Joseph discusses the challenges of training larger models and the successful application of quantization techniques developed by a team member. He highlights that their models were significantly larger than typical benchmarks, emphasizing the importance of exploring the trade-off space in model architecture. The conversation reveals that while they used standard methods, the interaction of these techniques led to promising results in both training and inference.
