For a few years now, NVIDIA has been offering their line of Jetson embedded system kits. Originally launched using Tegra K1 in 2014, the first Jetson was designed to be a dev kit for groups looking to build their own Tegra-based devices from scratch. Instead, what NVIDIA surprisingly found, was that groups would use the Jetson board as-is instead and build their devices around that. This unexpected market led NVIDIA to pivot a bit on what Jetson would be, resulting in the second-generation Jetson TX1, a proper embedded system board that can be used for both development purposes and production devices. This relaunched Jetson came at an interesting time for NVIDIA, which was right when their fortunes in neural networking/deep learning took off in earnest...
With the launch of their Polaris family of GPUs earlier this year, much of AMD’s public focus in this space has been on the consumer side of matters. However...39 by Ryan Smith on 12/12/2016
Ever since NVIDIA bowed out of the highly competitive (and high pressure) market for mobile ARM SoCs, there has been quite a bit of speculation over what would happen...36 by Ryan Smith on 9/28/2016
Deep learning, neural networks and image/vision processing is already a large field, however many of the applications that rely on it are still in their infancy. Automotive is the...1 by Ian Cutress on 9/27/2016
Over the last few months we have seen NVIDIA’s Pascal GPUs roll out among their consumer cards, and now the time has come for the Tesla line to get...37 by Ryan Smith on 9/13/2016
In a brief announcement as part of today’s Day 2 ketnote for IDF 2016, Intel has announced a new member of the Xeon Phi family. The new part, currently...24 by Ryan Smith on 8/17/2016
Although NVIDIA’s original plans for Tegra haven’t quite panned out as NVIDIA wanted to – at this point even tablet wins are few and far between – the company...34 by Ryan Smith on 11/10/2015
Slowly but steadily NVIDIA has been rotating in Maxwell GPUs into the company’s lineup of Tesla server cards. Though Maxwell is not well-suited towards the kind of high precision...24 by Ryan Smith on 11/10/2015