Nobel Prize lecture: Demis Hassabis, Nobel Prize in Chemistry 2024

Demis Hassabis delivers a Nobel lecture, tracing his journey into AI from early experiences with chess and coding AI programs to founding DeepMind and achieving breakthroughs like AlphaGo. He discusses using games as proving grounds for AI, leading to the development of AlphaFold, which revolutionized protein structure prediction. Hassabis explains the criteria for suitable AI problems, the architecture and impact of AlphaFold, and the potential of AI to transform biology and drug discovery. He touches on the broader implications of AI across various scientific fields, emphasizing responsible development and the possibility of classical systems modeling quantum systems, and concludes by thanking his teams, collaborators, and family.

Outlines

Part 1: Origins, Games, and AGI

Part 2: Solving Protein Folding with AlphaFold

Part 3: Digital Biology and Future Science

Part 4: Ethics and Responsibility

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Nobel Prize

Part 1: Origins, Games, and AGI

Introduction to Demis Hassabis and His Early Fascination with AI

DeepMind's Approach to AI Through Games

Part 2: Solving Protein Folding with AlphaFold

AlphaGo's Neural Network and the Protein Folding Problem

Data Availability, Benchmarks, and the Development of AlphaFold

AlphaFold2 Architecture and its Impact

Part 3: Digital Biology and Future Science

AlphaFold3 and the Future of Digital Biology

Conjecture on Classical Computing and the Broader Applications of AI

Part 4: Ethics and Responsibility

The Importance of Responsible AI Development and Acknowledgements

Nobel Prize lecture: Demis Hassabis, Nobel Prize in Chemistry 2024

Nobel Prize

Part 1: Origins, Games, and AGI

00:00Introduction to Demis Hassabis and His Early Fascination with AI

Introduction to Demis Hassabis and His Early Fascination with AI

03:12DeepMind's Approach to AI Through Games

DeepMind's Approach to AI Through Games

Part 2: Solving Protein Folding with AlphaFold

06:49AlphaGo's Neural Network and the Protein Folding Problem

AlphaGo's Neural Network and the Protein Folding Problem

12:32Data Availability, Benchmarks, and the Development of AlphaFold

Data Availability, Benchmarks, and the Development of AlphaFold

15:49AlphaFold2 Architecture and its Impact

AlphaFold2 Architecture and its Impact

Part 3: Digital Biology and Future Science

19:26AlphaFold3 and the Future of Digital Biology

AlphaFold3 and the Future of Digital Biology

23:35Conjecture on Classical Computing and the Broader Applications of AI

Conjecture on Classical Computing and the Broader Applications of AI

Part 4: Ethics and Responsibility

27:35The Importance of Responsible AI Development and Acknowledgements

The Importance of Responsible AI Development and Acknowledgements