Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how they do it. Researchers can observe the billions of parameters inside these systems changing during training, yet the internal logic of the models remains largely hidden. In a sense, the engineering is ahead of the science. Can science catch up and make LLMs and other deep neural networks mechanistically interpretable?
https://cacm.acm.org/news/can-we-understand-how-large-language-models-reason/



