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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.
This is Nvidia. Don't buy into this based on any promises of what is to come, no matter how reasonable they seem.
Last summer I bought a Nvidia Tegra Note 7 tablet based on promises that Android 5 (Lollipop) was coming out for it "real soon". They even stated that it was easy to port Lollipop on the Tegra Note 7 since it was basically a stock Android design with little or on deviation from the standard design. That "real soon" slipped to February of 2015 and when February 2015 came and went Nvidia became strangely mute on the subject, ignoring customers' inquiries.
A claimed Nvidia employee even posted here as an AC that it was a shame what happened to the Tegra Note 7 customers, but explained that the U.S.A. developers wanted to work on the new stuff and the Tegra Note 7 project was shipped overseas, where no one wanted to work on it either (and apparently did not).
My Tegra Note 7 tablet is the last thing that Nvidia will ever sell me. If you chose to do business with them then I may not be able to talk you out of it, but do so based on what they deliver today, not on promises of things that will never come.
I'm an American. I love this country and the freedoms that we used to have.
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.