The AI Daily Brief: Artificial Intelligence News and Analysis - Is Google Now the AI Leader?
Episode Date: September 4, 2025Google’s AI comeback is turning into something bigger. Today’s AI Daily Brief covers whether Google has taken the lead in the AI race, with multimodal breakthroughs, Gemini’s surge, and a huge a...ntitrust win around Chrome. We also dig into Anthropic’s $13B raise at a stunning $183B valuation, OpenAI’s billion-dollar acquisition and restructuring, and the intensifying AI talent wars across Apple, Meta, and beyond.Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsBlitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/Vanta - Simplify compliance - https://vanta.com/nlwThe Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.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/1680633614Interested in sponsoring the show? nlw@aidailybrief.ai
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Today on the AI Daily Brief, is Google now the AI leader?
Before that in the headlines, Anthropic closes a monster new round, plus the latest in the talent wars.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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sponsors at AIDDailyBreef.A.I., we are now officially selling into 2026. With that, let's get into
today's episode. Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in
around five minutes. Today, our main story is all about whether Google is now in the AI lead,
and so appropriately a lot of our headlines have to do with gyrations and moves among the big
labs. We kick off today with a story that I mentioned in passing yesterday as part of the
AI predictions, but will now give full coverage, which is that Anthropic has officially closed their
latest round of fundraising at a whopping $183 billion valuation. The company brought in 13 billion in
fresh capital, co-led by iconic fidelity and light speed venture partners. There was a laundry list
of participating funds, but very notably this round includes a lot of private equity, sovereign wealth,
and retirement funds alongside the usual VCs. This feels in many ways like the round where the AI
industry as a whole, not just OpenAI, have definitively outgrown the capacity of Silicon Valley
venture funds alone. Anthropics' previous round was $3.5 billion at a $61.5 billion valuation back in
February, meaning they've more than tripled in size. Now, part of why they were able to do this is that the
company has gone from $1 billion to $5 billion in ARR year to date. And much of that revenue is coming
now from high-ticket customers. Anthropic now claims 300,000 business customers and said that their
list of large accounts above $100,000 in annual spend has increased sevenfold this year. In a blog post,
Anthropic CFO, Krishna Rao, said, we are seeing exponential growth in demand across our
entire customer base. This financing demonstrates investors' extraordinary confidence in our financial
performance and the strength of their collaboration with us to continue fueling our unprecedented
growth. Claude has become a major business line, bringing in $500 million all by itself with
usage up at 10x since its full launch in June. The TLDR is that a company that already had the wind
in its sales just got a massive new war chest to continue its surge. Anthropic, however, was far from
the only major lab with big news this week. OpenAI is kickstarting their next era with new
CEO of applications Fiji-Simo officially at the helm. On Tuesday, OpenAI announced a big acquisition
and leadership restructuring to build out their applications team. The company bought analytics platform
Statsig for $1.1 billion in an all-stock deal, marking one of OpenAI's largest acquisitions
to date. Statsig specializes in AB testing and other product optimization services. In addition,
Statsig's CEO, Vijay, Raji, will be brought in as OpenAI's CTO of applications. He'll have
product engineering responsibilities for ChatGBT,
GBT, Codex, and other forthcoming product lines.
Statsing will continue to operate as an independent entity
and service their existing customer base out of their Seattle office.
Other personnel changes include engineering lead,
Trinivas Narayanianjanjan, moving on to the C-suite as OpenAI's CTO of B2B applications,
reporting directly into C.O. Brad Lightcap.
Kevin Weill, OpenAI's chief product officer, will be moving to the research side of the business,
also becoming the company's VP of AI for science.
his former product team, including the head of Chatchip T. NICT. Turley will now report directly into Simo.
Now, we saw that this was coming, but it is very clear that OpenAI is significantly delineating between the applications and research side of the company.
Speaking of Talent, the exodus of AI talent continues at Apple with four new departures.
