4 ms·

Bumped into this company some years ago that use light to perform 'random projection', which can be used to approximate matrix multiplication. Which is used a l

by ArnoVW 5y ago

Bumped into this company some years ago that use light to perform 'random projection', which can be used to approximate matrix multiplication. Which is used a lot in the AI space (reduction of dimension etc) How? They do the projection quite literally: with DLP projectors that project on CCD through a 'dirty' medium, for randomness. At current DLP resolutions and refresh rates, every pixel being one bit, I'll let you imagine how much data you can push through, using only 30W. The whole thing is sold as an appliance, a sort of co-processor that can do just one operation (but a really complex one) They released their first commercial product a couple of months ago, hope it works out for them as the idea sounds pretty amazing. edit: found their website https://lighton.ai/ https://lighton.ai/

mattbit 5y ago
Yeah, LightOn has been doing this for years already, it's kind of strange that there was no mention of them in the article. I know them because their offices are close to the research center where I work (in Paris, France). If I'm not wrong they were planning to offer their optical processor as a cloud service too.
- orange3xchicken 5y ago
  fyi the founder Igor Carron runs a pretty nice academic blog on compressive sensing (a bit less academic in recent months) https://nuit-blanche.blogspot.com/ https://nuit-blanche.blogspot.com/ Also hosts the advanced matrix factorization jungle website which is a nice browse if you're interested in mf techniques. https://sites.google.com/site/igorcarron2/matrixfactorizations https://sites.google.com/site/igorcarron2/matrixfactorizatio...
  - justicezyx 5y ago
    You might be well informed in compressive sensing: What's the status of the compressive sensing research, and commercialization if there is any?
  - andyxor 5y ago
    his presentation on LightOn is pretty interesting https://www.youtube.com/watch?v=0QtY4_UJF0w&ab_channel=LightOn https://www.youtube.com/watch?v=0QtY4_UJF0w&ab_channel=Light...
  - dcl 5y ago
    I remember that blog from when I was studying penalty/regularization methods over a decade ago. Was a great source of interesting papers and ideas.
- ineedasername 5y ago
  It looks like their rack mounted 2U sized device does up to 1900 dense matrix mps. Would you happen to know how that would compare to a typical (I guess mid-range) server for AI? I'd like to get a sense of the magnitude of improvement offered.

by ArnoVW 5y ago

mattbit 5y ago

Yeah, LightOn has been doing this for years already, it's kind of strange that there was no mention of them in the article. I know them because their offices are close to the research center where I work (in Paris, France). If I'm not wrong they were planning to offer their optical processor as a cloud service too.

orange3xchicken 5y ago
fyi the founder Igor Carron runs a pretty nice academic blog on compressive sensing (a bit less academic in recent months) https://nuit-blanche.blogspot.com/ https://nuit-blanche.blogspot.com/ Also hosts the advanced matrix factorization jungle website which is a nice browse if you're interested in mf techniques. https://sites.google.com/site/igorcarron2/matrixfactorizations https://sites.google.com/site/igorcarron2/matrixfactorizatio...
- justicezyx 5y ago
  You might be well informed in compressive sensing: What's the status of the compressive sensing research, and commercialization if there is any?
- andyxor 5y ago
  his presentation on LightOn is pretty interesting https://www.youtube.com/watch?v=0QtY4_UJF0w&ab_channel=LightOn https://www.youtube.com/watch?v=0QtY4_UJF0w&ab_channel=Light...
- dcl 5y ago
  I remember that blog from when I was studying penalty/regularization methods over a decade ago. Was a great source of interesting papers and ideas.
ineedasername 5y ago
It looks like their rack mounted 2U sized device does up to 1900 dense matrix mps. Would you happen to know how that would compare to a typical (I guess mid-range) server for AI? I'd like to get a sense of the magnitude of improvement offered.