There’s a few people I know who use it for boilerplate templates for certain documents, who then of course go through it with a fine toothed comb to add relevant context and fix obvious nonsense.
I can only imagine there are others who aren’t as stringent with the output.
Heck, my primary use for a bit was custom text adventure games, but ChatGPT has a few weaknesses in that department (very, very conflict adverse for beating up bad guys, etc.). There’s probably ways to prompt engineer around these limitations, but a) there’s other, better suited AI tools for this use case, b) text adventure was a prolific genre for a bit, and a huge chunk made by actual humans can be found here - ifdb.org, c) real, actual humans still make them (if a little artsier and moody than I’d like most of the time), so eventually I stopped.
Did like the huge flexibility v. the parser available in most made by human text adventures, though.
Compiling medical documents into one, any thing of that sort, summarizing, compiling, coding issues, it saves a wild amounts of time compiling lab results that a human could do but it would take multitudes longer.
Definitely needs to be cross referenced and fact checked as the image processing or general response aren’t always perfect. It’ll get you 80 to 90 percent of the way there. For me it falls under the solve 20 percent of the problem gets you 80 percent to your goal. It needs a shitload more refinement. It’s a start, and it hasn’t been a straight progress path as nothing is.
I don’t understand what people even use it for.
There’s a few people I know who use it for boilerplate templates for certain documents, who then of course go through it with a fine toothed comb to add relevant context and fix obvious nonsense.
I can only imagine there are others who aren’t as stringent with the output.
Heck, my primary use for a bit was custom text adventure games, but ChatGPT has a few weaknesses in that department (very, very conflict adverse for beating up bad guys, etc.). There’s probably ways to prompt engineer around these limitations, but a) there’s other, better suited AI tools for this use case, b) text adventure was a prolific genre for a bit, and a huge chunk made by actual humans can be found here - ifdb.org, c) real, actual humans still make them (if a little artsier and moody than I’d like most of the time), so eventually I stopped.
Did like the huge flexibility v. the parser available in most made by human text adventures, though.
I use it to generate a little function in a programming language I don’t know so that I can kickstart what I need to look for.
Compiling medical documents into one, any thing of that sort, summarizing, compiling, coding issues, it saves a wild amounts of time compiling lab results that a human could do but it would take multitudes longer.
Definitely needs to be cross referenced and fact checked as the image processing or general response aren’t always perfect. It’ll get you 80 to 90 percent of the way there. For me it falls under the solve 20 percent of the problem gets you 80 percent to your goal. It needs a shitload more refinement. It’s a start, and it hasn’t been a straight progress path as nothing is.