LIVE PULSE
4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election1 src1.1 Study Audits Misalignment in Multi-Modal World Models1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings1 src4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election1 src1.1 Study Audits Misalignment in Multi-Modal World Models1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE

#abstention

1 curated events
papersTODAY 04:00 UTC

arXiv paper proposes reward models for legal grounding and abstention

A new arXiv preprint introduces reward models designed to train language models to cite retrieved evidence when answering legal questions and to decline when that evidence is inadequate. The authors note that most existing reward models are not built for these high-stakes requirements. The work targets legal applications where unsupported or fabricated answers carry significant risk.