How Machines Learn to Ignore the Noise (Kevin Ellis + Zenna Tavares)

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Prof. Kevin Ellis and Dr. Zenna Tavares talk about making AI smarter, like humans. They want AI to learn from just a little bit of information by actively trying things out, not just by looking at tons of data. They discuss two main ways AI can "think": one way is like following specific rules or steps (like a computer program), and the other is more intuitive, like guessing based on patterns (like modern AI often does). They found combining both methods works well for solving complex puzzles like ARC. A key idea is "compositionality" - building big ideas from small ones, like LEGOs. This is powerful but can also be overwhelming. Another important idea is "abstraction" - understanding…