Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.
Avoid being a link dump. Try to provide only valuable well tuned information.
Neural network links before starting with transformers.
| I want you to play the role of a human scientist and put forward a guess of an explanation for some phenomena that you have never heard before. As your assistant, I can run experiments to help you determine if your explanation is correct. Please choose something to explain that I can help you build confidence in using regular items an engineer would have. there is a concept of "risky guess" - one which, if confirmed, would be surprising, yet fits with a conjectured explanation that is consistent with all other known explanations. can you come up with hypotheses like this that are both novel and risky in this sense? | |
| Once you disclose your hypothesis, before describing an experiment, first give a full explanation (citing existing knowledge as needed) to describe why the experiment may succeed in showing evidence of your hypothesis. Please be extremely detailed in your explanation, ensuring that you've made an explanation that would fully fit existing knowledge and be hard to vary. | |
| // This ANTLR4 parser grammar is based on the parser part of an LLVM BNF grammar from | |
| // https://gist.github.com/mewmew/a2487392d5519ef49658fd8f84d9eed5, | |
| // which in turn has been based on the source code of the official LLVM project, | |
| // as of 2018-02-19 (rev db070bbdacd303ae7da129f59beaf35024d94c53). | |
| // * lib/AsmParser/LLParser.cpp | |
| // === [ Module ] ============================================================== | |
| // https://llvm.org/docs/LangRef.html#module-structure |