Comment by party_possum | Hacker News Reader

Comment by party_possum | Hacker News Reader

Climbing route setting (when done at a high level) is constantly in conversation with itself. Many climbers don't realize that there are trends or fads in movement styles that sweep across the industry. This has only picked up steam in an era of social media.

Just like movie dorks will happily spend hours explaining how an individual shot in a movie is actually an insider reference to another movie, and as a result a statement of intent for the movie as a whole, professional route setters will talk your ear off about the way one of their problems embraces or rejects specific kinds of movement trends of the last 6 months.

That intentional rejection is interesting. Many route setters, especially for competitions, are in constant search of novelty. One kind of perfect problem is something that looks confusing and impossible, up until you see it done, at which point it seems almost obvious. It's the feeling of solving a sudoku. But critically, they want climbers to be initially confused.

I wonder if AI might actually be better than humans at sequencing these kinds of problems. Humans bring so much context and experience and expectation to the process that we are easily tricked. AI just looks through a few terabytes of video and says "What about this?".

> I wonder if AI might actually be better than humans at sequencing these kinds of problems

Probably a deeply unpopular take here, but without knowing anything about climbing routes, I'm gonna say no. I'm not saying that they won't have excellent quality output that might even solve problems that human output can't, but the process of creating something is meaningful, even commercially. Surely this will be useful in some respects, but I just don't buy the idea that humanity is destined to passively consume automated algorithm-generated utility products-- especially creative ones-- no matter how smooth, cheap, and clever they might be.

> the process of creating something is meaningful, even commercially.

That's true, but why does it mean that the answer to the more or less objective question "will AI actually be better than humans at sequencing these kinds of problems?" (As stated it's not really objective, but one could easily come up with metrics like, say, total time to a correct solution, or time spent observing the route or other climbers, or ….) One can imagine other, related questions that are less objective (like "will it be a good idea to integrate this AI assistance into climbing competitions?"), but, to me, the answer to the (implicit) original question has nothing to do with whether or not the activity is meaningful, or with humans' destiny one way or the other.

Sure, they may well be quantitatively better. If you were to create metrics to measure the number of mistakes or weird spots or overly annoying things, it's quite possible that the output from the algorithm could score better than human output, and the throughput would obviously be incomparable. But, whether or not something is qualitatively better is far more subjective-- it's influenced by our culture, our experiences, and everything else that creates the lens through which we see the world. Something's origin absolutely affects the way people experience it, be it a physical object, story, experience, etc. Don't get me wrong-- I realize there's real value in affordable quantity with with mediocre quality-- how many restaurants in the world are McDonald's? But then again, how many restaurants in the world aren't McDonald's? If McDonald's could sell you a ribeye comparable to Capital Grille, I'd be astonished if it put a dent in Capital Grille's bottom line. Applebees, however...

Right, those are important considerations, but I don't think that they're the same consideration. If you ask whether a celebrity chef is better at cooking a certain dish than I am, then the answer (no matter the dish, for I'm not much of a chef) is almost certainly "yes." If I answered instead no, that the provenance of a dish matters, that the celebrity-chef culture is bad for fine dining, and that my wife would rather have the dish made by me, then I think I'd be regarded as missing the point of the question, even if my objections were true on their own.

Well, I think that celebrity vs husband is not a good analog for human vs generated. I also think that in this case, origin has broader connotations than provenance, in that it includes context. What if the celebrity chef was your wife's brother? What if you had a degenerative neurological disease? What if it was the dish you cooked for her on your second date? Anything can seem very cut and dried if you impose artificial restrictions and examine it in a vacuum. And, because you can't easily define and quantify things like context, the engineering and tech worlds tend disregard them because they don't really factor into the engineering equation... and that's why designers exist.

I think your arguments against AI being better at creating routes reduce to:

1. You don’t like what that would mean about the destiny for humanity.

2. A human making it makes it inherently better.

3. If it’s lower quality, it’s lower quality.

I get why this would lead to strong beliefs. But these arguments aren’t very convincing.

I think you probably need to re-read what I wrote. I'm not against AI at all-- I use it all the time. I just don't think it's going to be qualitatively better than human creative output because how something was made matters to people. I also think the tech world thinks they're a lot better at judging creative output than they are.

Well, the tricky bit here is that the route setter, a human, is the one actually solving the problem. So the problem as set is (and must be) a human creation first. This is especially true in outdoor climbing, where the first ascent process might involve the installation of anchor fixtures, or the removal of poorly-secured features for safety. You'd need some pretty wild sensor suites to correctly differentiate between a really good hold, and a dangerous flake that will peel off the wall if the slightest force is applied to it. The AI just generates potential solutions to the problem once the holds are found/placed. Certainly, there's some interesting conversations about how satisfying it is to solve a rubick's cube using somebody's algorithm vs. just figuring it out, but its not like the computer is inventing a rubick's cube.

Embedded in your comment is the idea that AI might create boulder problems or routes in climbing gyms, and the human (or eventually robot) just follows that plan in bolting the holds to the wall. I expect that for a long time, AI generated climbing routes would rarely be good, but would consistently be physiologically impossible, feature uninteresting movement, or be too easy.

Its easy enough to shotgun holds up onto the wall based on some imagined sequence, the real skill of route setting is to (as the GP pointed out) figure out what's physically possible and also fun and challenging.

> You'd need some pretty wild sensor suites to correctly differentiate between a really good hold

Ah, I see.

> The AI just generates potential solutions to the problem once the holds are found/placed

Yeah and I think that's really going to be the sweet spot for generative tools for the forseeable future.

> Its easy enough to shotgun holds up onto the wall based on some imagined sequence, the real skill of route setting is to (as the GP pointed out) figure out what's physically possible and also fun and challenging.

Right right. I have a feeling that making a more convincing substitute is primarily a matter of having less access to data than say, paintings and photography which are certainly not less nuanced than this creative task. But as I said, a lot of people care about how something was made, too. I'll bet that's going to be a much bigger factor, at least in marketing, than many realize in the near future.

> Embedded in your comment is the idea that AI might create boulder problems or routes in climbing gyms, and the human (or eventually robot) just follows that plan in bolting the holds to the wall.

This would follow the exact path image GenAI evolved through.

Step 1: Teach a model to recognize objects from noisy data.

Step 2: Reverse-feed that model random noise and force it to hallucinate that noise back into likely objects.

As there's probably physics simulation at some point in this particular scenario, there'd probably also be step 3 of simulating a climb through the generated path to validate feasibility / specific qualities.

It doesn't sound impossible.

Its certainly not impossible, but that physics simulation is the biggest obstacle that I can see.

Spotting a refugee from rockclimbing.com on hacker news was not on my bingo card for the day. But I guess if I'm here (writing novels about route setting) then I shouldn't be surprised other people are too.

Outside of a short-lived usurper on instagram selling pet food dishes, I am still the only petsfed on the internet, since 1997.

What's really wild to me is how somebody would recognize a mid-tier poster from a website I thought effectively defunct for nearly 10 years now.

It just goes to show how impactful online communities are capable of being. rockclimbing.com was in it's heyday right as I was discovering climbing. I was a bored kid constructing my entire identity around climbing and there was no other place to do that outside of the gym. No mountain project. No youtube. No social media. I spent a lot of hours lurking those forums. There are only a handful of users I could still name, but I bet I would recognize a lot of them.

You mean AI might be better at setting or at reading? I feel like your question is getting misinterpreted.

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