> but language models frequently outperform us in reasoning
what
99% of the time their reasoning is laughable. Or even if their reasoning is on the right track, they often just ignore it in the final answer, and do the stupid thing anyway.
what
99% of the time their reasoning is laughable. Or even if their reasoning is on the right track, they often just ignore it in the final answer, and do the stupid thing anyway.
The result is a 2x2 matrix where several quadrants are deeply concerning to me.
I give you a 2x2x2 matrix.
That'd be a tensor, no?
I fully believe that LLMs encode enormous amounts of knowledge (some of which is even correct, and much of which their operator does not personally possess), are capable of working quickly and ingesting large amounts of data and working quickly, and have essentially no judgment or particularly strong intelligence of the non-memorized sort. This can still be very valuable!
Maybe this will change over the next few years, and maybe it won’t. I’m not at all convinced that scraping the bottom of the barrel for more billions and trillions of low-quality training tokens will help much.
It's not even a different strategy. It's just using rhetoric in a more limited way, and without human emotion.
These are style over substance machines. Their cognitive abilities are extremely ragged and unreliable - sometimes brilliant, sometimes useless, sometimes wrong.
But we give them the benefit of the doubt because they hide behind grammatically correct sentences that appear to make sense, and we're primed to assume that language = sentience = intelligence.
I think the problem is that despite feeding it all the context and having all the right MCPs agents hooked up, is that there isn't a human-in-loop. So it will just reason against itself causing these laughable stupid decisions. For simple boilerplate tasks this isn't a problem. But as soon as the scope is outside of a CRUD/boilerplate problem, the whole thing crumbles.
My personal experience the past five months has been very mixed. If I "let 'er rip" it's mostly junk I need to refactor or redo by micro-managing the AI. At the moment, at least for what I do, AI is like a fantastic calculator that speeds up your work, but where you still should be pushing the buttons.
I haven't seen an LLM stay on task anywhere near that long, like...ever. The only thing that works better left running overnight that has anything to do with ML, in my experience, is training.
I will assume you passed high-school based on your looks and not on your abilities.
99% chance you're using the wrong model.
Effective tool use is a valuable skill, arguably the only one that still matters.