Conference: Winning With AI

IT Blogs – IBM ‘Winning with AI’ Conference  –  About the Conference.

This Blog describes my thoughts about the upcoming (September 2018) IBM ‘Winning with AI’ Conference. This could potentially be an important conference, so check out my thoughts about it using the link above.  If you want to skip my thoughts and go directly to the Conference website, here it is:

IBM ‘Winning with AI’ Conference

Click on either of the links above to find help for your journey to integrate AI into your existing (or soon to be) operational systems.

Convergence: Operational & AI

As any of you who have either been following the changes in IT infrastructure or simply reading my whitepapers know, The Times They are a Changin’.  Just as Service Oriented Architecture (SOA) moved computing from a homogeneous “single computer type” to a heterogeneous distributed computing model, so too is the Cloud changing the computing landscape.

Rings-Three-Interlocking-LabelsIn addition to the “OS Centric” (mainframe, UNIX, Windows, IBM i, etc.) and “Distributed” (SOA, ESB, etc.) computing environments, “Cloud computing” environments are here to stay.  Modern computing will be spread across all three of these environments.  In fact, computing will be spread across multiple Cloud provider offerings as well as into internal “private” Clouds.  To make all of this happen, significant advancements in software integration have been, and are continuing to, be made.  The Istio Service mesh is a great example of the trend in this kind of integrative capability.

Much of my writing has been focused upon the impacts of Cloud Computing to the “Transactional” or “Operational” side of business computing.   These impacts are very real and they are amongst the first ones that IT organizations have to deal with.  After all, the purpose of IT is to drive business, not the other way around.  Software integration capabilities are, however, breaking down other barriers.

In addition to our historical “OS Centric” and “SOA” computing environments, types of computing were also siloed.  Transactional computing (Banking, Point of Sale, Airline Reservations, etc.) has traditionally been separated from Analytical computing (Data Warehouse, etc.).  This was largely due to the fact that they had very different computing infrastructure requirements as well as different usage requirements.  These differing requirements led to a separation of the data and hence a separation of the associated computing capability.

The scalability and integrative capabilities of Cloud Computing are now beginning to make it possible to re-integrate these heretofore disparate computational functions.  Analytical capabilities are increasingly being exposed as Cloud hosted “Services”.  These Services may easily be invoked either by “transactional” workloads running in existing infrastructures or in newly developed “Cloud Native” workloads.  Transactional data can be passed to the Cloud for “Deep Learning”.  A whole new world of possibilities is opening up!

To prepare for this Brave New World, both the “Transactional” and the “Analytical” technical staff will need to develop an understanding of the concepts and technologies that are used outside of their own disciplines.  This transition begins with education and mutual communication.  Fortunately, there are plenty of opportunities for both of those activities online.  This conversation is, however, mostly definitely NOT limited to only the technical folks!

The conversation must, of course, also include the Business leader(s) responsible for both the “Transactional” and “Analytical” domains.  Creativity, business insight, and technical acumen will all be initially needed to exploit the emerging opportunities.  This is an area of tremendous potential:  the risks are low and the rewards are high.  A couple of possible examples of the synergy between these two disciplines include:

  • Applying Deep Learning to credit approval processing.
  • Applying Watson Personality Insights in Customer Service applications.  

What should your next steps be?  First, start learning about other Data Processing disciplines.  There are plenty of online opportunities.  If you don’t know where to start, just take a look under the “Credentials” menu.  Links to a large number of classes are there.  Take a look at the “Deep Learning” badge in the “Watson” section if you want to take a first look into machine learning.

Second, start conversing with a wider group, both technically and from a business and management perspective, within your organization.  Challenge yourself and others with new ideas.  Innovation feeds off of new ideas.  The cost of throwing a new idea into the conversation is near zero.  The rewards of a new idea successful impacting the business are large.  So, start the conversation.

Finally, don’t be afraid to champion new ideas.  Not even if they’re yours!  Change needs drivers.  Drivers need passion.  So, get passionate (but please remain respectful).  Get communicating.  Get behind the changes that you believe in.  Remember, all journeys begin with the very first step.