The widespread use and increasing complexity of mission-critical and safety-critical systems at NASA and in the aerospace industry require advanced techniques that address these systems' specification, design, verification, validation, and certification requirements. The NASA Formal Methods Symposium (NFM) is a forum to foster collaboration between theoreticians and practitioners from NASA, academia, and industry. NFM's goals are to identify challenges and to provide solutions for achieving assurance for such critical systems. New developments and emerging applications like autonomous software for Unmanned Aerial Systems (UAS), UAS Traffic Management (UTM), advanced separation assurance algorithms for aircraft, and the need for system-wide fault detection, diagnosis, and prognostics provide new challenges for system specification, development, and verification approaches. Similar challenges need to be addressed during development and deployment of on-board software for both spacecraft and ground systems.

Scopio Labs, a leading provider of Full Field Morphology (FFM), announced that it was granted FDA clearance to market and sell its X100 with Full Field Peripheral Blood Smear (Full Field PBS) Application, unlocking the potential of in vitro hematology diagnosis. Full Field PBS is also available in Europe with CE mark certification granted earlier this year. Blood is one of the most foundational gateways to health information. Even with the adoption of digital tools, today's solutions do not showcase all required regions of interest in a PBS slide, only capturing snapshots of cells. To help improve diagnostic accuracy leveraging novel computer vision tools, Full Field PBS gives clinical laboratories an unprecedented ability to capture digital scans using advanced computational photography imaging and tailored AI tools.

An AI-powered computer analysis of the final 2020 presidential debate scored President Trump with the strongest performance on five out of seven topics. The analysis by VoiceVibes, a communication coaching software, graded the performance of Mr. Trump and Democratic challenger Joseph R. Biden at Thursday's debate based on vocal delivery or how professional and polished they sounded. TOP STORIES Lesley Stahl to Mike Pence: 'You have both insulted 60 Minutes' Robert Downey Jr. rips cancel culture as Chris Pratt labeled'White supremacist' Trump supporter U.S. has many files on Hunter Biden's money trail, congressional source says Mr. Biden scored highest on COVID-19 and immigration, according to the software. The winners for each topic were determined based on the vocal analysis of confidence and authenticity. Overall, Mr. Trump's best topic was health care and Mr. Biden's was immigration.

Armed militia stroll around London, picking fights where they please and shutting down small gatherings of masked protesters demanding their freedoms on street corners. In Watch Dogs Legion's future dystopian British capital, Brexit happened years ago, Scotland has seceded from the union, and the country has been overtaken by private, corporate interests who've wrested control from the government and framed a collective of hacker protesters, DeadSec, for a series of terrorist attacks. People are pissed off, and ready to rise up. You, the player, are the catalyst that makes that happen. Like Grand Theft Auto, Watch Dogs conjures a huge living city out of code, filled with thousands of individual characters who go about their lives, going to work, visiting their sister, driving around in the rain.

Indeed, it's now possible to impersonate practically anybody with astonishing verisimilitude, thanks to the artificial intelligence technology known as generative adversarial networks (GANs). Fortunately, deepfakes have not shown their ugly side in the US presidential election campaign that is now drawing to a close. No one has been able to point to any significant use of GANs to produce deceptive videos and thereby manipulate public opinion. Instead, GANs are increasingly popping up in socially beneficial applications, such as for photorealistic animation and live-action video post-production. As evidenced by several recent industry announcements, next-generation remote collaboration services are using GANs and other AI techniques to improve the quality of rendered streams while improving the productivity of participants on these calls.

Just as artificial intelligence (AI) and ML are being deployed in a wide variety of novel applications, threat actors can not only abuse the technology to …

The past few years has seen great advancement in the world of generative models (GANs), becoming one of the most promising approaches toward collecting all of the easily accessible open-source information available and using it to develop models and algorithms to analyze and understand. The below blog brings together a general explanation of GANs, alongside the newest papers, video presentations, application methods and more. For a model to be "Generative" must fit in a class of statistical models which contrast against discriminative models. Simply, a generative model is one that can generate new data after learning from the dataset. Therefore, "Generative" describes a class of statistical models that contrasts with discriminative models.

Once a dominion of science fiction (e.g., Star Trek,) facial recognition technology has not only caught up to us in reality this century, but awareness around its benefits and pitfalls has also risen with its heightened presence in the news over the last few months. We hope to shine some light on the reasons for this ascent and the myriad thoughts and actions it has raised. To be sure, all the complex issues, implications, and ethics surrounding facial recognition technology are far too important and expansive to cover in this piece. We also recognize there is much more worth exploring, and a variety of valid and informed views on the subject. Our aim is for this piece to be informative, unbiased, and thought-provoking as the topic of facial recognition technology continues to gain attention and relevance.

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The White House is in the final stretch of finishing guidance on how agencies in different sectors should regulate artificial intelligence (AI), according to a Wall Street Journal report on Wednesday (Oct. Chief Technology Officer Michael Kratsios said at the WSJ Tech Live virtual conference that the guidance is a follow-up to January's White House draft. The original draft consisted of 10 principles that outlined how agencies should approach AI in their respective industries. "We had a great, robust conversation with many stakeholders on it," Kratsios during a comment period. He added that the finished adaptation of the regulations should be completed soon.