[leoedin]

I briefly got excited about the possibility of local LLMs as an offline knowledge base. Then I tried asking Gemma for a list of the tallest buildings in the world and it just made up a bunch. It even provided detailed information about the designers, year of construction etc.

I still hope it will get better. But I wonder if an LLM is the right tool for factual lookup - even if it is right, how do I know?

I wonder how quickly this will fall apart as LLM content proliferates. If it’s bad now, how bad will it be in a few years when there’s loads of false but credible LLM generated blogspam in the training data?

[galaxyLogic]

That's the beauty of using AI to generate code: All code is "fictional".

[mulmen]

> I wonder how quickly this will fall apart as LLM content proliferates. If it’s bad now, how bad will it be in a few years when there’s loads of false but credible LLM generated blogspam in the training data?

There is already misinformation online so only the marginal misinformation is relevant. In other words do LLMs generate misinformation at a higher rate than their training set?

For raw information retrieval from the training set misinformation may be a concern but LLMs aren’t search engines.

Emergent properties don’t rely on facts. They emerge from the relationship between tokens. So even if an LLM is trained only on misinformation abilities may still emerge at which point problem solving on factual information is still possible.