Bloomberg reports that Apple's lead AI for robotics researcher, Jean Zhang, has left to join Meta's Robotics Studio.
separately a trio of AI researchers that Apple's in-house LLM team have left for greener pastures
at Anthropic and Open AI. The reporting states that the Foundation Models team has lost roughly
10 members, including their chief, over recent weeks. The departures come as Apple reportedly
mulls outsourcing their LLM needs to Google or Anthropic. Sources also said that Apple's staff
departures are expected to continue, with basically every other researcher actively interviewing
at other AI companies. Said the sources, the poor response to Apple's intelligence and the company's
potential shift towards using third-party models have contributed to worsening morale.
Yet when it comes to worsening morale and big questions around talent, the biggest lens right now is
squarely focused on meta. Reporting is rife with claims that there are riffs forming inside the new
superintelligence lab. The verge, for example, filled in the gaps from last week's reporting that
a trio of researchers had left the team. They reported that two had never formally begun their roles
before deciding to return to Open AI, while the third was a confirmed departure with the staff member
working a month before changing their mind. TechCrunch added that Scale AI's former senior VP of
Gen AI Product and Operations, Ruben Mayer, had left the company after two months. Mayor was brought across
as part of the $14.3 billion scale aquahire. Still, the reporting is a little strange. TechCrunch's
sources said that Mayor was never a part of TBD Labs and had instead been assigned to oversee AI data
operations teams, but Mayor himself disputed the source, stating that his initial position was to, quote,
help set up the lab with whatever was needed rather than just data. He also said that he was, quote,
part of TBD Labs from day one, rather than being excluded from the core AI unit.
He said that he did not report directly to Alexander Wang and was very happy with his
meta experience instead leaving for a personal matter. In addition to the departure,
TechCrunch reports that Meta is now partnering with alternate data labeling vendors,
including Surge and Mercor, instead of working exclusively with Scale.
A third piece from the Financial Times said that ChatGBT, co-creator Shangji
Zhao threatened to quit within days of signing with Meta. Now, Zhao was one of the highest profile
recruits to Meta and really cemented that they were having a lot of success in poaching top talent
from OpenAI. FT sources said that Zhao went so far is to sign employment paperwork to return to Open
AI within days of his recruitment. Shortly afterwards, Meta appointed him chief AI scientist
and published an introduction video featuring him sitting next to Alexander Wang and Mark Zuckerberg.
One investor close to Meta leadership commented, there's a lot of big men on campus.
For their part, Meta does seem to be getting a little frustrated with the frequent coverage,
with a spokesperson stating, we appreciate that there's outside.
interest in seemingly every minute detail of our AI efforts, no matter how inconsequential
or mundane, but we're just focused on doing the work to deliver personal superintelligence.
Look, at the end of the day, when it comes to these questions, there are two things.
The first is that when you spend the type of money and are as aggressive as this company was
in recruiting, that makes this all interesting canon fodder for media stories.
It's unavoidable, even if the Occam's razor explanation for this is that you're not going to be
able to be this aggressive without having some people change their minds. In general, I personally am a fan
for Occam's Razor explanations, and my best guess is that we're in some sort of settling phase,
rather than there being abnormally utter chaos given the extremes of the situation. The second thing to
note, though, is that the way to get people to shut up is to put out stuff that works. Now, we're barely
months into this. It would be unrealistic to expect even an incredibly performant team to be dropping
models and applications this fast, but the big do-or-die moment for meta-superintelligence labs
that will absolutely crater this and all other discussion,
like the discussion that's also happening around meta,
apparently considering partnerships with OpenAI or Google to power their products.
The only thing that's going to squash that ultimately is what they put out.
That is certainly what we will be watching for the rest of this year.
But with that, we wrap today's headlines.
Next up, the main episode.
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Welcome back to the AI Daily Brief.
Today we are nominally talking about Google's big win in their antitrust case.
TLDR on that is that they are not going to be forced to sell Chrome.
So we will talk about the implications of that, what it means for their positioning vis-a-a-I,
why Chrome might matter in the AI race.
