Indian committee OKs $4 billion buy of BrahMos missiles, more tech

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  September 19, 2018 | International, C4ISR

  Differentiating a port from a shipyard is a new kind of problem for AI

  By: Daniel Cebul It's well known that satellites and other intelligence, surveillance and reconnaissance platforms collect more data than is possible for humans to analyze. To tackle this problem, the Intelligence Advanced Research Projects Activity, or IARPA, conducted the Functional Map of the World (fMoW) TopCoder challenge from July 2017 through February 2018, inviting researchers in industry and academia to develop deep learning algorithms capable of scanning and identifying different classes of objects in satellite imagery. IARPA curated a dataset of 1 million annotated, high-resolution satellite images aggregated using automated algorithms and crowd sourced images for competitors to train their algorithms to classify objects into 63 classes, such as airports, schools, oil wells, shipyards, or ports. Researchers powered their deep learning algorithms by combining large neural networks, known as convolutional neural networks (CNNs), and computers with large amounts of processing power. The result was a network that, when fed massive amounts of training data, can learn to identify and classify various objects from satellite imagery. By combining a number of these networks into what is called an ensemble, the algorithm can judge the results from each CNN to produce a final, improved result that is more robust than any single CNN. This is how a team from Lockheed Martin, led by Mark Pritt, designed their deep learning algorithm for the challenge. Pritt explained to C4ISRNET, that he and his team developed their CNN using machine learning software and framework from online open source software libraries, such as Tensor Flow. Earning a top five finish, the algorithm designed by Pritt's team achieved a total accuracy of 83 percent, and was able to classify 100 objects per second. Pritt said that with fully functioning algorithm, this software could take an image recognition task that takes a human an hour to complete and reduce the process to a few seconds. The team's algorithm excelled at identifying classes with distinctive features, and successfully matched nuclear power plants, tunnel openings, runways, tool booths, and wind farms with accuracies greater than 95 percent, but struggled with more indiscreet classes such as shipyards and ports, hospitals, office buildings, and police stations. “Usually when you develop an algorithm its nice to see where it succeeds, but you actually learn the most where you look at where the algorithm fails or it doesn't do well,” Pritt said. In trying to decipher why the algorithms struggled, Pritt said the competitors suggested that some objects simply don't have any distinguishing features from the point of view of a satellite image for the algorithms to recognize. “Maybe the most important ingredient you need for these new types of algorithm to work is the dataset because these algorithms require a great amount of data to train on,” Pritt explained. “It's kind of analogous to the way a human will learn in childhood how to recognize things. You need lots of examples of what those things are and then you can start to generalize and make your own judgments,” he said. But even with large amounts of training data that is correctly labeled, it is also possible the deep learning technology of today cannot reach the higher levels of intelligence to recognize nuanced differences. For example, Lockheed Martin's algorithm confused shipyards and ports 56 percent of the time. Pritt said that people “look at an image and they can tell that it's a port or a shipyard, they are usually looking at very subtle things such as if there is a ship in dry dock or if there is a certain type of crane present. They are looking for details in the image that are maybe higher level or more complicated than what these deep learning algorithms can do right now.” However, the fact that these algorithms cannot do everything should not dismiss the significant contribution they could provide to the defense and intelligence community. Hakjae Kim, IARPA's program manager for the fMoW challenge, said the benefits of this technology could extend far beyond faster image processing. “I want to look at it more in the perspective that we can do things we weren't able to do before,” Kim said. “Because its technology that we are now able to do x, y and z, there are more applications you can create because with the human power it is just impossible to do before.” Kim and Pritt stressed managing expectations for CNN-based artificial intelligence. “This is a real technology that will work, but it also has limitations. I don't want to express this technology as a magic box that will just solve everything magically,” Kim said. “I don't want the users in the field to get disappointed by the initial delivery of this technology and say 'Oh, this is another technology that was oversold and this is not something we can use," he added. Part of managing our expectations for AI requires recognizing that although intelligence is in the name, this technology does not think and reason like humans. “A lot of the time we think that because we use the term AI, we tend to think these algorithms are like us, they are intelligent like us,” Pritt said. “And in someways they seem to mimic our intelligence, but when they fail we realize ‘Oh, this algorithm doesn't really know anything, [it] doesn't have any common sense.'” So how are IARPA and Lockheed Martin working to improve their algorithms? For IARPA, Kim's team is working on updating and maintaining their dataset to ensure algorithms have the most up to date information to train on, ultimately making the CNN-based algorithms easier to trust. “[S]ubtle changes in the area mess up the brains of the system and that system will give you a totally wrong answer,” Kim explained. “So we have planned to continuously look over the area and make sure the algorithm we are developing and reassessing for the government to test on and use to be robust enough for their application," he furthered. Work is also underway at American universities. Kim described how a team of researchers at Boston University are using the fMoW dataset and tested algorithms to create heat maps that visualize what part of the image algorithms are using to classify objects. They've found that sometimes it is not the object itself, but clues surrounding the object that aid most in classification. For example a “windmill that actually shows a shadow gives a really good indicator of what that object is,” Kim said. “Shadows show a better view of the object. A shadow is casting the side view of the object over on the ground, so [BU's heat map algorithm] actually points out the shadow is really important and the key feature to make the object identified as a windmill.” But don't expect these algorithms to take away the jobs of analysts any time soon. “I think you still need a human doing the important judgments and kind of higher level thinking,” Pritt said. “I don't think AI will take away our jobs and replace humans, but I think what we have to do is figure out how to use them as a tool and how to use them efficiently, and that of course requires understanding what they do well and what they do poorly," he concluded. https://www.c4isrnet.com/intel-geoint/2018/09/18/differentiating-a-port-from-a-shipyard-is-a-new-kind-of-problem-for-ai

