The mathematician and computer science pioneer Alan Turing hit on a promising direction for artificial intelligence research way back in 1950. "Instead of trying to produce a program to simulate the adult mind," he wrote, "why not rather try to produce one which simulates the child's?" Now AI researchers are finally putting Turing's ideas into action. They're realizing that by paying attention to how children process information, they can pick up valuable lessons about how to create machines that learn. DARPA, the Defense Department's advanced research agency, is embracing this approach.

Researchers, companies and countries around the world are racing to explore – and exploit – the possibilities of artificial intelligence technology. China is working on an extremely aggressive multi-billion-dollar plan for government investment into AI research and applications. The U.S. government has been slower to act. The Obama administration issued a report on AI near the end of its term. Since then, little has happened – until a Feb. 11 executive order from President Donald Trump encouraging the country to do more with AI. The executive order has several parts, including directing federal agencies to invest in AI and train workers "in AI-relevant skills," making federal data and computing resources available to AI researchers and telling the National Institute of Standards and Technology to create standards for AI systems that are reliable and work well together.

Researchers, companies and countries around the world are racing to explore -- and exploit -- the possibilities of artificial intelligence technology. China is working on an extremely aggressive multi-billion-dollar plan for government investment into AI research and applications. The U.S. government has been slower to act. The Obama administration issued a report on AI near the end of its term. Since then, little has happened -- until a Feb. 11 executive order from President Donald Trump encouraging the country to do more with AI.

To talk about artificial intelligence today usually involves talking about automation, lost jobs, and whether your Uber or Lyft will be a self-driving vehicle in 5 years time. Taking a step back from the apps in our phones, however, and what begins to emerge is a larger fight between the US and China, AI superpowers whose contest will likely decide the course of human civilization. In January 2019, the UN's World Intellectual Property Organization (WIPO), whose role is to help spread ideas and innovation around the world, released a report that highlighted the rapid advance of AI patent applications across the world. According to the report, the United States and China's AI-related patent applications outstripped every other nation's by far. "The U.S. and China obviously have stolen a lead. They're out in front in this area, in terms of numbers of applications, and in scientific publications," said Francis Gurry, WIPO Director-General, at a news conference last month announcing the report.

Deep learning is a useful tool to optimise and validate security posture. But until we overcome some of its challenges, positive security models and behavioural algorithms that are deterministic and predictable are still more effective for defence and mitigation. Most successful deep-learning applications in use today are based on supervised learning neural nets. They take an input and produce an output where the output provides a confidence level across a fixed set of labels. Given lots of data, the neural net will usually make the right "decision".

Deep learning is a useful tool to optimise and validate security posture. But until we overcome some of its challenges, positive security models and behavioural algorithms that are deterministic and predictable are still more effective for defence and mitigation. Most successful deep-learning applications in use today are based on supervised learning neural nets. They take an input and produce an output where the output provides a confidence level across a fixed set of labels. Given lots of data, the neural net will usually make the right "decision".

Two divisions of the Chinese networking giant Huawei pleaded not guilty Thursday to charges that it stole trade secrets from America's third-largest wireless carrier, T-Mobile, in a bid to copy its technology. In federal court in Seattle, Huawei -- one of the world's biggest wireless equipment makers -- said it was not guilty of committing trade secret theft, nor of conspiring to hide such a plan. The case involves Huawei Device Co., Ltd. and Huawei Device USA. A jury trial has been set for March 2, 2020, before Chief Judge Ricardo S. Martinez of the U.S. District Court for the Western District of Washington. The pleas follow a 10-count indictment unsealed last month alleging in part that the Huawei divisions tried to collect information about a robotic arm that T-Mobile used to simulate human touch on its smartphones.

The embrace of artificial intelligence has come quickly in government. In May 2017, Congress established the bipartisan Congressional Artificial Intelligence Caucus, and members have since introduced numerous pieces of AI legislation. More recently, the administration launched the American AI Initiative through a February 2019 executive order, and the Department of Defense released its own strategy on how to incorporate AI into national security. As government use of AI evolves, agency leaders will look for pathways to capitalize on opportunities, and the workforce will need new technical and social skills to succeed in AI-augmented workplaces. A new report -- More Than Meets AI: Assessing the Impact of Artificial Intelligence on the Work of Government -- aims to assist in that effort.

NASA's Lunar Orbital Platform-Gateway has its first international partner. The agency announced today that Canada will be joining the effort to set up the lunar-orbit space station that will help to house astronauts, generate research and eventually enable trips to Mars and beyond. Canada brings the expertise of space-based robotics to the project. The nation will be tasked with developing a smart robotic system, called the Canadarm3, that will be able to make necessary repairs to maintain the function of the Gateway. Canada has previously contributed to the construction of the International Space Station and repairs to the Hubble Space Telescope.

Previous work has shown that popular trending events are important external factors which pose significant influence on user search behavior and also provided a way to computationally model this influence. However, their problem formulation was based on the strong assumption that each event poses its influence independently. This assumption is unrealistic as there are many correlated events in the real world which influence each other and thus, would pose a joint influence on the user search behavior rather than posing influence independently. In this paper, we study this novel problem of Modeling the Joint Influences posed by multiple correlated events on user search behavior. We propose a Joint Influence Model based on the Multivariate Hawkes Process which captures the inter-dependency among multiple events in terms of their influence upon user search behavior. We evaluate the proposed Joint Influence Model using two months query-log data from https://search.yahoo.com/. Experimental results show that the model can indeed capture the temporal dynamics of the joint influence over time and also achieves superior performance over different baseline methods when applied to solve various interesting prediction problems as well as real-word application scenarios, e.g., query auto-completion.