The same mechanisms that let a maintainer vouch for a human contributor can cryptographically delegate limited authority to an AI agent or service, with separate credentials and trust contexts that can be revoked independently if something goes wrong. Researchers from the Harvard Applied Social Media Lab and others are already experimenting with compatible apps that blend human and AI participants in the same credential‑aware conversations, hinting at how Linux ID might intersect with future developer tooling.
Tribes grant the Colorado River legal personhood - can this help save it?
。业内人士推荐搜狗输入法2026作为进阶阅读
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Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.
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