Google DeepMind

Google's primary AI research division, which achieved silver-medal performance at IMO 2024 with AlphaProof and developed AlphaEvolve for mathematical exploration. - Developed AlphaProof and AlphaEvolve systems contributing to mathematical discovery

For the first time, AI systems are independently solving mathematical problems that stumped human researchers for decades. Since Christmas 2025, 15 problems from the legendary mathematician Paul Erdős's collection have been moved from 'open' to 'solved'—and 11 of those solutions specifically credited AI models. On January 6, 2026, a combination of OpenAI's GPT-5.2 Pro and Harmonic's Aristotle theorem prover produced the first fully autonomous AI solution to an Erdős problem that hadn't already been solved in the existing literature.

Updated Feb 13

Google's primary artificial intelligence research division, responsible for AlphaGo, AlphaFold, and the Gemini models. - Developer of Gemini model family

OpenAI launched the first commercial reasoning model in September 2024. Seventeen months later, Google claims its upgraded Gemini 3 Deep Think has pulled ahead on the benchmarks that matter most for science. The February 2026 update scored 84.6% on ARC-AGI-2—a test designed to measure how well artificial intelligence generalizes to novel problems—and 48.4% on Humanity's Last Exam, a collection of 2,500 expert-level questions crowdsourced from nearly 1,000 specialists worldwide.

Updated Feb 13

AI research laboratory that developed AlphaFold, solving the protein structure prediction problem and enabling genome-wide drug screening. - Developed AlphaFold, enabling DrugCLIP's approach

For decades, finding a drug meant testing millions of compounds one by one—a process that consumed years and billions of dollars before a single candidate reached patients. On January 9, 2026, researchers at Tsinghua University published DrugCLIP in Science, demonstrating a system that screened 500 million compounds against 10,000 human proteins in under 24 hours using just eight graphics processing units. The platform is 10 million times faster than conventional molecular docking.

Updated Feb 1

AI research laboratory that used graph neural networks to predict 2.2 million new stable materials. - Expanded materials database, validating predictions through partner labs

A new generation of AI systems can now design, execute, and analyze materials experiments with minimal human involvement. In January 2026, researchers at China's Shenzhen Institute of Advanced Technology published a system called MARS that coordinates 19 large language model agents with robotic platforms—optimizing perovskite nanocrystals in 10 iterations and designing novel water-stable composites in 3.5 hours. Traditional materials discovery takes 10 to 20 years from laboratory concept to commercial product.

Updated Feb 1

Google's AI research division, responsible for AlphaFold, AlphaMissense, and AlphaGenome. - Released AlphaGenome source code for non-commercial use

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 Jan 31

Google's AI research powerhouse, builder of AlphaGo, AlphaFold, AlphaTensor, and now AlphaEvolve. - Leading AGI race with Gemini 3, now 'engine room' of Google's AI efforts

Google DeepMind announced in May 2025 that AlphaEvolve—an AI agent powered by Gemini—discovered a way to speed up Gemini's own training by 23%. The system found smarter matrix multiplication algorithms, shaving 1% off training time for a model that costs $191 million to train. Small numbers, massive implications: AI just started improving the process that creates AI. In January 2026, DeepMind CEO Demis Hassabis told the World Economic Forum in Davos that genuine human-level AGI is now 'five to 10 years' away, with Google's latest Gemini 3 model topping performance leaderboards.

Updated Jan 31

Google's flagship AI research division, known for breakthrough achievements in game-playing AI, protein folding, and large language models. - Collaborative partner; maintains Montreal research office

For decades, creativity was considered AI's final frontier—the one domain where machines could never match human ingenuity. That assumption just cracked. A study published January 21, 2026 in Scientific Reports tested 100,000 humans against nine leading AI systems on standardized creativity measures. GPT-4 outscored the typical human participant. Google's GeminiPro matched average human performance.

Updated Jan 27

Alphabet's AI research lab pioneering large language models for scientific discovery across mathematics, biology, and materials science. - Opening first automated laboratory in UK 2026; partnering with U.S. DOE on Genesis

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. DeepMind announced its first automated laboratory in the UK for 2026, pairing Gemini with robotics to synthesize hundreds of materials daily. Google partnered with the U.S. Department of Energy on Genesis, a national AI-for-science platform mobilizing 17 national laboratories.

Updated Jan 22

The research powerhouse that achieved gold-medal mathematics and million-token context windows. - Technical leader in mathematical reasoning and multimodal capabilities

OpenAI's GPT-5 dropped on August 7, 2025, completing AI's transformation from chatbots that string words together to systems that actually think through problems step-by-step. Google DeepMind's reasoning models won gold at the International Math Olympiad, solving problems only five human contestants cracked. Anthropic's Claude, Meta's Llama, and every major AI lab sprinted to build models that pause, plan, and reason rather than just predict the next word.

Updated Jan 8

DeepMind is turning frontier research into default product behavior across Google. - Building Gemini models and pushing them into products at faster cadence.

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 clear note that Gemini 3-era Search grounding will begin billing on January 5, 2026.

Updated Dec 20, 2025