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The Biggest Lesson From 70 Years of AI Research
The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective. And I think scaling up feels, at the very least, again, necessary for building incredible, complex systems. It's possibly not sufficient barring that we need a couple of breakthroughs. But there's a bit of this notion of hardware lottery for scale that might actually have an impact on how fast we'll make progress to maybe a version of neural nets or whatever comes next That might enable truly intelligent agents.