8b models are great at converting unstructured data to a structured format. Say, you want to transcribe all your customer calls and get a list of issues they discussed most often. Currently with the larger models it takes me hours.

A chatbot which tells you various fun facts is not the only use case for LLMs. They're language models first and foremost, so they're good at language processing tasks (where they don't "hallucinate" as much).

Their ability to memorize various facts (with some "hallucinations") is an interesting side effect which is now abused to make them into "AI agents" and what not but they're just general-purpose language processing machines at their core.

Would be nice to point this at (pre-LLM) Wikipedia and fill out Wikidata!

You have a misunderstanding of what LLMs are good at.

Poster wants it to play Jeopardy, not process text.

Not sure if you're correct, as the market is betting trillions of dollars on these LLMs, hoping that they'll be close to what the OP had expected to happen in this case.

The market didn't throw trillions of dollars to develop Llama 3 8B.

What GP is expected to happen has happened around late 2024 ~ early 2025 when LLM frontends got web search feature. It's old tech now.

The GP’s point was about LLMs generally, no matter the interface. I agree that this particular model is (relatively speaking) ancient in AI the world, but go back 3 or 4 years and this (pretty complex “reasoning” at almost instant speed) would have seemed taken out of a science-fiction book.

I don't think he does. Larger models are definitely better at not hallucinating. Enough that they are good at answering questions on popular topics.

Smaller models, not so much.

Care to enlighten me?

Don't ask a small LLM about precise minutiae factual information.

Alternatively, ask yourself how plausible it sounds that all the facts in the world could be compressed into 8k parameters while remaining intact and fine-grained. If your answer is that it sounds pretty impossible... well it is.

Did you see the part in my original post where it said "Not unexpected for an 8k model"?

Oh I saw it, you still have a fundamentally flawed comprehension of LLMs.

The size of the model does not factor as tiny models can use Internet to fetch factual information.

But you think they are accurate repositories of knowledge, even though it's physically impossible unless lossless infinite compression algorithms exist (they don't, can't and won't).

I think you're overestimating your ability to assess what others think or comprehend.