Transfer Learning during LLM training tends to be 'broader' than that. Like how - Training LLMs on code makes them solve reasoning problems better - Training

Transfer Learning during LLM training tends to be 'broader' than that. Like how - Training LLMs on code makes them solve reasoning problems better - Training Language Y alongside X makes them much better at Y than if they were trained on language Y alone and so on. Probably because well gradient descent is a dumb optimizer and training is more like evolution than a human reading a book. Also, there is something genuinely weird going on with LLM chess. And it's possible base models are better. https://dynomight.net/more-chess/ https://dynomight.net/more-chess/