[isomorphic_duck]

My biggest gripe with the discourse around AI, especially by programmers with hubris about Machine Learning, is the idea that LLMs can’t come up with “novel solutions”. They can, and they have. CoT[0] is how LLMs can output tokens in “reasoning space” to guide their “thinking” to produce absolutely novel solutions. You can imagine reasoning being multi-layered, where the top layer is an abstract heuristic (examples of which can be “try special cases”, “try solving a part of the problem with relaxed constraints”). The lower layers become more and more concrete with the details of the problem, and the result is a solution of the problem.

You don’t even have to understand how modern reasoning LLMs work to be able to tell that your perception is warped and doesn’t reflect reality - there’s plenty of news to the contrary - OpenAI resolving a major Erdos problem[1], the First Proof endeavour[2], amongst others [3].

[0]: https://arxiv.org/abs/2201.11903 [1]: https://openai.com/index/model-disproves-discrete-geometry-c... [2]: https://1stproof.org/assets/docs/report.pdf [3]: https://archive.ph/2w4fi