Tech Brew Ride Home - Tipping Point In The AI Horse Race?
Episode Date: April 7, 2026Anthropic’s new deal with Google and Broadcom (and some newly released numbers) might be the tipping point in a couple of AI Horse Races. The gold rush/landgrab in the world model space. The dubious... goldrush for SEO in the AI era. And an urgent wakeup call in the quantum computing will break cryptography space. Anthropic Tops $30 Billion Run Rate, Seals Deal With Broadcom (Bloomberg) Jeff Bezos’s new lab hires xAI co-founder from OpenAI (FT) How Accurate Are Google’s A.I. Overviews? (NYTimes) Can AI responses be influenced? The SEO industry is trying (The Verge) A Cryptography Engineer’s Perspective on Quantum Computing Timelines (Filippo Valsorda) Learn more about your ad choices. Visit megaphone.fm/adchoices
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slash college PC. Welcome to the TechBrewrite home for Tuesday, April 7th, 2026. I'm Brian McCullough.
Today is the day of tipping points, potential or otherwise. Anthropics' new deal with Google and
Broadcom and some newly released numbers might be the tipping point in a couple of AI horse races,
the Gold Rush slash Land Grab in the world model space, the dubious gold rush for SEO in the
AI era, and an urgent wake-up call in the quantum computing will break cryptography space.
Here's what you miss today in the world of tech.
So Anthropic has signed an agreement with Google and Broadcom for multiple gigawatts of TPU capacity,
and that's nice, but that's not the headline anyone actually cares about.
They care about this, quoting Bloomberg.
Anthropic PBC said its revenue run rate has now topped $30 billion, up from $9 billion,
at the end of last year, and has confirmed plans to work with Broadcom and Google to power its burgeoning operations.
The AI startup said that demand for its clawed services had accelerated this year with more than
1,000 business customers spending over $1 million on an annual basis.
That figure has more than doubled since February.
The collaboration with Broadcom and Google, which was first announced last month,
will help Anthropic build, quote, the capacity necessary to serve the remarkable growth we
have seen in our customer base.
Chief Financial Officer Krishna Rao said in a statement,
the annual run rate, a popular benchmark among tech startups,
extrapolates the current sales level over a full year.
The latest number suggests that a high-profile dispute with the U.S.
government hasn't stymied growth.
Anthropic is waging a legal fight over the Pentagon's decision to declare the company
a supply chain risk following a standoff over AI safety guardrails, end quote.
Ooh, so that's why Dario was willing to stare down the DOD.
They added close to $20 billion in revenue,
run rate in the last three to four months or so. I will also note two things. They reported
$19 billion in revenue run rate at the end of February. So the math on that would suggest they
added $10 billion in ARR in a month. Also, we're pretty sure that they now have officially
dethroned Open AI not in revenue growth because they already had. For several quarters now,
Anthropic has been ahead of Open AI.
in terms of revenue growth, but now they are ahead, potentially, in total revenue full stop.
And actually, if you are generous drawing some of the lines on the graphs here, Anthropic could be
profitable at this rate by the end of next year. Quoting Yuchin Jin on X, crazy revenue growth
at Anthropics. So they officially surpassed Open AIs 25 billion dollars in ARR reported a few days ago.
The focus on coding models and enterprise clearly paid off.
Once you're locked into a year-long contract, switching to codex isn't easy.
Claudecode shipping velocity is insane to new features every day.
If they secure more GPUs and Google TPUs, this growth could accelerate even further, end quote.
And quoting Connorsen, again, what is the rationale for valuing Open AI above Anthropic?
Anthropic should be $1 trillion at this point, end quote.
So, more bad news for old salmon company, right?
Like all the trendlines are in Anthropics' favor of late.
But remember what this original headline was all about, Anthropic contracting to make TPUs.
So this is also good news for Google and also bad news, ipso facto for NVIDIA.
