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LLMs are good at producing what they/the public know. In this case: LLMs know the USB Spec very well. LLMs know how to read raw packet dumps. LLMs kno
by mmh0000 2mo ago
LLMs are good at producing what they/the public know.
In this case:
LLMs know the USB Spec very well.
LLMs know how to read raw packet dumps.
LLMs know how to convert a packet dump to USB spec
LLMs know how to write code to generate USB packets from the spec.
LLMs are also VERY good at transliteration, i.e., converting known-good Python to Rust.
Basically, If you have a well-documented problem, the LLM is a shortcut to learning it yourself. LLMs fail when you have a novel or poorly documented problem. They also fail when you provide the LLM with terrible context or too much context.
- CamperBob2 2mo agoDon't sell in-context learning short. Right now I'm waiting on Claude to wrap up the latest of a half-dozen extensive changes to XML files for a fairly-obscure (and obsolete) closed-source electronics CAD program. I am pretty sure it doesn't know anything about these files besides what's in the XML .DTD file (which I also gave it.) This is a very novel, reasonably-poorly-documented problem, and so far it has batted 1.000.
- mikeocool 2mo agoKinda sounds like you are finally realizing the dream of XML and DTD envisioned 25 years ago.
- CamperBob2 2mo agoExactly! Not to mention the belated realization of the so-called "expert systems" we were promised back in the 80s. Better late than never.
- toomuchtodo 2mo agoPlease consider writing a blog post on this project!