Having helped incorporate Paradox less than four years ago, we were proud to represent Paradox in this important financing, which signifies its status as one of Arizona's premier emerging growth companies,

The United States Patent and Trademark Office officially selected a new partner to support its increasing adoption of artificial intelligence and machine learning capabilities. General Dynamics Information Technology on Monday announced it was awarded a contract worth up to $50 million through USPTO's Intelligent Automation and Innovation Support Services blanket purchase agreement. GDIT is the latest of more than a dozen companies the agency tapped under the future-facing BPA. Other businesses who've made their own recent announcements detailing partnerships via the agreement include Octo and Steampunk. In the announcement, Vice President & General Manager Christopher Hegedus for GDIT's Diplomacy, Commerce and Government Operations business area noted the company's supported the agency for nearly two decades, and through this "new work, [aims to bring its] AI, ML and robotic process automation expertise to help USPTO develop solutions that accelerate the patent and trademark process to benefit American innovators."

For a few fleeting moments during the New York governor Andrew Cuomo's daily coronavirus briefing on Wednesday 6 May, the sombre grimace that has filled our screens for weeks was briefly replaced by something resembling a smile. "We are ready, we're all-in," the governor gushed. "We are New Yorkers, so we're aggressive about it, we're ambitious about it … We realise that change is not only imminent, but it can actually be a friend if done the right way." The inspiration for these uncharacteristically good vibes was a video visit from the former Google CEO Eric Schmidt, who joined the governor's briefing to announce that he will be heading up a panel to reimagine New York state's post-Covid reality, with an emphasis on permanently integrating technology into every aspect of civic life. "The first priorities of what we're trying to do," Schmidt said, "are focused on telehealth, remote learning, and broadband … We need to look for solutions that can be presented now, and accelerated, and use technology to make things better." Lest there be any doubt that the former Google chair's goals were purely benevolent, his video background featured a framed pair of golden angel wings.

UK Power Networks has successfully deployed its artificial intelligence (AI) 'smart' traffic lights in the UK. The smart system, called'autoGreen' makes automatic adjustments to traffic light signals in case of congestion, in order to allow maximum traffic flow during peak hours and while repair and installation work is being carried out. UK Power Networks trialled the system last year in Kent, before deploying it in the South East and East of England - it was noted to have brought down journey times by a'significant' margin, while also improving safety and air quality.

A new machine learning tool can calculate the energy required to make--or break--a molecule with higher accuracy than conventional methods. While the tool can currently only handle simple molecules, it paves the way for future insights in quantum chemistry. "Using machine learning to solve the fundamental equations governing quantum chemistry has been an open problem for several years, and there's a lot of excitement around it right now," says co-creator Giuseppe Carleo, a research scientist at the Flatiron Institute's Center for Computational Quantum Physics in New York City. A better understanding of the formation and destruction of molecules, he says, could reveal the inner workings of the chemical reactions vital to life. The team's tool estimates the amount of energy needed to assemble or pull apart a molecule, such as water or ammonia.

Intel and Penn Medicine are working on a huge, institution-spanning AI that will help identify brain tumors but without overstepping on strict medical privacy rules. The cross-location AI will use a technique known as "federated learning" as it spans 29 different healthcare and research institutions. Training artificial intelligences with data sets of illnesses, so that they can act as a filter on large numbers of cases, has been shown effective in a number of ways. However the downside is that for the most effective performance those data sets need to be considerable. An individual healthcare institution or research lab would likely struggle to feed a developing machine learning computer with all the information it requires.

The graph represents a network of 4,023 Twitter users whose tweets in the requested range contained "(Artificial Intelligence) OR #AI", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 14 May 2020 at 04:33 UTC. The requested start date was Thursday, 14 May 2020 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 1-day, 1-hour, 46-minute period from Tuesday, 12 May 2020 at 04:35 UTC to Wednesday, 13 May 2020 at 06:22 UTC.

Machine learning algorithms are now synonymous with finding patterns in data but not all patterns are suitable for statistics based data-driven techniques, for example when these patterns don't have explicitly labelled targets to learn from. In some cases, these patterns can be expressed precisely as a rule. Reasoning is the process of matching rule-based patterns or verifying that they don't exist in a graph. Because these patterns are found with deductive logic they can be found more efficiently and interpreted more easily than Machine Learning patterns which are induced from the data. This article will introduce some common patterns and how you can express them in the rule language, Datalog, using RDFox, a knowledge graph and semantic reasoning engine developed by Oxford Semantic Technologies.

NAGANO – Seiko Epson Corp., a major Japanese maker of printers and industrial robots, said Thursday it will make use of its paper recycling technology to start producing face masks from late May. Production will take place at two of its domestic plants and will eliminate the need to outsource masks for its employees. The company based in Nagano Prefecture will also donate 100,000 medical-grade masks, originally intended for internal use, to hospitals. It has also decided to donate 5,600 face shields, planned to be used by its employees in Japan and abroad, to the prefectural government to help ease medical supply shortages. The company has not yet decided whether it will sell any of the masks it produces to general consumers.

On Saturday, the US Air Force is expected to launch its secret space plane, X-37B, for a long-duration mission in low Earth orbit. The robotic orbiter looks like a smaller version of the space shuttle and has spent nearly eight of the past 10 years in space conducting classified experiments for the military. Almost nothing is known about what X-37B does up there, but ahead of its sixth launch the Air Force gave some rare details about its cargo. In addition to its usual suite of secret military tech, the X-37B will also host a few unclassified experiments during its upcoming sojourn in space. NASA is sending up two experiments to study the effects of radiation on seeds, and the US Air Force Academy is using the space plane to deploy a small research satellite.