Cognitive on Cloud

Cloud computing: A data-centric business model

By G C Network | October 3, 2015

According to the National Institute of Standards and Technology: “Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers,…

John Mayer At Dell World 2015!! (Oh, I’ll be there too.)

By G C Network | September 30, 2015

An artist who defies all boundaries, John Mayer has won seven Grammy Awards and sold more than 17 million albums worldwide. The singer, songwriter and guitarist’s skills have been widely…

Data-centric Security: The New Must Have

By G C Network | September 23, 2015

Where is your data right now? The explosion of cloud computing and consumer IT means that your data, as well as data about you, can be virtually anywhere.Having your data and the…

Personal email:Pathway to Cybersecurity Breaches

By G C Network | September 14, 2015

As a business communications tool, email is the dominant option, and many corporations have policies that allow the use of personal email on corporate computers. In a recent Adobe Systems…

IEEE Cloud Computing: Legal Clouds

By G C Network | September 11, 2015

The new issue of IEEE Cloud Computing is now available!   This special issue looks at how to balance privacy with legitimate surveillance and lawful data access. Some of the…

Cloud hosting: Look beyond cost savings and weigh pros, cons

By G C Network | September 3, 2015

Is your company struggling with the idea of using “cloud hosting” in order to save money? Truth be known, using cost savings as the primary reason for moving to cloud…

“Cloud First” Lessons Learned from ViON

By G C Network | August 25, 2015

In 2011, then United States CIO Vivek Kundra released the US Federal Cloud Computing Strategy [1]. In the executive summary he pointed to cloud computing as a key component of…

Looking for Security Peak Performance?

By G C Network | August 19, 2015

You can find it at Dell Peak Performance 2015!!! I’ll be there at the Aria Resort and Casino in Las Vegas attending as a social media correspondent with a full…

The Cybersecurity Sprint: Are we safe yet?

By G C Network | August 7, 2015

UPDATE: NBC News reports U.S. officials have disclosed a hack of the Pentagon’s Joint Staff unclassified email system, which took place on July 25. Recent unauthorized access to a U.S. government database…

Cloud Computing + Things = “Information Excellence”, Not IoT

By G C Network | July 31, 2015

The Internet of Things (IoT) has quickly become the next “be all to end all” in information technology. Touted as how cloud computing will connect everyday things together, it is…

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.

Cloud Musings

( Thank you. If you enjoyed this article, get free updates by email or RSS – © Copyright Kevin L. Jackson 2016)

Follow me at https://Twitter.com/Kevin_Jackson
Posted in

G C Network