The AI Daily Brief: Artificial Intelligence News and Analysis - AI Winners and Losers After Gemini 3
Episode Date: November 20, 2025An in-depth look at how Gemini 3 reshapes the AI landscape. The episode breaks down which companies gained momentum, which ones face new pressure, and what the launch signals for the broader market. T...opics include the Microsoft–Nvidia–Anthropic mega-deal, Bezos’s return with Project Prometheus, the latest on Grok 4.1, the state of OpenAI, and Google’s full-stack advantage. A clear map of the new frontier after the Gemini 3 release.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/AIpodcastsRovo - Unleash the potential of your team with AI-powered Search, Chat and Agents - https://rovo.com/AssemblyAI - The best way to build Voice AI apps - https://www.assemblyai.com/briefBlitzy.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/The 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? sponsors@aidailybrief.ai
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Today on the AI Daily Brief, the winners and losers following the launch of Gemini 3.
Before that, in the headlines, Bezos is back and he's doing AI.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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cases. It is at R.O.I.Survey.com. Welcome back to the AI Daily Brief,
Edelines edition, all the daily AI news you need in around five minutes. So today in the main episode,
we're looking at the winners and losers following Gemini 3. And actually for the headlines,
we're talking about two companies slash projects that I don't get into in depth in that main episode,
but really this kind of forms a complete, where do things stand now kind of combination.
The big one that we're going to talk about is Jeff Bezos coming out of retirement in the CEO slot
in order to build a new AI company. But I did want to also give a mention to XAI releasing GROC 4.1,
which both the company and Elon say brings significant improvement to real-world usefulness.
To train the model, XAI developed new reinforcement learning processes that allowed them to create
an autonomous training environment using agents. The model update is focused on improvements to
writing quality, personality, and instruction following. A-B testing has been conducted over the
past few weeks on X and on Grock.com, with XAI finding that users prefer responses from the new
model almost 65% of the time. Similar results were found on the L.L.M. Arena boards, where Grock
4.1 and 4.1 thinking leapfrog the other frontier models like Gemini 2.5 Pro,
Gaud Sonnet 4.5, and GpT5. GROC 4.4 had been ranked below those models prior to the upgrade.
Unfortunately, GROPT51 has not been included in LM Arena so we don't know how XAI's new model
stacks up against the latest from OpenAI. GROC 4.1 also tops the leaderboard on the EQ
bench measurement of emotional intelligence. On the creative writing V3 benchmark,
GROC 4.1 is beaten out slightly by GPT51, but out ranks all.
other models. Now, it goes without saying that this was announced just before Gemini 3, so Gemini
3 is not included on these yet. In addition to usability improvements, GROC 4.1 also has a dramatic
reduction in hallucinations compared to GROC 4 fast. Now, overall, it is interesting to see XAI
follow OpenAI and push an update focused on EQ and writing quality. Like the release of GPD-51,
this update didn't include any benchmarking of coding ability or the other typical objective
benchmarks. Professor Ethan Malik posted, interesting changes in Grokfor 1, decreases in harmful
responses, but also increases in sycophancy and deception. And this, of course, is one of the
great challenges when it comes to model personality is, are there ways for people to like their
interactions without the model just being endlessly coddling and sycophantic? That is something
that I'm sure we will continue to discuss. But now we have to get to what was the big news before Gemini
3, that Jeff Bezos is funding a new AI startup and much bigger that he's, he's a new, he's
he will be personally taking the lead as co-CEO.
The new startup is called Project Prometheus
and has apparently been operating in stealth
for some time ahead of this announcement.
Sources said that Prometheus already has nearly 100 employees,
including researchers poached from other labs,
including OpenAI, deep-minded meta.
Bezos's co-founder and co-CEO in the venture is Vic Bajaj,
a physicist and chemist who previously worked at Google Special Projects Division,
Google X.
Now, Google X is known for Moonshot projects,
which included the self-driving car,
prototype that became Waymo and a drone delivery service that turned into wing.
Vic most recently co-founded an AI and data science company called Forsyte Labs around three years
ago, with sources saying he left that job recently to focus on Project Prometheus.
So what is this company?
Is it another model company coming to sneak in and buy Nvidia GPUs and try to compete?
The short answer is no, absolutely not.
Instead, Project Prometheus appears to be focused on applying AI to physical tasks.
The New York Times, in their reporting, described the focus on AI for engineering and manufacturing
of computers, automobiles, and spacecraft.
Sources said the startup will be working in a similar direction to periodic labs,
who are aiming to automate experiments in material science.
