Demis Hassabis, CEO of DeepMind, reflects on AI's evolution, inspired initially by brain architectures like neural networks and reinforcement learning.
As we move from scaling massive foundation models to applying AI across sciences, Hassabis envisions a future where AI helps us analyze and understand the human brain itself, completing a fascinating loop.
Speaking at the Royal Palace in Stockholm with Nobel laureates from physics, chemistry, medicine, and economics, he highlighted how AI could redefine neuroscience and unlock the mysteries of human cognition.
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Originally in with the field of AI, there was a lot of inspiration taken from architectures of the brain, including your networks and an algorithm called reinforcement learning. Then we've gone into a kind of engineering phase now where we're scaling these systems up to massive size, all of these large foundation models or language models. And there's many leading models now. And I think we'll end up in the next phase where we'll start using these AI models to analyse our own brains and to help with neuroscience as one of the sciences that AI helps with. So actually. I think it's gonna come sort of full circle. Neuroscientists sort of inspired modern AI, and then I will come back and help us, I think, understand what's special about the break.
