I wonder about the transcendence take as well. I think a lot of us are strapped into this ride regardless. If there’s a fresh new paradigm awaiting, I hope it’s a good one.
But my main observation is mostly personal: I get taken in a lot by technology waves, hoping things will get better, but I haven’t ever crisply defined “better.” Or my criteria has been too loose and I conflate novelty with progress. If advanced models eventually accelerate science and medicine so that more people can lead healthy fulfilling lives, that sounds a lot better. But if a model helps me use an undocumented API of a random IoT device tomorrow, I don’t think anything is much better, and I didn’t even get much out of the process. When efficiency isn’t paramount, I’m often not clear on when to take the shortcut versus when to do the work.
Yeah, I think this is the issue more than anything having to do with LLMs. It’s also why I stopped switching to the latest JS library du jour many years ago. The one I had worked fine. I don’t need to learn React because it just came out after learning fourteen other paradigms / frameworks.
> Or my criteria has been too loose and I conflate novelty with progress.
Yup.
> If advanced models eventually accelerate science and medicine so that more people can lead healthy fulfilling lives, that sounds a lot better.
Agreed.
> But if a model helps me use an undocumented API of a random IoT device tomorrow, I don’t think anything is much better, and I didn’t even get much out of the process.
Disagree, but it depends on what you’re looking to get out of it. Is the interesting part the RE / discovery? Or do you just want to control your car from Home Assistant?
That is, once you’ve RE’d a React native app, you don’t really learn anything new by doing it again. I have no problem with an LLM helping me with that.
But if I want to learn to RE a binary or app? Then I’ll do that!
Just because you can doesn’t mean you must, even if everyone else is.
LLMs provide you with the illusion of “free concurrency,” and it sucks people in.