On the upcoming implosion of AI
- Thread starter johnbryanpeters
- Start date
That was a lot of words.
I mean, he's not wrong about a lot of it. The hype machine is at full tilt, and the big players are burning through cash to over-promise and under-deliver.
But that's true for essentially every technology ever. LLMs are way better than the author gives them credit for and they are extremely useful for some types of tasks. We use them at work, I use them personally, and they can be powerful tools. Again, like essentially every technology ever, some companies are going to rush to say, "how can we use this tool to solve a problem?" rather than, "what problem do we have that this tool can solve?"
This isn't new, and many of those companies will die.
As it turns out - surprise surprise - the hard problems are hard, and they're taking a while to solve. They may not even be solvable with the current approach; there are limits to a statistical model of existing writings. And there is the giant thorny issue of how you respect copyright while needing to shovel billions of words and seconds of video into the models - to me, that's a far more intractable issue than most of the technology gripes that the author goes on about (though he does acknowledge it).
But to me this doesn't feel much different from the web, or smart phones, or voice recognition, or internet of things, or whatever. New Tech arrives, everyone scrambles to stuff New Tech into their Things so they can advertise that their Things are now Moar Better with 110% New Technologies Added. Eventually the pendulum swings back as the excitement dies down. Rinse and repeat.
But as a tool for distilling crazy amounts of information, or being able to ask for answers using natural language, nuance and context, or for finding patterns in huge datasets, LLMs are fucking awesome. It's probabilistic so you need to verify the output, but I can ask a very specific question using specific context and conditions, and 9 times out of 10 the answer will at least give me the right places to look.
I mean, he's not wrong about a lot of it. The hype machine is at full tilt, and the big players are burning through cash to over-promise and under-deliver.
But that's true for essentially every technology ever. LLMs are way better than the author gives them credit for and they are extremely useful for some types of tasks. We use them at work, I use them personally, and they can be powerful tools. Again, like essentially every technology ever, some companies are going to rush to say, "how can we use this tool to solve a problem?" rather than, "what problem do we have that this tool can solve?"
This isn't new, and many of those companies will die.
As it turns out - surprise surprise - the hard problems are hard, and they're taking a while to solve. They may not even be solvable with the current approach; there are limits to a statistical model of existing writings. And there is the giant thorny issue of how you respect copyright while needing to shovel billions of words and seconds of video into the models - to me, that's a far more intractable issue than most of the technology gripes that the author goes on about (though he does acknowledge it).
But to me this doesn't feel much different from the web, or smart phones, or voice recognition, or internet of things, or whatever. New Tech arrives, everyone scrambles to stuff New Tech into their Things so they can advertise that their Things are now Moar Better with 110% New Technologies Added. Eventually the pendulum swings back as the excitement dies down. Rinse and repeat.
But as a tool for distilling crazy amounts of information, or being able to ask for answers using natural language, nuance and context, or for finding patterns in huge datasets, LLMs are fucking awesome. It's probabilistic so you need to verify the output, but I can ask a very specific question using specific context and conditions, and 9 times out of 10 the answer will at least give me the right places to look.
when tech bros have a boner for something, you have to assume its overblown hype and they're mostly full of shit