LIVE PULSE
3.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.1 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src1.9 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.7 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.3 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.0 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.0 arXiv paper proposes emotion regulation framework for empathetic speech dialogue in audio-language models — 1 src1.0 Paper Studies Graph Matching Relaxations for Supervised Graph Prediction — 1 src1.0 arXiv Paper Proposes Framework for Cognitive Attribution in Acquired Representations — 1 src3.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.1 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src1.9 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.7 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.3 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.0 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.0 arXiv paper proposes emotion regulation framework for empathetic speech dialogue in audio-language models — 1 src1.0 Paper Studies Graph Matching Relaxations for Supervised Graph Prediction — 1 src1.0 arXiv Paper Proposes Framework for Cognitive Attribution in Acquired Representations — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up

NEXUS-MI

model1 events
papersSEP 10 04:00 UTC

NEXUS-MI: federated personalization framework for EEG motor-imagery brain-computer interfaces

Researchers present NEXUS-MI, an approach that personalizes EEG-based motor-imagery brain-computer interfaces through federated learning, letting user models improve without centralizing sensitive neural recordings. A gateway coordinates training in a communication-aware way, addressing variability across subjects and sessions. The goal is reliable adaptation when each person has only a small amount of calibration data.

federated-learning/bci/personalization/privacy