressive new image model directly into Instagram and WhatsApp.
As part of the rollout, they introduced a feature that allowed users to include another person in their image generation by simply tagging their Instagram account in the prompt.
The model would then use public Instagram images as part of the context, with users able to disable
the feature. Still, despite the ability to disable the feature from the get-go,
controversy built over the following days, with the screen actors Guild warning their members
that they should disable the feature immediately, among much other similar discourse.
Ultimately, the decision to turn off the controversial feature isn't all that surprising,
but it does provide one more indicator of where and where not the public is when it comes to AI imagery.
Still, of the rest of the controversies and contentions we are going to discuss today,
about the least of them. So with that, we will close the headlines and move on over into the main
episode.
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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 environment,
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 caldron, that in-between moment that all of our stories operate today.
The first of which is that Apple has sued open AI 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
nominally about bad blood between the two for some time now, dating particularly back
to OpenAI partnering with legendary Apple designer Johnny Ive in May of last year. Many took that
partnership itself as a clear indication that Sam Haltman wanted OpenAI to become the next Apple
and to produce a device just as revolutionary as the iPhone. What followed,
followed was a huge poaching campaign, with OpenAI and Johnny Ives 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.
Liu 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 Liu had knowledge of a software bug
that allowed him to gain access to Apple's search.
servers. In their lawsuit, Apple included a text message from Lou to a then Apple employee named
Alyssa Peng. Loll, 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
Open AI to date, largely to work in their burgeoning hardware division. Apple point to former iPhone
design lien 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 Johnny Ive 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 on authorized 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 Simons of 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 round,
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
company's 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.
Gruglyoros wrote,
I am sometimes really surprised by how dumb very highly paid people in tech can be.
One, leave Apple.
Two, start building hardware at OpenAI.
Three, access confidential Apple files on hardware from an unreturned Apple laptop.
Four, 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
A.I. 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 Open AI 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-based 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 five, six soul 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 GPT-5-6 Seoul.
Indeed, that competition seems to be potentially giving us a little bit of a reprieve
of 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
5-6 sole 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 burn. 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 GPT-56 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 chat GPT work have been intense.
Three important updates.
One, temporarily removing the five-hour usage limit restriction for all plus business and pro plans.
Two, rolling out changes that will make GPT 5.6 sole 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.
Three, 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 GPT-56, many thought OpenAI would use the model release 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 GPT-56 was released. Then on Sunday, they extended
it again, including Fable and 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 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
at 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,
GPU, also known as Z.a.I, 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 Satinadella 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 carp and companies fear.
So what should enterprises do?
Well, Vercel's 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 Dear Druboso 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 context 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 Open AI 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 are 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 infralayer, 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 GPD 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 quad 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 they're leading Gemini model at the moment, can't match up with Fable and GBT 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.
