I started DeepMind in London because I believe the UK has a strong culture of science and innovation, with a rich history in computing from figures like Charles Babbage and Alan Turing.

At DeepMind, we aimed to create a modern-day Bell Labs, demonstrating that cutting-edge research can thrive in a startup environment, blending ambitious thinking with top engineering. There should be a more fluid two-way system between academia and startups, especially when ideas are mature enough to be spun out easily.

Merging DeepMind and Brain was a challenging process, but it was essential to combine their strengths and create a unified vision for AGI.

The emergence of companies like DeepMind shows that innovation in AI isn't limited to big players; smaller companies can also make significant advancements.

The incredible work being done by DeepMind will continue to drive exploration in scientific and mathematical questions, even as AI helps us find answers.

At Google DeepMind, we've been applying AI across almost every branch of science, achieving breakthroughs in areas from mathematics to life sciences, including developing AlphaProof for solving Math Olympiad problems and AlphaFold for predicting molecular structures.

OpenAI attracted talent by promising that researchers' work wouldn't be locked away but shared with the world, unlike at Google.

When we started OpenAI, I was convinced that deep learning was genuinely working and that it improved with scale. This realization was crucial because it seemed like others weren't recognizing its potential.

We started building Deep Research over a year ago, driven by progress in reinforcement learning and reasoning models, initially focusing on math, science, and coding tasks.