Researchers discover that Tirzepatide (Mounjaro) weight loss injection not only reduces appetite, but also activates brown adipose tissue, i.e. it stimulates a type of fat that specializes in ‘burning’ calories from food, in a new study in mice.

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This is all very tedious, formulaic, and difficult to write, so it is typical to generate this glue automatically using tools like embind or wasm-bindgen. This streamlines the authoring process, but adds complexity to the build process that native platforms typically do not require. Furthermore, this build complexity is language-specific; Rust code will require different bindings from C++ code, and so on.

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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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