Using AI to accelerate scientific discovery - Demis Hassabis (Crick Insight Lecture Series)

Subscribers:
663,000
Published on ● Video Link: https://www.youtube.com/watch?v=XtJVLOe4cfs



Duration: 1:29:20
67,073 views
1,833


Using AI to accelerate scientific discovery
Demis Hassabis, co-founder and CEO, DeepMind
At The Francis Crick Institute in King's Cross, London

Abstract:
The past decade has seen incredible advances in the field of Artificial Intelligence (AI). DeepMind has been in the vanguard of many of these big breakthroughs, pioneering the development of self-learning systems like AlphaGo, the first program to beat the world champion at the complex game of Go. Games have proven to be a great training ground for developing and testing AI algorithms, but the aim at DeepMind has always been to build general learning systems ultimately capable of solving important problems in the real world. Excitingly, I believe we are on the cusp of a new era in science with AI poised to be a powerful tool for accelerating scientific discovery itself. We recently demonstrated this potential with our AlphaFold system, a solution to the 50-year grand challenge of protein structure prediction, culminating in the release of the most accurate and complete picture of the human proteome.

The speaker:
Demis Hassabis is the Founder and CEO of DeepMind, the world's leading AI research company that aims to solve intelligence to advance science and benefit humanity

In 2016, DeepMind developed AlphaGo, the first program to beat a world champion at the complex game of Go. In 2020, its Alphafold program was heralded as a solution to the 50-year grand challenge of protein structure prediction and in 2021, DeepMind launched the AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome to date.

A chess prodigy, Demis reached master standard aged 13, and went on to program the multi-million selling simulation game Theme Park aged 17. After graduating from Cambridge University in computer science, he founded pioneering videogames company Elixir Studios, and completed a PhD in cognitive neuroscience at University College London. Science listed his neuroscience research on imagination as one of 2007’s top ten breakthroughs, and in 2021, AlphaFold2 was selected as the Breakthrough of the Year.

He is a Fellow of the Royal Society and the Royal Academy of Engineering. In 2017 he featured in the Time 100 list of most influential people, and in 2018 he was awarded a CBE for services to science and technology.




Other Videos By Google DeepMind


2022-07-28Using AlphaFold in the fight against plastic pollution - Google DeepMind
2022-07-28Unlocking a decade-old antibiotics resistance problem with AlphaFold - Google DeepMind
2022-07-28AI as a tool for science - EMBL-EBI and AlphaFold - Google DeepMind
2022-05-05Welcome to DeepMind: Embarking on one of the greatest adventures in scientific history
2022-03-28Match 2: 90 Second Summary - Google DeepMind Challenge Match
2022-03-28Match 5: 90 Second Summary - Google DeepMind Challenge Match 2016
2022-03-28Match 4: 90 Second Summary - Google DeepMind Challenge Match 2016
2022-03-28Match 3: 90 Second Summary - Google DeepMind Challenge Match 2016
2022-03-28Match 1: 90 Second Summary - Google DeepMind Challenge Match 2016
2022-03-15The promise of AI with Demis Hassabis - DeepMind: The Podcast (S2, Ep9)
2022-03-04Using AI to accelerate scientific discovery - Demis Hassabis (Crick Insight Lecture Series)
2022-02-28Fair for all - DeepMind: The Podcast (S2, Ep8)
2022-02-21Me, myself and AI - DeepMind: The Podcast (S2, Ep7)
2022-02-16AI for science - DeepMind: The Podcast (S2, Ep6)
2022-02-14The road to AGI - DeepMind: The Podcast (S2, Ep5)
2022-02-07Let's get physical - DeepMind: The Podcast (S2, Ep4)
2022-01-31Better together - DeepMind: The Podcast (S2, Ep3)
2022-01-25A breakthrough unfolds - DeepMind: The Podcast (S2, Ep1)
2022-01-25Speaking of intelligence - DeepMind: The Podcast (S2, Ep2)
2022-01-10DeepMind: The Podcast (S2 trailer)
2021-09-09DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1/13]