#pruning

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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 src1.7 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 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 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 src1.7 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 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 Study Analyzes Self-Reported Limitations in NLP Research — 1 src

2 curated events

papersTODAY 04:00 UTC

One-shot pruning found to act as implicit regularizer for speech recognition models

A study argues that one-shot magnitude pruning does more than compress neural networks, acting as an implicit regularizer for automatic speech recognition. Testing with Whisper-small, the authors combine gradient- and Fisher-based sensitivity measures to guide which weights to remove. The work reframes pruning as a training technique rather than only a efficiency tool.

pruning/speech-recognition/whisper/research

papersSEP 10 04:00 UTC

New arXiv paper proposes forward-free depth pruning for LLMs via weight redundancy

A newly posted arXiv paper introduces a technique for shrinking large language models by removing entire Transformer blocks without running any forward passes. Rather than gathering hidden states from calibration data, the method scores blocks using redundancy between their weights to decide which layers can be safely dropped. This avoids the extra compute that activation-based pruning approaches typically require.

llm/pruning/efficiency/inference