4 ms·

Through a Glass Darkly

65 points by ctoth 3y ago

pedalpete 3y ago
This is one example where I wish the HN title better represented the content. "Nobody predicted the AI revolution, except for the 352 experts who were asked to predict it."
- dang 3y ago
  I see your point, but sometimes it's good for HN readers to work a little (just a little!), and I feel like this is one of those cases. Not everything should be explicitly spelled out - especially when the title isn't obviously baity and the article is substantive. https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sort=byDate&type=comment&query=%22work%20a%20little%22%20by:dang https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...
  - pedalpete 3y ago
    With the link to Algolia, I feel like "work a little" is a tagline you are trying to promote. But look at it this way. Each title on HN is an advertisement to learn about an interesting...something. Does the title interest you enough to read the article? Because if it doesn't accomplish that task, it doesn't get clicked on, or potentially not clicked on by the correct people.
    - dang 3y ago
      It is! But I have dozens if not hundreds of similar taglines - and a different algolia link for most of them... There are titles that give you a pre-digested précis of the article, and then there are titles that intrigue. HN needs both kinds.
- andromaton 3y ago
  Also, copying the first few lines: "Through a Glass Darkly Scott Alexander Nobody predicted the AI revolution except" For the future: @dang, is that ok?
EvanKelly 3y ago
What would it mean for an AI to beat the best humans in a 5K race? Obviously robots can do that, is there some definition of "humanoid AI robot" which exists for such a task?
- kbenson 3y ago
  I think to have meaning the AI would have to work both as generally and usefully as a human, and fit entirely within a human size profile (not offloading compute remotely). What makes humans competing against each other even remotely worth paying attention to is the constraints, which is that we're all autonomous, we all have similar size, we all can function to a similar degree. Plenty of animals can beat humans at all sorts of things, but they can't do so while also standing in as a human, so the comparisons aren't very interesting. Building a robot that has a human profile and can run and beat humans at a 5k race also isn't very interesting (at this point), because fine, you created a running robot, but that robot's not going to do it's own taxes at the end of the year, so in the sense of AI, who cares.
  - mlyle 3y ago
    > beat humans at a 5k race also isn't very interesting (at this point), because fine, you created a running robot, but that robot's not going to do it's own taxes at the end of the year, so in the sense of AI, who cares. It depends exactly on what we're saying. So far we have machines that can navigate language well, but aren't good at navigating real world environments. If we're talking about a road 5k race, with myriad ways that courses are marked and many, many distracting, this is at least an interesting problem (perhaps as difficult as self driving vehicles).
    - kbenson 3y ago
      Being able to navigate the course is an interesting problem. I'm not sure beating a human at it is, unless we change the problem to be accomplishing something useful (lugging a certain amount of weight up a cliff face for rescue operations, for example), or make the contestant AI sufficiently human like. A 5k race is about competition, not about doing useful work. For AI or a robot to compete and win and have it mean anything means it needs to be similar enough to the other contestants to make that competition matter, otherwise I could slap a picture of my face on an RC car with enough batteries and "win". We all realize intuitively that a "win" such as that tells us nothing useful, so would ignore it even if it somehow was allowed. AI is a bit less intuitive to many at this point, so it's not always as obvious.
layer8 3y ago
> We should, as a civilization, operate under the assumption that transformative AI will arrive 10-40 years from now, with a wide range for error in either direction. So, this is not actually saying much. Anything that far out may well also just end up not happening, and it’s too vague an assumption to usefully operate on.
nickpeterson 3y ago
I’m not familiar with asterisk, anyone here a subscriber? Are the print editions nice?
- adamisom 3y ago
  I subscribe, print is gorgeous. It’s a new mag but right up my alley.
Animats 3y ago
Automated laundry folding is working just fine at industrial scale.[1][2] Chicago Dryer, a century old company in Chicago in a very boring business, is doing quite well at automated folding. Their approach is about 20% AI, 80% clever machinery, and it gets the job done at scale. Damp laundry fresh from the washer goes in, and folded stacks come out. There's a vision system with some AI finding corners for a robotic grabber. Another vision system decides if items are worn or damaged and should be sent to the reject bin. [1] https://www.chidry.com/products/genesis https://www.chidry.com/products/genesis [2] https://www.youtube.com/watch?v=7bd900ehE9M https://www.youtube.com/watch?v=7bd900ehE9M
- newaccount74 3y ago
  I think that's a case of moving goalposts. When I hear "folding laundry", I think "taking a load of laundry from the washing machine, including pants, shirts, underwear, bras, socks, sheets, towels, pillowcases with socks inside them and cycling pants, separating them, folding them, and putting them in stacks for each family member" The automated solution in the video seems to work for loads of identical white towels. Don't get me wrong, the automated laundry machines are impressive, but I don't think they accomplish what people thought of when they asked the question.
  - Animats 3y ago
    There was Foldimate, a startup which got publicity in 2019. They went bankrupt.[1] Willow Garage demonstrated folding with their mobile robot. They shut down when the funding ran out. There was Laundroid, priced around US$ 15000, bankrupt 2019.[2] Chicago Dryer's machines can fold shirts and pants. This is mostly used for commercial workwear, such as hospital uniforms. They have all the steps in the process automated. If you buy all the options, you can start with a bin of damp laundry direct from an extractor and get folded items out. (Other companies make washing systems with automated load and unload to feed the "clean side" of the process.) There are vision systems, machine learning, and robotic grippers inside those big machines. So home-sized is possible, but not cost-effective. Boring old Chicago Dryer is cost-effective compared to low-wage labor, and they have real products that sell. [1] https://www.facebook.com/FoldMate/videos/who-likes-folding-laundry/371599830208213/ https://www.facebook.com/FoldMate/videos/who-likes-folding-l... [2] https://www.youtube.com/watch?v=rl7iNRdTncQ https://www.youtube.com/watch?v=rl7iNRdTncQ
raajg 3y ago
Came across the magazine for the first time and really liking the presentation, typeface and feature like saving highlights. Clean interface too!
lvncelot 3y ago
What an insightful article. I vaguely remembered the questionnaire mentioned in the beginning paragraph, and how there were some inconsistencies. Glad I read the rest of the article before jumping in here to comment, because the author goes into detail about exactly those issues, where they might stem from, and what that says about the prediction domain. It's really well written - I haven't heard of asteriskmag before, glad I did.
klik99 3y ago
The 2022 survey is interesting - he marks "Write python code to implement algos like quicksort" and "Answer easily googleable factual but open-ended questions better than an expert" as "already happened" and the experts estimate 3 and 5 years in the future - this points to his expectations for what "happened" different than the experts. Like for the former "implement quicksort" they might be answering "write quicksort given an understanding of python and an understanding of the problem" rather than what happened which was "implement quicksort by reconstructing text from corpus". And on the latter - I'm not sure that we've achieved the "answer easily googleable factual questions better than an expert", unless by better he means answer it with more confidence than an expert (sarcasm). LLMs will flat out make up facts for factual questions and answer with complete confidence and there is no easy way to extract structured data out of those answers to confirm them. I think the idea of the marking these items as "these happened" is very handwavey and removes some of the interesting things about the survey. The most interesting thing in this article is where he compares the two articles and tracks deltas between the time estimates - I think that's a strong indicator of what we're finding is easier than we though in AI vs what is proving to be a bigger problem than we though in AI.
GuB-42 3y ago
"Provide phone banking service as well as a human". We got to that point, but mostly because of how much human provided service has degraded. I don't blame the humans in question, but how much they are trained to behave like robots, and the little they are trusted and allowed to do.

