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I don’t see how it’s obvious that LLM’s will be capable of any mathematical, “reasoning. LLM’s can infer relationships and maintain longer context chains in or
by agentultra 2y ago
I don’t see how it’s obvious that LLM’s will be capable of any mathematical, “reasoning.
LLM’s can infer relationships and maintain longer context chains in order to generate their output… it still happens that some times the output is correct depending on the training data, layers, context, etc. And it can get more accurate when we change the parameters of the model. But the algorithm isn’t “doing” anything here. It will generate something regardless of what it’s prompted with.
Maybe it’s right. But the algorithm is an algorithm. It doesn’t care what truth is. It’s generating BS essentially.
A human is doing a lot more work when performing mathematics.
It may be that LLM’s can be a useful tool in mathematical reasoning but it’s not obvious that it will ever be capable of it without a human, let alone be better than a human.
- resters 2y agoI think models could be designed that in separate layers created "logical system" representations which could feed back into the output, much like how attention works. Attention is about relevance, the logical layers could be based on logical schema-based patterns. Consider an LLM that happened to have some pre-trained layers that were trained abstractly on all the constructive proofs available for modern mathematics. LLMs with image recognition rely on existing visual pattern recognition layers, fwiw.
- agentultra 2y agoThere's another blog post that made it to the front-page of this site which sums up the state of the art nicely [0]. It's not obvious that they will be able to do any reasoning, in the formal sense, at all; let alone better than humans. LLMs are simply not sufficient for the kinds of tasks and work done when reasoning about mathematical problems. There's plenty of research demonstrating that they can be useful in small, constrained tasks -- which isn't anything to raise our noses at! ... it's just not _obvious_ in the sense that there is a clear step from LLM capabilities today to "better than humans." It's more an article of faith that it could be true, some day, if we just figure out X, Y, Z... which folks have been doing for decades to no avail. In other words, it's not obvious at all. [0] https://garymarcus.substack.com/p/llms-dont-do-formal-reasoning-and https://garymarcus.substack.com/p/llms-dont-do-formal-reason...
- resters 2y agoIt’s true that current models do not do formal reasoning, my point is that it is possible to use tokenization to do it. See my comment in the other thread.