This podcast episode discusses the training of language models, particularly the use of synthetic children's stories as a training dataset for smaller language models. Researchers have explored the use of these tiny language models due to the challenges associated with training large models, including cost and interpretability. The results suggest that tiny language models can achieve performance comparable to larger models trained on more diverse datasets, highlighting the importance of training data quality and simplicity. This episode provides insights into the potential benefits and future directions for training language models.