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  May 13, 2020 | International, Aerospace

  How the US Air Force is assembling its northernmost F-35 squadron amid a pandemic

  By: Valerie Insinna WASHINGTON — The COVID-19 pandemic could make it more difficult for the U.S. Air Force's newest F-35 squadron to organize its personnel and jets on schedule. On April 21, the 356th Fighter Squadron at Eielson Air Force Base, Alaska, became the service's northernmost fighter squadron after receiving its first two F-35s. Pilots began flying those jets for training three days later, and another four F-35s on loan from Hill Air Force Base in Utah flew to Alaska on April 27. But a couple key challenges could hamper the assemblage of the new squadron, said Col. Benjamin Bishop, commander of the base's 354th Fighter Wing. “We're actually on timeline,” he told Defense News in an exclusive interview on April 28. “We have the pilots and maintainers already here to support operations throughout the summer. However, as you know, the Department of Defense has put a stop-movement order through [June 30], and that is something we're working through on a case-by-case basis.” Under the current order, pilots and maintainers who are moving through the training pipeline have been granted a blanket exception to transfer to Eielson. But more experienced pilots, maintainers and support personnel coming from an operational base like Hill Air Force Base will need to receive an exception. Getting additional F-35s to Eielson could also be an obstacle, as Lockheed Martin assesses whether it must slow down deliveries of the F-35 due to disruptions to its supply chain. In a statement to Defense News, Lockheed spokesman Brett Ashworth could not say whether the company was on track to deliver F-35s to Eielson on schedule. “Lockheed Martin continues to work with our suppliers daily to determine the impacts of COVID-19 on F-35 production,” he said. “We are analyzing impacts at this time and should have more detail in the coming weeks.” If the coronavirus pandemic delays the pace of F-35 deliveries to Eielson, the squadron will have to mitigate the shortfall in jets, Bishop said. “Currently, we're at a good pace on the road to readiness for our F-35 program here, and we'll continue to adapt and adjust to bring this mission capability to its full potential in the Indo-Pacific theater,” he noted. Despite COVID-19 and the potential logistical challenges involved in sending people and F-35s to Eielson, day-to-day training operations have continued as normal, said Col. James Christensen, 356th Fighter Squadron commander. Having six F-35s on base allows maintainers to use the jets for training while also maximizing flight hours for the eight pilots currently in the 356th. “We still do the mission the way we always have. We have the masks and the wipe procedures and social distancing,” Christensen said. “So [we're] being creative but still being able to get the mission done.” There are strategic benefits to being the U.S. Air Force's northernmost fighter squadron, starting with access. With support from an aerial refueling tanker, the F-35s at Eielson can reach and target any location in Europe or the Asia-Pacific, Bishop said. And even the harsh climate of Eielson has its perks. It's a short flight away from the Joint Pacific Alaska Range Complex, the Defense Department's largest instrumented training range, with 77,000 square miles of airspace, according to the 354th Fighter Wing. “The F-35 is going to be able to fly in that airspace, but they're not going to be alone,” Bishop said. F-35s training in that area will regularly be joined by F-22s based at Joint Base Elmendorf-Richardson in Anchorage, as well as the F-16s in Eielson's 18th Aggressor Squadron that simulate enemy