The space projects have been dominated by government bodies until we saw the ambitious companies such as SpaceX and Blue Origin diving into this diverse area. These two are the most prominent names in the private space community and are often put on a face-off due to the similarity of its founders in other areas as well. Owned by two of the most powerful businessmen of all time -- Elon Musk and Jeff Bezos, they have been on the competition radar for their interest in the area of autonomous vehicles. Similarly, in the space segment, while the two companies might look quite similar in its attempts to explore space, the ideology and the approach of these companies vary quite significantly. But one thing cannot be denied that they both are developing large, reusable vehicles capable of carrying people and satellites across space. While we have often heard about SpaceX's missions and launches over the past few years, Blue Origin does not come out to be so ambitious in gaining traction.
The federal government continues its halting effort to field an enterprise cloud strategy, with Lt. Gen. Jack Shanahan, who leads the Defense Department's Joint AI Center (JAIC), commenting recently that not having an enterprise cloud platform has made the government's efforts to pursue AI more challenging. "The lack of an enterprise solution has slowed us down," stated Shanahan during an AFCEA DC virtual event held on May 21, according to an account in FCW. However, "the gears are in motion" with the JAIC using an "alternate platform" for example to host a newer anti-COVID effort. This platform is called Project Salus, and is a data aggregation that is able to employ predictive modeling to help supply equipment needed by front-line workers. The Salus platform was used for the ill-fated Project Maven, a DOD effort that was to employ AI image recognition to improve drone strike accuracy.
Each Fourth of July for the past five years I've written about AI with the potential to positively impact democratic societies. I return to this question with the hope of shining a light on technology that can strengthen communities, protect privacy and freedoms, or otherwise support the public good. This series is grounded in the principle that artificial intelligence can is capable of not just value extraction, but individual and societal empowerment. While AI solutions often propagate bias, they can also be used to detect that bias. As Dr. Safiya Noble has pointed out, artificial intelligence is one of the critical human rights issues of our lifetimes.
China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars. The move has led--at least in the West--to warnings of a global AI arms race and concerns about the growing reach of China's authoritarian surveillance state. But treating China as a "villain" in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government's approach to AI that are highly concerning and rightly should be condemned, it's important that this does not cloud all analysis of China's AI innovation.
Want to be a part of an elite team where our innovative technical solutions are delivered to customers that advance the state of the art while addressing long-term problems of importance to national security? At our Leidos' Multi-Spectrum Warfare Research and Analytics Systems (MSWRAS) Division, an organization in the Leidos Innovation Center (LInC), we are looking for you, our next Scientist who specializes in remote sensing data analytics. Join our team of Ph.D. level peers in designing and developing advanced technology-based solutions for contract research and development projects working in our Arlington, VA office. Fun roles you will have in this job: Describe instances of successful, proven, and demonstrable experience contributing to the technical work as part of cross-discipline teams in the development and integration of software-based solutions for competitive, contract-based applied research programs Work with teams composed of members from industry, small businesses, and academic-based researchers and should have experience working on projects focused on multiple technical fields such as machine learning, artificial intelligence, engineering, and software development and integration Describe how the work products to which they contributed had solved customers' problems in such domains as energy, health, and national security or in the commercial sector Work within the MSWRAS Division and across the LInC, performing basic and applied contract research and development projects both leading and working under the guidance of senior scientists and engineers. Processing, interpreting and analyzing large volumes of data collected by remote sensing platforms but may also include other types of phenomenological data such as field measurements, or weather data Independently design and undertake new research as well as partner in a team environment across organizations Contribute to the development of creative and innovative R&D approaches to solving major remote sensing analytics challenges and work with potential sponsors (customers or internal champions) to secure funding for new research efforts based on those topics Contribute to the productivity of teams composed of fellow researchers, data scientists, data engineers, and software engineers to execute complex R&D programs Under the guidance of a senior scientist or engineer, design and develop or integrate secure and scalable applications that are part of broader solutions, that are applicable across multiple domains.
The Sisense analytics platform is known for its augmented analytics capabilities and ease of use, and as it moves forward it will do so with a new leader in charge of its product development. Just over a year after its acquisition of Periscope Data, a purchase that added capabilities aimed at data scientists to the features geared toward business users Sisense was already know for, the New York-based vendor is focused on third-generation analytics in which AI and business intelligence embedded throughout the workflow will be prominent. Most recently, Sisense updated its analytics platform with new natural language query capabilities and introduced Knowledge Graph, a graph analytics engine the vendor developed that was trained on more than 650 billion past analytic events and informs the machine learning capabilities of the query tool. Now, to help shape its vision, Sisense has added Ashley Kramer as its first chief product officer. Kramer began her career as a software engineering manager at NASA.
Drug discovery is a hugely expensive and often frustrating process. Medicinal chemists must guess which compounds might make good medicines, using their knowledge of how a molecule's structure affects its properties. They synthesize and test countless variants, and most are failures. "Coming up with new molecules is still an art, because you have such a huge space of possibilities," says Barzilay. "It takes a long time to find good drug candidates." By speeding up this critical step, deep learning could offer far more opportunities for chemists to pursue, making drug discovery much quicker.
The Trump administration has reportedly awarded a contract to a California-based tech startup to set up hundreds of "autonomous surveillance towers" along the U.S.-Mexico border to aid its immigration enforcement efforts. U.S. Customs and Border Protection (CBP) announced on Thursday that the towers, which use artificial intelligence and imagery to identify people and vehicles, were now a "program of record" for the agency and that 200 would be deployed along the southern border by 2022. CBP did not mention the contract in its announcement, though the Washington Post reported that the effort includes a five-year agreement with Anduril Industries, a tech startup backed by investors such as Peter Thiel. Anduril executives told the Post that the deal is worth hundreds of millions of dollars. The company, which specializes in AI and other technologies, is valued at $1.9 billion, according to Bloomberg News.
The growth potential of the data economy is mind-blowing. In Europe alone, the figures and forecasts are eye-catching, to say the least. The European Commission expects the value of the data economy to rise to €829 billion by 2025, up from €301 billion in 2018. Focusing on the headline economic figures alone overlooks the enormous potential to use data to create lasting social change and improve the personal and professional lives of millions of European citizens. The term digital economy is a catch-all for a wide range of digital transformation activities.
Researchers at the U.S. Army Combat Capabilities Development Command's Army Research Laboratory say this may be changing as they endeavor to design computers inspired by the human brain's neural structure. As part of a collaboration with Lehigh University, Army researchers have identified a design strategy for the development of neuromorphic materials. "Neuromorphic materials is a name given to the material categories or combination of materials that provide both computing and memory capabilities in devices," said Dr. Sina Najmaei, a research scientist and electrical engineer with the laboratory. Najmaei and his colleagues published a paper, Dynamically reconfigurable electronic and phononic properties in intercalated Hafnium Disulfide (HfS2), in the May 2020 issue of Materials Today. The neuromorphic computing concept is an in-memory solution that promises orders of magnitude reductions in power consumption over conventional transistors, and is suitable for complex data classification and processing.