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4.9 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 src2.2 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 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src4.9 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 src2.2 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 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src

topic2 events

papersSEP 12 04:00 UTC

arXiv paper proposes automating QUBO formulation from natural language

A new arXiv preprint describes a method for generating Quadratic Unconstrained Binary Optimization formulations directly from natural language descriptions. QUBO is widely used in combinatorial optimization and works with quantum, hybrid quantum-classical, and quantum-inspired solvers. The work aims to remove the manual effort of translating problem statements into QUBO form.

quantum/optimization/research/nlp

papersSEP 10 04:00 UTC

GNN-guided graph coarsening cuts QUBO size for quantum-annealed vehicle routing

An arXiv paper pairs graph neural network-guided coarsening with adaptive penalty tuning to shrink the QUBO formulations that arise when capacitated vehicle routing problems with time windows are solved on a quantum annealer. Customers that are geographically close and have compatible delivery windows are merged into super-nodes, reducing the number of binary variables before the problem reaches the annealer. The goal is to make quantum annealing tractable for larger, more realistic logistics instances.

quantum/gnn/optimization/logistics