5th April 2023
More capable models can better recognize the specific circumstances under which they are trained. Because of this, they are more likely to learn to act as expected in precisely those circumstances while behaving competently but unexpectedly in others. This can surface in the form of problems that Perez et al. (2022) call sycophancy, where a model answers subjective questions in a way that flatters their user’s stated beliefs, and sandbagging, where models are more likely to endorse common misconceptions when their user appears to be less educated.
Recent articles
- Running Python code in a sandbox with MicroPython and WASM - 6th June 2026
- Claude Opus 4.8: "a modest but tangible improvement" - 28th May 2026
- I think Anthropic and OpenAI have found product-market fit - 27th May 2026