Andrew Lampinen is a research scientist at DeepMind. His research focuses on cognitive flexibility and generalization.

Andrew’s PhD thesis is titled "A Computational Framework for Learning and Transforming Task Representations", which he completed in 2020 at Stanford University.

We talk about cognitive flexibility in brains and machines, centered around his work in the thesis on meta-mapping. We cover a lot of interesting ground, including complementary learning systems and memory, compositionality and systematicity, and the role of symbols in machine learning.

• Episode notes: https://cs.nyu.edu/~welleck/episode38.html

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