I might, actually. Think of where electric cars were six years ago — 2018. Not much has changed. Or, at least, there are still fundamental problems to be solved.
In the same way I can imagine that by 2030 LLMs will still have memory problems and hallucinations. Although I’m sure by then we’ll have something better than pure LLMs.
I've heard claims that context without forgetfulness has already been reached 2 months ago, but as I'm not a domain expert I don't trust that I can differentiate breakthroughs from marketing BS, and I definitely can't differentiate either of those from a Clever Hans: https://arstechnica.com/information-technology/2024/03/claud...
I work in this field, so here's a comment with higher signal-to-noise ratio than you'll commonly find on HN when it comes to LLMs: notice how the demo use cases for very long context stuff deal almost universally with point retrieval, and never demonstrate a high degree of in-context learning. That is not coincidental. The ability to retrieve stuff is pretty great and superhuman already. The ability to reason about it or combine it in nontrivial ways leaves a lot to be desired still - for that you have to train (or at least fine tune) the underlying model. Which IMO is great, because it neatly plugs the gaps in human capability.
In the same way I can imagine that by 2030 LLMs will still have memory problems and hallucinations. Although I’m sure by then we’ll have something better than pure LLMs.