今日推薦英文原文：《The US, China and the AI arms race: Cutting through the hype》
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今日推薦英文原文：《The US, China and the AI arms race: Cutting through the hype》作者：Alison DeNisco Rayome
The US, China and the AI arms race: Cutting through the hypeArtificial intelligence — which encompasses everything from service robots to medical diagnostic tools to your Alexa speaker — is a fast-growing field that is increasingly playing a more critical role in many aspects of our lives. A country’s AI prowess has major implications for how its citizens live and work — and its economic and military strength moving into the future.
With so much at stake, the narrative of an AI “arms race” between the US and China has been brewing for years. Dramatic headlines suggest that China is poised to take the lead in AI research and use, due to its national plan for AI domination and the billions of dollars the government has invested in the field, compared with the US’ focus on private-sector development.
But the reality is that at least until the past year or so, the two nations have been largely interdependent when it comes to this technology. It’s an area that has drawn attention and investment from major tech heavy hitters on both sides of the Pacific, including Apple, Google and Facebook in the US and SenseTime, Megvii and YITU Technology in China.
“Narratives of an ‘arms race’ are overblown and poor analogies for what is actually going on in the AI space,” said Jeffrey Ding, the China lead for the Center for the Governance of AI at the University of Oxford’s Future of Humanity Institute. When you look at factors like research, talent and company alliances, you’ll find that the US and Chinese AI ecosystems are still very entwined, Ding added.
But the combination of political tensions and the rapid spread of COVID-19 throughout both nations is fueling more of a separation, which will have implications for both advances in the technology and the world’s power dynamics for years to come.
“These new technologies will be game-changers in the next three to five years,” said Georg Stieler, managing director of Stieler Enterprise Management Consulting China. “The people who built them and control them will also control parts of the world. You cannot ignore it.”
The origins of the US-China arms race
The first was in March 2016, when AlphaGo — a machine-learning system built by Google’s DeepMind that uses algorithms and reinforcement learning to train on massive datasets and predict outcomes — beat the human Go world champion Lee Sedol. This was broadcast throughout China and sparked a lot of interest — both highlighting how quickly the technology was advancing, and suggesting that because Go involves war-like strategies and tactics, AI could potentially be useful for decision-making around warfare.
The second moment came seven months later, when President Barack Obama’s administration released three reports on preparing for a future with AI, laying out a national strategic plan and describing the potential economic impacts (all PDFs). Some Chinese policymakers took those reports as a sign that the US was further ahead in its AI strategy than expected.
This culminated in July 2017, when the Chinese government under President Xi Jinping released a development plan for the nation to become the world leader in AI by 2030, including investing billions of dollars in AI startups and research parks.
“China has observed how the IT industry originates from the US and exerts soft influence across the world through various Silicon Valley innovations,” said Lian Jye Su, principal analyst at global tech market advisory firm ABI Research. “As an economy built solely on its manufacturing capabilities, China is eager to find a way to diversify its economy and provide more innovative ways to showcase its strengths to the world. AI is a good way to do it.”
Despite the competition, the two nations have long worked together. China has masses of data and far more lax regulations around using it, so it can often implement AI trials faster — but the nation still largely relies on US semiconductors and open source software to power AI and machine learning algorithms.
And while the US has the edge when it comes to quality research, universities and engineering talent, top AI programs at schools like Stanford and MIT attract many Chinese students, who then often go on to work for Google, Microsoft, Apple and Facebook — all of which have spent the last few years acquiring startups to bolster their AI work.
The impact of coronavirus
China’s fears about a grand US AI plan didn’t really come to fruition. In February 2019, US President Donald Trump released an American AI Initiative executive order, calling for heads of federal agencies to prioritize AI research and development in 2020 budgets. It didn’t provide any new funding to support those measures, however, or many details on how to implement those plans. And not much else has happened at the federal level since then.
Meanwhile, China plowed on, with AI companies like SenseTime, Megvii and YITU Technology raising billions. But investments in AI in China dropped in 2019, as the US-China trade war escalated and hurt investor confidence in China, Su said. Then, in January, the Trump administration made it harder for US companies to export certain types of AI software in an effort to limit Chinese access to American technology.
Just a couple weeks later, Chinese state media reported the first known death from an illness that would become known as COVID-19.
In the midst of the coronavirus pandemic, China has turned to some of its AI and big data tools in attempts to ward off the virus, including contact tracing, diagnostic tools and drones to enforce social distancing. Not all of it, however, is as it seems.
“There was a lot of propaganda — in February, I saw people sharing on Twitter and LinkedIn stories about drones flying along high rises, and measuring the temperature of people standing at the window, which was complete bollocks,” Stieler said. “The reality is more like when you want to enter an office building in Shanghai, your temperature is taken.”
The US and other nations are grappling with the same technologies — and the privacy, security and surveillance concerns that come along with them — as they look to contain the global pandemic, said Elsa B. Kania, adjunct fellow with the Center for a New American Security’s Technology and National Security Program, focused on Chinese defense innovation and emerging technologies.
“The ways in which China has been leveraging AI to fight the coronavirus are in various respects inspiring and alarming,” Kania said. “It’ll be important in the United States as we struggle with these challenges ourselves to look to and learn from that model, both in terms of what we want to emulate and what we want to avoid.”
The pandemic may be a turning point in terms of the US recognizing the risks of interdependence with China, Kania said. The immediate impact may be in sectors like pharmaceuticals and medical equipment manufacturing. But it will eventually influence AI, as a technology that cuts across so many sectors and applications.
Speeding the separation
Despite the economic impacts of the virus, global AI investments are forecast to grow from $22.6 billion in 2019 to $25 billion in 2020, Su said. The bigger consequence may be on speeding the process of decoupling between the US and China, in terms of AI and everything else.
The US still has advantages in areas like semiconductors and AI chips. But in the midst of the trade war, the Chinese government is reducing its reliance on foreign technologies, developing domestic startups and adopting more open-source solutions, Su said. Cloud AI giants like Alibaba, for example, are using open-source computing models to develop their own data center chips. Chinese chipset startups like Cambricon Technologies, Horizon Robotics and Suiyuan Technology have also entered the market in recent years and garnered lots of funding.
But full separation isn’t on the horizon anytime soon. One of the problems with referring to all of this as an AI arms race is that so many of the basic platforms, algorithms and even data sources are open-source, Kania said. The vast majority of the AI developers in China use Google TensorFlow or Facebook PyTorch, Stieler added — and there’s little incentive to join domestic options that lack the same networks.
The US remains the world’s AI superpower for now, Su and Ding said. But ultimately, the trade war may do more harm to American AI-related companies than expected, Kania said.
“My main concern about some of these policy measures and restrictions has been that they don’t necessarily consider the second-order effects, including the collateral damage to American companies, as well as the ways in which this may lessen US leverage or create much more separate or fragmented ecosystems,” Kania said. “Imposing pain on Chinese companies can be disruptive, but in ways that can in the long term perhaps accelerate these investments and developments within China.”
Still, “‘arms race’ is not the best metaphor,” Kania added. “It’s clear that there is geopolitical competition between the US and China, and our competition extends to these emerging technologies including artificial intelligence that are seen as highly consequential to the futures of our societies’ economies and militaries.”