However...the fact China not only built the world's fastest supercomputer but did it with chips they designed and manufactured themselves, see 2016's "Milestone: China Builds The (NEW) World's Fastest Supercomuter Using Only Chinese Components (and other news) INTC; NVDA; IBM" combined with our first hit of the three cities named in: November 21, 2016 "Artificial Intelligence: What Could Derail NVIDIA? A Lab in Shenzhen; A Basement in Moscow; An Office in Bristol (NVDA)", albeit a year later:
"Sequoia Backs Graphcore as the Future of Artificial Intelligence Processors" (NVDA; INTC)
November 13, 2017makes one think the lab in Shenzhen idea is not as far out as it had been.
BRISTOL, England, Nov. 13, 2017 — Graphcore has today announced a $50 million Series C funding round by Sequoia Capital as the machine intelligence company prepares to ship its first Intelligence Processing Unit (IPU) products to early access customers at the start of 2018....
From Nanalyze, January 11:
There is a new arms race, but we’re not talking thermonuclear war—unless we give machines the launch codes. Artificial intelligence is one of the key technologies that we cover, and it’s been a wild ride the last few years. Industries from healthcare to recruitment have embraced AI to gain efficiencies and a competitive edge. Heck, even Coca Cola is giving you Coke with AI. While the software can be sexy, it’s the hardware, or computing power, which has made many of the advancements in AI possible. One of the companies leading the charge is Nvidia (NASDAQ:NVDA), which has become the gold standard for big computing applications ranging from gaming to supercomputers to neural networks. More than a few AI chip startups have emerged in the last year or two, but the real competition will likely come from established players like AMD or Google. And then there’s China.
Most companies would want to be Nvidia, whose stock gained more than 100 percent in the last year.
We recently told you about all the ways China is Kicking America’s Ass in Tech. We didn’t mention AI because China isn’t there. Yet. However, the Chinese government has plans to reach parity with the United States in AI as early as 2020. It’s putting up the money to do it, starting with a $2 billion AI business park that will be home to 400 enterprises. The country hopes to generate about $60 billion from AI technology by 2025.
Credit: 2017 China-US AI Venture Capital State and Trends Research Report
Despite the official line, Chinese companies are still going with Nvidia, which signed a deal last year to provide its new Volta GPU chips into data centers run by three of China’s biggest tech companies—Alibaba, Baidu and Tencent. It’s little wonder that Nvidia’s stock gained more than 100 percent last year and is off to a scorching start in 2018. Wired reported that Nvidia is in the Chinese government’s crosshairs, urging its industry to develop a chip that is 20 times more powerful and energy efficient than Nvidia’s M40 chip used for artificial neural networks.One thing not mentioned in the Nanalyze report that is critical to understanding Chinese R&D is the importance of the People's Liberation Army (Navy) and the advantage the closed loop of academia, end-user and PLA contracted-and-government-owned companies conveys:
A Cambrian Explosion
That goal landed Beijing-based Cambricon Technologies $100 million in funding last August. Alibaba and Lenovo participated in the Series A, which was led by the Chinese government’s largest state-owned investment holding company. That investment propelled Cambricon, founded only in 2016, into the Unicorn Club of companies valued at $1 billion or more. Cambricon hopes to put its AI hardware into one billion smart devices and corner as much as 30 percent of China AI chip market in three years, China Money Market reported. The company recently appeared on CB Insights AI 100 startups list.
Last year, the company released a ton of new products, including three AI processors that can be used in all sorts of applications, from computer vision to autonomous driving to natural language generation. Cambricon also produced a couple of high performance machine learning chips for servers, one market where China lags behind despite being home to more supercomputers than the United States (many of which sport Nvidia hardware). That’s not surprising, as AI Chinese startups like Cambricon have been mainly focused on chips for mobile devices and wearables. In 2016, for example, it made $15 million in licensing fees for its Cambricon-1A chip from smartphone manufacturers and wearable device makers.
A Really, Really Smart Phone
In fact, it makes sense that much of the Chinese AI chip market has been focused on mobile applications, given the country’s emphasis on mobile technology, from social media and e-commerce on WeChat to eSports gaming. Case in point: Semiconductor manufacturer HiSilicon, owned by Chinese telecommunications giant Huawei Technologies, released a wicked fast Kirin 970 processor that features a traditional CPU, a Nvidia-like GPU and an NPU, for neural processing unit, which handles the AI workload. The NPU particularly excels at image recognition, processing a reported 2,000 images per minute. Here how it compares to less-smart smart phones:...MUCH MORE
Military AI: China, Russia and the U.S. are Running Neck-and-Neck in an Arms Race
China might be ahead, tough to tell but that's the way to bet....So, we'll try to stay on top of developments and let you know when we see something out oif Shenzhen.
Or Moscow.
