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 src2.0 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 src1.4 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 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 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 src2.0 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 src1.4 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 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up

GDPR

topic2 events
papersTODAY 04:00 UTC

GRIN+ Method Targets Machine Unlearning in Imbalanced Medical Data

A new arXiv preprint introduces GRIN+, a machine unlearning approach aimed at removing patient data from trained medical models both quickly and effectively. The work focuses on imbalanced clinical datasets, a setting where existing unlearning methods tend to degrade model performance. It frames the problem around privacy rules such as GDPR and HIPAA that grant patients the right to have their data erased.

machine-unlearning/medical-ai/privacy/gdpr
papersSEP 10 04:00 UTC

New arXiv paper introduces OmniMed-FL, a multimodal federated learning framework for clinical diagnosis

A recently posted arXiv preprint presents OmniMed-FL, a federated learning framework that combines medical imaging with patient record data for diagnostic tasks. The design keeps model training distributed across institutions rather than centralized, aiming to accommodate privacy rules such as HIPAA and GDPR. The paper appears in both the machine learning and artificial intelligence listings.

federated-learning/healthcare/privacy/multimodal