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The first thing I tell the juniors under my supervision: any LLM is not a fact machine, even though sometimes it pretends to be. Double check everything!
The old joke is that you can get away with anything with a hi-vis vest and enough confidence, and LLM's pretty much work on that principle
The first thing I tell the juniors under my supervision: any LLM is not a fact machine, even though sometimes it pretends to be. Double check everything!
The thing I always tell those who heavily trust its output is to ask it something you either already know the answer to or are something of an expert in; the flaws become much more evident. The old joke is that you can get away with anything with a hi-vis vest and enough confidence, and LLM's pretty much work on that principle
It's also important to say what it isn't. LLM detractors, for lack of a better word, expect an oracle and then when they find out it's just a lossily compressed blob of human knowledge with natural language as a query interface they say the tool is useless. I've got my opinion on whether that's useful or not and it's quite a bit more nuanced. You don't zoom-enhance JPEGs for a reason either.
Tell that to the Google Pixel product team:
I can also see them as very clever search engines, since this is one way I use them a lot: ask hard questions about a huge and legacy codebase.
These analogies do not really work for generating new code. A new metaphor I am starting to use is "translator engine": it is translating from human language to programming language. It in a way explains a lot of the stupidity I am seeing.
I disagree with that analogy, because LLMs have a lot of connections between text fragments, which an encyclopedia doesn't have to such a deep degree. An encyclopedia also can't interpret and output relevant knowledge from an input prompt.