LIVE PULSE
4.8 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.1 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 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 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 Paper Examines How First Query Shapes Agentic Deep Search — 1 src1.3 Conformance-Driven Iterative Refinement for Natural-Language to SysMLv2 Translation — 1 src1.3 Neural Operators for Nonlinear Functionals on RKHS — 1 src4.8 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.1 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 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 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 Paper Examines How First Query Shapes Agentic Deep Search — 1 src1.3 Conformance-Driven Iterative Refinement for Natural-Language to SysMLv2 Translation — 1 src1.3 Neural Operators for Nonlinear Functionals on RKHS — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up

distributed intelligence

topic1 events
papersTODAY 04:00 UTC

Paper Introduces Robust Communication Method for Multi-Agent Reinforcement Learning

A new arXiv preprint presents a method for making the messages exchanged between agents in multi-agent reinforcement learning both informative and resilient to physical constraints. The work targets distributed intelligence settings where learned communication must stay reliable under real-world limitations. It is listed under both cs.AI and cs.LG.

multi-agent/reinforcement-learning/communication/arxiv