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Blimey, this is really stretching the definition of AI, surely? It’s a piece of glass that has been designed by a lot of trial and error to perform one specific

Blimey, this is really stretching the definition of AI, surely? It’s a piece of glass that has been designed by a lot of trial and error to perform one specific task. It sounds like humans were analysing the fitness and making the modifications. I wouldn’t call it “unpowered AI” any more than I’d call a coin sorter that.

Grustaf 7y ago
I agree, but then again how is this different from using pretty much the same mechanics but in software form? Most “AI” that is used in consumer apps uses pre-made models, that are then applied to input data. This seems very similar.
- sp332 7y ago
  It's not different, that's the point. We already know that these "mechanics" are very powerful, and now this paper shows that we can get results at nearly the speed of light.
  - kolinko 7y ago
    Speed of light, and using analog form of computation. This single piece of glass can do as many visual recognitions as physics allows, using no energy (light aside).
the_seraphim 7y ago
yeah... the glass "learned" if the definition of learned can be that it was melted down and reformed with new parts in new places - its the equivalent of sticking a brain in a blender and whizzing it repeatedly until it lands in a configuration that can play chess... its not AI
atoav 7y ago
Because it uses glas as a substrate and light as a information carrier? Most of what we call “AI” today also uses prelearned weights for their neural networks and in many use cases these weights are not touched after deployment. I don’t see why a neural network encoded in glas should not be an AI while the same neural network on a computer is one — either you have to call both AI or neither.
- silveroriole 7y ago
  At least the neural networks were at some point self-assessing and self-modifying, and plausibly could be said to “learn” something. Here it seems more plausible to say that the humans learned what structure to produce than that the glass did. But you’re right, I think many “AIs” shouldn’t really be named that either!
  - prashnts 7y ago
    I skimmed the paper linked there. They did use a digital model for glass-impurity substrate, to adjust the location of the impurities. This doesn’t sound much different than training with activation weight propagation — except, here one can literally see those weights. I don’t see why it wouldn’t fit usual definition of a neural network.
    - Voloskaya 7y ago
      It may have been designed using AI, but it's not AI. The impurities are not the weights, they are the output of the design software. It is the design software that has been learning something, not the pane of glass. It is like using AI to design, say, the most aerodynamic plane. Only here they used an AI to design something that performs a task that we traditionally use as a benchmark for AI models. But this piece of glass, just like the plane mentionned above, is not learning anything and it's not an AI.
      - kolinko 7y ago
        Out of curiosity - did you ever work with neural networks? (as in - the algorithms, not the high level abstractions?)
        Voloskaya 7y ago
        Yes, pretty much every day.
      - prashnts 7y ago
de_watcher 7y ago
How it's different from an FPGA that has some classifier encoded? It's just all "fiber optic" instead of electricity.
- sp332 7y ago
  This is faster and it doesn't use electricity.
darepublic 7y ago
Coin sorter analogy seems apt
dekhn 7y ago
I should mention, people have been using lenses to approximate FFTs for 150 years.
ant6n 7y ago
> The AI works by taking advantage of small bubbles deliberately incorporated into the glass, as well as embedded impurities such as graphene. As the light waves reflected off the handwritten numbers pass through the glass AI, they are bent in specific ways by the bubbles and impurities. This bending process focuses the light onto one of ten specific spots on the other side of the glass, depending on the number presented. (...) > Training the AI involved presenting the glass with different images of handwritten numbers. If the light did not pass through the glass to focus on the correct spot, the team adjusted the size and locations of impurities slightly. After thousands of iterations, the glass “learned” to bend the light to the right place. (...) This sounds pretty much like they're training a neural network.
sp332 7y ago
There are two different kinds of neural networks. Large models are fed lots of data to train them. But when the training is done, the results can be closely approximated by a much smaller network. The smaller networks can be distributed more easily and even used on phones. But they are fixed, not used for training anymore. It's definitely AI - it's still recognizing a handwritten digit. But not all AI applications require further training. Sometimes you just need the end result.
tsumnia 7y ago
The issue is what is defined as "AI". From [1], some of those definitions include - Thinking Humanly - the ability to problem solve, introspection, and learning (Cognitive Science) - Thinking Rationally - the ability to perceive, reason, and act (Logic) - Acting Humanly - simply do things that (at the moment) humans do better (Turing Machines) - Acting Rationally - the design of intelligent agents (the focus of the textbook, Betty's Brain[2]) Yes, they all vaguely sound the same, but the point is, if you took the glass and had to select which definition it marks off, which would it be? My point is what about this glass makes it "intelligent"? The end of the article starts to talk about a combination of AI-glasses could form some sort of efficient image recognition process. Since we still don't have a clear definition of what intelligence is, is it simply a combination of tiny little perceptrons (from neural networks) that have specific differentiation tasks? [1] http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/ [2] https://wp0.vanderbilt.edu/oele/bettys-brain/ https://wp0.vanderbilt.edu/oele/bettys-brain/
bufferoverflow 7y ago
> It’s a piece of glass that has been designed by a lot of trial and error to perform one specific task And you're a peace of matter that has been designed by a lot of trial and error to perform one specific task: to propagate your species.
- airstrike 7y ago
  Except we do it intelligently and the glass doesn't. The parent is not saying the glass is useless, just that it isn't intelligent
  - shitgoose 7y ago
    "glass isn't intelligent" and silicon is?
    - shitgoose 7y ago
      hint - material is not relevant, what it does is relevant.
Zenst 7y ago
It hardly passed the litmus paper test for what we class as AI. Though that said, by their definition, litmus paper is equally AI as it takes an input and produces an output. Just seems a bit like being told you can buy a flying car, only to find out that it's a short flight time, not flying very high and depends upon approaching a ramp at speed.
erikpukinskis 7y ago
I believe the definitions of “intelligent” and “adaptive” are intertwined. I’m not sure what the distinction is between those two words, but I know they are connected. Because this system can’t adapt, I agree it is probably not meaningfully “intelligent”.
jonplackett 7y ago
Haha. You just basically described machine learning to a tee
- klyrs 7y ago
  This was my response to the article too. 'This isn't AI... uhhh... oh but it is machine learning... ugh'
somebodythere 7y ago
If you take "AI" to be a marketing buzzword for machine learning, it is AI in the sense that is a passive inference technology.
wodenokoto 7y ago
This is a feed-forward neural network implemented in glass.
3327 7y ago
Agree, I would say its more like a logic-tree or more like an optical circuit. Even academics are choosing hot names for papers, basically in CS today, if your paper does not have AI in it, good look getting attention. source, me: Stanford CS grad.
xaedes 7y ago
What people call “AI” is actually a long historical process of crystallizing collective behavior, personal data, and individual labor into privatized algorithms that are used for the automation of complex tasks: from driving to translation, from object recognition to music composition. Just as much as the machines of the industrial age grew out of experimentation, know-how, and the labor of skilled workers, engineers, and craftsmen, the statistical models of AI grow out of the data produced by collective intelligence. https://www.e-flux.com/journal/101/273221/three-thousand-years-of-algorithmic-rituals-the-emergence-of-ai-from-the-computation-of-space/ https://www.e-flux.com/journal/101/273221/three-thousand-yea... https://news.ycombinator.com/item?id=20249150 https://news.ycombinator.com/item?id=20249150

