译者之一李芝芳是塔可夫斯基的校友，毕业于莫斯科国立电影学院，深耕苏联电影研究多年。另一位译者刘馨浓曾在俄罗斯圣彼得堡生活学习，有多年编辑经验，是资深的塔可夫斯基影迷。
While the potential for physical hazards in Antarctica is high, Precious says social dynamics can prove more problematic. When relationships break down, the fallout can be hard to rectify, and hard to control, he says.
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巨头入局，眼里是生态和生意巨头纷纷重注AI硬件，背后其实是纯软件商业模式日益清晰的瓶颈。
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.