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Comment by benlivengood | Hacker News Reader

Weren't the last AI-is-impossible holdouts hanging onto creativity as the domain of true intelligence?

I disregard the narrow-AI-only folks almost on principle; Terrence Tao, Albert Einstein, Mozart, and Van Gogh couldn't do each others' jobs.

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Is this creativity, or is it remixing pieces of the creativity from the authors in the training data samples? Would it come up with anything that seems creative if the training data isn’t creative in the first place? I guess it’s a philosophical question, how to define “creativity”.

> or is it remixing pieces of the creativity from the authors in the training data samples?

I think you just described the majority of what is (for many) the "creative process".

Putting on my visual artist and composer hats, I assert that all creativity is synthesis. When a listener finds one of my compositions surprising, it’s because they don’t know all the sources of the micro elements of the composition. But I often do. If I thought about it harder, I could say I usually do.

My first reaction was annoyance: "It's just stealing work from thousands of other artists!" But then I realized that I, as an artist, basically do the same thing. Why is it ok for me to do, but not a machine?

Artists that produce something truly new currently seem to be once in a generation geniuses.

I think it's easier to label these images as 'creative' than it is to label them as 'art'. Art is a very slippery subject (it's subjective). Personally, I'd be happy seeing many of these images on an acid trip. Do they provide any social commentary, connect with me emotionally, or give me any food for thought? No. But then, a lot of the stuff churned out by modern media is equally as vacuous.

They do all the things you mentioned. There’s definite social commentary (cognitive merchant) and several of them are emotionally evocative.

Art has clearly developed over the millennia and it's possible to trace the lineage of ideas, techniques, subjects, and style back through history which means that most human art is substantially a remixing of older art.

That’s exactly what humans do too which is why is easy to break down art into schools/styles/epochs

I'm hanging on to folding clothes as my litmus test of AI :)

Or driving a car everywhere I can.

https://foldimate.com/

The last update to their blog was in 2019, so I think it's safe to say this is dead. When I click on their FAQ, I get the message, "This HappyFox account is expired. Please contact Administrator."

I did find a video[0]. It's just an automated version of the doohickey you see at any clothing store. Seems to require a lot of human input and orientation.

When I say "folding clothes" as a challenge for AI, I mean a device that is smart enough to take a pile of laundry, straight from the dryer, and fold each piece correctly. So if it's a t-shirt, then fold the arms inward, then fold that in half so the front is visible. If it's a pair of trousers, then fold each leg along the creases, match them together, and fold over the knee.

[0] https://www.youtube.com/watch?v=NcKz63DGHrA

I'm with you :)

(see my sibling comment)

FWIW, it's probably going to be the case that some AI will be able to correctly produce the picture of what an item will look like, once it is folded.

(and when that is pointed out, it will be met with counter-arguments of "goalpost moving")

https://www.theverge.com/2019/4/23/18512529/laundroid-laundr...

Hang on to NP complete problems instead, that one will stick around for a while I expect.

Folding clothes is more of a robotics problem than an AI problem. Paralyzed people are just as intelligent as everyone else!

I don't think robotics are the part holding back a clothes folding robot.

If you hooked up some basic manipulators to a VR controller, I'm pretty sure I could fold some shirts.

Not particularly well or quickly, but to a level that I'd be happy to see from a first generation shirt folding robot.

They're talking about the motion control and planning, which is certainly in the scope of what ML/AI is solving nowadays.

I'm sure that the physical part of this problem is also hard. But I have a lot more faith in robotics people coming up with the right "hands" with appropriate sensors on them to grasp a single piece of clothing and separate it from a pile, and then to manipulate that item on a large work area until it is folded. Maybe some delicate load sensors in the fingertips to adjust gripping force appropriately between the silk blouse and the corduroy trousers. Maybe no fingers at all, and just vacuum-and-pneumatic fabric handling devices. Or some other combination.

The things I've seen on assembly lines are beautiful and clever. But they all rely on a sort of consistency of input.

So yeah, that part is hard. But I think the intelligent control of whatever apparatus is used is harder still. To be able to recognize the different items, know when to turn them inside out, know when to bring the unbuttoned halves of a dress shirt together, etc. That's all very hard! Going from a chaotic pile of mixed clothing to a neat stack of folded garments is something a child can do easily, but no AI controlled robot in the world can do at all.

And if it fails on fitted bottom sheets, I won't dock it any points. Even I can't do that!

The thing is, I really think you could train a folding robot if you had the dataset to do it, just hire a few hundred clothes folding people who work for a large industrial laundry to wear eye tracker things and full body movement trackers. It'll probably 'just work' just like this and we still won't have an idea how, heh.