Grustaf 7y ago

I agree, but then again how is this different from using pretty much the same mechanics but in software form? Most “AI” that is used in consumer apps uses pre-made models, that are then applied to input data. This seems very similar.

sp332 7y ago
It's not different, that's the point. We already know that these "mechanics" are very powerful, and now this paper shows that we can get results at nearly the speed of light.
- kolinko 7y ago
  Speed of light, and using analog form of computation. This single piece of glass can do as many visual recognitions as physics allows, using no energy (light aside).

the_seraphim 7y ago

yeah... the glass "learned" if the definition of learned can be that it was melted down and reformed with new parts in new places - its the equivalent of sticking a brain in a blender and whizzing it repeatedly until it lands in a configuration that can play chess... its not AI

atoav 7y ago

Because it uses glas as a substrate and light as a information carrier? Most of what we call “AI” today also uses prelearned weights for their neural networks and in many use cases these weights are not touched after deployment. I don’t see why a neural network encoded in glas should not be an AI while the same neural network on a computer is one — either you have to call both AI or neither.

silveroriole 7y ago
At least the neural networks were at some point self-assessing and self-modifying, and plausibly could be said to “learn” something. Here it seems more plausible to say that the humans learned what structure to produce than that the glass did. But you’re right, I think many “AIs” shouldn’t really be named that either!
- prashnts 7y ago
  I skimmed the paper linked there. They did use a digital model for glass-impurity substrate, to adjust the location of the impurities. This doesn’t sound much different than training with activation weight propagation — except, here one can literally see those weights. I don’t see why it wouldn’t fit usual definition of a neural network.
  - Voloskaya 7y ago
    It may have been designed using AI, but it's not AI. The impurities are not the weights, they are the output of the design software. It is the design software that has been learning something, not the pane of glass. It is like using AI to design, say, the most aerodynamic plane. Only here they used an AI to design something that performs a task that we traditionally use as a benchmark for AI models. But this piece of glass, just like the plane mentionned above, is not learning anything and it's not an AI.
    - kolinko 7y ago
      Out of curiosity - did you ever work with neural networks? (as in - the algorithms, not the high level abstractions?)
      - Voloskaya 7y ago
        Yes, pretty much every day.
    - prashnts 7y ago

de_watcher 7y ago

How it's different from an FPGA that has some classifier encoded? It's just all "fiber optic" instead of electricity.

