> There is no theoretical or empirical basis for LLMs having any reasoning capability. Deep learning models are specifically designed for automatic pattern rec

> There is no theoretical or empirical basis for LLMs having any reasoning capability. Deep learning models are specifically designed for automatic pattern recognition. That includes patterns of reasoning and problem solving. > The only reason it can solve it is because side the creators of these top models specifically trained the models on problems like this to give the appearance of intelligence. That's not how deep learning works, and not how machine learning works in general. The models can automatically recognize patterns of reasoning then apply those methods to problems it has never seen before. > The only way it can do so is not through reasoning, but by having been trained on a structurally similar puzzle. This is a fundamental misunderstanding of how it works. The large deep learning models have 100+ layers, modelling extremely abstract features of the data, which include abstract patterns of problem solving and reasoning. They are not simply regurgitating training examples.