The arrest of Harvard Professor Charles Lieber for failing to reveal his work for the Chinese is more than alarming. One of the world's leading experts in nanotechnology, Mr. Lieber contributed to China's Thousand Talents Program and assisted China in its military arms race with the United States, whether knowingly or not. Americans should be concerned that China is pursuing military nanotechnology solutions, including linking soldiers' brains directly to computers. Since at least 2000, when President Clinton proclaimed his National Nanotechnology Initiative, U.S. government agencies have been heavily engaged in nanotechnology research. A significant part of the work has been funded by the Defense Department, and the long-term goal is to create a new kind of warrior linking the human brain to machines, to millions of sensors and to the computer cloud.

World leaders have woken up to the potential of artificial intelligence (AI) over the past year. Billions of dollars in governmental funding have been announced, dozens of hearings have been held, and nearly 20 national plans have been adopted. In the past couple of months alone, Canada and France launched the International Panel on AI (IPAI), modeled on the Intergovernmental Panel on Climate Change, to examine the global impacts of AI; the U.S. Congress created a National Security Commission on the subject; and the Pentagon tasked one of its top advisory bodies with devising ethical principles for its use of AI. "AI" broadly refers to the science and technology of machines capable of sophisticated information processing. Current applications include face recognition, image analysis, language translation and processing, autonomous vehicles, robotics, game-playing, and recommendation engines. Many more applications are likely to emerge in the coming years and decades.

The U.S. Postal Service (USPS) said on Nov. 7 that it would average 20.5 million packages per day through the remainder of the year. That adds up to a projected 800 million package deliveries between Thanksgiving and New Year's Day. The USPS is making an investment in new artificial intelligence technology to make the processing of those millions of packages more efficient. Although it will not impact this holiday season's shipments, the USPS is testing a range of hardware and software solutions from Nvidia to speed up the processing of packages, according to a November statement. Engineering teams from the Postal Service and Nvidia have been collaborating for several months on the project.

Digital fraud continues to flourish, with recent surveys finding that security breaches have increased 67 percent since 2014 and 11 percent since 2018. Casualties of these breaches in the first half of 2019 alone include 4.1 billion personal records exposed in a variety of ways: 52 percent through hacking; 33 percent via phishing; and 32 percent through social engineering, with many involving more than one method. Organizations and security developers are investing billions of dollars in fighting these fraud attempts. Worldwide spending on security systems is projected to hit $131 billion by the end of 2020, and $174 billion over the next two years. Artificial intelligence (AI) and machine learning (ML) applications often form the core of these cybersecurity systems and are being deployed across banks, retailers, telecommunications companies and many other businesses.

"Sorry, guys, I made the mistake this round," it says. "I know it may be hard to believe, but robots make mistakes too." This scenario occurred multiple times during a Yale-led study of robots' effects on human-to-human interactions. The study, which will publish on March 9 in the Proceedings of the National Academy of Sciences, showed that the humans on teams that included a robot expressing vulnerability communicated more with each other and later reported having a more positive group experience than people teamed with silent robots or with robots that made neutral statements, like reciting the game's score. "We know that robots can influence the behavior of humans they interact with directly, but how robots affect the way humans engage with each other is less well understood," said Margaret L. Traeger, a Ph.D. candidate in sociology at the Yale Institute for Network Science (YINS) and the study's lead author.

"Sorry, guys, I made the mistake this round," it says. "I know it may be hard to believe, but robots make mistakes too." This scenario occurred multiple times during a Yale-led study of robots' effects on human-to-human interactions. The study, which will publish on March 9 in the Proceedings of the National Academy of Sciences, showed that the humans on teams that included a robot expressing vulnerability communicated more with each other and later reported having a more positive group experience than people teamed with silent robots or with robots that made neutral statements, like reciting the game's score. "We know that robots can influence the behavior of humans they interact with directly, but how robots affect the way humans engage with each other is less well understood," said Margaret L. Traeger, a Ph.D. candidate in sociology at the Yale Institute for Network Science (YINS) and the study's lead author.

When searching through theoretical lists of possible new materials for particular applications, such as batteries or other energy-related devices, there are often millions of potential materials that could be considered, and multiple criteria that need to be met and optimized at once. Now, researchers at MIT have found a way to dramatically streamline the discovery process, using a machine learning system. As a demonstration, the team arrived at a set of the eight most promising materials, out of nearly 3 million candidates, for an energy storage system called a flow battery. This culling process would have taken 50 years by conventional analytical methods, they say, but they accomplished it in five weeks. The findings are reported in the journal ACS Central Science, in a paper by MIT professor of chemical engineering Heather Kulik, Jon Paul Janet PhD '19, Sahasrajit Ramesh, and graduate student Chenru Duan.

Currently, the European Union does not have any specific legislative instrument or standard to regulate the use and development of AI. However, these requirements are likely to set the stage for future legislation, similar in scope and effect as the General Data Protection Regulation (GDPR) for privacy, therefore indicating that the European Union may be on the cusp of providing for specific and unique AI regulatory legislation.

On February 19, 2020, the European Commission presented its White Paper on Artificial Intelligence – A European Approach to Excellence and Trust, a much-anticipated policy document setting out concrete measures and proposed regulation with the objective of promoting the development, uptake and use of AI applications, while also addressing the resulting fundamental rights challenges. The document has raised concerns among companies about whether new rules on AI will negatively impact businesses developing or deploying AI solutions across the EU. Feedback on the white paper can be provided until May 19, 2020. The white paper proposes a dual approach. It aims to establish an "ecosystem of excellence" on the one hand, and "an ecosystem of trust" on the other hand.

UPS has partnered with the German tech company Wingcopter to build a fleet of rugged, high speed delivery drones. The drones will be based on a model designed by Wingcopter, which can travel at speeds of up to 150mph and has a range of 75 miles. The drones can also endure a variety of difficult weather conditions, including wind speeds of up to 45mph. The agreements marks the first external partnership for UPS's Flight Forward program, which is focused on developing a range of drone delivery options, according to a report in TechCrunch. 'Drone delivery is not a one-size-fits-all operation,' UPS's Bala Ganesh said.