R to @MistralAI: The model takes moderation policy as a plain-language question and returns a…

TL;DR - Mistral AI announced a moderation model that accepts a moderation policy expressed as a plain-language question and returns a calibrated score, handling both text and images through a single interface. It matters because it shifts content safety from fixed taxonomies to policy-as-prompt, letting operators define their own rules without retraining a classifier per category.

• Policy is supplied at inference time as a natural-language question rather than baked into a fixed label set, so moderation criteria are configurable per deployment.
• Output is a calibrated score (not just a binary flag), which is what allows threshold tuning against a given risk tolerance.
• One unified interface covers text and image inputs, removing the need for separate modality-specific moderation pipelines.
• Details are thin in the post itself — it points to an accompanying arXiv technical report for methodology and evaluation, none of which is described in the announcement.