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4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 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 src1.8 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 src4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 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 src1.8 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

#tensor-networks

2 curated events

papersSEP 10 04:00 UTC

Tensor-Train Weak SINDy Aims to Cut Cost of Learning High-Dimensional Dynamics

A new arXiv preprint introduces TT-weak-SINDy, a method that combines weak-form system identification with tensor-train decompositions. The approach is designed to reduce the memory and computational burden that current weak-form techniques face when applied to high-dimensional dynamical systems. The authors position it as a scalable alternative for data-driven discovery of nonlinear dynamics.

arxiv/dynamical-systems/tensor-networks/research

papersSEP 10 04:00 UTC

Tensor network method recovers moral graphs of causal DAGs from discrete distributions

Researchers describe a technique for inferring the moral graph of a causal directed acyclic graph using only the probability distribution over a set of discrete variables. The method represents the distribution with fully connected tensor networks and applies nuclear-norm regularization to the bond correction matrices to guide recovery. The paper adds a tensor-based approach to the toolkit for causal structure learning.

causality/tensor-networks/research