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Nice insights on Idea-Driven (ID) vs. Goal-Driven (GD) research by John Schulman. GD: define a success condition, then find the shortest path that satisfies it. ID: choose a problem X and a method Y, and "explore" X by applying Y to X without any prior expectationshttps://twitter.com/hardmaru/status/1223057947237875712 …
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GPT-2 is a test of empiricism. GOFAI was a test of nativism. So far, they have both failed. Solution: neuro-symbolic approaches exhibit the best of both worlds. Prior world knowledge to reason compositionally, alongside flexibility to generalize to new experiences
@GaryMarcushttps://twitter.com/GaryMarcus/status/1221178444769161217 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Kevin Tan proslijedio/la je Tweet
I'm curious. If you're in machine learning, do you know what the Levels of Analysis are? If so, do you think they are important or relevant for research today in machine learning?
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