It doesn't seem like the company has fully picked a direction at this stage.
However, a lot of the speculation is that the work would likely intersect with Bezos' interest in space exploration through his company Blue Origin.
Now, aside from Bezos returning to the CEO role,
one element of the story that's grabbing a lot of attention is the,
a 6.2 billion. That's billion with a B in seed funding. That immediately makes Project
Prometheus one of the most well-resourced early-stage startups in AI. For comparison,
Miramirati's thinking machines lab raised $2 billion in seed funding in July, while Ilius Sutskaver's
safe superintelligence raised $3 billion across two rounds late last year and earlier this year.
Now, as you might imagine, much of the funding is said to be coming from Bezos himself.
Still, the startup will have whatever resources it needs to hire an extremely elite team of researchers
and do pretty much whatever they want.
Given that Bezos hasn't run a small company in a very long time,
a lot of the reporting is wondering what it's going to be like
for him to be the CEO of a hundred-person startup.
Since he retired his Amazon CEO in 2021,
Bezos has mostly made headlines for his mega-yot
and his extravagant wedding.
But throughout the 2010s, Bezos was the darling of NBA programs around the world.
He was never known as a technologist like Elon or a marketer like Steve Jobs.
Instead, he was seen as an elite manager able to harness a huge workforce
to drive massive growth and domination of multiple sectors.
The Bezos philosophies that drove Amazon's success
were largely built around the idea of scaling without losing agility.
But those lessons might be outdated at this point.
AI-native organizations have been obsessed with the idea of staying as small as possible
given how much leverage a small team of people empowered with AI can really have.
Now, how able to adapt he is to the new world, we'll have to wait and see.
Elon jokingly welcomed Bezos back with a tweet that said,
ha ha no way copycat. While others pointed out the significance of AI being enough to lure him back,
Mary G writes, Bezos couldn't even make it three years without being CEO again. Man saw everyone
doing AI startups and said, hold my six billion. Now while some incorrectly assumed that any AI
company was just going to be another model company, others were quick to point out that there is
something very different going on here. Roheet-Mittal writes, Jeff Bezos becoming a CEO of a new company
is one of the most bullish signs for the AI Times, and he's choosing to work on AI for
manufacturing, the most bullish sign for American manufacturing in a long time. AI Tools Hub 2.0
writes, Bezos isn't chasing another shiny chatbot. He's quietly aiming at the boring trillion-dollar layer,
AI that moves atoms, factories, supply chains, engineering. First wave was models. Next wave is
whoever wires them into the real economy. I think this is a great take and that is exactly why I'm
excited to see what happens with this. For now, however, that is going to do it for the headlines.
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Welcome back to the AI Daily Brief.
As is to be expected, following the launch of Google's Gemini 3,
the discussion surrounding the entire AI space is all about,
one, how the model is performing in practice, not just on the benchmarks,
and two, how the release of Gemini 3 changes.
the overall AI landscape. Now, when it comes to that first question, how the model is performing,
I have had a chance to start to put some reps in. I've had initially really positive experiences
with some data analysis and visualization that I was doing on the AI-R-OI benchmarking study,
but I'm not yet in a position to give a full review and to talk about the use cases that I think
Gemini 3 is most valuable for. Look for that sometime later in the week, as both my experiments
and other people's experiments have a little bit more time to mature. The other part of the
conversation, however, around what the release of Gemini 3 does for the industry is something we can
discuss right now. I went through and I gave a bunch of different groups, red light for having a bad
day, yellow light for having a mixed day, and green light for having a good day, and we're going to
use that as a framework to also look at a bunch of recent news. Now, where we're going to start is with
a big announcement from Microsoft, Nvidia, and Anthropic. This dropped about an hour before the launch
of Gemini 3, and I can't really tell exactly if it was timed to try to sneak in under the wire,
or if this was just planned as a big announcement as part of Microsoft Ignite, and it happened to
coincide with Gemini 3. In any case, what was announced was a big deal between Nvidia, Microsoft,
and Anthropic, a massive new multidimensional strategic partnership. As part of the deal,
Anthropic commits to buy $30 billion of Azure compute capacity. Invitya is investing $10 billion
in Anthropic. Microsoft will invest $5 billion in Anthropic. Invitya and Anthropic are going to
collaborate around design and engineering, as well as establishing what they call a deep
technology partnership.
As Microsoft CEO Satya Della pointed out, Microsoft Foundry customers will now also be able
to access Anthropics Frontier Cloud models, although it should be noted that although they
will be available through Azure, Amazon will remain Anthropics primary cloud and training partner
for the time being.
