TAP Accelerates Artificial Intelligence

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By G C Network | September 9, 2008

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By G C Network | September 8, 2008

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By G C Network | September 4, 2008

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By G C Network | September 4, 2008

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By G C Network | September 3, 2008

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Boeing Gives Up On Interoperable Modelling and SimulationNnetworks

By G C Network | September 3, 2008

Last week a Flightglobal article reported on the softening of Boeing’s stance on the need to establish standards for networking protocols across the US and global defence industry. Citing the…

Cisco: A Cloud Computing Company?

By G C Network | September 2, 2008

Yes Cisco ! Red Herring’s report on Cisco’s acquisition of PostPath last week presents a strong case for this. If finalized, PostPath would become Cisco’s fifteenth acquisition in less than…

Cloud Computing at top of Hype Cycle

By G C Network | August 29, 2008

Computerworld reports that Gartner see cloud computing as being at the top of the hype cycle. They have also settled on a definition: “a style of computing where massively scalable…

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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