5.1 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.8 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.6 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.3 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src1.4 Perceptual Reality Transformer Explores What Illustrations Must Preserve — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.1 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.8 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.6 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.3 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src1.4 Perceptual Reality Transformer Explores What Illustrations Must Preserve — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src
ECAS: Edge-Controlled Agentic System for Validation-Gated Scientific Execution
A new arXiv paper introduces ECAS, an agentic system that uses large language models to turn a scientist's high-level goal into correct, target-scale runs on high-performance computing resources. The approach places control at the edge and gates execution behind validation checks, aiming to address how brittle and labor-intensive it currently is to translate research intent into working HPC workflows. The authors position the work as a step toward more reliable LLM-driven scientific computing.