Cognitive on Cloud

December 20, 2016 / G C Network / Comments Off

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Federal Cloud Computing Strategy Officially Launched

By G C Network | February 14, 2011

Federal CIO Vivek Kundra officially launched the Federal Cloud Computing Strategy today. While this is clearly not new news, the document does state the government’s position in a very succint manner.…

GEOINT’s Future is in the Cloud

By G C Network | January 31, 2011

Recently, Geospatial Intelligence Forum Magazine asked me for my thoughts on the role of cloud computing in the future of geospatial intelligence.My response was recently published in their December 2010…

eTechSuccess: Patterns of Success – Kevin Jackson

By G C Network | January 27, 2011

My sincere appreciation to John Baker for the eTechSuccess: Patterns of Success interview. John and I worked together IBM as part of the Wireless Emerging Business Organization. His team and…

USBE&IT Winter Issue Focuses on Cyber Security

By G C Network | January 19, 2011

Thank You USBE&IT Publisher Mr Tyrone Taborn for such an inspiring issue and my sincere appreciation to Mr. Frank McCoy for my inclusion in his list of Cyber visionaries! The Homeland…

Global GovCloud with Cisco and VCE

By G C Network | January 18, 2011

Last week I had the awesome experience of participating in a global telepresence conference on government cloud computing. Joining me as presenters were Blake Salle, Senior Vice President of VCE,…

NIST Cloud Computing Collaboration Twiki Launches

By G C Network | December 30, 2010

Today I received my credentials for the NIST Cloud Computing Collaboration Site. “The National Institute of Standards and Technology (NIST) has been designated by Federal Chief Information Officer Vivek Kundra…

GovCloud Predicitons for 2011

By G C Network | December 30, 2010

Happy New Year All!! 2011 will be the breakout year for GovCloud! Pressure to reduce budget, pressure to manage I resources better and the political pressure of the next presidential…

Vivek Kundra Unveils 25-Point IT Management Reform Program

By G C Network | December 10, 2010

Yesterday the US Federal CIO, Vivek Kundra, unveiled an ambitious 25-point implementation plan for delivering more value to the American taxpayer. This plan focuses on execution and is designedto establish…

GSA and Unisys/Google Marks GovCloud Watershed

By G C Network | December 4, 2010

As widely reported this week, the United States General Services Administration (GSA) has awarded a contract to Unisys to create a secure cloud-based email and collaboration platform. The solution will…

NIST Moves Forward on Cloud Computing

By G C Network | November 8, 2010

Last week the National Institute of Standards and Technology (NIST) held their second Cloud Computing Forum and Workshop. Skillfully shepherded by Ms. Dawn Leaf, the agency’s senior executive of cloud computing,…

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Photo credit: Shutterstock

According to the IBM Institute for Business Value the market will see a rapid adoption of initial cognitive systems. The most likely candidates have moved beyond descriptive and diagnostic, predictive and routine industry-specific capabilities. 70 percent of survey respondents are currently using advanced programmatic analytics in three or more departments. In fact, the widespread adoption of cognitive systems and artificial intelligence (AI) across various industries is expected to drive worldwide revenues from nearly US$8.0 billion in 2016 to more than US$47 billion in 2020.

The analyst firm IDC predictsthat the banking, retail, healthcare and discrete manufacturing industries will generate more than 50% of all worldwide cognitive/ AI revenues in 2016. Banking and retail will each deliver nearly US$1.5 billion, while healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3% and 61.4%, respectively. Education and process manufacturing will also experience significant growth over the forecast period.

Figure 1– Credit Cognitive Scale Inc.

So what can cognitive computing really do? Three amazing examples of this burgeoning computing model include:

· DeepMind from Google that can mirror some of the brain’s short-term memory properties. This computer is built with a neural network capable of interacting with external memory. DeepMind can “remember” using this external memory and use it to understand new information and perform tasks beyond what it was programmed to do. The brain-like abilities of DeepMind mean that analysts can rely on commands and information, which the program can compare with past data queries and respond to without constant oversight.

· IBM Watson which has a built-in natural language processor and hypothesis generator that it uses to perform evaluations and accomplish dynamic learning. This system is a lot more advanced than the digital assistants on our smartphones and allows users to ask questions in plain language, which Watson then translates into data language for querying.

· The Qualcomm Zeroth Cognitive Computing Platform that relies on visual and auditory cognitive computing in to reflect human-like thinking and actions. A device running the platform can recognize objects, read handwriting, identify people and understand the overall context of a setting. Zero
th’s ability to replicate intuitive experiences provides a number of opportunities within sentiment analysis. With its ability to understand scenes and context, it can decipher how people are feeling based off facial expressions or voice stress levels.

This shift to cognitive computing will occur within the next 12 to 14 months for many organizations and cognitive era success requires data centric management culture, a common requisite for secure cloud computing. This similarity should not be surprising because both computing models:

Need robust and simplified data classification processes in order to more easily deliver industry and business model specific value;
Require the implementation of information technology security controls that are driven by data value and role based access control paradigms; and
Leverage software applications that should be developed using ISO 27034 which is a multi-part standard on specifying, designing/selecting and implementing information security controls through a set of processes integrated throughout an organization’s Systems Development Life Cycle/s (SDLC).

Companies that are leveraging cloud today must also prepare for the cognitive computing era. This blend of cloud and cognitive has, in fact, created a brand new application development model.

Referred to as “Cognitive on cloud”, this model delivers cognitive services running in the cloud that are consumable via representational state transfer (REST) APIs. These services are available as part of platform-as-a-service (PaaS) offerings such as Bluemix and can be easily bound to an application while coding.

Using this approach, cognitive analytics such as voice (tone analyzer, speech-to-text) and video (face detection, visual recognition) capabilities enables quick analysis of petabytes of unstructured data. Developing cognitive applications to run on mobile devices has provided new insights which help organizations create totally new revenue streams. When selecting a cloud service provider however cognitive on cloud ROI requires more than just a total cost of ownership comparison. In addition to this basic analysis, an organization must consider which cloud is cognitive enabled at the Platform-as-a-Service (PaaS) layer. The convergence of cognitive computing and cloud is driving this cognitive-oriented digital economy and the potential return is seemingly unlimited.

This post was brought to you by IBM Global Technology Services. For more content like this, visit IT Biz Advisor.