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Debian has started voting on decisions regarding AI and LLM contributions, which may impact open-source software development.
GitHub invites the community to vote on which sessions should take the main stage at GitHub Universe, shaping the conference lineup.
This paper identifies a fundamental constraint on multi-model LLM systems: accuracy is capped by the rate at which all models fail on the same query. Across 67 frontier models, the all-wrong rate is significantly underestimated by common metrics, limiting gains from voting, routing, and ensemble strategies.
Bubbles.town is a Hacker News-style aggregator for independent blogs, ranking posts by votes and freshness.
This paper analyzes power distortions in stake-weighted voting systems used in Proof-of-Stake blockchains, using both analytical methods and empirical data from the Cardano ecosystem's Project Catalyst to show how large stakeholders can dominate decision-making.