In a study published this week on the preprint server Arxiv.org, Google and University of California, Berkely researchers propose a framework that combines learning-based perception with model-based controls to enable wheeled robots to autonomously navigate around obstacles. They say it generalizes well to avoiding unseen buildings and humans in both simulation and real-world environments and that it leads to better and more data-efficient behaviors than a purely learning-based approach. As the researchers explain, autonomous robot navigation has the potential to enable many critical robot applications, from service robots that deliver food and medicine to logistical and search robots for rescue missions. In these applications, it's imperative for robots to work safely among humans and to adjust their movements based on observed human behavior. For example, if a person is turning left, the robot should pass the human to the right to avoid cutting them off, and when a person is moving in the same direction as the robot, the robot should maintain a safe distance between itself and the person.

"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.

Japanese police arrested or took other action against 115 people for civil aviation law violations linked to unauthorized drone flights in 2019, up 31 from the previous year, government data showed Thursday. The National Police Agency tally included 51 foreign nationals, of whom 19, the largest group, were Chinese. Seven were from the United States. Last year, the number of cases that led to police actions stood at 111. Of them, 54 cases happened as offenders tried to take commemorative pictures, while 34 cases were flight operation exercises, according to the NPA data.

Quantum computers have been quite the rage recently with different tech companies vying for the top spot when it comes to building the most powerful quantum machine. While IBM and Google were in the headlines last year for achieving quantum supremacy, other companies like the Industrial giant Honeywell have been quietly working on its own quantum tech. The company plans to make available its quantum machine to clients via the internet in the next three months. However, Honeywell's approach is a little different than the traditional quantum computers which use superconducting qubits to operate. Honeywell's quantum computer uses a different technology, called ion traps, which hold ions in place with electromagnetic fields.

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.

Increases in the occurrence and global effect of mental illness have made the prevention and treatment of mental health problems a public health priority. To address the need for more access to mental health treatment, digital psychotherapy programs, such as internet-delivered Cognitive Behavioral Therapy (iCBT), have evolved and have achieved clinical outcomes comparable to traditional face-to-face therapy when it comes to meeting the needs of clients who are experiencing mental health problems. However, to attain desired outcomes, sustaining good client engagement with iCBT programs remains a key challenge. Research has demonstrated that including a trained coach, who provides tailored guidance and encouragement to the client throughout their otherwise self-guided treatment journey, improves client engagement and leads to better mental health outcomes than unsupported interventions. From the evidence, it's clear that forming a strong therapeutic alliance in these situations is critical to client engagement, making clients feel listened to and actively supported by coaches who care about their well-being.

Bank of China has launched an artificial intelligence-based forex trading signal prediction application through the Refinitiv Eikon desktop. Known as DeepFX, the tool was developed by the digital asset management division of Bank of China using deep learning technology to predict short-term price movements on major foreign exchange currency pairs. "With the unprecedented increase in market volatility across global financial markets in recent months, the Bank of China's DeepFX application is a timely and practical tool to empower users with the insights they need to navigate the turbulent FX landscape," said Nicole Chen, Head of China at Refinitiv. Bank of China said the'Lite' released version of the DeepFX app provides forecasting in real-time of FX trade signals in 5-minute intervals, while displaying back-test results within 10 days. Bank of China added the app is aimed at helping traders, quant developers, FinTech innovation heads, as well as data scientists.

Just imagine the world without a transport facility! If you want to travel for long distances, how would you go? And, if a leading manufacturing company has to transport goods to its customer locations, then how it will do that without a transport facility? I think you understood the significance of the transportation industry. Do you believe or not history of the initiatives across the transportation industry have exploded in 1787 when steamboat has invented.

The EU has been forced to rethink its new digital strategy, which includes measures to boost its data independence and significantly alter the way European AI algorithms are trained. Unveiled in February, the stringent set of rules for the development and use of AI products is designed to ensure the nascent technology is used responsibly. The new rules introduce stipulations around data quality and also demand AI algorithms developed in the EU are trained using European data, which could prove prohibitive. The rapid spread of the novel coronavirus has emphasised the critical importance of agility and collaboration across continents, which the EU's proposed measures (if unchanged) will render extremely difficult, steeping the process in bureaucracy. The 12-week consultation on the new digital strategy - which will determine its final form - is set to take place at the end of May, but will now likely be postponed.