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Google just quit the AI race on purpose, and it is about to make MORE money than everyone still running it.
4 of the most cited AI researchers alive walked out of Google in a single afternoon.
Jeff Dean, the man who built the systems Google runs on, gone after 27 years. Sanjay Ghemawat, his longtime partner, gone. Oriol Vinyals, a Gemini co-lead, gone. Quoc Le, a Google Brain co-founder, gone.
That same day, Demis Hassabis stepped back from running DeepMind. Hassabis co-founded the lab, won a Nobel Prize for AlphaFold, and had been the face of Google AI for a decade.
The stock dropped 5% within hours. Analysts called it a brain drain. Headlines called it the day Google fell behind.
But turns out that's completely wrong, because the numbers underneath tell a completely different story:
Google is not trying to win the frontier model race anymore. It looked at where the money is and walked toward it.
Gemini, Google's flagship model business, generated about $12 billion in annual revenue last quarter. That is the entire payoff from competing head to head with OpenAI and Anthropic.
Now look at the other number.
By the end of 2027, Google Cloud is projected to do over $73 billion selling AI infrastructure to other companies, plus another $120 billion selling its TPU chips. That is roughly $200 billion of external sales at high margins, against a $12 billion model business.
Google understood that the frontier race is the expensive part while selling the shovels is the profitable part.
And the customers buying those shovels include Google's own rivals.
Over 20% of Google's TPU shipments for 2026 and 2027 are going to Anthropic, one of the two labs supposedly beating Gemini. Google now makes money every time Anthropic trains a model designed to crush Google's OWN product.
Cede the frontier, own the layer underneath it, and collect a toll from everyone racing across the top.
The researchers leaving is the symptom of a company that already decided models are not where it wins.
Jeff Dean said it himself on the way out. He told the New York Times that leaving a public company gives him room to make decisions "not necessarily in the company's purist financial interests."
Read that from Google's side:
The people who wanted to chase the science left, because Google is now optimizing for the FINANCIAL interest.
Gemini 3.5 Pro is running months behind, with staff blaming low morale. DeepMind's comms, legal, and marketing teams are being folded into Google proper. A former manager told the Guardian the era of DeepMind as an independent lab is over.
None of that reads as failure once you see the strategy.
Yet Wall Street is pricing this as Google losing.
The parallel that should worry the frontier labs:
If open weight models keep compressing the price of inference, being the best model stops being a business. It becomes like semiconductor fabrication, strategically vital and financially brutal, a race you win and still lose money running.
Google is the first giant to admit that.
The company that invented the transformer just handed the frontier to OpenAI and Anthropic, and positioned itself to get paid on every model both of them ship.
Those labs will be burning billions to stay one benchmark ahead, and Google will be cashing in hundreds of billions from it.
The model business is actually just a race where everyone loses.
Apple understood that from the get-go and never joined the race, Google understood it now and left it to OpenAI and Anthropic.
Who will go bankrupt first?
“AI AGENTS COULD MAKE 80% OF APPS OBSOLETE.”
Creator of OpenClaw, Peter Steinberger argues that AI agents could fundamentally transform the software industry by replacing many standalone apps.
- Agents can unify context that individual apps never had.
- subscription model could be disrupted.
[users will pay an agent to solve problems, with the agent deciding which services to use and how much to spend.]
- Software will shift from tools you operate to systems that operate for you.
- User interface itself could become dynamically generated.
- Many apps could become invisible infrastructure.
He argues that many apps will disappear entirely, while others could transform into APls that agents use behind the scenes.
Entirely new software businesses will emerge around agent execution.
Demis Hassabis on why world models are his longest standing passion and the benefits vs. language models:
▫️ “I think language models are able to understand a lot about the world. More than we expected because language is actually probably richer than we thought. But there's still a lot about the spatial dynamics of the world, spatial awareness and the physical context we're in — and how that works mechanically — that is hard to describe in words and isn't generally described in corpuses of words.
Alot of this is allied to learning from experience. There's a lot of things which you can't really describe something. You have to just experience it. Maybe the senses and so on are very hard to put into words.
Whether that's motor angles and smell and these kinds of senses, it's very difficult to describe that in any kind of language.”▫️
***
From the Google DeepMind podcast in December 2025.
Today, @GoogleResearch introduced AMIE, our research medical AI system that can now conduct real-time video consultations with a first-of-its-kind demonstration of expert-level performance in a randomized controlled study.
Learn more from @GoogleForHealth
En Colombia, grabaron a un gallinazo (pariente del buitre) tocando la campana de una iglesia antes del terremoto
100 años de soledad no era realismo mágico, era un libro de anécdotas