BigStock Photo China wants to become the world leader in artificial intelligence by 2030 — but by Seattle’s , or AI2, suggests that Chinese researchers are on track to take the lead well before that. The analysis is based on a tally of the most impactful research papers in the AI field, as measured by AI2’s academic search engine. “If current trends continue, within five years, China will surpass us in terms of the top, highest-impact papers,” the institute’s CEO, Oren Etzioni, told GeekWire. “The other thing to realize is that citations are what you might call a lagging indicator, because the paper has to be published, people have to read it, and they have to write their own paper and cite it.” Thus, the analysis is likely to understate China’s current influence in AI research, Etzioni said. “The bottom line is, Chinese AI research is startling in quantity and quality,” he said. AI2’s findings are consistent with what tech analysts have been saying over the past year or two. Last year, found that 48 percent of the $15.2 billion invested in AI startups globally in 2017 went to China, with just 38 percent going to U.S. startups. Oren Etzioni is the CEO of the Allen Institute for Artificial Intelligence. (GeekWire Photo / Alan Boyle) That’s just the start: China’s State Council has by 2030 — and put that expertise in the service of what’s becoming a . Etzioni said the AI2 analysis shows that research in artificial intelligence has grown dramatically over the past three decades, from 5,000 published papers in 1985 to 140,000 in 2018. Over that time, there have been many studies tracking the progress of AI research, but Etzioni said Semantic Scholar provides new perspective. “First of all, this is the most up-to-date result, because we’ve analyzed papers through 2018,” he said. “Secondly, what’s unique is we looked at this notion of most-cited papers, because we’re after impact.” The analysis shows that, in terms of sheer volume of research papers, China surpassed the U.S. back in 2006. Since then, China’s trend line has gone through ups and downs (and ups), but never fell below the U.S. totals. Semantic Scholar told a different story when it came to the top 50 percent, the 10 percent and the top 1 percent of academic studies, as measured by citation counts. Those charts show a gradual decline in the percentage of papers attributed primarily to U.S. authors, and an accelerating rise in the Chinese percentage. The Chinese Academy of Sciences led the list of China’s research institutions when it came to citations, followed by Nanyang Technological University, Tsinghua University, the Chinese University of Hong Kong and the Hong Kong University of Science and Technology. If the trend lines are extended, China should surpass the United States this year for the top 50 percent, next year for the top 10 percent, and by 2025 for the top 1 percent. This chart shows the market share for the top 1 percent of AI papers, as determined by citation impact. Extending the trend lines suggests that Chinese researchers will produce more of the “cream of the crop” in AI research by 2025. (AI2 Graphic / Field Cady / Oren Etzioni) China’s AI rise has already sparked concerns in Washington, D.C., leading to the establishment of a as well as a at the Pentagon. The White House budget proposal for fiscal year 2020, , would set aside $208 million for the AI center. Etzioni argued that the federal government’s AI strategy should put more emphasis on basic research. “We need to stop what the Trump administration has been doing, which is using various ways to discourage immigration of students and scholars into this country,” he said. “We need more of those talented people, like we always have. AI2 is highly international, and that’s been a huge boon for us.” Setting aside more money for basic research in AI will also be essential, Etzioni said. Last month, President Donald Trump , and this week’s budget proposal made . But those documents didn’t provide specifics. “We need those specifics,” Etzioni said. “And we need them even sooner than we had thought.” Authors of the AI2 analysis, ” are Field Cady and Oren Etzioni. The researchers used to classify AI papers for the purpose of the study. Check the full analysis for details about the methodology.