But I thought it would be interesting to use this as a chance to do a little bit of a retrospective
around where Google has been.
I think when it comes to the major labs, no one has gone through such wild swings of where
they sit in the AI race as has Google.
There is a growing chorus of people who believe that Google is now firmly in a lead when
it comes to AI. That's showing up not just in random tweets, but on prediction markets. Since all the way
back in May, Google has been slightly in the lead when it comes to the polymarket prediction market
for which company will have the best AI model by the end of 2025, but since the release of GPT5,
the number has absolutely skyrocketed up to Google having a 75% chance. Now, on the one hand,
this shouldn't be all that surprising. Google has had a longer relationship with generative AI
building than most of their competitors. They had the talent, the money, the motivation, and the drive,
which is why it was so shocking how far behind they found themselves when Chatchipit was launched.
The piece that we're looking at is from Forbes in February of 2023. It was called AI First to Last,
how Google fell behind in the AI boom, and was one of a series of pieces with similar themes around
that time. The piece discussed Google's early lead in AI. They talked about how just a few months
after becoming CEO back in 2016, Sundar Pichai declared that Google would become an AI-first company.
Now, interestingly, even back then, they already felt like they had their back to the wall, at least a little bit.
Amazon's release of Alexa had taken Google by surprise, feeling like they should have been first to market with that product.
Forbes wrote, seven years later, Google finds itself in a similar position, again beaten to market in a field
it should have dominated. But this time, it's worse. The usurper is OpenAI, a comparatively small San
Francisco startup and not a deep-pocketed giant like Amazon. The product is chat GPT, a bot that can
generate sitcom plots, resignation letters, lines of code, and other texts on almost any subject conceivable
as if written by a human, and it was built using a technology breakthrough Google itself had pioneered
years ago. Now, of course, part of what made this all the more frustrating was that Microsoft,
by dint of their relationship with OpenAI,
had moved into more of a software leadership role
than they'd had in some time.
And for much of 2023,
Google's story and AI was all about catching up.
There were a bunch of product announcements
with names that you might or might not remember,
for example, Bard,
but nothing that could be considered even close to GPT4 level,
in other words, close to the state of the art,
until the very end of the year when Google announced Gemini.
Now, I was already six months into the show at that time,
And I remember that the general sentiment was that it was very much a pressured and rushed announcement
forced by how far ahead OpenAI was.
Although it was announced in December, it was announced with a bunch of pre-recorded demos,
and the most performant model wasn't even available yet.
That wouldn't come until the beginning of the next year.
And when it did, it did little to improve Google's rough position.
First of all, Google got itself completely caught up in the culture war
by releasing an image generation model that tried extremely,
hard to add diversity into historical images in places that were completely inappropriate.
For example, putting people of color into Nazi uniforms as emblematic examples of early 1940s
German soldiers. Hold aside the political dimensions of this, it was bad enough that Google
pulled the model entirely and later apologized for releasing something that was so far out of sync
with reality. A couple months later, we had the first incarnation of Google's AI overviews.
While they've now become totally de rigour and very much a part of the search experience,
At the beginning, all that anyone could talk about were things like where Google suggested that
people use glue as an ingredient in pizza.
Now, whereas the problems with the image generator were extremely widespread, Google did try
to say that the examples going public with the AI overviews were more isolated, but still
it all contributed to this narrative of Google being incredibly far behind.
Behind the scenes, though, there was a lot going on at the company.
Some of that was personnel.
One of the issues with Google had been that AI was.
so big at the company that it was spread across a lot of different divisions rather than consolidated
and focused. Over the course of 2024, there was a set of its sometimes painful consolidation
to bring everything basically under DeepMind and DeepMind leader Demis Havas. For example, it took until
October of 2024 for Google to fold the team that was responsible for the Gemini app into DeepMind officially.
But where things really started to turn around for Google was, of course, the release of Notebook
LM. Or more specifically, the release of audio overviews in Notebook LM.
