Why Models Are AI’s Next Training Dataset with Damian Borth - #772
Weight space learning treats trained neural networks as training data for future models
Researcher Damian Borth proposes treating existing trained models as a new source of training data, bypassing raw data collection by learning from the distilled knowledge encoded in model weights. This 'weight space learning' approach could reduce costs of developing specialized models and sidestep the data wall facing frontier model scaling. The idea is conceptually significant but remains academic research without production adoption.