combat jets. “You're going to see amazing fifth-generation tactics and integration tactics emerge,” he said. Russia is investing in its Arctic infrastructure, and the U.S. military must make its own improvements to how it operates from and trains in the region, said Gen. Terrence O'Shaughnessy, who leads U.S. Northern Command and the North American Aerospace Defense Command. “It's great to see some of the additional forces that are going in, whether it's the F-35s going to Eielson, whether it's the work of the Coast Guard to develop icebreakers,” he said during a May 4 event. “These are all relevant things for us to be able to operate in the Arctic. And that is absolutely, to me, key to our ability to defend ourselves.” As the 356th stands up and becomes combat-ready, it will participate in the next Red Flag-Alaska, a multinational air-to-air combat training exercise slated to be held this August. The squadron is also looking for opportunities to deploy around the Asia-Pacific so that pilots can acclimate themselves to the long geographical distances that characterize the region, Christensen said. “Everyone is excited just to have F-35s here because of the awesome training we can do, but we're also thinking about at some point we have to project this air power out into the Indo-Pacific theater as a combat force. And transitioning everyone, including the wing and including [Pacific Air Forces] — they all have to adjust the mission of Eielson,” he said. Unlike other fighter bases, which usually swap out existing aircraft of existing squadrons with new jets, the two F-35 squadrons coming to Eielson aren't replacing anything, and infrastructure needs to be built to accommodate the anticipated growth in both people and aircraft. When the first members of the 356th Fighter Squadron arrived on base in July 2019, Eielson was home to about 1,750 active-duty personnel, Bishop said. By December 2021, that number is expected to double, with the addition of about 1,500 airmen. In that time, 54 F-35s will be delivered to the base for a total of two squadrons — a notable increase from the 30 F-16s and KC-135s previously at Eielson. An estimated $500 million will be spent on military construction to support the buildup at Eielson, including new operations buildings, a simulator building, heated hangars and other maintenance facilities, and a new cafeteria. A total of 41 facilities will be either built or refurbished with that funding, with 29 of those projects finished and others still under construction to support a second F-35 squadron, Bishop said. And everything — from constructing new facilities to maintaining runways — is tougher in the subzero temperatures of the Arctic. “Early on in this job, I learned that there are two seasons in Alaska,” Bishop said. “There's winter and construction season, with the former a lot longer than the latter. From a beddown perspective, how you put your construction plan together, you have to maneuver around that season.” “In order to maintain efficiency of fighter operations up here, one of the things we did is we built walled weather shelters for our aircraft, so all of our aircraft are actually housed in weather shelters," he added. "That's not necessarily for the aircraft. That's more for the maintainers because having that insulated and heating facility, now you can do maintenance around the clock.” Corrected at 5/12/20 at 2:53 p.m. with the correct size of the JPARC, which was recently expanded to 77,000 square miles of airspace. https://www.defensenews.com/smr/frozen-pathways/2020/05/11/how-the-us-air-force-is-assembling-its-northernmost-f-35-squadron-amid-a-pandemic/

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  February 15, 2024 | International, Land

  US Army calls halt to keystone FARA programme