- Japan’s May 2023 policy change explicitly exempts AI training data from copyright, allowing use “regardless of non-profit or commercial purpose, reproduction vs. other acts, or source legality,” setting a global precedent for unrestricted dataset ingestion.  
- Participants debated the epistemic limits of prediction markets, with one analyst arguing markets are “no dumber than their average participant weighted by wealth” and become the most profitable way to exploit private knowledge, while others warned of emergent anti-inductive or perverse behaviors.  
- A link to the arXiv paper “Information Thermodynamics of Prediction Markets” (arXiv:2010.01905) was shared, framing market makers as Szilárd-engine–like entities that minimize information-theoretic cost.  
- The National Academies released the report “Third International Summit on Human Genome Editing: Expanding Capabilities & Participation,” covering global governance and technical progress in CRISPR and related technologies.  
- “De novo design of protein structure and function with RFdiffusion” (Nature, 2023) was highlighted as a breakthrough in generative protein design, demonstrating diffusion models that create novel folds and binding sites.  
- Discussion surfaced on automating archival retrieval for dead links in LLM training corpora; archive.org’s Wayback Machine was noted as cumbersome to script, prompting a search for existing GitHub grabbers.