65 points by ctoth 3y ago

This is one example where I wish the HN title better represented the content. "Nobody predicted the AI revolution, except for the 352 experts who were asked to predict it."

dang 3y ago
I see your point, but sometimes it's good for HN readers to work a little (just a little!), and I feel like this is one of those cases. Not everything should be explicitly spelled out - especially when the title isn't obviously baity and the article is substantive. https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sort=byDate&type=comment&query=%22work%20a%20little%22%20by:dang https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...
- pedalpete 3y ago
  With the link to Algolia, I feel like "work a little" is a tagline you are trying to promote. But look at it this way. Each title on HN is an advertisement to learn about an interesting...something. Does the title interest you enough to read the article? Because if it doesn't accomplish that task, it doesn't get clicked on, or potentially not clicked on by the correct people.
  - dang 3y ago
    It is! But I have dozens if not hundreds of similar taglines - and a different algolia link for most of them... There are titles that give you a pre-digested précis of the article, and then there are titles that intrigue. HN needs both kinds.
andromaton 3y ago
Also, copying the first few lines: "Through a Glass Darkly Scott Alexander Nobody predicted the AI revolution except" For the future: @dang, is that ok?

EvanKelly 3y ago

What would it mean for an AI to beat the best humans in a 5K race? Obviously robots can do that, is there some definition of "humanoid AI robot" which exists for such a task?

kbenson 3y ago
I think to have meaning the AI would have to work both as generally and usefully as a human, and fit entirely within a human size profile (not offloading compute remotely). What makes humans competing against each other even remotely worth paying attention to is the constraints, which is that we're all autonomous, we all have similar size, we all can function to a similar degree. Plenty of animals can beat humans at all sorts of things, but they can't do so while also standing in as a human, so the comparisons aren't very interesting. Building a robot that has a human profile and can run and beat humans at a 5k race also isn't very interesting (at this point), because fine, you created a running robot, but that robot's not going to do it's own taxes at the end of the year, so in the sense of AI, who cares.
- mlyle 3y ago
  > beat humans at a 5k race also isn't very interesting (at this point), because fine, you created a running robot, but that robot's not going to do it's own taxes at the end of the year, so in the sense of AI, who cares. It depends exactly on what we're saying. So far we have machines that can navigate language well, but aren't good at navigating real world environments. If we're talking about a road 5k race, with myriad ways that courses are marked and many, many distracting, this is at least an interesting problem (perhaps as difficult as self driving vehicles).
  - kbenson 3y ago
    Being able to navigate the course is an interesting problem. I'm not sure beating a human at it is, unless we change the problem to be accomplishing something useful (lugging a certain amount of weight up a cliff face for rescue operations, for example), or make the contestant AI sufficiently human like. A 5k race is about competition, not about doing useful work. For AI or a robot to compete and win and have it mean anything means it needs to be similar enough to the other contestants to make that competition matter, otherwise I could slap a picture of my face on an RC car with enough batteries and "win". We all realize intuitively that a "win" such as that tells us nothing useful, so would ignore it even if it somehow was allowed. AI is a bit less intuitive to many at this point, so it's not always as obvious.

