As Future Vertical Lift Gets Underway, Army Eyeing Chinook Replacement

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  March 29, 2019 | International, Other Defence

  DARPA: Designing Chips for Real Time Machine Learning

  The current generation of machine learning (ML) systems would not have been possible without significant computing advances made over the past few decades. The development of the graphics-processing unit (GPU) was critical to the advancement of ML as it provided new levels of compute power needed for ML systems to process and train on large data sets. As the field of artificial intelligence looks towards advancing beyond today's ML capabilities, pushing into the realms of “learning” in real-time, new levels of computing are required. Highly specialized Application-Specific Integrated Circuits (ASICs) show promise in meeting the physical size, weight, and power (SWaP) requirements of advanced ML applications, such as autonomous systems and 5G. However, the high cost of design and implementation has made the development of ML-specific ASICs impractical for all but the highest volume applications. “A critical challenge in computing is the creation of processors that can proactively interpret and learn from data in real-time, apply previous knowledge to solve unfamiliar problems, and operate with the energy efficiency of the human brain,” said Andreas Olofsson, a program manager in DARPA's Microsystems Technology Office (MTO). “Competing challenges of low-SWaP, low-latency, and adaptability require the development of novel algorithms and circuits specifically for real-time machine learning. What's needed is the rapid development of energy efficient hardware and ML architectures that can learn from a continuous stream of new data in real time.” DARPA's Real Time Machine Learning (RTML) program seeks to reduce the design costs associated with developing ASICs tailored for emerging ML applications by developing a means of automatically generating novel chip designs based on ML frameworks. The goal of the RTML program is to create a compiler – or software platform – that can ingest ML frameworks like TensorFlow and Pytorch and, based on the objectives of the specific ML algorithms or systems, generate hardware design configurations and standard Verilog code optimized for the specific need. Throughout the lifetime of the program, RTML will explore the compiler's capabilities across two critical, high-bandwidth application areas: 5G networks and image processing. “Machine learning experts are proficient in developing algorithms but have little to no knowledge of chip design. Conversely, chip designers are not equipped with the expertise needed to inform the design of ML-specific ASICs. RTML seeks to merge these unique areas of expertise, making the process of designing ultra-specialized ASICs more efficient and cost-effective,” said Olofsson. Based on the application space's anticipated agility and efficiency, the RTML compiler provides an ideal platform for prototyping and testing fundamental ML research ideas that require novel chip designs. As such, DARPA plans to collaborate with the National Science Foundation (NSF) on this effort. NSF is pursuing its own Real Time Machine Learning program focused on developing novel ML paradigms and architectures that can support real-time inference and rapid learning. After the first phase of the DARPA RTML program, the agency plans to make its compiler available to NSF researchers to provide a platform for evaluating their proposed ML algorithms and architectures. During the second phase of the program, DARPA researchers will have an opportunity to evaluate the compiler's performance and capabilities using the results generated by NSF. The overall expectation of the DARPA-NSF partnership is to lay the foundation for next-generation co-design of RTML algorithms and hardware. “We are excited to work with DARPA to fund research teams to address the emerging challenges for real-time learning, prediction, and automated decision-making,” said Jim Kurose, NSF's head for Computer and Information Science and Engineering. “This collaboration is in alignment with the American AI Initiative and is critically important to maintaining American leadership in technology and innovation. It will contribute to advances for sustainable energy and water systems, healthcare logistics and delivery, and advanced manufacturing.” RTML is part of the second phase of DARPA's Electronics Resurgence Initiative (ERI) – a five-year, upwards of $1.5 billion investment in the future of domestic, U.S. government, and defense electronics systems. As a part of ERI Phase II, DARPA is supporting domestic manufacturing options and enabling the development of differentiated capabilities for diverse needs. RTML is helping to fulfill this mission by creating a means of expeditiously and cost-effectively generating novel chip designs to support emerging ML applications. Interested proposers will have an opportunity to learn more about the RTML program during a Proposers Day, which will be held at 675 North Randolph Street, Arlington, VA 22203 on Tuesday April 2, 2019 from 09:00 am – 03:00 pm EDT. Additional information about the event and registration are found here: https://www.fbo.gov/index?s=opportunity&mode=form&id=29e4d24ce31d2bf276a2162fae3d11cd&tab=core&_cview=0 Additional details on the RTML program are in the Broad Agency Announcement, published to fbo.gov: https://www.fbo.gov/index.php?s=opportunity&mode=form&id=a32e37cfad63edcba7cfd5d997422d93&tab=core&_cview=0 https://www.darpa.mil/news-events/2019-03-21

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  May 13, 2020 | International, Naval, C4ISR

