These are tasks that would have taken months of development or millions of dollars in manual effort before. It's not just hype.
What’s the deal here with liability and accountability? That’s a serious problem when considering using these for anything other than toy problems.
Wherein you discover that unless you ask it to consider the fact that PDFs are ... very hard to parse [1] [2] you get something that misses whole blocks of text or turns them into something they aren't and the rest of the program misses chunks of the document.
[1]: https://news.ycombinator.com/item?id=22473263 [2]: https://web.archive.org/web/20200303102734/https://www.filin...
LMAO! It's so hilarious that people like you forget that the alternative is relying on bureaucracies managed by people that get things wrong more often and are both too lazy and too stubborn to process your application to review your drilling report again.
If using both human-level and AI-level analysis is cheaper and much more accurate (but still imperfect), I'm willing to settle for a better system than oppose all change and die holding out for a perfect system.
Let's say some of your drilling reports contain a pattern that indicates balrog activity, which the LLM misses. The legal or insurance context requires you to monitor and address potential balrog activity. How do you plan for these failures?
In almost every case I've seen, the plan is to not have a plan, which is another way of saying that the data doesn't matter so long as no one complains about the results.
Once again they are selling it like something that's for everyone right now. This is the problem. THe same with the metaverse. It has some really great usecases, but they made it out like next year we would all ditch our phones and work exclusively in a VR headset. Obviously that didn't happen, as the tech was nowhere near that and probably people don't want it either.
Also, if you really need to be sure that those 30.000 drilling reports really didn't contain any hazards, you still have to go through it all yourself. Don't forget LLMs aren't reproducible.
But no, my point was exactly that it's not just hype. There are genuine useful usecases, I totally agree.
As there were for metaverse, and probably even for blockchain (NFT not so sure tho :) I always thought they were really a solution looking for a problem). The key thing about a hype is that they overblow the potential benefits way too much though. I see this happening here once again.
