How AI Is Unlocking the Secrets of Nature and the Universe | Demis Hassabis | TED

TED・2 minutes read

Demis Hassabis turned to AI to tackle big questions inspired by physics and a lack of progress in understanding fundamental laws. From AI playing Atari games to predicting protein structures, DeepMind's breakthroughs show the potential for AI to revolutionize scientific discovery and drug design, emphasizing the need for collaboration to shape the future of AI and ensure safety.

Insights

  • Demis Hassabis turned to AI to tackle big questions inspired by physics and the lack of progress in understanding fundamental laws.
  • DeepMind's AlphaFold program revolutionizes scientific discovery by predicting protein structures with incredible accuracy, potentially saving billions of years of research time and benefiting fields like biology, drug design, and disease understanding.

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Recent questions

  • How did Demis Hassabis use AI?

    To tackle big questions and find answers.

  • What sparked Demis Hassabis' interest in AI?

    Games, especially chess, and the brain's thinking processes.

  • What is Deep reinforcement learning?

    Allowing AI systems to learn directly from pixels.

  • What is AlphaFold's goal?

    To predict the 3D structure of proteins.

  • What is Isomorphic focusing on?

    Extending AlphaFold's work into chemistry for drug design.

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Summary

00:00

"Demis Hassabis: AI for Big Questions"

  • Demis Hassabis wanted to tackle big questions and turned to AI as a tool to find answers.
  • He was inspired by physics and the lack of progress in understanding fundamental laws.
  • AI can help find patterns and insights in vast amounts of data for human scientists to interpret.
  • Demis Hassabis was captaining the England Under 11 team at nine years old.
  • Games, especially chess, sparked his interest in AI and the brain's thinking processes.
  • DeepMind's breakthrough in 2010 involved using AI to play classic Atari games, leading to surprising strategies.
  • Deep reinforcement learning allowed AI systems to learn directly from pixels on the screen without explicit instructions.
  • DeepMind's AlphaGo program made history by beating the world champion at Go and inventing new strategies.
  • AlphaZero, starting from zero prior knowledge, quickly surpassed world-champion level in chess within 24 hours.
  • AlphaFold, DeepMind's program, aims to predict the 3D structure of proteins from amino acid sequences, potentially revolutionizing scientific discovery.

12:33

AlphaFold revolutionizes protein folding, accelerates drug design.

  • AlphaFold folded 200 million proteins in one year, saving a billion years of PhD time.
  • The accuracy of AlphaFold's predictions is within the width of an atom on average.
  • AlphaFold's predictions are crucial for biologists, drug design, and disease understanding.
  • AlphaFold's results were open-sourced on a database with the European Bioinformatics Institute.
  • Isomorphic, a new company spun out of Google, extends AlphaFold's work into chemistry for drug design.
  • Isomorphic aims to design chemical compounds that bind to specific protein spots without side effects.
  • Isomorphic is developing AI models in chemistry to predict outcomes.
  • Isomorphic's work may lead to dramatic breakthroughs in health and medicine.
  • The competition between tech giants investing in AI supercomputers raises concerns about safety and collaboration.
  • Governments, civil society, academia, and industry labs must collaborate to shape the future of AI and prevent a race dynamic.
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