  Failure to communicate: US Navy seeks faster data transfers amid Arctic ice

  Andrew Eversden WASHINGTON — Research in the Arctic Ocean is no small feat. The area can prove inaccessible at times, and sensors can fail to communicate data from under the ice or get crushed by slabs of ice. But with the Arctic getting warmer and ice melting at an accelerated rate, the U.S. Navy is preparing to operate in newly available waterways. To do that effectively, the service knows it will take intense research to create durable, innovative solutions that can withstand harsh conditions, while also relaying data to researchers. “If the Navy's thinking about having to run operations up there with submarines, surface vessels and aircraft, you really need to understand that operational environment,” Scott Harper, the Office of Naval Research's program manager for Arctic and global prediction, told Defense News in a May 4 interview. “Where is that sea ice and how quickly is it retreating? And what is it doing to the upper water column in the ocean? "To really understand all that, you need to have a lot of observations.” Navy and academic researchers are working together to improve the service's forecasting models in the Arctic. The Navy currently has research buoys, sensors and other technology floating in the water to track a variety of metrics: waves, atmospheric and water circulation, sea ice thickness and cover, speed at which the ice moves, and several other factors. All those metrics factor into Arctic forecasting. In order to improve its forecasting capabilities, the Navy needs to improve its numerical models, or complex equations used in predictions. But to do that, the service needs more up-to-date data. “These numerical models are kind of like balancing your checkbook,” Harper said. “You need to start with what your current checking account balances [to[ if you're going to predict what it's going to be at the end of the month. And so even if you had a perfect numerical model that you could use to make a forecast, if you don't know what the conditions are right now, you're not going to be able to forecast what the future state is going to be.” To do this, the Navy wants to more quickly collect data through an effort called the Arctic Mobile Observing System, or AMOS. The program aims to create near-real-time data transmission of the sea condition under the ice, and communicate that information to the Navy via satellite. “You have satellites that can look down at the surface of the Arctic Ocean and the sea ice conditions,” Harper said. “But what we don't have [is] the ability to look under the ice and understand what the ocean conditions are, and that's what we're really trying to enable with Arctic Mobile Observing System prototype.” The AMOS program has deployed gliders underneath the sea that are collecting and storing data about the oceanic conditions under the ice, and tracking the location of frozen water using acoustics. In a few months, Harper said, researchers will send an icebreaker to the Arctic and gather the data collected by the gliders. The Office of Naval Resarch, however, would like to bypass the multi-month delay involved in collected the data. To do so, the office plans to enable two-way communication so underwater sensors can communicate data via floating buoys in the ice that, in turn, communicate the data via satellites back to the Naval Oceanographic Office. The project is currently two years into the five-year project. According to the project website, it's slated to end in fiscal 2023 with the recovery and evaluation of the initial prototype in the late summer of 2023. Harper said the project's biggest success has been the navigation system that's currently working underneath the ocean surface. “The fact that we can put sensors out that will know where they are without having to come to the surface to get a GPS fix — because they can't come to the surface because there's sea ice there for nine months out of the year," he said. "That's a big win.” Another critical component to the real-time data collection are the buoys that ultimately must be able to survive the cruel nature of Arctic ice. The AMOS team has deployed prototypes of “ice-hardened” buoys that survived “multiple months” in the Arctic environment, Harper said, paving the way for a fully equipped communications buoy that can talk with underwater sensors. “You can go out there and you can put your sensors in the ice, but a lot of times they'll fail,” Harper said. “And they'll fail because they'll get crushed in the ice or tipped over or toppled by changing ice conditions. And so the ability to deploy a buoy that is robust enough to survive the sea ice is one of the technological hurdles to doing this.” https://www.c4isrnet.com/smr/frozen-pathways/2020/05/11/failure-to-communicate-us-navy-seeks-faster-data-transfers-amid-arctic-ice/

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  October 4, 2018 | International, Aerospace

  Boeing Wins $63M Navy Deal for F/A & E/A-18 Aircraft Support

  By Zacks Equity Research, Zacks.com The Boeing Company BA recently won a $62.7-million contract for providing inspections, Inner Wing Panel (IWP) modifications, and repairs for the F/A-18 E/F and EA-18G aircraft. Such designated efforts are expected to restore aircraft and IWP service life projections to new design specifications. Work related to the deal will be majorly carried out in Jacksonville, FL; St. Louis, MI; and Lemoore, CA. The entire task related to the deal is expected to get completed in September 2019. The deal was awarded by the Naval Air Systems Command, Patuxent River, Maryland. A Brief Note on F/A-18 and E/A-18 Boeing's F/A-18 Block III Super Hornet is a twin-engine, supersonic, all weather multirole fighter jet. The U.S. Navy's tactical and air superiority aircraft is capable of performing virtually every mission in the tactical spectrum, including air superiority, day/night strike with precision-guided weapons, fighter escort, close air support, suppression of enemy air defenses, maritime strike, reconnaissance, forward air control and tanker missions. Whereas, the EA-18G Growler is the most advanced airborne electronic attack (AEA) platform, which operates from either an aircraft carrier or from land-bases. What's Favoring Boeing? Boeing, being one of the major players in the defense business, stands out among its peers by virtue of its broadly diversified programs, strong order bookings and solid backlog. Furthermore, the company's expertise lies in programs related to wide variety of aircraft components, repairs and modification works. Considering Boeing's combat-proven aerospace programs and associated services along with the rapidly growing need for military aircraft in light of the enhancing geopolitical uncertainties worldwide, the company witnesses a solid inflow of orders from Pentagon. These contract wins, in turn, boost top-line growth for the company's defense business segment. Evidently, in second-quarter 2018, revenues at the Boeing Defense, Space & Security (BDS) segment, which manufactures military jets like F/A-18, EA-18 Growler and its related components, increased 9% year over year to $5.59 billion. In line with this, we may expect the latest contract win to help this unit deliver similar top-line performance, in coming quarters. Meanwhile, toward the end of June 2018, the U.S. Senate approved the fiscal 2019 defense budget that provisions for major war fighting investments worth $21.7 billion for aircraft. Boeing, being the largest aircraft manufacturer in the United States, will surely be a significant beneficiary from the budget, which further includes an investment plan of $2 billion for procuring 24 F/A-18E/F aircraft. Such inclusions reflect solid growth prospects for the BDS segment, which, in turn, are likely to boost Boeing's profit margin. Price Movement Boeing's stock has gained 53.4% in the past 12 months compared with the industry 's growth of 25.1%. The outperformance was primarily led by the robust worldwide demand for its commercial aircraft and military jets. Full article: https://www.nasdaq.com/article/boeing-wins-63m-navy-deal-for-fa-ea-18-aircraft-support-cm1032450