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Microsoft vs Google in Cloud Computing
Many took note of the Randall Stross essay in the New York Times last weekend. In it he succintly described why Microsoft is failing in it’s attempt to bridge the…
IBM at Forrester IT Forum
At the Forrester IT Forum yesterday in Las Vegas, Rick Lechner, VP Enterprise Systems at IBM, made the following comments The changing face of globalization (transformation from exporting to multi-nationals…
HP & EDS
In an interesting take on his Enterprise Architecture blog, Chris Pearson sees the HP acquisition of EDS as a ploy by HP to remain relevant in a cloud computing world.…
The Library of National Intelligence (LNI) – A Possible Cloud Application
In the MAZZ-INT Blog a couple of weeks ago, Joe Mazzafro artile on “Intelliigence and the Concept of Customer” stated that a “realistic business model for the IC to assume…
Net-Centric Enterprise Services – An Update
Net-Centric Enterprise Services (NCES) is about to enter the initial operational test and evaluation phase. NCES are a set of capabilities that support network-centric warfare operations and information sharing. It…
Microsoft Renews Yahoo Bid
Microsoft renews Yahoo bid and is now offering to buy a piece of Yahoo. I believe this is just the opening of the second round. Follow me at https://Twitter.com/Kevin_Jackson
Cloud Computing Risk
CIO.com reviewed the top three concerns that the IT executives have regarding the adoption of cloud computing – security, latency, and SLA. These concerns seem similar to those previously assigned…
Grid vs. Cloud – May 17, 2008
From Geva Perry’s April 25th blog Cloud Computing overtaking the term Grid Computing With the term “cloud computing” rapidly being hyped everywhere, I did this little exercise on Google Trends…
Blogsphere Clouds – May 16, 2008
The cloud is billowing in the blogsphere !! Virtual Computing in the Cloud — How a Universal Dialtone Will …Virtual Cloud Computing represents the next wave of virtualization and offers…
Gartner on Cloud Computing / Yahoo vs. Icahn- May 15, 2008
Gartner thinks that cloud computing may be the next big thing: By 2012, 80 percent of Fortune 1000 enterprises will pay for some cloud computing service and 30 percent of…
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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