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OpenAI 9 years ago 29
Researchers at Anthropic and DeepMind have developed an algorithm that learns human preferences by comparing pairs of proposed behaviors rather than requiring explicit goal functions to be written. The system evaluates which of two actions a human prefers, using this feedback to infer the underlying objective. This approach reduces risks from misaligned proxy goals or incorrectly specified objectives in AI systems.
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8 August 2026
Mistral AI's release of Shieldstral 1.0 3B marks a practical inflection point in content moderation: safety classifiers are shedding their fixed rulebooks. The 3B model takes policies as plain-language prompts at inference time—meaning a single deployment can enforce different standards for different customers without retraining—while matching the performance of a 20B baseline on both text and multimodal content. It runs on a single 16GB GPU and ships under Apache 2.0, making it available for local deployment across vLLM and llama.cpp. For teams managing multiple content policies or operating across jurisdictions, this matters because moderation no longer requires separate model forks or constant retraining cycles.
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