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Eugene Yan x.com
When evaling models, we anchor on the median task. But this is like how devs estimate the median task accurately but underestimate the mean which tends to be ~2x estimated (thus "double your estimates"). This applies to models too—we optimize for time/cost on median tasks. But it's the tail tasks that determine a project's completion, and reliable models (like Fable and Opus) are the diff between success and failure. Work with models as collaborators, not tools. Go beyond pair-programming, where given a narrow spec, the tool just executes in minutes. Instead, explain your intent and what succ…
The the words it uses that this site has seen least often elsewhere. Posts are matched on those words alone — nothing here is a summary of this one.
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17 September
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korrents.com
Anthropomorphizing AI systems is necessary for reasoning about, explaining, and predicting their behavior accurately.Their words
Anthropomorphizing the AIs is the only way to reason about, explain to civilians about, or make good predictions about current AIs.
14 August
3 August
13 June
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Their words
Once we can accurately predict cancer 5+ years ahead, the era of primary prevention will go into high gear.
7 June
3 May
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korrents.com
Software development will shift from centralized systems to highly personalized, proliferating software abundance.Their words
Going forward, I think the future will be filled with software abundance, or, more accurately, I'd call it "software proliferation". That is, centralized development will be history. Software will be highly personalized, especially for open source software.
4 September 2025
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korrents.com
Local-first sync architectures are a natural fit for AI agents, since both are inherently multiplayer.Their words
Agentic and sync are natural complements because local-first is multiplayer by default, and agents are another sort of "player" in addition to human collaborators.
16 July 2025
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Their words
The state-of-the-art today can be more accurately described as "last-minute, black-box product testing" rather than auditing, and I think this situation threatens public safety, international stability, and sustainable commercial adoption of AI.
28 November 2024
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Their words
Reward hacking exists because RL environments are often imperfect, and it is fundamentally challenging to accurately specify a reward function.
Reward Hacking in Reinforcement Learninglilianweng.github.io
1 July 2022
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