sp332 7y ago
This is faster and it doesn't use electricity.

darepublic 7y ago

Coin sorter analogy seems apt

dekhn 7y ago

I should mention, people have been using lenses to approximate FFTs for 150 years.

ant6n 7y ago

> The AI works by taking advantage of small bubbles deliberately incorporated into the glass, as well as embedded impurities such as graphene. As the light waves reflected off the handwritten numbers pass through the glass AI, they are bent in specific ways by the bubbles and impurities. This bending process focuses the light onto one of ten specific spots on the other side of the glass, depending on the number presented. (...) > Training the AI involved presenting the glass with different images of handwritten numbers. If the light did not pass through the glass to focus on the correct spot, the team adjusted the size and locations of impurities slightly. After thousands of iterations, the glass “learned” to bend the light to the right place. (...) This sounds pretty much like they're training a neural network.

sp332 7y ago

There are two different kinds of neural networks. Large models are fed lots of data to train them. But when the training is done, the results can be closely approximated by a much smaller network. The smaller networks can be distributed more easily and even used on phones. But they are fixed, not used for training anymore. It's definitely AI - it's still recognizing a handwritten digit. But not all AI applications require further training. Sometimes you just need the end result.

tsumnia 7y ago

The issue is what is defined as "AI". From [1], some of those definitions include - Thinking Humanly - the ability to problem solve, introspection, and learning (Cognitive Science) - Thinking Rationally - the ability to perceive, reason, and act (Logic) - Acting Humanly - simply do things that (at the moment) humans do better (Turing Machines) - Acting Rationally - the design of intelligent agents (the focus of the textbook, Betty's Brain[2]) Yes, they all vaguely sound the same, but the point is, if you took the glass and had to select which definition it marks off, which would it be? My point is what about this glass makes it "intelligent"? The end of the article starts to talk about a combination of AI-glasses could form some sort of efficient image recognition process. Since we still don't have a clear definition of what intelligence is, is it simply a combination of tiny little perceptrons (from neural networks) that have specific differentiation tasks? [1] http://aima.cs.berkeley.edu/ http://aima.cs.berkeley.edu/ [2] https://wp0.vanderbilt.edu/oele/bettys-brain/ https://wp0.vanderbilt.edu/oele/bettys-brain/

bufferoverflow 7y ago

> It’s a piece of glass that has been designed by a lot of trial and error to perform one specific task And you're a peace of matter that has been designed by a lot of trial and error to perform one specific task: to propagate your species.

airstrike 7y ago
Except we do it intelligently and the glass doesn't. The parent is not saying the glass is useless, just that it isn't intelligent
- shitgoose 7y ago
  "glass isn't intelligent" and silicon is?
  - shitgoose 7y ago
    hint - material is not relevant, what it does is relevant.

Zenst 7y ago

It hardly passed the litmus paper test for what we class as AI. Though that said, by their definition, litmus paper is equally AI as it takes an input and produces an output. Just seems a bit like being told you can buy a flying car, only to find out that it's a short flight time, not flying very high and depends upon approaching a ramp at speed.

erikpukinskis 7y ago

I believe the definitions of “intelligent” and “adaptive” are intertwined. I’m not sure what the distinction is between those two words, but I know they are connected. Because this system can’t adapt, I agree it is probably not meaningfully “intelligent”.

jonplackett 7y ago

Haha. You just basically described machine learning to a tee

klyrs 7y ago
This was my response to the article too. 'This isn't AI... uhhh... oh but it is machine learning... ugh'

somebodythere 7y ago

If you take "AI" to be a marketing buzzword for machine learning, it is AI in the sense that is a passive inference technology.

wodenokoto 7y ago

This is a feed-forward neural network implemented in glass.

3327 7y ago

Agree, I would say its more like a logic-tree or more like an optical circuit. Even academics are choosing hot names for papers, basically in CS today, if your paper does not have AI in it, good look getting attention. source, me: Stanford CS grad.

xaedes 7y ago

What people call “AI” is actually a long historical process of crystallizing collective behavior, personal data, and individual labor into privatized algorithms that are used for the automation of complex tasks: from driving to translation, from object recognition to music composition. Just as much as the machines of the industrial age grew out of experimentation, know-how, and the labor of skilled workers, engineers, and craftsmen, the statistical models of AI grow out of the data produced by collective intelligence. https://www.e-flux.com/journal/101/273221/three-thousand-years-of-algorithmic-rituals-the-emergence-of-ai-from-the-computation-of-space/ https://www.e-flux.com/journal/101/273221/three-thousand-yea... https://news.ycombinator.com/item?id=20249150 https://news.ycombinator.com/item?id=20249150