Notebook LM was first announced earlier in the year as part of a string of announcements and was
frankly kind of buried when it came. However, in the fall, they released a new feature called
audio overviews, which was basically a way to auto-generate a podcast based on any subject matter.
You could drop a set of documents or source links into Notebook LM, and in a couple of minutes,
you would get an audio conversation between two hosts, explaining the material in ways that
were engaging and really fell into all the tropes of podcasting. Now, this is the type of thing that could
easily just become a novelty, something that people tried once or twice and then went away from.
That didn't happen. And I think part of why it didn't is that Google really had unlocked a different
medium for consuming information that some number of people found really useful. For example,
for me on the podcast, it was sometimes a more engaging way to deal with complex technical topics
that I wanted to then share with this audience. I knew law firms who were using it to help some
summarize case files. You had students who were using it as a study tool. And the point was that for the
first time, Google AI had a genuine bona fide hit on their hands that people were really thrilled about.
I think it was also a testament to the goodwill and good brand that Google has built over the last
decades, that there was almost a sense of relief of Google getting back in the AI game and doing
something well, as though the aberration had always been when they were behind. As the year closed out,
it was clear that heading into 2025, AI competition was going to be the big mission.
In a December town hall, CEOs in Darpichai told the company,
I think 2025 will be critical.
I think it's really important we internalize the urgency of this moment
and need to move faster as a company.
The stakes are high.
These are disruptive moments.
In 2025, we need to be relentlessly focused on unlocking the benefits of this technology
and solve real user problems.
And indeed, 2025 has been an absolute flurry of products.
One interesting inflection point came at the I.O. conference in May.
Google made an odd decision heading into the
conference, releasing AI mode for search the prior week. When he took the stage for his keynote,
Pichai said, normally you wouldn't have heard much from us in the weeks leading up to I.O.
Because we'd be saving our best models for the stage. But in our Gemini era, we're just as
likely to ship our most intelligent model on a Tuesday in March or announce a really cool
breakthrough a week before. We want to get our best models into your hands and our products
ASAP, so we're shipping faster than ever. And ship they did. Google coverage listed 100 different things
announced at I.O. And a very meaningful portion of them were AI-related. And there was definitely a
sense that Google was starting to get its groove back. Now, there are two big areas where Google has
been very on the ball this year. One of them is multimodal, which we'll talk about in just a moment.
And where I think more than anything else, the sense of Google maybe now being in the leader
or pole position with AI comes from. But it's also important to note that they recognized quite early
in the year that agenetic coding was going to be a massive, massive theme. Back in
In February, they released a version of Gemini 2.0 that was fine-tuned for coding.
Again, CEO Sundarpe Chai tweeted,
New Gemini 2.0 updates for developers.
Starting today, you can use Gemini Code Assist for free in your favorite IDE.
It's Gemini 2.0 fine-tuned for coding, including 180K code completions per month,
90x what others currently offer.
Plus, Gemini 2.0 Flashlight is now GA and cost-effective for projects that use long
context windows.
And so what I think is notable here is that one, they understood that models that were
specific to coding were going to be important, and two, they knew that they wanted to compete on
cost because the increase in performance of these models was going to ultimately lead to a big
increase in the tokens that would ultimately be consumed. A couple months later in May, they
released an updated Gemini 2.5 Pro, once again, focused on coding. Google Demis Hemein's CEO
DeMeshas tweeted, very excited to share the best coding model we've ever built. Today, we're launching
Gemini 2.5 Pro Preview I-O edition with massively improved coding capabilities. It's especially
good at building interactive web apps. A couple months later in June, and Taylor Mullin tweeted,
this is truly a proud moment for me. For the past few months, we've pushed nonstop to build Gemini
CLI. It's been a journey and I couldn't be happier to finally share it with all of you.
Okay, so the point here is clearly that Google was focused on this coding use case. And if you need evidence
of whether it worked, look no further than an announcement from July, where Google shared that they had jumped from
processing 480 trillion tokens in May to 980 trillion by July, 104% growth in just a couple of months.
