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I think the most commercially successful application of computer vision has been quality-control devices (citation needed). Agriculture is very interested in CV

by wyc 10y ago

I think the most commercially successful application of computer vision has been quality-control devices (citation needed). Agriculture is very interested in CV for a return-optimization technique known as precision farming. Manufacturers pay for inspection of production throughout the pipeline. To predict where a mass-market CV could be successful, I think we should look for industries with similar problems but cannot currently afford a bespoke custom modeling solution.

madenine 10y ago
I feel like the places where CV always proves most useful are places where either we need more eyes than would be financially viable, or we need eyes in places its hard/unsafe/expensive to have them. The tipping point on training+pay for a human vs an ML/CV system for a lot of tasks is coming down. I saw a Microsoft spotlight last fall on a company that's using drones + CV to inspect power infrastructure in Scandinavia. As much as the tech to do that has cost, its probably cheaper than sending out helicopters with specialists all the time to check power line towers for wear/damage.
- nostrademons 10y ago
  Or we need eyes that can drive a physical response faster & more accurately than a human can react. This is the whole robotics/drone/hardware market. Right now, most of these efforts work at the same speed humans work (probably because we still need to monitor them to make sure they're doing the right thing). But imagine self-driving cars with no traffic lights, because the cars can react & communicate fast enough to avoid a collision without any macro-scale signaling. Manufacturing processes where molten metal is shaped directly into whatever shape desired, where computers do real-time calculations of the effect of gravity & cooling rate on the position of the material. Airliners that never land and can take on passengers anywhere, because passengers ascend in a personal drone that mates with the mothership under computer control. Unfortunately CVaaS isn't really suitable for this, because the network delays transmitting the data to a datacenter will outweigh any speed benefits of computerizing it. But I could see a big market for services that let you train a model in the cloud at high-speed, and then download the computed model for execution on a local GPU or TPU.
  - sharun 10y ago
    For human level vision and speech (and even search) long term we might not need computational clouds and data centers. We don't see them in nature. The models/indexes will likely just come prepackaged on device.
    - nojvek 10y ago
      This is only a matter of time. The imagenet model can already run on my iPhone on the gpu with BNNS. Not real-time but going there very soon. Once you have real time local inferencre on your mobile phone. Boom!
visarga 10y ago
CV will be the technology that kills what jobs we still have left: in agriculture (picking fruit, weeding), in logistics (picking items from shelves), in custodial work (cleaning bots), security, driving, reading MRIs and x-rays - practically all the jobs that depended on vision and could only be done by people in the last 60 years are going to be automated. When CV is fully deployed, the world will be totally different. I'm pretty excited about precision agriculture, but for plant-life on earth it will mean that now really there will grow nothing outside the system. Bots are going to monitor all plant life. It might be plant-utopia for some species, with timely water and nutrient dispensing, but for other species it might mean being automatically killed by agrobots.
- ComodoHacker 10y ago
  > When CV is fully deployed, the world will be totally different. It's really scary to think about the long-term consequences of this. You know what evolution does to features not required for survival anymore.

by wyc 10y ago

madenine 10y ago

I feel like the places where CV always proves most useful are places where either we need more eyes than would be financially viable, or we need eyes in places its hard/unsafe/expensive to have them. The tipping point on training+pay for a human vs an ML/CV system for a lot of tasks is coming down. I saw a Microsoft spotlight last fall on a company that's using drones + CV to inspect power infrastructure in Scandinavia. As much as the tech to do that has cost, its probably cheaper than sending out helicopters with specialists all the time to check power line towers for wear/damage.

nostrademons 10y ago
Or we need eyes that can drive a physical response faster & more accurately than a human can react. This is the whole robotics/drone/hardware market. Right now, most of these efforts work at the same speed humans work (probably because we still need to monitor them to make sure they're doing the right thing). But imagine self-driving cars with no traffic lights, because the cars can react & communicate fast enough to avoid a collision without any macro-scale signaling. Manufacturing processes where molten metal is shaped directly into whatever shape desired, where computers do real-time calculations of the effect of gravity & cooling rate on the position of the material. Airliners that never land and can take on passengers anywhere, because passengers ascend in a personal drone that mates with the mothership under computer control. Unfortunately CVaaS isn't really suitable for this, because the network delays transmitting the data to a datacenter will outweigh any speed benefits of computerizing it. But I could see a big market for services that let you train a model in the cloud at high-speed, and then download the computed model for execution on a local GPU or TPU.
- sharun 10y ago
  For human level vision and speech (and even search) long term we might not need computational clouds and data centers. We don't see them in nature. The models/indexes will likely just come prepackaged on device.
  - nojvek 10y ago
    This is only a matter of time. The imagenet model can already run on my iPhone on the gpu with BNNS. Not real-time but going there very soon. Once you have real time local inferencre on your mobile phone. Boom!

visarga 10y ago

CV will be the technology that kills what jobs we still have left: in agriculture (picking fruit, weeding), in logistics (picking items from shelves), in custodial work (cleaning bots), security, driving, reading MRIs and x-rays - practically all the jobs that depended on vision and could only be done by people in the last 60 years are going to be automated. When CV is fully deployed, the world will be totally different. I'm pretty excited about precision agriculture, but for plant-life on earth it will mean that now really there will grow nothing outside the system. Bots are going to monitor all plant life. It might be plant-utopia for some species, with timely water and nutrient dispensing, but for other species it might mean being automatically killed by agrobots.

ComodoHacker 10y ago
> When CV is fully deployed, the world will be totally different. It's really scary to think about the long-term consequences of this. You know what evolution does to features not required for survival anymore.