I use it many times a day for coding and solving technical issues. But I don’t recognize what the article talks about at all. There’s nothing affective about my conversations, other than the fact that using typical human expression (like “thank you”) seems to increase the chances of good responses. Which is not surprising since it better matches the patterns that you want to evoke in the training data.
That said, yeah of course I become “addicted” to it and have a harder time coping without it, because it’s part of my workflow just like Google. How well would anybody be able to do things in tech or even life in general without a search engine? ChatGPT is just a refinement of that.
I use it to make all decisions, including what I will do each day and what I will say to people. I take no responsibility for any of my actions. If someone doesn’t like something I do, too bad. The genius AI knows better, and I only care about what it has to say.
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.
I use it many times a day for coding and solving technical issues. But I don’t recognize what the article talks about at all. There’s nothing affective about my conversations, other than the fact that using typical human expression (like “thank you”) seems to increase the chances of good responses. Which is not surprising since it better matches the patterns that you want to evoke in the training data.
That said, yeah of course I become “addicted” to it and have a harder time coping without it, because it’s part of my workflow just like Google. How well would anybody be able to do things in tech or even life in general without a search engine? ChatGPT is just a refinement of that.
I use it to make all decisions, including what I will do each day and what I will say to people. I take no responsibility for any of my actions. If someone doesn’t like something I do, too bad. The genius AI knows better, and I only care about what it has to say.
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.