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NVIDIA Hopes To Sell More Chips By Bringing AI Programming To the Masses
jfruh writes: Artificial intelligence typically requires heavy computing power, which can only help manufacturers of specialized chip manufacturers like NVIDIA. That's why the company is pushing its Digits software, which helps users design and experiment with neural networks. Version 2 of digits moves out of the command line and comes with a GUI interface in an attempt to move interest beyond the current academic market; it also makes programming for multichip configurations possible.
Crunch all you want, we'll make more. Sounds artificially intelligent.
I am not sure if their strategy will work. Training a neural net requires massive compute resources, usually in the form of GPUs. But once the NN is trained, it doesn't require much computing to use it. For instance, a Go playing NN took 5 days to train, running on high end GPUs, but once trained, could consistently beat Gnu Go (which can consistently beat me) while using far less computing time.
From TFA there was no pic of the UI, nor any mention of tech specs aside from a lot of nebulous details. From nVidia's website ...
* https://developer.nvidia.com/d...
They are really trying to get people on board about how much better / faster their GPU solutions are ...
* http://www.nvidia.com/object/m...
The problem is that there are lot of "niche" use cases. If your problem domain maps to the GPU then yeah, mjaor speedup. If not, well, then you're SOL running on "slow" CPUs.
NV open sourced CUDA in 2011, but I don't believe there are any other implementations out there. The rest of the world continues adopting OpenCL and now the whole Khronos supergroup is super hyper for Vulkan (NV even giving a solid thumbs up), with Apple and NV being the two rogue vendors pushing proprietary wares (Metal and CUDA). Even with NVidia doing really *really* well in the GPGPU market, even with a really great dev env, the extreme proprietary-ness of CUDA makes it really hard to sell to the alpha techies.
Cuda has a lot of traction in academic and applied fields, but the technical industry doesn't take it seriously, isn't comfortable saddling themselves to a one-trick-horse offering from NVidia. This ridiculously powerful box, and it's cool software with cool visibility into a neat problem, but it's really a pipeline play, to get you into NVidia's world. For some, going full in on NVidia is ok, but I don't think it's unlike going full in as a MS Developer or iOS developer- you're picking up, putting on the blinders, and all you'll be able to do is sprint towards a fixed, not too far away point.