When it comes to the Nvidia part of the relationship, Anthropic is committing up to one gigawatt
of compute capacity using Invidia Blackwell and Vera Rubin systems, and a lot of the other
points of collaboration are at this stage a little bit hand-wavy, although I'm sure they get more real
over time as the companies dig in.
Anthropics Chief Product Officer Mike Krieger points out that Anthropic is now the only
frontier AI lab that is partnered with all three major clouds, Google Amazon and Microsoft,
and I think this is pretty reflective of the place that we find ourselves at this point
in the AI competition.
As much as there is a vicious competition in battle between these providers, and ultimately
there will be winners and losers.
At this stage, everyone needs everyone.
It's a lot more frenemies than kumbaya, but no one has the ability to go it alone or even
stick closely with their solo strategic partnerships. The speed of things is moving too fast,
the constraints the development are too great for any one company to support on its own,
and as much as the markets are squawking about the circularity of deals, the reality is just
basically that the 10 to 20 biggest companies in AI are all going to work with each other on
basically every aspect they can for the foreseeable future, based on the presumed ubiquity
and market penetration that this industry ultimately will have. Now, one note about the investment,
The $15 billion being invested into Anthropic from Microsoft and Nvidia
pushes the company's valuation up to the $350 billion range,
a massive number that puts them a lot closer to OpenAI's half trillion.
Still, it wasn't the big fundraising that led me to give Anthropic
that mixed rating on the winners and losers' charts from yesterday's Gemini 3 announcement.
On the one hand, there is some inherent challenge for any other frontier model provider
given Google Gemini's size, growth rate, and the incredible apparent capabilities that this model has.
In other words, it's harder to compete with Google,
when they've released Gemini 3 as compared to when they had Gemini 2.5.
At the same time, when you look at the benchmarks,
the two that Gemini 3 didn't win outright were both behind Claude Sonnet 4.5.
They tied at 100% for AIME 2025 with code execution,
but the big one, given Anthropics dominance as a coding model,
is that on Sween bench verified, Claude Sonnet 4.5 still outperforms Gemini 3 Pro,
and, by the way, GPD 5.1.
I saw a number of different independent testers that found something similar.
Bindu Ready wrote, Gemini 3 barely inches out GPT5 but is behind Sonnet 4.5 on coding and agendic
capabilities.
Sonnet 4.5 continues to rule in the combined agentic and coding arena.
So like I said in the note, I think Anthropic had a surprisingly mixed day, especially when
you consider that we're talking about Sonnet 4.5, not Opus 4.5.
Next up, let's talk about OpenAI.
In the same way that I think Anthropic has harder competition now than they did before the launch
of Gemini 3.
I think the same applies for OpenAI and ChatGPT.
And indeed, there was no shortage of it's so over for OpenAI posts.
OpenAI in particular had an even more skeptical eye given their recent spate of dealmaking.
Jen Zhu writes,
So if Google has a better flagship model,
Quinn, Kimmy Deepseek have better open source models with wider adoption-free and cheap API,
Anthropic is winning enterprise and XAI is better on long-context reasoning with real-time access to X.
How will OpenAI get $100 billion in revenue by 2027?
There were other folks who were less snarky, but just pointed out the resource constraint challenge.
Elmer de Bravan writes,
Why ChatGBT is going to fall behind Gemini and GROC,
OpenAI can't scale up compute fast enough.
Sure, they are trying, but they're too slow in comparison to Elon and Google.
The difference in intelligence will eventually next year become clear.
At the same time, I think this is much more mixed than people are giving it credit for.
Yes, the benchmarks show a meaningful improvement between Gemini 3 and GPT 5.1.
5.1 is a great model.
and is basically having exactly the opposite response from consumers as GPT-5 did.
The folks who want more personality are liking it better,
and the people who want better strategic collaborative thinking are liking it better.
Plus, there are already specific examples of use cases where people are finding
5-1 still beating out Gemini 3.
Swix runs an AI-c curated AI newsletter and did a comparison and came to the conclusion
GPT-5-1 is better than Gemini 3 is better than all the others, and it's not particularly
close. He also gave about eight reasons why he thinks 5-1 wins. Alex Finn, who it seems has a very
similar set of use cases as mine, writes, I've been testing Gemini 3 for over a week, and it's
incredible, extremely smart, the best straight-up problem solver and getting answers AI ever. If you need
information, there's no tool better. It's not quite there yet, though, when it comes to vibes.
