This is a lecture by Dr. Demis Hassabis, founder and C.E.O. of DeepMind. The title of this lecture is ‘Using AI to Accelerate Scientific Discovery,’ which is DeepMind’s primary goal.
DeepMind is a company where neuroscience and artificial intelligence begin to merge. Their task is to develop machine learning algorithms that resemble intelligent behavior.
At DeepMind, they found that two-person games were a great training ground to test ideas on how to build machine learning and AI algorithms. This would eventually lead to AI applications for significant, real-world problems.
DeepMind’s domain is Artificial General Intelligence, a field that models the environment, in contrast to traditional AI that focuses on specific tasks. Their mission, ‘Solving intelligence to advance science and benefit humanity,’ encapsulates their transformative vision for the future of AI in scientific discovery, a vision that holds immense promise for the betterment of our world.
In his lecture, Demis describes some details of active reinforcement learning and training generalized neural networks. He describes AlphaGo as having fantastic success in playing the oriental game of ‘Go.’ This led to Alpha0, which can play any two-player game without even being told the game’s rules.
Dr. Hassabis delves into AlphaFold, a model that can take an amino acid string and predict the resulting protein structure. This revolutionary tool is currently being used worldwide in biology, medicine, and pharmacy research, underlining the global impact of DeepMind’s work. He then invites the audience to envision the myriad potential applications of these generalized models, a thought-provoking exercise that underscores the far-reaching implications of their research.
Content Link: Using AI to Accelerate Scientific Discovery – YouTube
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