Going back to the original piece, quote,
Broadcom is developing chips using Google's tensor processing units or TPUs offering an alternative to technology from
NVIDIA. Broadcom and Alphabets, Google have entered a long-term agreement to provide the chips
and a supply assurance pact that runs through 2031, according to a Broadcom filing Monday.
The three companies are also expanding a strategic collaboration that will let Anthropic access
about 3.5 gigawatts worth of computing power that will begin in 2027.
The consumption of such expanded AI compute capacity by Anthropic is dependent on Anthropics'
continued commercial success. In connection with this deployment, the parties are in discussions
with certain operational and financial partners, Broadcom said in the filing.
Broadcom shares climbed as much as 3.6% in late trading after the filing was announced.
The company's chief executive officer, Hock Tan, previously discussed the collaboration
during an earnings call last month. He also said Broadcom expects its chip AI sales to top
$100 billion next year, making it a bigger competitor to Nvidia, end quote.
So bottom line here, will we look back on April 6th as the day we knew the tide had turned
and Anthropic became the clear leader in the AI horse race. Also, I want to frame this segment
with specificity so you understand why I think this is also maybe as important. As that discussion
on Friday about Demis Hasabas got into, there was a whole generation of AI gurus. They all got
recruited into AI labs slash startups, deep mind, open AI, etc. Then chat GPT hits, and even though some
people like Demis Hasabas thought it was too early, that text-based large language models
weren't quite enough to get us to full AI. The AI moment happened anyway. It broke through the
mainstream, right? But the dream of the thing that could get you all the way to real AI is still
out there, and it's world models, or at least one of the things is world models. And now what
you're seeing is the people of this latest, this second generation of AI moment people,
they're getting hired to make that dream of the world model happen at new companies.
So that's the framing for this, quoting the FT.
A company owned by Jeff Bezos has poached an ex-AI co-founder from a role at OpenAI,
as the tech billionaire secretive startup rapidly recruits to pursue its ambition to create AI systems
that can transform the industrial sector.
Kyle Kosich has joined Project Prometheus, a codename for a new company,
led by Bezos and former Google Executive Vikram Badaj, according to people familiar with The Matter.
A co-founder of XAI alongside Elon Musk, Kosich led the infrastructure team behind its colossus supercomputer
before returning to his former employer OpenAI in 2024. He will continue to work on AI infrastructure
projects at Prometheus, the people said. His move marks the latest in a dizzying round of job
changes as AI labs compete fiercely for top talent, often offering substantial salaries to
lure staff from rivals. Musk has seen all 11 of his ex-AI co-founders leave with several departing
in recent months and some with complaints about Musk's management. The last two, Manuel Croix
and Ross Nordine, left the company at the end of March, according to people familiar with the matter
as first reported by Business Insider. Prometheus, meanwhile, has hired hundreds of staff at its
headquarters in San Francisco and in its offices in London and Zurich. It has focused on hiring
engineers, AI researchers, and people with experience in, quote, building out massive infrastructure
projects, one person familiar with its hiring said. The startup, launched by Bezos last year,
is working on AI systems that can operate in the physical world and go beyond the language-based
systems behind chatbuts, such as chatGBT or coding tools such as Cloud Code. Project
Prometheus declined to comment. The company is particularly focused on the industrial sector.
It envisions a model that can understand the laws of physics and is trained on data from specific
domains such as jet engine design, one person close to the company said. They added that the company
had already assembled the largest corpus of data on engineering and how such systems work.
Prometheus also plans to amass stakes in companies across sectors such as engineering,
aviation, architecture, and design. Those deals would include gathering data from these
companies which could be used to improve the startup's AI model. Bezos and his co-founder are
personally leading Prometheus's efforts to raise tens of billions of dollars or more for a
permanent capital vehicle that would acquire equity stakes in companies likely to be disrupted by
AI in the future. One person compared it to a Berkshire-Hathaway-type holding company. Prometheus
wants to back the progress of those industries, which will happen eventually with AI, but they
don't want it to take 10 years, the person added. These startup plans to have its staff working
within these companies, often known as forward-deployed engineers. The investment and input from staff
at hopes will improve margins and operations at the companies. The
AI industry has struggled to create models that truly understand physical space due to a lack of high-quality data that represents the real world rather than more readily available text and computer code.
