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▲ bayindirh 6 hours ago

In a world where masses believe that LLMs are "everything boxes", some reality check is always good.

▲jacquesm 5 hours ago | parent | next [-]

The problem is that they are 'everything boxes'. They're the first application that can actually lay claim to being a universal computing aid. What then happens is that people will start using their newfound hammer and before you know it everything becomes a nail, even if for a particular problem there is a better solution you can't beat 'nothing to invest, nothing to learn, get an answer in 10 seconds flat' from a convenience perspective. If I look at the things people use LLMs for I wonder why they take such an unsuitable tool, and then I marvel at the fact that they actually get more-or-less to where they would have gotten with the proper tools, and most likely in less time.

Slide rules displaced tables, calculators displaced slide rules and calculators themselves were displaced for the most part (they are still in use, in education but not nearly as much as they used to be outside of that) by the PC.

LLMs do that sort of thing for just about every information processing aid.

▲ehsankia 6 hours ago | parent | prev | next [-]

LLMs should be for general/high level work. For example, an LLM with the right harness could fetch and use that CNN, or train it's own CNN or other model to use for this task.

The harness in my experience makes a huge different too. Out of curiosity I tried having Gemini chat (with Argon) try to solve a level of this new puzzle game I'm linking (Order of the Sinking Star). It just got in an infinite loop and crashed. Then I try Antigravity with Flash 3.8 and it solved it easily. I saw the harness looked at other sokoban puzzles, coded some stuff, tried to replicate the level, etc. All things that a pure Gemini Chat doesn't really do.

LLMs are great for the high level harness, but if you want to count letters for example, it will still rely on "tools" like a piece of code to do it more reliably. Similarly in the above example, you wouldn't have the LLM directly try to analyze the images, but instead fetch and use the best tool for the job. But that can only be as good as the harness/tools it has access to.

▲bayindirh 5 hours ago | parent [-]

We don't disagree by a great margin. I'm not an anti-LLM person. I'm anti-hype in this case.

▲grumbel 6 hours ago | parent | prev [-]

LLMs are pretty good at writing calculators.

▲bayindirh 5 hours ago | parent [-]

I'd rather use a verified one. Scientific calculations on a ALU is tricky. There are many traps and hardware limitations to consider.