I think a huge part of that was the emergence of this coding use case.
Still, it's impossible to talk about Google AI right now without recognizing that where they
have really started to break out into a distinct lead is around multimodal, specifically when
it comes to video, image generation, and world models.
For a while, all the buzz in video was around OpenAI SORA.
Over time, however, SORA stayed very much in a behind-the-scenes for paid partners-only kind of mode,
and when Google released V-O-3, it had one very specific transformative difference
that made, as it turns out, all the difference in the world.
That was the ability to generate sound and video at the same time.
For the first time with AI video generation,
people didn't have to create the video clips and the audio clips separately
and lay them together with some program.
Instead, they could generate in a single shot,
the full clip, including video and audio. AI-generated video absolutely exploded from there.
I did a show back in July about 10 AI video trends taking over the internet, and if you've
spent any time on TikTok or Instagram Reels or any social media in the last three months,
you have absolutely been inundated with VO3 generated videos. Of course, it's not just video.
More recently, we've got Genie 3, which is Google's experimental world model where you can
generate entire interactive environments with just a prompt. This is still a little bit more firmly
in the realm of the future and the experimental, rather than something you're seeing people deploy
for a lot of different use cases right now, but it's still contributed to this sense that when
it comes to multimedia and multimodality, Google is just on a different plane. And then, of course,
more recently, you'll know if you've been listening to the show, that everyone's been talking
about nanobanana, or as it's technically called Gemini 2.5 Flash image, or something along those
lines. Now, what may Nanobanana different is its ability to do editing of a particular image
in a way that is extremely high fidelity to the prompt. It captured more attention than any
image generation model we've seen since the Studio Ghibli trend of earlier in the year from OpenAI,
and while the Ghibli trend was a cultural moment, the image editing capabilities of nanobanana
are actually opening up a new variety of use cases that people are finding really economically
useful. When Andreessen Horowitz came out with its latest edition of its top 100 Gen.A.I. Consumer
app. The first trend that they noticed was Google making big moves. Google had four different entries
to the list. Gemini was number two behind only chat GPT, but Google AI Studio, notebook LM, and Google Labs
all showed up in the top 50 as well. AI Studio was number 10 and notebook LM was 13, so three Google
properties in the top 15 Gen AI apps for consumers. All of which brings us to the latest news,
that one of Google's biggest overhangs has been resolved. A judge's ruled that Google will
not be forced to divest of Chrome in order to cure their monopoly on search. What's more,
they will still be allowed to pay to be the default search engine on other platforms, which is,
of course, the relationship that they've had with Apple. The only prohibition is that they can't
arrange exclusive deals for distribution. The judge also ruled that Google has to share their search
data freely with competitors to make their moat less complete. Now, this had been a big topic of
conversation recently. We are in the beginning innings of the AI browser wars. Perplexity
has been making moves with their comet browser. OpenAI is reportedly going to release an AI browser,
and both of those companies had expressed interest in buying Chrome if Google was forced to divest.
Perplexity had even announced an official $34.5 billion offer, despite the fact that that was more
than the company is currently valued at. And Tam Altman said that if Google was forced to divest,
it was something that they would have to look into and that they would, of course, be interested.
Now, alongside the decision that Google would not have to sell off Chrome, there were a few other
interesting notes on the AI competition that came out of the decision. First, the court explicitly
recognized that Apple would be a big loser if Google were no longer able to pay to be the default
search engine. Not exactly a comment on AI, but certainly a demonstration of how utterly
directionless they are, given that they're reliant on a $20 billion a year deal with a competitor
as a major source of revenue. The bigger point that the judge recognized was that AI is rapidly
changing the landscape of search, so intervention isn't obviously necessary. The judge stated that
AI startups, quote, are already in a better position, both financially and technologically,
to compete with Google than any traditional search company has been in decades, except perhaps
Microsoft. The judge added, there are strong reasons not to jolt the system and to allow
market forces to do the work. Google, for their part, said that the decision, quote,
recognizes how much the industry has changed through the advent of AI and validates their position
that, quote, competition is intense and people can easily choose the services they want. Now, Google is
still reviewing the decision and could appeal the slim penalties they received, namely the forced
data sharing under the guise of protecting user privacy. For their part, the markets rejoiced
upon hearing the news, sending Google stock soaring by almost 9%. Analysts were quick to note that the
ruling allows Google to sign similar distribution deals on AI as they established in the search era.
