Demis Hassabis

Founded DeepMind with the explicit mission to 'solve intelligence and use it to make the world a better place.' The key methodological insight: AI research should be grounded in understanding how biological brains work. Reinforcement learning, episodic memory, and working memory models were all inspired by neuroscience and shaped DeepMind's research agenda.

AlphaGo's defeat of world champion Lee Sedol in 2016 demonstrated that RL + deep learning could master domains previously considered beyond AI reach. AlphaGo Zero (2017) then solved Go from scratch, learning purely from self-play with no human data — showing that AI could bootstrap superhuman expertise without human knowledge.

AlphaFold 2 solved the 50-year 'protein folding problem' at near-experimental accuracy, winning the 2020 Critical Assessment of Protein Structure Prediction (CASP) by an unprecedented margin. This earned Hassabis the 2024 Nobel Prize in Chemistry. His argument: AI is not just a productivity tool but a tool for fundamental scientific discovery.

Unlike some industry leaders who downplay AGI timelines, Hassabis believes AGI is achievable and potentially near-term. But unlike those who argue speed is the answer, he advocates 'bold and responsible' development — moving fast on capabilities while investing heavily in safety, interpretability, and alignment research.