Comment on LLMs and Humans are Cognitive Cousins – Sean Carroll podcast w/Dr. Chandra Sripada
nymnympseudonym@piefed.social 2 weeks agoWe train in bursts because we need a ground truth/scoring function to guide the learning
These are completely orthogonal things.
We train in bursts ("epochs") because empirically it leads to more rapid convergence on an acceptable error minimum.
The fact that a scoring function is needed is almost a tautology. You have to have some differentiable function to say what direction is lower error. Typically you segment your training corpus, and use the scoring function to get the error for one batch at a time to a certain threshold before proceeding to the next batch. Then go to the first batch and push the error bar even lower, and so on.
Kinda like tightening nuts on a car wheel. You don’t fully tighten the first one first; you have to wiggle the system into its final configuration.
TehPers@beehaw.org 2 weeks ago
We’re comparing this to the observable behaviors of humans, though. Humanity engages in unsupervised learning without a scoring function (let alone a differentiable one) and, as a result, can not only train on the fly, but can also find its own ways to self-evaluate its learning. Humans also have hormones which change how the brain works even further.
This is also all disregarding the ability for the human mind to become faster and more accurate on recall when it has more knowledge to search in a field. LLMs can’t recall very effectively, instead becoming less effective the more information it needs to search.