And with Apple seemingly vacating the field, it seems entirely likely that Google will pay up big
to use the iPhone as a major distribution channel for Gemini.
DOJ antitrust head Abigail Slater seemed satisfied with the results posting,
the court recognized the key inflection point we are in with the development of AI. The court gave a leg
up to the United States in the global AI race, preventing Google from slowing down AI innovation
with the same anti-competitive playbook it used to freeze search competition. Still, you've got to think
this seems like a huge advantage for Google as they seek to get out into the lead position when it
comes to AI. This was nothing like the antitrust actions suffered by Microsoft at the 90s. Google
will still be allowed to pursue acquisitions, signed distribution deals, and generally use their size
as an advantage. And all at all, it seems like there is a lot more coming. A couple hours before I
recorded this, I noticed a new piece on the information about Google ramping up their AI chip competition
with Nvidia. We'll probably get into this more later this week. But information sources suggest that
Google has recently been approaching small cloud providers that primarily rent out Nvidia chips about
also hosting Google's AI chips in their data centers. And at least one agreement has been reached.
There is also a slew of rumors about Gemini 3 being right on the horizon. Kat Kovic, the director of product at
Google Labs seem to be dropping some sort of hint on Tuesday posting it's a big week with a
squid emoji, although it turned out that was about their Jules coding agent. Then of course, there was this
widely seen tweet from Semi Analysis who wrote, because Google is so bad at tweeting will do it for them.
Gemini 3 is shaping up to be an incredibly performant model, especially on coding and multimodal
capabilities. So as we wrap up, is Google officially in the AI lead right now?
I think that there are somewhere between two and four potential counter positions. The first is that while
yes, Google has four properties in the top 50 of consumer AI apps, Gemini at number two behind
ChatGBTGBT has only 12% of ChatGPT's visits on the web. The gap is narrower on mobile,
but still very significant. The reality is that for an entire generation, ChatGPT simply is
AI. And for as much as Google might be beating OpenAI in those other models, a huge percentage
of current usership is focused on those core LLM chatbots. I think a second and maybe third
potential argument is less about where things are today and where about things will be,
which is that it's pretty dangerous to ever fully count either Elon or Mark Zuckerberg out.
X-AI has put on extreme moves when it comes to catching up in this race and is on an incredibly
impressive trajectory. When it comes to Zuckerberg in Meadow, we haven't seen the outputs of the
talent wars yet, but certainly they've been aggressive enough about acquiring talent and appear
to be aggressive enough about acquiring compute that it's not inconceivable that things
could look very different about a year from now. Speaking of trajectory, Anthropic has put out by far
the fastest growing products in this space this year, really cementing their lead in that key category
of coding, even if Google has also been doing well in that area. And then there's the whole mess
of Chinese companies, which has continued to put out very impressive models very often in an open
source way. And so that's the reason for the question mark in this title. I'm certainly not ready
to declare yet that there is one company that is distinctly in the lead. There are lots of different
advantages that different companies have in different ways to squint at it. But for Google, the fact that
they have come from confusing laughing stock 18 months ago to growing consensus at their place atop the heap
has got to feel good. I also think that regardless of anything else, even if they just won multimodal,
there are so many stones to turn over when it comes to the amazing things that we're going to get to
create with future image models, video models, and world models that the future of Google AI is
looking very bright. That's however we're going to do it for today's AI Daily Brief. Thanks as always
for listening and watching. And until next time, peace.