Google’s four AI departures: “We wanted to build something differently”

At the start of 2025, investors wondered whether Google could keep pace with OpenAI. By December, Alphabet was completing its best year on the stock market since 2009, helped by growing confidence in Gemini and Google’s broader AI strategy.

Much of that work came out of DeepMind, the British AI lab Google acquired in 2014 for about £400 million ($659 million in 2014). Now, Google is changing its leadership, while four of its best-known engineers are leaving to start an automated research lab.

DeepMind’s leadership reshuffles

Google announced Wednesday that DeepMind founder Demis Hassabis will step away from the lab’s day-to-day operations to become chair of Google DeepMind and chief scientist of Alphabet. Koray Kavukcuoglu, DeepMind’s chief technology officer and Google’s chief AI architect, will take control of Gemini model development, frontier AI research, the Gemini app and its developer teams.

At the same time, Jeff Dean, Sanjay Ghemawat, Oriol Vinyals and Quoc Le are also leaving Google to start Discovery Loop. As a public-benefit corporation, the company wants to use AI to automate scientific and engineering research. Google will remain involved as a founding investor and cloud provider. Just one person will now oversee everything from research to products.

In a January interview for CNBC’s podcast The Tech Download, Hassabis described DeepMind as the “engine room” of Google’s AI efforts. Hassabis said DeepMind develops Google’s core AI technology before it is distributed across the company’s products.

To get new AI into products faster, Google had to do more than update its models. DeepMind spent years reworking Google’s infrastructure so its AI work could move out the door quicker. That infrastructure push has extended to silicon, too — Google recently bet its inference future on a chip built for one model, a sign of how tightly the company is coupling hardware to its Gemini roadmap.

Hassabis said Google never struggled to invent new technology. After all, its researchers came up with the transformer architecture, which became the backbone of large language models. The problem was turning that research into products fast enough.

And moving faster is exactly what Google did. Hassabis pointed to Gemini 2.5, which landed in March 2025, as a turning point. Gemini 3 came out in November and put Google back in the mix with OpenAI and Anthropic — both of which have been making aggressive moves of their own to capture developer share.

By January, Hassabis said he and Google CEO Sundar Pichai were speaking almost every day, sometimes adjusting product plans and research roadmaps daily.

Kavukcuoglu inherits the Gemini roadmap

Kavukcuoglu has been at DeepMind for 13 years, started the deep learning team, and worked on projects like WaveNet and DQN. Now, model research, the Gemini app, and developer products are all on his plate. The flagship version of Gemini 4 remains unreleased after a planned June launch, according to Reuters. Hassabis confirmed the model’s name in his note to employees, saying Google was making progress on Gemini 4.

Discovery Loop’s founding engineers

Dean joined Google in 1999 and helped create Google Brain before becoming a technical co-lead for Gemini. Working with Ghemawat, he developed systems including MapReduce, Bigtable, and Spanner. Dean was one of the primary designers of TensorFlow, while Ghemawat worked on the infrastructure behind Google Search and several generations of its distributed computing systems.

Vinyals and Le made foundational contributions to deep learning and Gemini. Along with former OpenAI chief scientist Ilya Sutskever, they co-authored the influential 2014 paper that introduced sequence-to-sequence learning with neural networks. Their new company plans to use that experience to work on machine learning itself, at least to start.

“We are building AI solutions that can automatically solve important problems in machine learning, science, and engineering,” Discovery Loop says on its website.

“We are building AI solutions that can automatically solve important problems in machine learning, science, and engineering.”

The idea that AI can automate scientific discovery is no longer speculative. OpenAI’s Astra recently proved 10 long-standing math and science theorems for about $2,000 in token costs — a data point that suggests Discovery Loop is entering a space where early results are already landing.

Discovery Loop is built around the idea that AI can automate the entire experimental cycle. At Y Combinator‘s Startup School in July, Dean said the system could run the entire process, from proposing and carrying out an experiment to evaluating the results and deciding what to test next.

Ghemawat told Wired that Google’s systems were designed to support products such as Search, advertising and large consumer applications. Discovery Loop wants to build specialized infrastructure around research instead.

“We wanted to build something differently than how things are built at Google right now,” he said.

“We wanted to build something differently than how things are built at Google right now.”

Google keeps a stake

Rather than cut ties with the departing engineers, Google is investing in Discovery Loop and has signed a cloud partnership to provide the startup with computing capacity. That arrangement gives Discovery Loop access to the infrastructure needed to run large numbers of experiments without first building its own data centers. It gives Google a stake in anything the new company discovers and another major AI workload for Google Cloud.

Rather than cut ties with the departing engineers, Google is investing in Discovery Loop and has signed a cloud partnership to provide the startup with computing capacity.

Google has already lost Gemini co-leader and transformer co-author Noam Shazeer to OpenAI and AlphaFold researcher John Jumper to Anthropic. Worth noting, Alphabet shares fell more than 5% following Wednesday’s announcement.

Hassabis, meanwhile, will focus more of his attention on long-term AGI strategy and Isomorphic Labs, the drug-discovery company spun out of DeepMind.

In his message to employees, he said AGI now feels “close at hand” and that he wants more time to influence what happens next — a sentiment that carries extra weight as some of the most powerful AI labs face growing pressure to slow down.

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