If you want to argue in favor of your slop machine, you’re going to have to stop making false equivalences, or at least understand how its false. You can’t make ground on things that are just tangential.
A computer in 1980 was still a computer, not a chess machine. It did general purpose processing where it followed whatever you guided it to. Neural models don’t do that though; they’re each highly specialized and take a long time to train. And the issue isn’t with neural models in general.
The issue is neural models that are being purported to do things they functionally cannot, because it’s not how models work. Computing is complex, code is complex, adding new functionality that operates off of fixed inputs alone is hard. And now we’re supposed to buy that something that creates word relationship vector maps is supposed to create new?
For code generation, it’s the equivalent of copying and pasting from Stack Overflow with a find/replace, or just copying multiple projects together. It isn’t something new, it’s kitbashing at best, and that’s assuming it all works flawlessly.
With art, it’s taking away creation from people and jobs. I like that you ignored literally every point raised except for the one you could dance around with a tangent. But all these CEOs are like “no one likes creating art or music”. And no, THEY just don’t want to spend time creating themselves nor pay someone who does enjoy it. I love playing with 3D modeling and learning how to make the changes I want consistently, I like learning more about painting when texturing models and taking time to create intentional masks. I like taking time when I’m baking things to learn and create, otherwise I could just go buy a box mix of Duncan Hines and go for something that’s fine but not where I can make things when I take time to learn.
And I love learning guitar. I love feeling that slow growth of skill as I find I can play cleaner the more I do. And when I can close my eyes and strum a song, there’s a tremendous feeling from making this beautiful instrument sing like that.
I have a book from the early 90s which goes over some emerging technologies at the time. One of them was bubble memory. It was supposed to have the cost per MB of a hard drive and the speed of RAM.
Of course, that didn’t materialize. Flash memory outpaced its development, and it’s still not quite as cheap as hard drives or as fast as RAM. Bubble memory had a few niche uses, but it never hit the point of being a mass market product.
Point is that you can’t assume any singular technology will advance. Things do hit dead ends. There’s a kind of survivorship bias in thinking otherwise.
AI is not a technology, it’s just a name for things that were hard to do. It used to be playing chess better than a human was considered AI, but when it turned out you can brute force it, it wasn’t considered AI anymore.
A lot of people don’t consider AlphaGo to be AI, even though neural networks are the kind of technique that’s considered as AI.
AI is a moving target so when we get better at something we don’t consider it true AI
I’m quite aware of the history of the field, thanks. It’s had a lot of cycles of fast movement followed by a brick wall. You can’t assume it’ll have a nice, smooth upward trajectory.
I think the problem is that you think you’re talking like a time traveler heralding us about the wonders of sliced bread, when really it’s more like telling a small Victorian child about the wonders of Applebee’s and in the impossible chance they survive to it then finding everything is a lukewarm microwaved pale imitation of just buying the real thing at Aldi and cooking it in less time for far tastier and a fraction of the cost.
If you want to argue in favor of your slop machine, you’re going to have to stop making false equivalences, or at least understand how its false. You can’t make ground on things that are just tangential.
A computer in 1980 was still a computer, not a chess machine. It did general purpose processing where it followed whatever you guided it to. Neural models don’t do that though; they’re each highly specialized and take a long time to train. And the issue isn’t with neural models in general.
The issue is neural models that are being purported to do things they functionally cannot, because it’s not how models work. Computing is complex, code is complex, adding new functionality that operates off of fixed inputs alone is hard. And now we’re supposed to buy that something that creates word relationship vector maps is supposed to create new?
For code generation, it’s the equivalent of copying and pasting from Stack Overflow with a find/replace, or just copying multiple projects together. It isn’t something new, it’s kitbashing at best, and that’s assuming it all works flawlessly.
With art, it’s taking away creation from people and jobs. I like that you ignored literally every point raised except for the one you could dance around with a tangent. But all these CEOs are like “no one likes creating art or music”. And no, THEY just don’t want to spend time creating themselves nor pay someone who does enjoy it. I love playing with 3D modeling and learning how to make the changes I want consistently, I like learning more about painting when texturing models and taking time to create intentional masks. I like taking time when I’m baking things to learn and create, otherwise I could just go buy a box mix of Duncan Hines and go for something that’s fine but not where I can make things when I take time to learn.
And I love learning guitar. I love feeling that slow growth of skill as I find I can play cleaner the more I do. And when I can close my eyes and strum a song, there’s a tremendous feeling from making this beautiful instrument sing like that.
Its because the tech bros have 0 empathy or humanity. Llm slop is perfect for them.
Oh my God, that’s perfect. It’s kit bashing. That’s exactly how it feels.
Stockfish can’t play Go. The resources you spent making the chess program didn’t port over.
In the same way you can use a processor to run a completely different program, you can use a GPU to run a completely different model.
So if current models can’t do it, you’d be foolish to bet against future models in twenty years not being able to do it.
Buy any bubble memory lately?
I have a book from the early 90s which goes over some emerging technologies at the time. One of them was bubble memory. It was supposed to have the cost per MB of a hard drive and the speed of RAM.
Of course, that didn’t materialize. Flash memory outpaced its development, and it’s still not quite as cheap as hard drives or as fast as RAM. Bubble memory had a few niche uses, but it never hit the point of being a mass market product.
Point is that you can’t assume any singular technology will advance. Things do hit dead ends. There’s a kind of survivorship bias in thinking otherwise.
AI is not a technology, it’s just a name for things that were hard to do. It used to be playing chess better than a human was considered AI, but when it turned out you can brute force it, it wasn’t considered AI anymore.
A lot of people don’t consider AlphaGo to be AI, even though neural networks are the kind of technique that’s considered as AI.
AI is a moving target so when we get better at something we don’t consider it true AI
I’m quite aware of the history of the field, thanks. It’s had a lot of cycles of fast movement followed by a brick wall. You can’t assume it’ll have a nice, smooth upward trajectory.
I think the problem is that you think you’re talking like a time traveler heralding us about the wonders of sliced bread, when really it’s more like telling a small Victorian child about the wonders of Applebee’s and in the impossible chance they survive to it then finding everything is a lukewarm microwaved pale imitation of just buying the real thing at Aldi and cooking it in less time for far tastier and a fraction of the cost.