[ITmedia News] ポケモン新作「ポケットモンスター ウインド・ウェーブ」 Switch 2で2027年に発売へ

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Москвичи пожаловались на зловонную квартиру-свалку с телами животных и тараканами18:04

Disposable Linux containers for AI coding agents, powered by TrueNAS and Incus.

发展趋势。关于这个话题,safew官方下载提供了深入分析

An attorney for Meta parsed through Burke’s notes from her sessions with Kaley extensively in a cross examination that lasted about three hours. He highlighted Kaley’s negative experiences with in-person bullying, other school-based sources of stress and anxiety and issues with her family. Mentions of social media in the notes were mostly limited to Kaley saying she didn’t feel she had a place at home, at school or among her peers, but did feel she had a place to be seen on social media.

Returning back to the Anthropic compiler attempt: one of the steps that the agent failed was the one that was more strongly related to the idea of memorization of what is in the pretraining set: the assembler. With extensive documentation, I can’t see any way Claude Code (and, even more, GPT5.3-codex, which is in my experience, for complex stuff, more capable) could fail at producing a working assembler, since it is quite a mechanical process. This is, I think, in contradiction with the idea that LLMs are memorizing the whole training set and uncompress what they have seen. LLMs can memorize certain over-represented documents and code, but while they can extract such verbatim parts of the code if prompted to do so, they don’t have a copy of everything they saw during the training set, nor they spontaneously emit copies of already seen code, in their normal operation. We mostly ask LLMs to create work that requires assembling different knowledge they possess, and the result is normally something that uses known techniques and patterns, but that is new code, not constituting a copy of some pre-existing code.

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