Can you inspect the weights in GPT-3 and tell me what does? The mathematics of neural networks leads to huge numbers of parameters with small contributions on

Can you inspect the weights in GPT-3 and tell me what does? The mathematics of neural networks leads to huge numbers of parameters with small contributions on the overal result. There's tons of work in ML to try and go in the opposite direction, LASSO being probably the most famous. Yes, you can inspect the weights. But compared to other models, neural networks are still a black box. Interpretable means a human being able to explain what the model does. LASSO gets you this by narrowing down on a small number of important parameters. Decision trees are interpretable. Even allowing for some groupings of neural network parameters like convolutional filters or certain network architecture choices that can characterize an entire layer, there's still too many parameters to explain.