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5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 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 src1.8 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 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 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 src1.8 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 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src

2 curated events

papersSEP 12 04:00 UTC

Amulet: Python Library for Assessing Interactions Among ML Defenses and Risks

A new arXiv paper introduces Amulet, an open-source Python library designed to evaluate how machine learning defenses interact with one another. The authors note that defenses are typically built to counter a single risk, such as a security, privacy, or fairness threat, but may unintentionally shift a model's exposure to other risks. Amulet aims to give researchers and practitioners a way to measure these cross-risk effects systematically.

python/ml-security/safety/research

papersSEP 12 04:00 UTC

Study Measures Gap Between Static Analysis Passes and Dynamic Failures in Python

A new arXiv paper examines cases where Python code passes static security checks but fails when actually executed, a discrepancy the authors call the static-pass dynamic-fail gap. The work focuses on security-sensitive code as well as code produced by large language models, arguing that static analysis alone is insufficient as a security gate. The authors frame the measurement as a step beyond reliance on static guarantees for evaluating generated software.

static-analysis/llm-generated-code/security/python