ECS Federal LLC, Fairfax, Virginia, was awarded a $78,725,114 modification (P00003) to contract W911QX-18-C-0037 for machine learning and computer vision engineering. Work will be performed in Fairfax, Virginia, with an estimated completion date of July 16, 2022. Fiscal year 2018 and 2019 research, development, test and evaluation funds in the amount of $35,847,000 were obligated at the time of the award. U.S. Army Contracting Command, Aberdeen Proving Ground, Maryland, is the contracting activity.
The U.S. Cyber Command has released a list of 39 challenge problems fitting under 12 categories: vulnerabilities, malware, analytics, implant, situational awareness, capability development, persona, hunt, mission management, attack, security and blockchain.
The Navy is seeking advanced cybersecurity solutions based on artificial intelligence and machine learning technologies, the Naval Information Warfare Systems Command announced in a recent statement.
The Command, known now as NAVWAR, and the Program Executive Office for Command, Control, Communications, Computers and Intelligence (PEO C4I) are co-sponsoring the so-called Artificial Intelligence Applications to Autonomous Cybersecurity Challenge (AI ATAC).
Hughes Network Systems LLC, Germantown, Maryland, was awarded an $11,823,659 cost-plus-fixed-fee contract for the research and development effort to research solutions, prototype products and demonstrate solutions that include machine learning to improve transport and network performance availability and reliability. One bid was solicited with one bid received. Work will be performed in Germantown, Maryland, with an estimated completion date of December 30, 2023. Fiscal year 2019 research, development, test and evaluation funds in the amount of $1,863,123 were obligated at the time of the award. U.S. Army Contracting Command, Aberdeen Proving Ground, Maryland, is the contracting activity (W56KGU-19-C-0016).
Artificial intelligence and machine learning techniques could help information and network defenders recognize patterns of potential attackers so their next moves can be proactively blocked. In addition, cyber tools enhanced with these capabilities could provide a much more detailed picture of the cyber battlefield and increase the potential of success in a cyber campaign. This knowledge would complement the kinetic battlefield and could permit war planners to choose the appropriate mix of cyber and kinetic operations.
Rekor Systems, Inc. has announced that it will provide automatic license plate recognition (ALPR) solutions to the U.S. Defense Department. The contract with the department is for the purchase of 200 licenses to use Rekor's machine learning-enabled vehicle recognition system powered by the company’s OpenALPR software.
The Defense Security Service (DSS) and Defense Information Systems Agency (DISA) have awarded nearly $75 million to Perspecta Enterprise Solutions LLC of Herndon, Virginia, to help reform and modernize the security clearance personnel vetting processes and develop the National Background Investigation Service (NBIS) information technology system.
Asked which technology will be most critical to artificial intelligence in the coming years, experts agree: artificial intelligence, hands down.
Two experts from academia and industry—Mathew Gaston, director of the Emerging Technology Center at the Carnegie Mellon University Software Engineering Institute, and Fletcher Previn, chief information officer at IBM Corporation—participated in a fireside chat at the AFCEA TechNet Cyber 2019 conference and predicted artificial intelligence will be the number one technology most critical to national security in the next several years.
The Defense Information Systems Agency (DISA) is acquiring an array of cutting-edge technologies using rapid development processes and could begin fielding some of those technologies within the next two years.
The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems. Scientists at the Army Research Laboratory, specializing in adversarial machine learning, are working to strengthen defenses and advance this aspect of artificial intelligence.
The National Science Foundation’s Directorate for Computer and Information Science and Engineering is working to create a big data ecosystem. As part of that effort, the NSF, as it is known, is expanding the National Network of Big Data Regional Innovation Hubs, first created three years ago. The hubs, with one location for each U.S. Census region—the Midwest, Northeast, South and West—grew out of the need to aid the development of big data research and to help solve complex societal problems. The hubs are having a positive impact on the growth of machine learning, increasing the access to data, methods, networks and expertise, experts say.
Burgeoning computer capabilities often are unreliable, or brittle, at first. Capabilities that work successfully in one instance may fail miserably when applied to another area. At the moment, machine learning is no different, experts say, and the government and private industry are endeavoring to get past the limitations to improve its use.
Artificial intelligence (AI) has come a long way in recent years, but the technology still has hurdles to overcome if machines are to become true partners and collaborators with humans. To help push the systems to that next level, the Defense Advanced Research Projects Agency (DARPA) is hosting a two-day conference aimed at spurring the next wave of AI advances.
The U.S. Navy is in the nascent stages of a plan to revolutionize readiness through the use of artificial intelligence, machine learning and data analytics. It also may include the establishment of two new offices: a chief readiness office and an analytics office.
The Intelligence Advanced Research Projects Activity (IARPA) is seeking information on research efforts in the area of machine learning with a particular focus on deep learning and in the area of cooling systems for small mobile devices.
Artificial intelligence and machine learning are two of the many technologies that will change the way the military operates, according to a panel of experts. However, despite the revolutionary innovations that lie ahead, humans always will need to be the controlling factor in any operation.
These experts offered their views of the future on the second day of AFCEA’s TechNet Asia-Pacific 2018, held November 14-16 in Honolulu. In a panel sponsored by the Young AFCEANs, the five experts presented a younger generation’s perspective on the advantages and pitfalls of a data-centric battlespace.
Applied Research Solutions, Beavercreek, Ohio, has been awarded a $38,788,878 cost-plus-fixed-fee contract, plus an option amount of $5,967,447, for sensing, learning, autonomy, and knowledge engineering research and development. This contract is to conduct research and develop multi-domain technologies and strategies to orchestrate closed-loop sensing that manages knowledge from environment understanding to mission effects, across multiple missions. Work will be performed at Wright-Patterson Air Force Base and in Dayton, Ohio, and is expected to be completed by March 4, 2024. Fiscal year 2019 research and development funds in the amount of $1,254,000 are being obligated at the time of award.
Russia’s ability to evolve its use of information operations to leverage social media and the cyber domain continues to shock and challenge the world community. The country’s actions, especially during the 2016 U.S. elections, have brought cyber information operations out of the shadows and into the limelight. Now, state and nonstate actors are frequently using similar techniques to influence the public and achieve political goals once only attainable through armed conflict.
It has become increasingly evident that artificial intelligence (AI) and machine learning (ML) are poised to impact government technology. Just last year, the General Services Administration launched programs to enable federal adoption of AI, and the White House encouraged federal agencies to explore all of the possibilities AI could offer. The benefits are substantial, but before the federal government can fully take advantage of advancements like AI, federal agencies must prepare their IT infrastructure to securely handle the additional bandwidth.
U.S. Army officials conducting the third annual Cyber Quest experiment, which ends today, will issue a report in about 30 days that will determine which of the systems involved will transfer to programs of record. The exercise consists of an array of systems, including artificial intelligence and machine learning, that help provide situational understanding of the cyber and electronic warfare realms.