2min chapter

Machine Learning Street Talk (MLST) cover image

#54 Gary Marcus and Luis Lamb - Neurosymbolic models

Machine Learning Street Talk (MLST)

CHAPTER

GPT-3 vs GPT-2 - What's the Difference?

In the good old fashioned AI days we had human captured knowledge, right? And we had the knowledge acquisition bottleneck because I'm a huge believer in the kind of semantics you're talking about. Although after the conversation with Sholeo was somewhat convinced that there's an appropriate kind of substrate for an appropriate problem. So, you know, type one might be good for MNIST. But interestingly, there's a type two abstraction for any situation. You can abstract MNIST into a discrete categorization.

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