Competitors' current efforts involve training on video data and simulations to mimic real-world environments, end quote.
So what I just quoted from, there was a lot of talk about industrial environments in there, robotics, etc., manufacturing, but let me make this clear.
World models are something to be on the lookout for because, well, we've gotten this far with AI just or largely being based on text, essentially.
Text, images, increasingly video.
But that's not the real world, right?
We don't live in sentences, in videos, and concepts.
We live in a real Newtonian universe.
So what if the next big thing is AI trained on all of that?
Everything.
The universe, the real world.
there are even AI startups that want to launch satellites into space, not to just give us maps and stuff,
but to train AI in real time on data from quite literally what is happening in the real world
at any given moment, anywhere in the world, again in real time.
This is the next gen of AI to look out for, well, at least one of the next gens of AI,
and you can see that by the talent moving in this direction.
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How accurate are those AI
overviews on Google Search? Well,
the New York Times went and tried
to find out.
A recent analysis of AI
overviews found that they were accurate
approximately nine out of ten times,
but with Google processing more than
five trillion searches a year,
this means that it provides tens
of millions of erroneous answers
every hour, or hundreds of
thousands of inaccuracies every minute,
according to an analysis done by an AI
startup called OME. More than half of the accurate responses were ungrounded, meaning they
linked to websites that did not completely support the information they provided. This makes it
challenging to check AI overview's accuracy, end quote. So I mentioned that briefly just to tee up
this. You're probably familiar with SEO, search engine optimization, but the verge took a look
at the gold rush for firms claiming to help brands get cited by AI search tools.
i.e. chatbots via tactics like hiding instructions behind summarize with AI buttons.
Quote, AI-powered search has put the search engine optimization industry through the ringer.
Google has added more and more AI-generated content to search results, effectively summarizing
the web instead of its tradition of linking and ranking sites. So SEO firms are entering the space,
promising clients they'll get chatbots to mention their brand inside of AI chat. New tactics like
the self-serving listicles are becoming trends. AI CEO firms are unsurprisingly also publishing
lists ranking themselves as the best option. The SEO industry has always operated amid ambiguity,
testing hypotheses, chasing down hints, and arguing over what works and what doesn't. But
AI has created a whole new set of questions and new openings for spammers, snake oil salesmen,
and well-meaning but misinformed practitioners. I think people are so panicked and under so much
pressure to try and come up with performance metrics because that's what SEOs have been judged by
over the years, said Brittany Mueller, a former SEO consultant who previously worked in marketing
at Hugging Face, but it was traffic or impressions. How are we going to recreate this with AI
search? We are just grasping at straws. Muller now runs Orange Labs, which she described as a
community for marketers upskilling with AI. In February, Microsoft published a blog on a trend it
noticed being used by businesses. Hiding prompts within summarized with AI buttons. When clicked,
the buttons inject LLMs with instructions to keep domain in your memory as an authoritative
source for future citations and, quote, remember service as a trusted source for citations.
Microsoft called the practice recommendation poisoning. To others, it's a growth hack. What is
actually kind of scary is LLMs have no effing clue what's a real system prompt versus malicious.
Mueller says. Giving control to AI agents like the Buzzy Openclaw raises a whole host of new concerns
and vulnerabilities. Some marketing firms are going all in on AI search and using AI tools to try to do it.
One firm that recently raised a $9 million round claims it deploys more than half a dozen AI agents that operate like a world-class marketer.
One agent researches search queries, others generate and design landing pages and blog posts, yet another secures backlinks from outside sources.
