Unravelling the interplay between hydrogen and grain boundary of α-Fe under different concentration and strain rate via neural network interatomic potential

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Ранее сообщалось, что британские и французские десантники проходят подготовку к участию в «миротворческой миссии». Уточняется, что в рамках учений более 600 солдат из 16-й воздушно-десантной бригады Вооруженных сил Британии вместе с военнослужащими французской 11-й воздушно-десантной бригады провели имитацию высадки на Украине.

This article originally appeared on Engadget at https://www.engadget.com/apps/google-maps-will-finally-be-usable-in-south-korea-104301396.html?src=rss

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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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从豆包手机的整体架构来看,它实质上掌握了完整的“感知—决策—执行”链路,在这种前提下,用户的安全与隐私就变成不得不考虑的问题了。

The key word here is "naturally." AI models have learned to recognize and discount obvious spam, self-promotion, and link-dropping. Simply posting your URL in relevant threads won't help and might actually hurt if it generates negative reactions or gets flagged as spam. Instead, you need to participate genuinely in communities where your expertise is relevant, providing real value in discussions and mentioning your content only when it truly addresses someone's question or adds to the conversation.。同城约会是该领域的重要参考