This program, like everything that has been called "AI", is following an algorithm. It's an impressive algorithm but not fundamentally different from my dishwasher.

In the Enlightenment period, philosophers and scientists marvelled at mechanical automata, machines that simulated aspects of digestion, the circulatory system and the brain. New developments in machine learning are rehashing the same philosophical questions that were raised in the 17th century in response to technological progress.

But it doesn't. That's different for neural networks : there is no pre-made algorithm that someone would implement (well, except for the overall architecture, but that's not what we are talking about).

An algorithm with an indeterminate output is still an algorithm.

The issue here is not so much that it's the output that is indeterminate, but the "algorithm" itself.

There's nothing indeterminate about the algorithm though. It's a fixed set of instructions fed into a Turing compatible machine like any other program.

And there's nothing indeterminate about the results of a pseudo-random number generator, but you seem to be missing my point ?

Let's just keep moving those goal posts.

The goalposts should be to create something useful, not trying to reach some nebulous criterion of "true intelligence". Submarine engineers don't labour over the question of whether their new designs are "truly swimming".

I, as a human, am following an algorithm similar to QCD for moving subatomic particles around which is fundamentally the same way a dishwasher moves particles around. Intelligence is mechanical in the Physics sense.

It will just be goalpost moved again: "I'll believe it when AI makes a number 1 on spotify hit song". After that happens they'll say "a human still selected the song from the 10 created by AI". Or something similar.

Creativity is not challenged here, because it's human who created all those base materials, all those styles, and all those biases. DALL-E simply picks up and mix those biaes, images, and styles, all based on human instruction. Ideas are all from human here.

The thing is, the hardest part in "creativity" is that one must voluntarily do it. That turned out to be not so easy for computer. (But I would not dare to declare it straight impossible.)

Humans did the same just with what’s other humans did before them. Would a Dall-e 2 trained only on other Dall-e images satisfy what you’re gatrkeeping here?

No, because DALL-E is only doing statistics, so training based on other DALL-Es doesn't add anything fundamentally new to the dataset.

I want to point out that most people actually get creativity wrong. It's an unfortunate truth that most of the "creative" tasks in the field are largely about association, perhaps with some errors, either intentional or not. It's really just all about querying (finding solutions), planning (arranging found solutions), and executing (apply the solutions accordingly). Human can perform these tasks both intuitively and logically, but, people normally mistake the intuitive approaches as "creative", even though it does the exact same things as logical approaches.

Let me give you an example.

Say, you're a designer and your client wants you to draw a bear drinking coffee. Unfortunately, that's usually all you get in reality, just like queries for DALL-E. You should figure out which kind of bear it is, which style it is drawn in, which type of cup it's holding, where the heck the bear is, blah blah...

You naturally start with surveying, probably by googling "bear" and "coffee". You browse through different types of bear and different types of coffee cups. Perhaps, you may have some specific images already in your head if you've drawn many enough bears and cups of coffee. In either cases, you come up with some base materials.

Now, you choose materials to use: which bear to use, which cup to use, which background to use, etc. You can use your gut feelings, of course, but you also can take numerical approaches and sort them by popularity on the internet, or by the ratings from your clients if you have data, etc. Anyways, you choose materials based on something.

After that you lay materials out - do mind that layouts are also subject to surveying and sorting - and draw a white bear drinking coffee in a ceramic tea cup, relaxing on a hump of snow. Perhaps near an igloo, because it's snowing! Since you got all your materials ready beforehand, this part is mostly about blending them into one scene.

... and let me ask you here: is this process really creative? I mean, this whole things sounds more like engineering to me. It's a highly logical process, with some room for incorporating intuitive association. Perhaps it's a lower-tier of creativity, if one really doesn't want to change the view.

So, what on the earth is creativity?

Since I'm not authoritative here, I can only humbly suggest it's an ability to push the boundaries of the (base) reality. If association is an exploration inward to find what's known, creativity is an exploration outward to find what has never been known. It's a trip into an virgin territory, which certainly requires meta-perceptual ability to conduct.

Anyways, so, if an AI is creative, it should be pushing the boundaries of what it's supposed to be doing. If the AI generates images, it should come up with a completely new style of art, new characters that no one has ever designed, etc. It should be contributing to the human society by introducing new cultural elements.

However, in case of DALL-E, it's just an external association engine. It allows untrained people to query, arrange, layout, and stitch image materials, though customization is close to zero. It's users are currently trying to push the boundary of this AI, meaning it's the users who are creative here. DALL-E itself is a tool for actual creative activities.

Thus creativity has never been challenged, unlike what enthusiasts love to claim. The whole hype here is rather a cheap word play.

still can't do hands, and has to be told what to do

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