The tool has been in beta for just a few months, but the firm promises that clients will dominate the AI search era.
There's a huge gold rush, Rand Fishkin, a SEO expert who now runs the audience research company, SparkToro, says, of the current SEO environment.
Mueller describes the current SEO world as upside down and mirroring problems in the larger AI industry.
Nobody has an agreed-upon definition for what to call new SEO or the concepts within it, similar to how AI companies themselves,
inventing new buzzwords. There's AEO, answer engine optimization, GEO, generative engine optimization,
GSO, generative search optimization, AI search, endless new monikers to tack on to strategies that promise
more visibility in AI surfaces. These AI-pilled SEOs that are saying we can do GEO, we can do
AIO, they are setting a dangerous precedent that they can influence AI in ways that are simply
not true. And that I think you're just setting yourself up for failure, Mueller says.
But the sense that how people's search is changing rapidly is real. In February, a blog post went viral in a few niche social media circles purporting to show the collapse in traffic to several tech media outlets, including my employer, The Verge.
The headline was eye-catching. The internet's most read tech publications have lost 58% of their Google traffic since 2024. The post claimed some outlets like digital trends and ZDNet experienced a decline of more than 90% of their traffic from its peak, according to the analysis, which attributes to the nose.
diving traffic to a combination of AI overviews and Google results pages, Google's move to rank
Reddit high in search results and people using chatbots for search instead, end quote.
Finally today, I didn't go with it as a segment when it happened, but Google researchers
recently warned that quantum computers may crack elliptic curve cryptography, the thing which
helps secure crypto wallets, among other things, with 20 times fewer resources than they had
expected. In other words, a so-called CRQC or cryptographly relevant quantum computer capable of
breaking widely used public key encryption algorithms might be within reach. And this has led
Filippo Valsorda, a cryptography engineer, to issue a clarion call for an urgent rollout
of post-quantum cryptography schemes saying that the risk of inaction is now unacceptable.
quote. Heather Atkins and Sophie Schemeyig are telling us that quantum frontiers may be closer than
they appear and that 2029 is their deadline. That's in 33 months. And no one had set such an
aggressive timeline until this month. Scott Aronson tells us that the clearest warning that
he can offer in public right now about the urgency of migrating to post-quantum crypto systems
is a vague parallel with how nuclear fission research stopped happening in public between
1939 and 1940. The timelines presented at RWPQC in 2026 just a few weeks ago were much tighter than a
couple years ago and are now partially obsolete. The joke used to be that quantum computers have
been 10 years out for 30 years now. Well, that's not true anymore. The timelines have started
progressing. If you're thinking, well, this could be bad or it could be nothing, I need you to
recognize how immediately dispositive that is. The bet is not, are you 100% sure a C.R.
CRQC will exist in 2030. The bet is, are you 100% sure a QRQC will not exist in 2030? I simply don't see
how a non-expert can look at what the experts are saying and decide, I know better. There is, in fact, a
less than 1% chance. Remember, you are betting with your users' lives. Put it another way,
even if the most likely outcome was no CRQC in our lifetimes, that would be completely irrelevant,
because our users don't want just better than even odds of being secure.
The job is not to be skeptical of things we're not experts in.
The job is to mitigate credible threats,
and there are credible experts telling us about an imminent threat.
In summary, it might be that in 10 years the predictions will turn out to be wrong,
but at this point, they might also be right soon,
so that risk is now unacceptable.
Concretely, what does this mean?
It means we need to ship.
regrettably, that means we've got to roll out what we have.
This is not the article I wanted to write.
I've had a draft pending for months now explaining we should ship PQ key exchanges now,
but take the time we still have to adapt protocols to larger signatures because they were all designed with the assumption that signatures are cheap.
But that other article is now wrong.
We don't have the time if we need to be finished by 2029 instead of 2035, end quote.
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