German AI foodtech startup Foodforecast raises €8 Million to cut ultra-fresh food waste

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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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Max Rushden is joined by Barry Glendenning, Lars Sivertsen and Mark Langdon to dissect a dramatic Champions League night

拉长时间线来看,有披露研发人员的企业数量从2021 年度的3895 家增至2025 年度的5309 家,五年间增长36.30%,增幅高于入库企业总数变动(20.81%)。随着这一增长,有披露研发人员的企业占比呈逐年攀升的态势,从66.60%增至75.15%。

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