Shifting Focus: From Architecture to Data and loss Functions
While the Transformer has been a transformative breakthrough, Karpathy noted that the focus in the AI community has shifted away from the architecture itself. He observed that companies and researchers are nOW more concerned with the quality and availability of data, as well as the design of the loss functions used to train these models.
Karpathy highlighted the potential of synthetic data as a solution to the perceived "data wall" that AI systems may face. He discussed the importance of maintaining diversity and entropy in synthetic data, to avoid the problem of "silent collapse" where models become overly specialized and lose the richness of their outputs.