3 ms·

"5-by-6 pixel array" These are not exactly high res images.

etskinner 4y ago
Once a proof-of-concept exists, scaling it up is conceivable. Computers used to have kilobytes of RAM, now some have terabytes. Digital cameras used to have sub-megapixel resolution, now some are measured in gigapixels.
- mensetmanusman 4y ago
  “1 pixel should be enough for everyone”
  - touisteur 4y ago
    It could! https://opg.optica.org/oe/fulltext.cfm?uri=oe-28-19-28190&id=437999 https://opg.optica.org/oe/fulltext.cfm?uri=oe-28-19-28190&id...
  - mhh__ 4y ago
    Most zoom calls are fine with 0 thank you very much
- daniel-cussen 4y ago
  Mmm...but scaling up is not the same in photonics as it is in digital. Everyone thinks of scaling in terms of digital, like Alan Turing, von Neumann, and later Moore talked about, if you have an amplifier you can amplify it with another amplifier, so as long as it's totally digital the signals can be manipulated at arbitrarily small scales. Not true for analog or photons or quantum, there's weird caveats and they're not well researched, this scaling works only for digital.
  - haswell 4y ago
    Sure, our existing understanding and models for scale may not directly apply. That doesn’t limit the creation of new models and new understanding. Just because scaling might be different doesn’t mean it’s impossible. Our existing models did not exist at some point in the past.
  - hndamien 4y ago
    You can make digital optical logic gates - https://www.youtube.com/watch?v=pS1zAAD1nXI https://www.youtube.com/watch?v=pS1zAAD1nXI
wgd 4y ago
Equally important: "nine neurons". This is not a deep circuit. When we say that a CPU is running at some frequency that's essentially the speed at which a signal propagates through all the gates of its slowest pipeline stage, and the individual gates have a transition frequency an order of magnitude higher. So if a CPU is running at 4GHz, it completes a clock cycle in 0.25ns (250ps), but that means that individual transistors must have latencies <=0.025ns (25ps). If you built a tiny little 9-neuron single-layer network out of those transistors then the network's latency would be around the single-gate latency and it would appear to be 20x better than this photonic setup, and even if those 9 neurons were laid out sequentially it would outperform this photonic chip by 2x. Now granted, that's comparing the performance of a mature IC process using equipment that cost billions of dollars to set up, to something that was built in a university lab on a substantially smaller budget, so direct performance comparisons aren't exactly fair in that sense. But it's also misleading to take a direct hardware implementation of an itty bitty neural network and handwave away the very real issues with scaling such an approach.
- causi 4y ago
  Yes, this is seriously blurring the line between image recognition and a bandpass filter. There doesn't seem to be anything in the way of actual computation going on until the step where the results are read.

Once a proof-of-concept exists, scaling it up is conceivable. Computers used to have kilobytes of RAM, now some have terabytes. Digital cameras used to have sub-megapixel resolution, now some are measured in gigapixels.

mensetmanusman 4y ago
“1 pixel should be enough for everyone”
- touisteur 4y ago
  It could! https://opg.optica.org/oe/fulltext.cfm?uri=oe-28-19-28190&id=437999 https://opg.optica.org/oe/fulltext.cfm?uri=oe-28-19-28190&id...
- mhh__ 4y ago
  Most zoom calls are fine with 0 thank you very much
daniel-cussen 4y ago
Mmm...but scaling up is not the same in photonics as it is in digital. Everyone thinks of scaling in terms of digital, like Alan Turing, von Neumann, and later Moore talked about, if you have an amplifier you can amplify it with another amplifier, so as long as it's totally digital the signals can be manipulated at arbitrarily small scales. Not true for analog or photons or quantum, there's weird caveats and they're not well researched, this scaling works only for digital.
- haswell 4y ago
  Sure, our existing understanding and models for scale may not directly apply. That doesn’t limit the creation of new models and new understanding. Just because scaling might be different doesn’t mean it’s impossible. Our existing models did not exist at some point in the past.
- hndamien 4y ago
  You can make digital optical logic gates - https://www.youtube.com/watch?v=pS1zAAD1nXI https://www.youtube.com/watch?v=pS1zAAD1nXI

wgd 4y ago

Equally important: "nine neurons". This is not a deep circuit. When we say that a CPU is running at some frequency that's essentially the speed at which a signal propagates through all the gates of its slowest pipeline stage, and the individual gates have a transition frequency an order of magnitude higher. So if a CPU is running at 4GHz, it completes a clock cycle in 0.25ns (250ps), but that means that individual transistors must have latencies <=0.025ns (25ps). If you built a tiny little 9-neuron single-layer network out of those transistors then the network's latency would be around the single-gate latency and it would appear to be 20x better than this photonic setup, and even if those 9 neurons were laid out sequentially it would outperform this photonic chip by 2x. Now granted, that's comparing the performance of a mature IC process using equipment that cost billions of dollars to set up, to something that was built in a university lab on a substantially smaller budget, so direct performance comparisons aren't exactly fair in that sense. But it's also misleading to take a direct hardware implementation of an itty bitty neural network and handwave away the very real issues with scaling such an approach.

causi 4y ago
Yes, this is seriously blurring the line between image recognition and a bandpass filter. There doesn't seem to be anything in the way of actual computation going on until the step where the results are read.