Demis Hassabis

New Capabilities

Leading Google's AI efforts; 2024 Nobel laureate in Chemistry

OpenAI launched the first commercial reasoning model in September 2024. Seventeen months later, Google's upgraded Gemini 3 Deep Think pulled ahead on the benchmarks that matter most for science.

Updated 8 hours ago

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Expects Isomorphic Labs' first AI-designed drug candidates to enter clinical trials by end-2026, following $2.1 billion Series B raise

In January 2026, researchers at Tsinghua University published DrugCLIP in Science—a system that screened 500 million drug compounds against 10,000 human proteins in under 24 hours using eight GPUs. That is 10 million times faster than conventional molecular docking. The results are publicly available in GenomeScreenDB, giving any lab access to screening data across roughly half the human genome.

Updated 3 days ago

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2024 Nobel Prize Laureate in Chemistry

For twenty years after scientists sequenced the human genome, 98% of it remained essentially unreadable. The protein-coding genes were mapped, but the vast regulatory regions—the genome's operating system—stayed opaque. On January 28, 2026, Google DeepMind released the full source code for AlphaGenome, an artificial intelligence model that predicts how genetic variants in these non-coding regions affect gene regulation and disease.

Updated 3 days ago

New Capabilities

Leading DeepMind's reasoning breakthroughs and AGI research

OpenAI's GPT-5 dropped August 7, 2025, completing AI's shift from chatbots that string words together to systems that think through problems step-by-step. Google DeepMind's models won the International Math Olympiad by solving problems only five humans cracked, as Anthropic's Claude, Meta's Llama, and every major AI lab raced to build reasoning models.

Updated May 19

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Leading development of self-improving AI systems, predicting AGI within 5-10 years

In May 2025, DeepMind's AlphaEvolve became the first commercial AI to optimize its own training—shaving 23% off a critical computation kernel. Since then, the loop has tightened: by April 2026, Anthropic's Claude agents were outperforming human alignment researchers on safety experiments, and GPT-5.5 had rewritten its own serving infrastructure to run 20% faster.

Updated May 19

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CEO of Google DeepMind; announced UK automated lab and Genesis DOE partnership

Science magazine named large language models doing frontier science a runner-up breakthrough of 2025. Within weeks, the prediction became reality: OpenAI's GPT-5.2 solved previously unsolved Erdős mathematics problems in 15 minutes, achieving 40% accuracy on expert-level mathematics that stumped earlier systems.

Updated May 19

New Capabilities

Runs all of Google's AI research and Gemini development

Sundar Pichai opened Google I/O 2026 with a Gemini model that can run a user's desktop. The keynote unveiled Android XR smart glasses too. Aluminium OS, a laptop platform merging Android and ChromeOS, will ship as 'Googlebooks' from Acer, ASUS, Dell, HP, and Lenovo.

Updated May 19

New Capabilities

Overseeing Gemini’s research-to-product pipeline as releases accelerate.

The rollout didn't stop at "Flash is the default." In the days after launch, Google filled in the missing contract with developers. Gemini 3 Flash Preview is now explicitly priced in the Gemini API, with context caching rates, batch pricing, and a note that Gemini 3-era Search grounding will begin billing on January 5, 2026.

Updated May 15

New Capabilities

Led the Gemma 4 release strategy

For two years, the most capable artificial intelligence models lived behind paywalls and API meters. Google made that harder to justify on April 2, 2026, when it released Gemma 4 — four open models ranging from 2 billion to 31 billion parameters, capable of handling text, images, video, and audio, under a fully permissive Apache 2.0 license with no usage restrictions. The competitive response was nearly immediate: Meta released Llama 5 just six days later, significantly ahead of its previously signaled Q3 2026 target, and Chinese lab DeepSeek followed on April 24 with its V4 model — a 1.6 trillion-parameter system also shipped as open-source under an MIT license. What began as a bilateral licensing contest between Google and Meta has become a six-way open-model race.

Updated Apr 24

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2024 Nobel laureate in Chemistry; leads both DeepMind's research and its drug-discovery spinoff

Determining the three-dimensional shape of a single protein used to take a graduate student an entire career. In March 2026, Google DeepMind released AlphaFold 4, a system that predicts the structure of multi-protein complexes in minutes rather than hours or days, extending a streak of capability gains that began when the original AlphaFold won a protein-prediction competition in 2018. Weeks earlier, DeepMind's drug-discovery spinoff Isomorphic Labs disclosed a proprietary model called IsoDDE that more than doubles AlphaFold 3's accuracy on key drug-design benchmarks, while a team at the National University of Singapore published D-I-TASSER, a tool that outperforms both AlphaFold 2 and AlphaFold 3 on difficult multi-domain proteins.

Updated Apr 23

New Capabilities

Leading Google's push into physical AI

For decades, industrial robots have been powerful but rigid—they follow pre-programmed instructions and break when the world deviates from what engineers anticipated. Google DeepMind's Gemini Robotics-ER 1.6, released on April 14, 2026, represents the sharpest version yet of a new approach: giving robots the same kind of flexible reasoning that powers chatbots like Gemini, but aimed at understanding and acting in physical space. The model can now read pressure gauges, thermometers, and digital readouts with 98% accuracy when paired with its agentic vision system—a capability that emerged directly from collaboration with Boston Dynamics, whose Spot robot patrols industrial facilities.

Updated Apr 21

New Capabilities

Leading Google's AI-for-science strategy

Google released an AI system in February 2025 that doesn't just search scientific literature — it proposes original hypotheses, then refines them through internal debate among six specialized AI agents. In one early test, the system independently arrived at the same mechanism for how antibiotic-resistance genes spread between bacterial species that a team at Imperial College London had spent a decade proving in the lab. It did so in two days, without access to their unpublished findings.

Updated Mar 28

New Capabilities

2024 Nobel Laureate in Chemistry for AlphaFold

It took thirteen years and $2.7 billion to read the first human genome. Now a single AI model, trained on 9 trillion DNA base pairs from more than 128,000 species, can predict whether an uncharacterized mutation in a breast cancer gene is dangerous—with 90 percent accuracy—without ever being shown that gene. On March 4, the Arc Institute and NVIDIA published Evo 2 in Nature, the largest biological foundation model ever built: 40 billion parameters, a context window of one million nucleotides, and the ability to design synthetic genomes the size of a simple bacterium.

Updated Mar 5