Efficient problem-solving in science involves building models to narrow down possibilities in vast search spaces. For instance, in chemistry, with the vast number of possible compounds, a model can guide the search towards the most feasible options. This approach is applicable in various scientific fields like protein folding, drug discovery, material science, and battery design. The speaker believes that AI is on the brink of designing drugs for major diseases like cardiovascular cancer, although clinical trials remain a crucial step.
This week’s episode is a conversation with Demis Hassabis, the head of Google’s artificial intelligence division. We talk about Google’s latest A.I. models, Gemini and Gemma; the existential risks of artificial intelligence; his timelines for artificial general intelligence; and what he thinks the world will look like post-A.G.I.
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