NVidia actually care about research, researchers and the scientific computing market.
Next time someone complains about the lack of OpenCL support, again, in another framework remember how much work NVidia puts into supporting people who use their cards for scientific computing, and how they listen to them.
Microsoft also carefully listened to developers while building DirectX and by versions 8 and especially 9, it really showed. But only Windows benefited from this. Having the control of important GPU tech so strongly centered about a single company is never a good idea, it sets up a conflict of interest.
Something like OpenCL does not face the same conflict nVidia would if porting core APIs across a wide set of competing technologies. With CUDA, nVidia prioritizes themselves above AMD, intel, FPGAs and whatever parallel compute technology the future holds.
But the truth is that without the hardware vendors putting significant resources into OpenCL it just isn't competitive and won't be until that happens.
The truth is that most of the work in Deep Learning is developing new NN architectures and other algorithmic optimisations. If you are working in the field there is no reason to put up with second class support from non NVidia vendors - just build in TensorFlow, Torch or a couple of other frameworks and wait for the day (one day, we are promised!) when OpenCL is competitive. Then the framework backends get ported, your code keeps running the same, and it can run on all those other architectures.
Everyone has been waiting for that day since One Weird Trick[1]. There isn't really anything to indicate it is getting closer, and AMD's dismissal of the NVidia "doing something in the car industry"[2] doesn't give me a lot of confidence.
Anyway, I hope I'm wrong. Maybe Intel will step-up.
While ATI was always about gaming, gaming, gaming, NVidia always worried about the Pro market (Quadro, Linux support, even with proprietary modules, etc) and now with Deep Learning
And now they can sell their deep learning processor for embedded applications (equals $$$)
There are some numbers for 2015 at [1]. In the Enterprise, HPC and Auto markets they had a bit more than $1B in revenue. I believe the Auto market includes some Tegra numbers, but that is "only" $180M.
Gaming is a little more than $2B, and "OEM & IP" is $1B.
NVidia actually care about research, researchers and the scientific computing market.
Next time someone complains about the lack of OpenCL support, again, in another framework remember how much work NVidia puts into supporting people who use their cards for scientific computing, and how they listen to them.