TAP Accelerates Artificial Intelligence

Strategies And Technologies for Cloud Computing Interoperability (SATCCI)

By G C Network | March 4, 2009

As I alluded to in an earlier post, a major cloud computing interoperability event will be held in conjunction with the Object Management Group (OMG) March Technical Meeting on March…

Government Cloud Computing E-zine Launched

By G C Network | March 3, 2009

Today marks the launch of a new electronic magazine dedicated to addressing cloud computing within the government space. Over the last year during my personal exploration of this marketspace, I’ve…

NCOIC Plenary: Cloud Computing Working Group

By G C Network | March 2, 2009

Last week, I had the pleasure of participating in the NCOIC Cloud Computing Working Group. Led by Cisco Systems Distinguished Engineer, Mr. Krishna Sankar of Cisco Systems, the meeting purpose…

2nd Government Cloud Computing Survey – A Sneak Peek

By G C Network | February 25, 2009

This month, we’re in the middle of collecting data for our 2nd Government Cloud Computing Survey. to peek your curiosity (an to entice your participation) here is a sneak peek…

Government could save billions with cloud computing

By G C Network | February 23, 2009

In a recent study, published by MeriTalk, Red Hat and DLT Solutions, the Federal government could save $6.6 billion by using cloud computing or software-as-a-service. “Looking at 30 federal agencies,…

Cloud Games at FOSE 2009

By G C Network | February 19, 2009

ONLINE REGISTRATION NOW AVAILABLE Booz Allen Hamilton is launching its Cloud Computing Wargame (CCW)T at FOSE March 10-12, 2009 in Washington, DC. The CCW is designed to simulate the major…

IBM and Amazon

By G C Network | February 16, 2009

According to the Amazon Web Services (AWS) site, you can now use DB2, Informix, WebSphere sMash, WebSphere Portal Server or Lotus Web Content Management on Amazon’s EC2 cloud. “This relationship…

A Berkeley View of Cloud Computing

By G C Network | February 13, 2009

Yesterday, Berkeley released their View of Cloud Computing with a view that cloud computing provides an elasticity of resources, without paying a premium for large scale, that is unprecedented in…

Cloud Economic Models

By G C Network | February 11, 2009

One of the most important drivers of cloud computing in the Federal space is its perceived “compelling” economic value. Some initial insight on the economic argument is now available on…

Cloud Computing In Government: From Google Apps To Nuclear Warfare

By G C Network | February 10, 2009

Today, I want to thank John Foley of InformationWeek for an enjoyable interview and his excellent post, Cloud Computing In Government: From Google Apps To Nuclear Warfare. Our discussion covered…

Photo credit: Shutterstock

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.


Impressive innovations in big data algorithms have also added fuel to the explosive growth of AI. The mostimportant of these algorithm categories include:
  • 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:

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.

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