layer8 3y ago

> We should, as a civilization, operate under the assumption that transformative AI will arrive 10-40 years from now, with a wide range for error in either direction. So, this is not actually saying much. Anything that far out may well also just end up not happening, and it’s too vague an assumption to usefully operate on.

nickpeterson 3y ago

I’m not familiar with asterisk, anyone here a subscriber? Are the print editions nice?

adamisom 3y ago
I subscribe, print is gorgeous. It’s a new mag but right up my alley.

Animats 3y ago

Automated laundry folding is working just fine at industrial scale.[1][2] Chicago Dryer, a century old company in Chicago in a very boring business, is doing quite well at automated folding. Their approach is about 20% AI, 80% clever machinery, and it gets the job done at scale. Damp laundry fresh from the washer goes in, and folded stacks come out. There's a vision system with some AI finding corners for a robotic grabber. Another vision system decides if items are worn or damaged and should be sent to the reject bin. [1] https://www.chidry.com/products/genesis https://www.chidry.com/products/genesis [2] https://www.youtube.com/watch?v=7bd900ehE9M https://www.youtube.com/watch?v=7bd900ehE9M

newaccount74 3y ago
I think that's a case of moving goalposts. When I hear "folding laundry", I think "taking a load of laundry from the washing machine, including pants, shirts, underwear, bras, socks, sheets, towels, pillowcases with socks inside them and cycling pants, separating them, folding them, and putting them in stacks for each family member" The automated solution in the video seems to work for loads of identical white towels. Don't get me wrong, the automated laundry machines are impressive, but I don't think they accomplish what people thought of when they asked the question.
- Animats 3y ago
  There was Foldimate, a startup which got publicity in 2019. They went bankrupt.[1] Willow Garage demonstrated folding with their mobile robot. They shut down when the funding ran out. There was Laundroid, priced around US$ 15000, bankrupt 2019.[2] Chicago Dryer's machines can fold shirts and pants. This is mostly used for commercial workwear, such as hospital uniforms. They have all the steps in the process automated. If you buy all the options, you can start with a bin of damp laundry direct from an extractor and get folded items out. (Other companies make washing systems with automated load and unload to feed the "clean side" of the process.) There are vision systems, machine learning, and robotic grippers inside those big machines. So home-sized is possible, but not cost-effective. Boring old Chicago Dryer is cost-effective compared to low-wage labor, and they have real products that sell. [1] https://www.facebook.com/FoldMate/videos/who-likes-folding-laundry/371599830208213/ https://www.facebook.com/FoldMate/videos/who-likes-folding-l... [2] https://www.youtube.com/watch?v=rl7iNRdTncQ https://www.youtube.com/watch?v=rl7iNRdTncQ

raajg 3y ago

Came across the magazine for the first time and really liking the presentation, typeface and feature like saving highlights. Clean interface too!

lvncelot 3y ago

What an insightful article. I vaguely remembered the questionnaire mentioned in the beginning paragraph, and how there were some inconsistencies. Glad I read the rest of the article before jumping in here to comment, because the author goes into detail about exactly those issues, where they might stem from, and what that says about the prediction domain. It's really well written - I haven't heard of asteriskmag before, glad I did.

klik99 3y ago

The 2022 survey is interesting - he marks "Write python code to implement algos like quicksort" and "Answer easily googleable factual but open-ended questions better than an expert" as "already happened" and the experts estimate 3 and 5 years in the future - this points to his expectations for what "happened" different than the experts. Like for the former "implement quicksort" they might be answering "write quicksort given an understanding of python and an understanding of the problem" rather than what happened which was "implement quicksort by reconstructing text from corpus". And on the latter - I'm not sure that we've achieved the "answer easily googleable factual questions better than an expert", unless by better he means answer it with more confidence than an expert (sarcasm). LLMs will flat out make up facts for factual questions and answer with complete confidence and there is no easy way to extract structured data out of those answers to confirm them. I think the idea of the marking these items as "these happened" is very handwavey and removes some of the interesting things about the survey. The most interesting thing in this article is where he compares the two articles and tracks deltas between the time estimates - I think that's a strong indicator of what we're finding is easier than we though in AI vs what is proving to be a bigger problem than we though in AI.

GuB-42 3y ago

"Provide phone banking service as well as a human". We got to that point, but mostly because of how much human provided service has degraded. I don't blame the humans in question, but how much they are trained to behave like robots, and the little they are trusted and allowed to do.