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111. Mo Gawdat - Scary Smart: A former Google exec’s perspective on AI risk

Towards Data Science

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Is There a Future for Algorithms?

I want abroad the that i'm in agreement with the idea, that i think a lot more resources should be directed to this sort of work. But one of the challenges today is that we're not actually quite clear on what the what the architectures will look like that get us there. We know probably deep learning, and we know maybe reinforcement learning, some open ended learning, but nothing's quite congealed. And this creates like, a problem for theorists who want to develop alinment solutions, because then they don't have anything concrete to work with. They just have abstractions that can't really be pinned down. That's the whole point. The whole point for me is the

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