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.
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 U.S. Coast Guard is pursuing digital solutions to support its unique set of military, law enforcement, humanitarian, regulatory and diplomatic responsibilities. It is no small feat to provide information technology to its workforce of 87,570, as well as to its cutters, boats, and aircraft that move along the coastline and inland waterways protecting the United States.
The U.S. Defense Department lags the hype cycle for artificial intelligence, machine/deep learning and implementations like natural language processing by years. It needs to uncover the root causes contributing to this delay and create winning strategies to overcome institutional obstacles to get ahead of industrial partners and adversaries who are further along the adoption curve.
Possessing technology is neither deterministic nor decisive when waging war. The effective employment and deliberate application of technologies to enhance warfighting capabilities implies advantage over an adversary when suitably coupled with offensive and defensive tactics.
Later this month a team of researchers plans to release an online wargame that will use machine learning and data analytics to study nuclear conflict escalation and the strategic stability of nations in an artificial world.
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.
Implementing a new system can be an exciting time, but the nagging questions and doubts about the fate of data you’ve literally spent years collecting, organizing and storing can dampen this excitement.
This legacy data often comes from a variety of sources in different formats maintained by a succession of people. Somehow, all the data must converge in a uniform fashion, resulting in its utility in the new solution. Yes, it is hard work and no, it is not quick. Fortunately, this scrubbing and normalization does not have to be a chaotic process replete with multiple failures and rework.
Artificial intelligence can be surprisingly fragile. This is especially true in cybersecurity, where AI is touted as the solution to our chronic staffing shortage.
It seems logical. Cybersecurity is awash in data, as our sensors pump facts into our data lakes at staggering rates, while wily adversaries have learned how to hide in plain sight. We have to filter the signal from all that noise. Security has the trifecta of too few people, too much data and a need to find things in that vast data lake. This sounds ideal for AI.
The Securities and Exchange Commission issued several Qualitative Research and Analytical Data Support (QRADS) indefinite delivery, indefinite quantity (IDIQ) contracts to TCG. The company, an information technology solutions and advisory services provider based in Washington, D.C., is now supporting four lines of business at the SEC—classified as Channels 2,3,4 and 5—according to recent company statements. TCG is one company out of several that received work under the multi-award IDIQs, with other winners on each channel.
Researchers at North Carolina (NC) State University have developed a new computational model that draws on normally incompatible data sets, such as satellite imagery and social media posts, to answer questions about what is happening in targeted locations. The model identifies violations of nuclear nonproliferation agreements.
Traffic on optical transport networks is growing exponentially, leaving cyber intelligence agencies in charge of monitoring these networks with the unenviable task of trying to sift through ever-increasing amounts of data to search for cyber threats. However, new technologies capable of filtering exploding volumes of real-time traffic are being embedded within emerging network monitoring applications supporting big data and analytics capabilities.
When National Science Foundation officials announced in February that three major providers of cloud computing were donating up to $9 million collectively for big data research, they already were looking for ways to broaden the effort to include a wider variety of topics, including cybersecurity. The expansion is intended to benefit both research and education initiatives and is necessary, in part, because the cloud providers now acquire cutting-edge hardware before it is made available to researchers.
Federal mandates and economic concerns are pushing businesses and government agencies to migrate their IT services to the cloud. As a result, decision makers must consider how to proceed in a way that meets compliance requirements in a timely, affordable and secure fashion.
Two data migration experts at experienced commercial organizations recently offered their advice to organizations that are just beginning on the data migration trail or are well on their way but hitting a few bumps in the road.
ECS Federal LLC, Fairfax, Virginia, was awarded a $48,000,608 modification to provide analysis of large structured and unstructured data sets in order to provide insight to the warfighter on the tactical edge using modern computational and algorithmic techniques through creation of a prototype environment with prototype technologies to uncover key insights with large data sets using robust ontologies created through data science partnership with the Department of Defense research laboratories and universities. Work will be performed in Fairfax, Virginia, with an estimated completion date of March 28, 2019. Fiscal 2018 research, development, test and evaluation funds in the amount of $14,000,000 were obligated at the time of the award.
With an onslaught of new technologies ever present on the horizon, the U.S. Marine Corps (USMC) is working to make sense of what technologies will work for them, not only in the traditional warfighting domains, but also in cyber—the new domain. Right now, they have a long list of priorities associated with modernizing the network, meeting standards and mandates, and fielding new capabilities.
ECS Federal LLC, Fairfax, Virginia, was awarded a $9,529,017 modification to provide analysis of large structured and unstructured data sets. The company will assist the Army in providing insight to the warfigher on the tactical edge using modern computational and algorithmic techniques through creation of a prototype environment with prototype technologies, DOD said. The goal is to uncover key insights with large data sets using robust ontologies created through data science partnership with DOD research laboratories and universities. Work will be performed in Fairfax, Virginia, with an estimated completion date of September 28, 2019.
In a $350 million deal, San Francisco, California-based Splunk Inc. will purchase Phantom Cyber Corporation, a Palo Alto, California-based cyber security firm specializing in security orchestration, automation and response, known as SOAR. Splunk will acquire Phantom using a combination of cash and stock. The transaction is expected to close during the first half of 2018, subject to customary closing conditions and regulatory reviews. Oliver Friedrichs, Founder and CEO, Phantom will report to Haiyan Song, senior vice president and general manager of security markets, Splunk.
Part of the Office of Naval Research’s efforts in command, control, communications and computers is to provide key analytical tools to planners, analysts and commanders swamped by data. To that end, the office, known as the ONR, is conducting basic and applied research in applications that will cut maneuver planning time, expand access to data, enhance analytical processing and improve predictions. The tools are meant to improve decision making across antisubmarine warfare, integrated air and missile defense, electromagnetic maneuver warfare, and expeditionary and integrated fires missions.
In 2016, big data software company Splunk promised to donate a minimum of $100 million in software licenses, training, support and education to nonprofit organizations and educational institutions over the next 10 years. The company’s Splunk4Good initiative supports nonprofit organizations, academic research and social improvements.