Artificial intelligence could open the door to applications in a variety of technological fields. (NIST Illustration / N. Hanacek) The White House is moving forward with the American AI Initiative, a set of policies aimed at focusing the full resources of the federal government on the frontiers of artificial intelligence. President Donald Trump is due to sign an executive order launching the initiative on Monday. Among its provisions is a call for federal agencies to prioritize AI in their research and development missions, and to prioritize fellowship and training programs to help American workers gain AI-relevant skills. The initiative also directs agencies to make federal data, models and computing resources more available to academic and industry researchers, “while maintaining the security and confidentiality protections we all expect.” “This action will drive our top-notch AI research toward new technological breakthroughs and promote scientific discovery, economic competitiveness and national security,” the White House said in a statement. As a trust-building measure, federal agencies are being asked to establish regulatory guidelines for AI development and use across different types of technology and industrial sectors. The National Institute of Standards and Technology is being given the lead role in the development of technical standards for reliable, trustworthy, secure and interoperable AI systems. The White House says an action plan will be developed “to preserve America’s advantage in collaboration with our international partners and allies.” “In , President Trump committed to investing in cutting-edge industries of the future,” Michael Kratsios, deputy assistant to the president for technology policy, said in a prepared statement. “The American AI Initiative follows up on that promise with decisive action to ensure AI is developed and applied for the benefit of the American people.” This week’s action comes amid rising concern about American competitiveness in artificial intelligence research and development. and the are both pushing ahead with multibillion-dollar AI research and development programs. In response, the White House has , and a with Amazon’s Andy Jassy and Microsoft’s Eric Horvitz among its members. and are among the hundreds of companies that are making AI a high priority in R&D, resulting in well-known products such as Amazon’s Alexa and Microsoft’s Cortana AI voice assistants (as well as similar AI agents offered by Apple and Google). AI capabilities such as machine learning and computer vision are also key to the development of and . Stacey Dixon, director of the , or IARPA, said AI applications are also highly relevant to national security. “Understanding imagery is one of the most evident opportunities for us to use AI, due to the sheer quantity of data to be analyzed and AI’s demonstrated effectiveness at image categorization,” she said. “However, IARPA also develops AI to address other intelligence challenges, including human language transcription and translation, facial recognition in real-world environments, sifting through videos to find nefarious activities, and increasing AI’s resilience to many kinds of attacks by adversaries.” Those AI tools could be used for nefarious purposes as well, however. , a consortium including the and called on policymakers to collaborate closely with researchers to investigate, prevent and mitigate potentially malicious uses of AI.
Michael Kratsios, who’s currently in charge of the White House’s Office of Science and Technology Policy, addresses scores of executives, experts and officials at a White House summit focusing on artificial intelligence. (OSTP via Twitter) The White House brought together scores of industry representatives for a summit focusing on artificial intelligence and its policy implications today — including representatives from Amazon, Microsoft, Google and Facebook — and set up an advisory panel of government officials to assess AI’s impact. The Select Committee on Artificial Intelligence will advise the White House on AI research and development priorities, and will help forge partnerships involving government agencies, researchers and the private sector, . “In the summer of 1956, a dozen American scientists gathered on Dartmouth’s campus with the goal to ‘find out how to make machines solve the kinds of problems now reserved for humans.’ Now, nearly 62 years later, the age of artificial intelligence is here, and with it the hope of better lives for the American people,” Michael Kratsios, deputy assistant to the president for technology policy and acting head of the Office of Science and Technology Policy, said in prepared remarks provided to Nextgov. The committee is to be housed within the National Science and Technology Council and chaired by OSTP leadership. According to Nextgov and other news outlets, committee members also include: Walter Copan, undersecretary of commerce for standards and technology, and director of the National Institute of Standards and Technology. Mike Griffin, undersecretary of defense for research and engineering. Paul Dabbar, undersecretary for science at the U.S. Department of Energy. France Cordova, director of the National Science Foundation. Peter Highnam, director of the Defense Advanced Research Projects Agency, or DARPA. Jason Matheny, director of the Intelligence Advanced Research Projects Agency. There’ll also be representatives from the National Security Council, the Office of the Federal Chief Information Officer and the Office of Management and Budget. The makeup reflects the model set by the White House’s , which was re-established by the Trump administration last year. In a , the White House pointed to a variety of AI-related initiatives conducted over the past year, including international talks on AI innovation and programs to boost STEM education and apprenticeships. Last year, Treasury Secretary Steven Mnuchin downplayed the potential impact of AI in . He said it would be “50 or 100 more years” before the U.S. had to worry about the impact of automation on jobs. Kratsios took the concern more seriously in today’s prepared remarks. “To a certain degree, job displacement is inevitable,” “But we can’t sit idle, hoping eventually the market will sort it out. We must do what Americans have always done: adapt.” In 2016, the Obama White House convened a series of workshops on AI and its implications, starting with a workshop in Seattle. That process resulted in a calling for better information sharing, improved training to understand AI, targeted support of AI research and other policy initiatives. During today’s summit, which was closed to the media, more than 100 researchers, government officials and industry executives met to discuss what they’re doing in the fields of artificial intelligence, robotics and automation. In addition to the usual tech titans, the guest list included representatives from Boeing, Mastercard, Ford, Land O’Lakes and United Airlines. that Amazon would be represented by Rohit Prasad, vice president and head scientist for the Alexa AI program. Among the topics on the agenda are; Concerns about privacy, sparked by the recent scandal focusing on Cambridge Analytica’s use of Facebook data for political purposes. Concerns about America’s international competitiveness in AI research and development, stoked by multibillion-dollar initiatives and the . Concerns about regulatory requirements for AI. Bloomberg News reported that Kratsios promised a hands-off regulatory approach in his prepared remarks. “We didn’t cut the lines before Alexander Graham Bell made the first telephone call,” Kratsios said. “We didn’t regulate flight before the Wright Brothers took off at Kitty Hawk.”
