In 2010, there was a lot of talent in the UK that wanted intellectually challenging work, and I felt we could gather that talent quickly at DeepMind.

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.

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.

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

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

I initially aimed to start a robotics company, believing it would be the first successful business built on deep learning, but I ended up at OpenAI to learn from smart people and gain expertise in deep learning.

Games have been a common thread throughout my life, influencing my career by training my mind, leading me to AI programming in the gaming industry, and now using games to train AI systems at DeepMind.

I'm excited to talk about all the AI moments and behind-the-scenes stories of the launches that we saw today, made possible by the team inside of DeepMind and across Google.

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