I use AI 80% of the time for business planning and creative writing. I use it to be my project manager,
come up with new novel ideas for products and features to build, and as a business consultant to
bounce ideas off of. It doesn't quite have that human feel GPD 51 thinking has. So on his use case list,
creative writing and business planning still go to 51 thinking. Like I said, it's too early right now for me to
make a strong statement about anything, but my initial instincts are that I'm going to find something
similar. 51 is my favorite model for creative and business strategic collaborations since 03,
and I've been finding myself enjoying it enough that it's actually significantly increasing the
amount of time I'm spending interacting with AI on those types of use cases. The point of all this,
is that ultimately I think that Gemini 3's launch, even its improvement relative to 5-1 on some
of the benchmarks, feels within the band of expectations and not some mortal blow.
And despite Google being the bigger company overall, chatchipatee does have the unassailable
brand association with AI chatbots. For many people out there, it is simply what AI is.
Now, one company that I think we have to discuss that's not primarily a model or chatbot company,
but that does have implications from yesterday, I believe, is Invidia.
And for them, I'm suggesting that they had a red not so good day.
The simple reason for that can be read on page two of Gemini 3 Pro's model card,
where they write, Gemini 3 Pro was trained using Google's tensor processing units.
TPUs are specifically designed to handle the massive computations involved in training LLMs
and can speed up training considerably compared to CPUs.
Now, it's not surprising, obviously, we know that Google has been building these TPUs,
but the fact that TPUs and not Nvidia GPUs were used to train what is now the most
state-of-the-art model, at least according to the benchmarks, does, I think, have implications
for the unassailability of Nvidia's position. John Guibis writes, people are sleeping on how
impressive it is that Gemini 3 is fully trained on TPUs. Kakashi writes, TPUs are Jensen's biggest
nightmare. That's one of the main reasons he's pushing Nvidia GPUs onto Anthropic with the investment
incentives and urging OpenAI to keep using cloud providers that rely on Nvidia rather than Google.
Entrepreneur Siki Chen writes, regarding Gemini 3, for the past four years, I've had the
plurality of our liquid net worth in NVIDIA. About a month ago, I sold it all and rotated into Google.
Take from that what you will. Now, I don't want to overstate things. Invita is still in an incredibly
advantage's position, and at this stage, TPUs are still a Google internal advantage rather than
something that they're selling to the market, but there certainly opens up more opportunities for them
as their own business line in ways that could impact Nvidia in the longer term. Now, it was interesting
as I was preparing this note, how much meta didn't come into the conversation. When it comes to
meta and AI this year, the story has really been two parts. The positive side is that at this stage,
they have the only AI-related wearable that people actually like, which is of course the meta-ray
bands, and that's, I think, a much bigger advantage than maybe people are appreciating.
Still, mostly this year has been all about restructuring and reorganizing of their internal
processes. It's been about Zuckerberg going and poaching and building the superintelligence team,
about the bringing in of Alexander Wang from scale to lead the new efforts, and
really were waiting to see what comes out of that.
Ultimately, the next big test will be whatever model they choose to put out next,
but the short of it is they really needed to be a banger.
One optimistic thing is that a couple of years ago, when Google was struggling,
it was because they had a lot of divided and distributed efforts around AI,
in a similar way to how meta has up until the last couple of months
where they've been trying to sort of ruthlessly align things in a new way.
It took multiple layers of Google reorganization,
and ultimately bringing everything together under DeepMind and naming it in one direction
for their efforts to really start to come to the four.
But from here, now we have to get into who were winners from yesterday's announcement.
And the first category absolutely is the AI market bulls.
There is incredible fear in the market right now.
In fact, in the Fear and Greed Index generally, we're at a 13 with extreme fear driving the U.S. market.
A big part of that is concerns around overspending on the AI buildout and the potential of an AI bubble popping.
So much of the economy is tied up in AI.
expectations, that people are, of course, getting more and more nervous. Now, we've been following
this quite closely, and so I don't need to belabor the point, but one of the things that is important
to note is that among the signals that people are looking for when it comes to whether they
think we're in boom or bubble territory is whether it seems like we're hitting performance
plateaus. A big part of the latest leg of this bubble talk was, of course, the feeling of plateau
that happened around G505, even though it wasn't exactly true. And we've consistently had a
correlation between the sense that AI is hitting a wall or hitting scaling limits and the
market's general sense of the AI bubble. We talked yesterday about how these benchmarks at least
represent a major jump and really throw some cold water on the idea of a scaling wall being
hit. In fact, Adam GPT, who does go to market out of Open AI, shared a meme of a man wagging
his finger saying, no wall for you, capturing the sense among many, that Gemini 3 really shows that
there is more to get when it comes to scaling these LLMs. Google's Oriole Vignals actually
talked a little bit about how they got the performance that they did. He tweeted,
The secret behind Gemini 3, simple. Improving pre-training and post-training. On pre-training,
contrary to the popular belief that scaling is over, the team delivered a drastic jump. The
delta between 2.5 and 3.0 is as big as we've ever seen. No walls in sight. On post-training,
still a total green field. There's lots of room for algorithmic progress and improvement,
and 3-0 hasn't been an exception thanks to our stellar team. So like I said, AI Market Bulls,
big winners from yesterday's announcement.