A 3-D visualization of human cells is color-coded to highlight substructures. (Allen Institute for Cell Science) What happens when you cross cell biology with artificial intelligence? At the Allen Institute for Cell Science, the answer isn’t super-brainy microbes, but new computer models that can turn simple black-and-white pictures of live human cells into color-coded, 3-D visualizations filled with detail. The online database, known as the , is now being made publicly available — and its creators say it could open up new windows into the workings of our cells. “From a single, simple microscopy image, you could get this very high-contrast, integrated 3-D image where it’s very easy to see where all the separate structures are,” Molly Maleckar, director of modeling at the Seattle-based Allen Institute, told GeekWire. “You can actually look at the relationships between them, and eventually apply a time series, so you can see dynamically how those change as well,” she said. “That’s something that’s totally new.” Molly Maleckar and Graham Johnson work on the Allen Integrated Cell project. (Allen Institute Photos) Eventually, the database could make it easier to monitor how stem cells transform themselves into the different types of cells in our bodies, see how diseases affect cellular processes, and check the effects that drugs have on individual cells. “These methods are allowing us to see multiple structures where they are in the cell, relative to one another, reliably, at the same time, while perturbing the cell as little as possible,” said Graham Johnson, director of the Allen Institute’s Animated Cell project. “Our goal is to get them as close to their native, happy state as possible, without hurting them with light, without messing up their function.” The effort began with the institute’s collection of gene-edited human , or hiPSC lines. These special cells have been engineered to add fluorescent labels, making it possible for researchers to pinpoint the substructures inside them. Examples of such substructures include the , the energy-producing and the that serve as cellular scaffolds. Researchers trained an artificial intelligence program to recognize the glow-in-the-dark substructures in thousands of cells. Then they applied that deep-learning model to simpler black-and-white images of cells that didn’t have fluorescent labels. The resulting “label-free model” makes it possible to generate highly detailed 3-D visualizations from the kinds of views you get from a standard high-school microscope. The method is described in depth in a . Another model developed at the institute can accurately predict the most probable shape and location of structures in any pluripotent stem cell, based solely on the shape of the cell membrane and the nucleus. The models could help researchers develop detailed information about cellular interactions over time without having to use chemical dyes, laser scans or other methods that disrupt the cells being studied. Maleckar said the technique could be used for drug discovery, but she’s just as excited about the potential applications for regenerative medicine. “A really interesting thing there is, how do we engineer heart muscle cells so we can grow them, and they become a functional cell and eventually functional tissue?” she said. “One way we can improve that process is by learning how that process occurs.” For now, the Allen Institute is working to fine-tune the computer modeling tools rather than moving on to the clinical applications. “We’re really excited about the downstream applications, but that’s not our major focus right now,” Maleckar said. “We’re really trying to probe the limits of the technology.” Today, the tools can turn high-school-level microscopy into visualizations for professional researchers — but someday, even high-school students could benefit. Johnson recalled how some of the cells he saw through the microscope during his high-school years just looked like blobs with a couple of spots on them. “To be able to take that same high-school scope, run the software on it one day, and be able to see six or eight different things inside that cell, and understand how those different components are connected, and why the pieces are moving the way they are — that would be so exciting,” he said. Johnson said he was so intrigued by the idea that he wrote himself a reminder to try out the system on microscope images from an actual high school. “That’d be really cool,” he said.