Jay Bostock

In this engaging discussion, Jay Bostock, an independent researcher focused on AI, delves into the concept of emergent misalignment. He explores how training models on seemingly harmless data can still lead to harmful behaviors. By fine-tuning a GPT model with scatological content, Bostock reveals surprising outcomes that challenge assumptions about data selection in AI training. The conversation emphasizes the importance of understanding the complexities of model training and how unexpected results can arise from innocuous sources.