Strands, the New York Times' elevated word-search game, requires the player to perform a twist on the classic word search. Words can be made from linked letters — up, down, left, right, or diagonal, but words can also change direction, resulting in quirky shapes and patterns. Every single letter in the grid will be part of an answer. There's always a theme linking every solution, along with the "spangram," a special, word or phrase that sums up that day's theme, and spans the entire grid horizontally or vertically.
Что думаешь? Оцени!
。Line官方版本下载是该领域的重要参考
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.。Line官方版本下载对此有专业解读
"objectives": [