21–30 of 33 posts
It's tricky to get the prompts right I think and you won't necessarily get novel insights, more like the distilled common wisdom of an area.
You can ask it to pretend to write the response to a subreddit. And you get an approximation of a subreddit filled with the type of experts you want, instantly answering your questions. Although they occasionally just spout non-sense.
While I have been using GPT-3 via OpenAI’s APIs for about a half a year and I very much also appreciate using GitHub’s CoPilot because it saves me time, I wish for much more research into hybrid AI systems that are multi paradigm: deep learning, symbolic AI, new types of RL learning, breakthroughs in scaling conventional search, etc., etc.
There is so much work to get to the point where AI systems can effectively do counter factual reasoning, autonomously develop better models of the world, etc.
Symbolic AI as I learned it in the 1980s and deep learning in the last ten years are all great first steps, but we have a long way to go. Assuming parallel work in AI ethics, I don’t think there are any real limits on how much this technology can improve our lives.
Earlier quoted context omitted.
I am still greatly disappointed by the insistence on end-to-end black-box models. In the end, as impressive as these results are, they are fundamentally trending in the wrong direction. All the benefits and certainty (e.g. security, correctness, and reproducibility) provided by theorem provers and model-driven systems are thrown out the window in favour of fast but potentially wrong or insecure results. The worst par…
>in favor of fast but potentially wrong or insecure results. Formal methods don't eliminate wrong or insecure results. Formal methods tell you that a program matches the specification when certain conditions are true eg. no bit flips, the computer does not crash, the kernel doesn't kill your process, that allocations succeed, that your program can make progress (the kernel can decide to never schedule your program),…
Yes, they do. That's the entire purpose of a proof. Of course formal methods cannot prevent or even detect wrong specifications, but that's no different from generated code either.
> Using formal methods slows you down compared to things like testing which can get us most of the way there in less time.
But that's the point - formal methods are slow if people have to apply them. Automated theorem provers exist and can work on generated ASTs, so why not add the step and create a hybrid system that verifies the generated result?
>> Instead of turning the uploaded image into a mosaic as intended, the generated code simply creates a fixed-size black-and-white checker-board pattern
> It worked fine for an image I just tried. Just like the prompt it "convert[ed] the image to a 32x32 mosaic." There was no checkerboard, but it may be worth noting that it converted transparent pixels to black.
The code may have been changed - it works for me now, too, when before it definitely didn't.
Earlier quoted context omitted.
> Mediocre programmers use APIs, while good programmers know what's behind the curtain and can debug them. I suspect this will stay the same, no matter how many layers of abstraction we add. The skill of both such categories (API developers and developers who use API's) is defined by the ability to know the _least_ amount of complexity needed for a given set of requirements. You may be appealing to some "deeper" sens…
> Mediocre programmers use APIs, while good programmers know what's behind the curtain and can debug them. Personally I'd like to not know what's behind the curtain until I have to. Which category does that put me in?
This - along with GPT - are great ways to create originality detectors, something desperately needed. The generators get all the attention, but we should be finding ways to use these as discriminators, so that we can find innovative and original projects. I would love to get a list of Github repos or Steam games ranked on originality/chronologically. Things that are innovative within their own time. There are people…
This is one of those things that's so incredible and mind-blowing I really want to share it with friends or family, but WHY it is so impressive is locked behind a high enough sophistication that it would mostly be lost on them. Having written a script a decade ago about a future in which software issues would be solved not by debugging or programming, but by finding the right way to communicate concepts to AIs, it's…
I am still greatly disappointed by the insistence on end-to-end black-box models. In the end, as impressive as these results are, they are fundamentally trending in the wrong direction. All the benefits and certainty (e.g. security, correctness, and reproducibility) provided by theorem provers and model-driven systems are thrown out the window in favour of fast but potentially wrong or insecure results. The worst par…
This - along with GPT - are great ways to create originality detectors, something desperately needed. The generators get all the attention, but we should be finding ways to use these as discriminators, so that we can find innovative and original projects. I would love to get a list of Github repos or Steam games ranked on originality/chronologically. Things that are innovative within their own time. There are people…
Original != Good - you'd need a discriminator for "goodness".
Seeing something that could be argued to be "bad" or "dumb" yet completely unique would be my preference.
Earlier quoted context omitted.
I am still greatly disappointed by the insistence on end-to-end black-box models. In the end, as impressive as these results are, they are fundamentally trending in the wrong direction. All the benefits and certainty (e.g. security, correctness, and reproducibility) provided by theorem provers and model-driven systems are thrown out the window in favour of fast but potentially wrong or insecure results. The worst par…
People are going to generate black-box code, launch it as an MVP, and then hire engineers to iron out bugs or even do whole rewrites if the product gets traction. It's all going to just fit back into the same standard model.