My naive middle-of-the-night Claude question said the same thing. At least for this approach. I have not read the paper closely enough to refute you. But the concept of a lower-dimensional closed-form solution — which the paper seeks to discuss, please correct me if you read differently — is tantalizing, if only because it opens the path to different math, which can lead to optimization.
Is it though? Brute force searching generally scales like 2^n. LLMs on the other hand can obviously be trained, and even though training is massively resource intensive, it's not 2^n.
Comments
No it is way worse since computationally they are same things with symbolic having overhead of attending to the symbols.
My naive middle-of-the-night Claude question said the same thing. At least for this approach. I have not read the paper closely enough to refute you. But the concept of a lower-dimensional closed-form solution — which the paper seeks to discuss, please correct me if you read differently — is tantalizing, if only because it opens the path to different math, which can lead to optimization.
Is it though? Brute force searching generally scales like 2^n. LLMs on the other hand can obviously be trained, and even though training is massively resource intensive, it's not 2^n.