The Verge: China and the US are battling to become the world’s first AI superpower

["Dave Farber" <farber () gmail com>]

> Begin forwarded message:
>
> From: Allan Davidson <alland () heckerty com>
> Subject: The Verge: China and the US are battling to become the world’s first AI superpower
> Date: August 6, 2017 at 2:18:34 PM EDT
> To: Dave Farber <farber () gmail com>
>
> May be of interest to the list: 
> China and the US are battling to become the world’s first AI superpower
> The Verge
>
> In October 1957, the Soviet Union launched the Earth’s first artificial satellite, Sputnik 1. The craft was no bigger 
> than a beach ball, but it spurred the US into a frenzy of research and... Read the full story 
> <https://apple.news/AzmMMYhmrTa-zddZlJztXwg>
> In October 1957, the Soviet Union launched the Earth’s first artificial satellite, Sputnik 1. The craft was no bigger 
> than a beach ball, but it spurred the US into a frenzy of research and investment that would eventually put humans on 
> the Moon. Sixty years later, the world might have had its second “Sputnik moment.” But this time, it’s not the US 
> receiving the wake-up call, but China; and the goal is not the exploration of space, but the creation of artificial 
> intelligence.
> The second Sputnik arrived in the form of AlphaGo, the AI system developed by Google-owned DeepMind. In 2016, AlphaGo 
> beat South Korean master Lee Se-dol at the ancient Chinese board game Go, and in May this year, it toppled the 
> Chinese world champion, Ke Jie. Two professors who consult with the Chinese government on AI policy told The New York 
> Times that these games galvanized the country’s politicians to invest in the technology. And the report the pair 
> helped shape — published last month — makes China’s ambitions in this area clear: the country says it will become the 
> world’s leader in AI by 2030.
> “It’s a very realistic ambition,” Anthony Mullen, a director of research at analyst firm Gartner, tells The Verge. 
> “Right now, AI is a two-horse race between China and the US.” And, says Mullen, China has all the ingredients it 
> needs to move into first. These include government funding, a massive population, a lively research community, and a 
> society that seems primed for technological change. And it all invites the trillion-dollar question: in the coming AI 
> Race, can China really beat the US?
> Strength in numbers
> To build great AI, you need data, and nothing produces data quite like humans. This mean’s China’s massive 1.4 
> billion population (including some 730 million internet users) might be its biggest advantage. These citizens produce 
> reams of useful information that can be mined by the country’s tech giants, and China is also significantly more 
> permissive when it comes to users’ privacy. For the purposes of building AI, this compares favorably with European 
> countries and their “citizen-centric legislation,” says Mullen. Companies like Apple and Google are designing 
> workarounds for this privacy problem, but it’s simpler not to bother in the first place.
> In China, this also means that AI is being deployed in ways that might not be acceptable in the West. For example, 
> facial recognition technology is used for everything from identifying jaywalkers to dispensing toilet paper. These 
> implementations seem trivial, but as any researcher will tell you, there’s no substitute for deploying tech in the 
> wild for testing and developing. “I don’t think China will have the same level of existential crisis about the 
> development of AI that the West will have,” says Mullen.
> The adventures of Microsoft chatbots in China and the US make for a good comparison. In China, the company’s Xiaoice 
> bot, which is downloadable as an app, has more than 40 million users, with regulars talking to it every night. It 
> even published a book of poetry under a pseudonym, sparking a debate in the country about artificial creativity. By 
> comparison, the American version of the bot, named Tay, was famously shut down in a matter of days after Twitter 
> users taught it to be racist.
> Matt Scott, CTO of Shenzhen machine vision startup Malong Technologies, says China’s attitude toward new technology 
> can be “risk-taking” in a bracing way. “For AI you have to be at the cutting edge,” he says. “If you’re using 
> technology that’s one year old, you’re outdated. And I definitely find that in China — at least, my community in 
> China — is very adept at taking on these risks.”
> A culture of collaboration
> The output of China’s AI research community is, in some ways, easy to gauge. A report from the White House in October 
> 2016 noted that China now publishes more journal articles on deep learning than the US, while AI-related patent 
> submissions from Chinese researchers have increased 200 percent in recent years. The clout of the Chinese AI 
> community is such that at the beginning of the year, the Association for the Advancement of Artificial Intelligence 
> rescheduled the date of its annual meeting; the original had fallen on Chinese New Year.
> What’s trickier, though, is knowing how these numbers translate to scientific achievement. Paul Scharre, a researcher 
> at the think tank Center for a New American Security, is skeptical about statistics. “You can count the number of 
> papers, but that’s sort of the worst possible metric, because it doesn’t tell you anything about quality,” he says. 
> “At the moment, the real cutting-edge research is still being done by institutions like Google Brain, OpenAI, and 
> DeepMind.”
> In China, though, there is more collaboration between firms like these and universities and government — something 
> that could be beneficial in the long term. Scott’s Malong Technologies runs a joint research lab with Tsinghua 
> University, and there are much bigger partnerships like the “national laboratory for deep learning” run by Baidu and 
> the Chinese government’s National Development and Reform agency.
