alt Hacker NewsNobody disputes that the LLM was drawing on knowledge in its training data. Obviously it was! But you'll need to be a bit more specific with your critique, because there is a whole spectrum of interpretations, from "it just decompressed fuzzily-stored code verbatim from the internet" (obviously wrong, since the Rust-based C compiler it wrote doesn't exist on the internet) all the way to "it used general knowledge from its training about compiler architecture and x86 and the C language."
Your post is phrased like it's a two sentence slam-dunk refutation of Anthropic's claims. I don't think it is, and I'm not even clear on what you're claiming precisely except that LLMs use knowledge acquired during training, which we all agree on here.
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The result is a fuzzy reproduction of the training input, specifically of the compilers contained within. The reproduction in a different, yet still similar enough programming language does not refute that. The implementation was strongly guided by a compiler and a suite of tests as an explicit filter on those outputs and limiting the acceptable solution space, which excluded unwanted interpolations of the training set that also result from the lossy input compression.
The fact that the implementation language for the compiler is rust doesn't factor into this. ML based natural language translation has proven that model training produces an abstract space of concepts internally that maps from and to different languages on the input and output side. All this points to is that there are different implicitly formed decoders for the same compressed data embedded in the LLM and the keyword rust in the input activates one specific to that programming language.
"clean room" usually means "without looking at the source code" of other similar projects. But presumably the AIs training data would have included GCC, Clang, and probably a dozen other C compilers.