this post was submitted on 08 Mar 2024
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This is dumb. Literally nothing has changed. Anyone who knows anything about LLM's knows that they've struggled with math more than almost every other discipline. It sounds counter intuitive for a computer to be shit at math, but this is because LLM's "intelligence" is through mimicry. They do not calculate math like a calculator. They calculate all responses based on a probability distribution constructed from billions of human text inputs. They are as smart, and as fallible, as wikipedia + reddit + twitter, etc, etc. They are as fallible as their constructing dataset.
Think about how ice cream sales correlate with drownings. There is no direct causality, but that won't stop an LLM from seeing the pattern or implying causality, because it has no real intelligence and doesn't know any better.
"Prompt engineering" is about understanding an LLM's strengths and weaknesses, and learning how to work with them to build out a context and efficiently achieve an end result, whatever that desired result may be. It's not dead, and it's not going anywhere as long as LLM's exist.
Prompt engineering is about expressing your intent in a way that causes an LLM to come to the desired result. (which right now sometimes requires weird phrases, etc.)
It will go away as soon as LLMs get good at inferring intent. It might not be a single model, it may require some extra steps, etc., but there is nothing uniquely "human" about writing prompts.
Future systems could for example start asking questions more often, to clarify your intent better, and then use that as an input to the next stage of tweaking the prompt.
Current systems already do that. But they're expensive and it might be cheaper to have a human do it. Prompt engineering is very much a thing if you're working with high performance low memory consumption language models.
We're a long way from having smartphones with a couple terabytes of RAM and a few thousand GPU cores... but our phones can run basic models and they do. Some phones use a basic LLM for keyboard auto correct for example.