Intel could dent Nvidia's and AMD's prospects in the Artificial Intelligence (AI) space, and drag NVDA stock and AMD stock.
Shares of NVIDIA Corporation (NASDAQ:NVDA) and Advanced Micro Devices Inc (NASDAQ:AMD) had a dream run in 2016. More recently though, Nvidia's seemingly unstoppable rally was somewhat temporarily stalled, after Citron Research issued an extremely bearish call on the stock. While some of the concerns raised by Citron are probably debatable, one threat in particular warrants a deeper look. And that's the looming threat in the Artificial Intelligence (AI) space from Intel's latest salvo, its third-generation Xeon Phi processor, dubbed Knights Mill. While Intel's renewed aggression is also a threat to AMD's fledgling foray in the deep learning and AI segment, the threat is larger for Nvidia, given that a large part of the optimism around the stock is tied to the company's prospects in the burgeoning field of AI.
Intel's Xeon Phi Knights Mill - A Real Threat To Nvidia And AMD?
We all know how Intel Corporation (NASDAQ:INTC) all but owns the data centre processor market, with an estimated market share of 99%. Yet, the giant chipmaker hasn't managed to gain much ground in futuristic markets like AI, where Nvidia reigns supreme. To take on Nvidia, in August 2016, Intel announced a new server processor, its third-generation Xeon Phi processor code-named Knights Mill, aimed specifically at artificial intelligence applications.
Can CPUs take on GPUs, which are currently a clear favorite in this market? While some believe that Intel needs a GPU to take on the likes of AMD and Nvidia, the notion may not be entirely correct, going by this article on Extreme Tech:
"GPUs are good at these kinds of computing projects because the projects map well on to the hardware we use for gaming — not because there’s something magic about graphics processors that makes them uniquely and specifically suited to the tasks."
The article also explains that Intel could get the job done by building "a GPU-style compute engine without any of the IP blocks or hardware that transform it into a graphics card." While Intel's Xeon Phi was introduced as a GPU, only to be "reinvented into a vector processor", Joel Hruska of Extreme Tech opines that "There’s nothing to say Intel can’t bend it back a bit, possibly by building lower-precision registers or offering them as options on certain types of hardware."
How Intel Claims To Have The Edge Over Nvidia
In fact, Intel claims that GPUs aren't even a scalable solution for the future. The primary reason for GPUs to be used in machine learning applications is their ability to run multiple calculations simultaneously. However, Intel's executive vice president and general manager of the Data Center Group, Diane Bryant, claims that "The market is still nascent, so the current implementations are small enough that they could use GPUs, but it won't scale in the future." Intel claims it's Xeon Phi processor is way faster than Nvidia's GPUs for machine learning algorithms. To be specific, 2.3 times faster. Of course, Nvidia has refuted the claim, brushing aside Intel's assertion with a counter-claim which suggests that the opposite is true:
"Nvidia claimed if Intel had used the latest technology, Nvidia would achieve 30% faster training machine learning models over Intel."
As you'd expect, Intel responded by explaining how current systems use a Xeon processor in combination with GPU accelerators, which the company claims is "suboptimal implementation." According to the article on Forbes, Intel's vice president and general manager of cloud, Jason Waxman said:
"the new Xeon Phi processor will eliminate the need to swap between a central processor and a GPU accelerator. With a chip like the upcoming Xeon Phi, all the processing required for machine learning tasks takes place on a single chip, thus eliminating the need to switch between a main processor and a GPU accelerator."
Given Intel's grip over the data center processor market, which translates to an estimated 99% market share, the option to partially or fully do away with GPU accelerators could be an enticing proposition for some, if not all of its customers.
So What's The Net Result Of This War Of Words?
Intel's next generation of Xeon Phi is expected to be launched in 2017, and we will probably have to wait until then for conclusive results. However, it's worth noting that irrespective of the claims that Nvidia has hurled at Intel, the latter seems to be finding favor indeed, at least from Chinese search giant Baidu (NASDAQ:BIDU). Baidu will reportedly use Xeon Phi chips to power Deep Speech, its natural language processing service, rather than using Nvidia's GPUs, which the company used thus far to run its deep learning models.
Summing It Up
Specifically in the case of Nvidia, much of the stocks dream run in 2016 was based on optimism around the company's prospects in this small, but fast growing space. As for AMD, much is expected from its Vega line up of GPUs, which some expect, will even outdo Nvidia's best GPU, dubbed Titan X. Expectations from AMD in the AI and deep learning space also found new fuel in the company's recent deal with Google, which will avail AMD's GPUs a spot in Google's cloud offerings. However, if Intel does manage to edge out GPUs from AI applications, both AMD and Nvidia will stand to lose. And as Intel looks set to end its GPU tech licensing agreement with Nvidia this March, which could drag the latter's EBITDA by as much as 17%, the Chipzilla could end up dealing a double blow to Nvidia.
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