> Other aspects of research seem influential, but are difficult to gauge. Scott, who started working in machine 
> learning 10 years ago with Microsoft, suggests that China has a particularly open AI community. “I think there is a 
> bit more emphasis on [personal] relationships,” he says, adding that China’s ubiquitous messaging app WeChat is a 
> rich resource, with chat groups centered around universities and companies sharing and discussing new research. “The 
> AI communities are very, very alive,” he says. “I would say that WeChat as a vehicle for spreading information is 
> highly effective.”
> Remember: the government helped make the internet
> What most worries Scharre is the US government’s current plans to retreat from basic science. The Trump 
> administration’s proposed budget would slash funding for research, taking money away from a number of agencies whose 
> work could involve AI. “Clearly [Washington doesn’t] have any strategic plan to revitalize American investment in 
> science and technology,” Scharre tells The Verge. “I am deeply troubled by the range of cuts that the Trump 
> administration is planning. I think they’re alarming and counterproductive.”
> The previous administration was aware of the dangers and potential of artificial intelligence. Two reports published 
> by the Obama White house late last year spelled out the need to invest in AI, as well as touching on topics like 
> regulation and the labor market. “AI holds the potential to be a major driver of economic growth and social 
> progress,” said the October report, noting that “public- and private-sector investments in basic and applied R&D on 
> AI have already begun reaping major benefits.”
> In some ways, China’s July policy paper on AI mirrors this one, but China didn’t just go through a dramatic political 
> upheaval that threatens to change its course. The Chinese policy paper says that by 2020 it wants to be on par with 
> the world’s finest; by 2025 AI should be the primary driver for Chinese industry; and by 2030, it should “occupy the 
> commanding heights of AI technology.” According to a recent report from The Economist, having the high ground will 
> pay off, with consultancy firm PwC predicting that AI-related growth will lift the global economy by $16 trillion by 
> 2030 — with half of that benefit landing in China.
> Where do we go from here? 
> For Scharre, who recently wrote a report on the threat AI poses to national security, the US government is laboring 
> under a delusion. “A lot of people take it for granted that the US builds the best tech in the world, and I think 
> that’s a dangerous assumption to make,” he says, saying that a wake-up call is due. China may have had the “Sputnik 
> moment” it needed to back AI, but has the US?
> Others question whether this is necessary. Mullen says that while the momentum to be the world leader in AI currently 
> lies with China, the US is still marginally ahead, thanks to the work of Silicon Valley. Scharre agrees, and says 
> that government funding isn’t that big of an issue while US tech giants are able to redirect just a little of their 
> ad money to AI. “Money you get from somewhere like DARPA is just a drop in the ocean compared to what you can get 
> from the likes of Google and Facebook,” he says.
> These companies also provide a counterpoint to the argument that China’s demographics give it an unmatchable 
> advantage. It’s certainly good to have a huge number of users in one country, but it’s probably better to have that 
> same number of users spread across the world. Both Facebook and Google have more than 2 billion people hooked on to 
> their primary platforms (Facebook itself and Android) as well as a half-dozen other services with a billion-plus 
> users. It’s arguable that this sort of reach is more useful, as it provides an abundance of data, as well as 
> diversity. China’s tech companies may be formidable, but they lack this international reach.
> Scharre suggests this is important, because when it comes to measuring progress in AI, on-the-ground implementations 
> are worth more than research. What counts, he says, is “the ability of nations and organizations to effectively 
> implement AI technologies. Look at things like using AI in healthcare diagnoses, in self-driving cars, in finance. 
> It’s fine to be, say, 12 months behind in research terms, as long as you can still get ahold of the technology and 
> use it effectively.”
> In that sense, the AI race doesn’t have to be zero sum. Right now, cutting-edge research is developed in secret, but 
> shared openly across borders. Scott, who has worked in the field in both the US and China, says the countries have 
> more in common than they think. “People are afraid that this is something happening in some basement lab somewhere, 
> but it’s not true,” he says. “The most advanced technology in AI is published, and countries are actively 
> collaborating. AI doesn’t work in a vacuum: you need to be collaborative.”
> In some ways, this is similar to the situation in 1957. When news of Sputnik’s launch first broke, there was an air 
> of scientific respect, despite the the geopolitical rivalry between the US and USSR. A contemporary report said that 
> America’s top scientists “showed no rancor at being beaten into space by the Soviet engineers, and, as one of them 
> put it, ‘We are all elated that it is up there.’”
> Throughout the ‘60s and early ‘70s, America and Russia jockeyed back and forth to be “first” in the space race. But 
> in the end, the benefits of this competition — new scientific knowledge, technology, and culture — didn’t just go to 
> the winner. They were shared more evenly than that. By this metric, a Sputnik moment doesn’t have to be cause for 
> alarm, and the race to build better AI could still benefit us all.
> Shared from Apple News <https://www.apple.com/news/>




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