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The Sensors Division focuses on advanced sensor system technology, from airborne and surface-based radar and electronic warfare to underwater acoustics, EO/IR and hyperspectral imaging. This position is with the Electronic Warfare and Novel Capabilities Group in the STR Sensors Division. We focus on technology development for advanced sensor systems, in the areas of airborne/surface-based radar, electronic warfare, data communications, and hyperspectral imaging. We develop algorithmic and hardware components, conduct experiment campaigns, and prototype systems. Design, build, and test roles within the Group include RF analog/digital hardware, advanced electronic warfare algorithms and techniques, signal processing and machine learning algorithms, cognitive electronic warfare applications, tracking/fusion, and real-time embedded processor implementation.
Netflix has an excellent international library, including German sci-fi gem Dark -- one of the best series on Netflix full stop. This adult animated anthology series spans a range of genres, with plenty of episodes hitting the Black Mirror comparison button. Robots in a post-apocalyptic city, farmers piloting mech suits and a space mission gone wrong all pop up in the first season. While the episodes can be hit and miss (some have been criticized for their treatment of women), you'll find plenty of thought-provoking and impressive animation. This apocalyptic sci-fi from Belgium will probably turn you off from flying any time soon.
This partnership will help health systems address the increasing volume of medical images and the worldwide radiologist labor shortage. Integration of Boneview into Aidoc's AI platform will give many more clinicians access to a tool to help them identify fractures in limbs, pelvis, thoracic and lumbar spine, and rib cage. Aidoc's end-to-end AI platform already includes numerous third-party AI vendors including Imbio, Riverain, Subtle, Icometrix and ScreenPoint. Over 152 million X-rays are performed every year in the US. Although there are about 37,000 radiologists in the US, they are not evenly distributed.
As artificial intelligence gets better at performing tasks once solely in the hands of humans, like driving cars, many see teaming intelligence as a next frontier. In this future, humans and AI are true partners in high-stakes jobs, such as performing complex surgery or defending from missiles. But before teaming intelligence can take off, researchers must overcome a problem that corrodes cooperation: humans often do not like or trust their AI partners. MIT Lincoln Laboratory researchers have found that training an AI model with mathematically "diverse" teammates improves its ability to collaborate with other AI it has never worked with before, in the card game Hanabi. Moreover, both Facebook and Google's DeepMind concurrently published independent work that also infused diversity into training to improve outcomes in human-AI collaborative games.
A century ago, English mathematician Lewis Fry Richardson proposed a startling idea for that time: constructing a systematic process based on math for predicting the weather. In his 1922 book, "Weather Prediction By Numerical Process," Richardson tried to write an equation that he could use to solve the dynamics of the atmosphere based on hand calculations. It didn't work because not enough was known about the science of the atmosphere at that time. "Perhaps some day in the dim future it will be possible to advance the computations faster than the weather advances and at a cost less than the saving to mankind due to the information gained. But that is a dream," Richardson concluded.
May 11 (Reuters) - The science-fiction is harder to see in Google's second try at glasses with a built-in computer. A decade after the debut of Google Glass, a nubby, sci-fi-looking pair of specs that filmed what wearers saw but raised concerns about privacy and received low marks for design, the Alphabet Inc (GOOGL.O) unit on Wednesday previewed a yet-unnamed pair of standard-looking glasses that display translations of conversations in real time and showed no hint of a camera. The new augmented-reality pair of glasses was just one of several longer-term products Google unveiled at its annual Google I/O developer conference aimed at bridging the real world and the company's digital universe of search, Maps and other services using the latest advances in artificial intelligence. "What we're working on is technology that enables us to break down language barriers, taking years of research in Google Translate and bringing that to glasses," said Eddie Chung, a director of product management at Google, calling the capability "subtitles for the world." Selling more hardware could help Google increase profit by keeping users in its network of technology, where it does not have to split ad sales with device makers such as Apple Inc (AAPL.O)and Samsung Electronics CO (005930.KS)that help distribute its services.
When prepping for a job interview, the first place I go is Google. After all, the company's search engine is a launchpad to learn about your potential company, workshop possible questions, and walk away feeling knowledgable and prepared. Now, Google is stepping up its interview game even further--by implementing an interviewing tool powered by artificial intelligence. Before you call your parents for interview advice, check out Google's solution. This piece of artificial intelligence is called "Interview Warmup," a simple yet powerful program you can use to practice common interview questions for different professions.
Artificial intelligence (AI) algorithms trained on real astronomical observations now outperform astronomers in sifting through massive amounts of data. AI helps them to find new exploding stars, identify new types of galaxies and detect the mergers of massive stars, accelerating the rate of new discovery in the world's oldest science. But AI, also called machine learning, can reveal something deeper, University of California, Berkeley, astronomers found: unsuspected connections hidden in the complex mathematics arising from general relativity -- in particular, how that theory is applied to finding new planets around other stars. In a paper appearing this week in the journal Nature Astronomy, the researchers describe how an AI algorithm developed to more quickly detect exoplanets when such planetary systems pass in front of a background star and briefly brighten it -- a process called gravitational microlensing -- revealed that the decades-old theories now used to explain these observations are woefully incomplete. In 1936, Albert Einstein himself used his new theory of general relativity to show how the light from a distant star can be bent by the gravity of a foreground star, not only brightening it as seen from Earth, but often splitting it into several points of light or distorting it into a ring, now called an Einstein ring.
The Pentagon has tapped artificial intelligence ethics and research expert Diane Staheli to lead the Responsible AI (RAI) Division of its new Chief Digital and AI Office (CDAO), FedScoop confirmed on Tuesday. In this role, Staheli will help steer the Defense Department's development and application of policies, practices, standards and metrics for buying and building AI that is trustworthy and accountable. She enters the position nearly nine months after DOD's first AI ethics lead exited the Joint Artificial Intelligence Center (JAIC), and in the midst of a broad restructuring of the Pentagon's main AI-associated components under the CDAO. "[Staheli] has significant experience in military-oriented research and development environments, and is a contributing member of the Office of the Director of National Intelligence AI Assurance working group," Sarah Flaherty, CDAO's public affairs officer, told FedScoop.