> Most people I talk to are at the point now where getting completely incorrect answers 10% of the time
A year back that number was 30%, and a couple of years back it was 60%. There will be a point where it'll be good enough. There are also better and better ways to verify answers these days.
It'll never be a solution for everything, but that's similar to many engineering problems we have: for example, ORMs aren't great for all types of queries, but they're sufficient for a good part of them.
It contributes little to discuss a hypothetical future. Maybe we'll have fusion energy, delivery drones, everyone using VR, etc. Maybe we will go into a deep recession due to trade wars, or maybe not.
The meaningful discussion is about how they perform NOW and the edge cases that have persisted since GPT-2 which no one has yet found a good solution for.
I disagree though, it is useful as this problem has been whittled down and I think there is expectation that there will be continued effort. Its of course worth discussing but I find that for my workflows, I rarely encounter issues with hallucinations, they certainly exist but its gotten to a point that I don't have major issue with it.
At best, a proof of concept of experimental delivery drones exist, but only for small, lightweight items, and only in a few places, only in the right weather, and only if you place a target on your driveway and are there to receive the item in person, and all at the cost of a very high noise level. That's not exactly a real service.
You are sort of moving the goal post. The fact remains, drone delivery exists and is a solved problem. Major metro areas like Dallas, Texas have it through retailers like Walmart. Just because it does not meet your specific goal post does not mean it's a proof of concept.
A year back that number was 30%, and a couple of years back it was 60%. There will be a point where it'll be good enough. There are also better and better ways to verify answers these days.
It'll never be a solution for everything, but that's similar to many engineering problems we have: for example, ORMs aren't great for all types of queries, but they're sufficient for a good part of them.