TAP Accelerates Artificial Intelligence

Cloud Computing and the Process Integration Era

By G C Network | December 17, 2008

The Industry Advisory Council (IAC) is a non-profit, non-partisan organization dedicated to fostering improved communications and understanding between government and industry. through its affiliation with the American Council for Technology…

The Tactical Cloud

By G C Network | December 16, 2008

When cloud computing first came in vogue, there was a rather serious discussion about the private cloud concept. The whole idea of cloud computing seemed to argue against implementing such…

“Cloud Musings” Now on SYS-CON Media “Cloud Computing Journal” !!

By G C Network | December 15, 2008

I’m happy to announce that a recent “Cloud Musings” article, “Commercial vs Federal Cloud Computing ” has been reposted on SYS-CON Media’s “Cloud Computing Journal“. Thank you SYS-CON for making…

How to make clouds interoperable and standard !!

By G C Network | December 12, 2008

This has been a huge part of my life over the past few weeks! This is my personal view. WARNING: DON’T EXPECT THE ANSWER TO BE FOUND BELOW !!! There…

The Tension between Public and Private Clouds

By G C Network | December 11, 2008

Last week, during discussion on cloud interoperability and standards in Israel, I saw for the first time a real dichotomy in the value of public (external) and private (internal) clouds.…

Cloud Computing for Continuity of Operations (COOP)

By G C Network | December 10, 2008

Recently, I’ve been focusing on cloud computing for COOP. The way I looked at it, many government agencies are already using commercial shared facilities as COOP sites and that the…

NCOIC Plenary Session

By G C Network | December 9, 2008

Hopping a plane to the west coast today to attend the NCOIC Plenary in Costa Mesa, California. First day “Cloud Computing for Net-Centric Operations” agenda includes: David Ryan, Chief Architect…

Dataline named “Top 100 Cloud Computing Company”

By G C Network | December 9, 2008

SYS-CON’s Cloud Computing Journal included Dataline in its expanded list of the most active players in the cloud ecosystem. In adding Dataline to the “Top 100” list, Jeremy Geelan noted…

Autoscaling into the cloud- Good or Bad?

By G C Network | December 8, 2008

I always thought saw the ability to autoscale into a cloud infrastructure as a good thing. George Reese presented a differing view on the O’Reilly blog recently. “Auto-scaling is the…

Cloudera must be reading the script!

By G C Network | December 4, 2008

“Cloud computing leapt out as the most obvious way to address enterprise large data problems” – Ken Pierce, IT Specialist, DIA-DS/C4ISR “We view Hadoop as the key enabler…[in] optimizing the…

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.

Cloud Musings

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