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From PC Break/Fix to CloudMASTER®
https://www.linkedin.com/in/stevendonovan It was late 2011 and Steven Donovan was comfortable working at SHI International Corporation, a growing information technology firm, as a personal computer break/fix technician. His company had been…
Is Data Classification a Bridge Too Far?
Today data has replaced money as the global currency for trade. “McKinsey estimates that about 75 percent of the value added by data flows on the Internet accrues to “traditional”…
Vendor Neutral Training: Proven Protection Against Cloud Horror Stories
Cloud computing is now entering adolescence. With all the early adopters now swimming in the cloud pool with that “I told you so” smug, fast followers are just barely beating…
Cognitive Business: When Cloud and Cognitive Computing Merge
Cloud computing has taken over the business world! With almost maniacal focus, single proprietors and Board Directors of the world’s largest conglomerates see this new model as a “must do”.…
Government Cloud Achilles Heel: The Network
Cloud computing is rewriting the books on information technology (IT) but inter-cloud networking remains a key operational issue. Layering inherently global cloud services on top of a globally fractured networking…
System Integration Morphs To Cloud Service Integration
Cloud Service Brokerage is changing from an industry footnote toward becoming a major system integration play. This role has now become a crucial component of a cloud computing transition because…
Networking the Cloud for IoT – Pt 3 Cloud Network Systems Engineering
Dwight Bues & Kevin Jackson (This is Part 3 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design. Networking the Cloud for IoT –…
Networking the Cloud for IoT – Pt. 2 Stressing the Cloud
Dwight Bues & Kevin Jackson This is Part 2 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design. Part…
Networking the Cloud for IoT – Pt. 1: IoT and the Government
Dwight Bues & Kevin Jackson This is Part 1 of a three part series that addresses the need for a systems engineering approach to IoT and cloud network design:…
Parallel Processing and Unstructured Data Transforms Storage
(This post originally appeared on Direct2Dell, The Official Dell Corporate Blog) Enterprise storage is trending away from traditional, enterprise managed network-attached storage (NAS) and storage area networks (SAN) towards a…
Over the past few years, the use of artificial intelligence has expanded more rapidly than many of us could have imagined. While this may invoke fear and dread in some, these relatively new technology applications are clearly delivering real value to our global society. This value is generally seen in four distinct areas:
- Efficiency – Delivering consistent and low-cost performance by characterizing routine activities with well-defined rules, procedures and criteria
- Expertise – augment human sensing and decision makingwith advice and implementation support based on historical analysis
- Effectiveness – improve the overall ability of workers and companies by improving coordination and communication across interconnected activities
- Innovation – enhance human creativity and ideation by identifying alternatives and optimizing recommendations.
One of the key drivers in sustained growth of AI is the rapidly increasing availability of data. The broadening global use of the Internet and the connectivity the Internet affords have combined to deliver data in volumes that have never been experienced before. Applications to capitalize on this use and connectivity have also helped society grow from generating approximately 5 zettabytes of unstructured data in 2014 to a projected approximation of 40 zettabytes of unstructured data in 2020.
- Crunchers. algorithms use small repetitive steps guided with simple rules to number crunch a complex problem.
- Guides.These algorithms guide us on how to best navigate a policy, process, or workflow based on historic actions that were successful
- Advisors.These algorithms advise us on our best options by providing us with predictions, rankings, and likelihood-of-success based on historic patterns
- Predictors.These algorithms predict future human behaviors and events by using small repeatable decisions and judgments that interpret historic behaviors and events
- Tacticians.These algorithms tactically anticipate short-term behaviors and react accordingly
- Strategists. These algorithms strategically anticipate behaviors and plan accordingly
- Lifters.These algorithms help us by automating our mundane and repetitive work freeing us to do what we’ve been hired to do
- Partners.They have a large amount of subject matter expertise in our area allowing us to be more productive and more focused
- Okays. They are useful for business planning, strategic change, and culture change.due to an ability to building the big picture through deep analysis and looking at things from all angles
- Supervisors.These algorithms orchestrate human activity other AI algorithms to help in meeting strategic long-term objectives
One of the most powerful open source big data analytics tools is The TrustedAnalytics Platform. Optimized for performance and security, TAP is being used to accelerate the creation of advanced analytics and machine learning solutions. It simplifies solution development through the use of a collaborative, flexible integrated environment within which all tools, components and services are centrally accessible. Using TAP, many AI solution development barriers can be quickly overcome by removing limited accessibility to advanced algorithms and masking the complexity often cited as a hindrance to big data analytics projects. Some of the most impressive TAP based solutions include:
- Doctors at PennMedicine’s heart failure and transplant program that improved heart health by identifying patients who require proactive treatment.
- The “Collaborative Cancer Cloud” at Oregon Health and Science University allows hospitals to securely share patient genomic data in order to look for new ways of determining overall health
- Using data from US Geological Survey to train models that can be used to detect “data outliers” in real-time which can be very useful in detecting unusual seismic behaviors and forecasting intense earthquakes
Learn more about how TAP is accelerating the adoption of artificial intelligence by visiting https://trustedanalytics.org/. While there you can actually test drive TAP!
This content is being syndicated through multiple channels. The opinions expressed are solely those of the author and do not represent the views of GovCloud Network, GovCloud Network Partners or any other corporation or organization.
( Thank you. If you enjoyed this article, get free updates by email or RSS – © Copyright Kevin L. Jackson 2016)
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