The second big winner category is the vibe coders,
and specifically I'm talking about here the non-technical vibe coders.
In other words, the section of the vibe coders, like myself,
who are not ashamed of the vibe coding title,
and who are not wrestling with the autonomy spectrum
and how much we want AI to respond to us versus be independent agents
that go off and code on their own.
No, I am talking about the mass democratization of people
who can create with code now thanks to these vibe coding tools.
And for all of us, and I think there are a lot of,
of us, 3O totally kicks butt. 3O. appears to be a big jump up. Now, we did talk yesterday about
anti-gravity, the new IDEE from Google. And so you might be wondering, should I have a rating
for the AI coding companies like windsurf and cursor, et cetera, that now have a new competitor.
I guess if I did, I would also have it in the yellow column in the sense that new competition
from Google is meaningful and they have to take it into consideration. But they also all have
experiences where they get to take advantage of the latest models as well. And you're already seeing that
with a way, for example, that Replit has integrated Gemini 3 into their new design experience.
Now, this is one that I've had a chance to play around with a little bit.
And good Lord, is this so much better than the off-the-shelf design
that you were getting from some other vibe-coding tools just a few minutes ago.
I haven't had that much time to play around with it yet,
but it appears to me that Gemini 3, at least integrated into this overall experience
that Replit is offering,
represents a major advance in the quality of the design that comes with vibe-coding.
And that is something that I will absolutely be taking big advantage of.
There are also so many people who have shared the games that they vibe-coded.
Overall, I think that one of the biggest green categories of winners from the Gemini 3 announcement is the vibe coders.
And of course, the other big winner on the day is Google themselves.
This really represents the capstone, where Google went from how the hell are they behind,
to underwhelming bard, to the first versions of Gemini suggesting rocks and glue on pizza,
to their image models creating black Nazis.
To, by the end of last year, hey, notebook L.M is a pretty cool product.
getting their groove back to a year this year where the number of users has rocketed to 650 million
monthly active users, where the amount of tokens processing has jumped dramatically in the last six
months, and where Gemini 3 is now, at least by the benchmarks, the best model in the world,
and certainly in rarefied air, even among consumer preferences, for that very top slot.
On top of that, as we've discussed in this show, and as Ben Dixon points out, Google is the only
company that has control over the full stack, applications, foundation models, cloud, information,
and acceleration hardware.
Menlo Ventures, Didi Das writes,
we're in the, what if Google does that part of the AI cycle.
They can make cheaper models, better models,
distribute products at no cost to billions of users,
get good unit economics because they own TPUs,
and use it to retain premium talent cheaper.
He points out, of the big tech giants,
Amazon and Microsoft chose to be infrastructure partners,
Apple chose not to play,
meta shot the bed,
Google is coming out on top.
Interestingly, this is sort of consensus enough,
that others are simply asking how it happened.
Eric Katakana writes,
what I want to know is how did Google go from way behind
to easily number one in all domains of modern AI in like a year?
The answer, by the way, to many,
was what Peter Levels pointed out,
the return and re-involvement of Google co-founder Sergey Brin.
Whatever truth there is in that,
ultimately, Google is heading into 2026
in an incredibly strong position,
and at least from a consumer in an enterprise perspective,
whatever else happens next,
that is nothing but gravy and upside for all of us users.
So that is my sense of the lay of the land, the winners and losers after Gemini 3-Day,
how long this remains the state of things remains to be seen.
People are still just starting to experiment with GROC 4.1,
and Elon seems to think it's a bigger deal than people are giving it credit for.
And when it comes to Anthropic and OpenAI, we could still get GPT-51 Pro and Opus 4.5,
and things could feel quite different again.
Like I said, ultimately, the biggest winner is all of us users,
who seemingly every couple of weeks have new capabilities and new use cases that get unlocked.
and I certainly plan on taking the time to go take advantage of them.
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.
