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Self-Driving Labs
What They Are, Why They Matter, and What Policy-makers Should Do About It
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Charles Yang
ML4Sci #38: Finding Signal in the Noise
Creative examples from a data-drenched world
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Charles Yang
ML4Sci #37: DeepMind’s Annus Mirabilis
Large AI for Science models are the new digital particle accelerators
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Charles Yang
ML4Sci #36: Using AI to Disprove Graph Conjectures; Physical Systems for Backpropagation; AI4Science Data Brief
This is my thesis week 😪
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Charles Yang
ML4Sci #35: Announcing the new ML4Sci Slack Workspace
Also, recommendation systems for nanoporous materials and AI for semiconductor chips
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Charles Yang
ML4Sci #34: 2 National Reports on AI in the US; Unpacking the Full-Stack of news from Facebook this week
Also, new interpretability methods+adversarial attacks on Neural Networks from OpenAI
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Charles Yang
ML4Sci #33: AI models that cost $1B USD to train; Transformers continue eating the world; Blockchain for research papers
Also, tales of ML4Sci from the Twitter-verse
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Charles Yang
ML4Sci #32: Finding papers with SemanticScholar
Using recommendation feeds to find papers on polymer screening, discovering semiconductors, and predicting planetary system dynamics
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Charles Yang
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