decision-making-under-uncertainty

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

topic2 events

papersTODAY 04:00 UTC

Uncertainty Quantification Method Proposed for Earth System Foundation Models

A new arXiv preprint addresses how to quantify uncertainty in spatiotemporal foundation models used for Earth system modeling. The authors frame the problem around decision-making and risk control rather than pure prediction accuracy. The work aims to make such models more reliable when their outputs inform real-world choices.

research/uncertainty-quantification/earth-science/foundation-models

papersSEP 11 04:00 UTC

arXiv Paper Proposes Data-Driven Framework for Supply Chain Decision-Making

A new arXiv preprint describes an approach that combines statistical learning from data with robust decision-making for supply chain networks. The work targets structural uncertainty, market volatility, and operational disruptions that modern supply chains face, and aims to connect data-driven methods with practical decision support. It is an announcement of a cross-listed machine learning paper rather than a released product.

arxiv/supply-chain/research/decision-making