It is hard not to wonder how current technology would have altered the events surrounding the tragic death of John F. Kennedy. On the afternoon of November 22, 1963, shots rang out in Dallas, TX, taking the life of JFK, one of the most beloved Americans. Given the same circumstances today, surely the advances in IT alone, would have drastically changed the outcome of that horrible day. Would the government have recognized that there was a viable threat looming over JFK? Would local and government agencies have been more prepared for a possible assassination attempt? Would the assortment of everyday communication devices assisted in the prevention of the assassination, not to mention, provided greater resources into the investigation? With all that the IT world has to offer today, how would it have altered the JFK tragedy?

As many conspiracy theories have rocked the foundation of the official story presented by government agencies, realization of the expansive nature of technology provides equal consideration as to how the event would have been changed had this technology been available during the time of the shooting. There were T.V. cameras, home 8mm recorders, even single shot-hand held cameras snapping away as the car caravan approached. Yet, there remains little documentation of the shooting and even less information pertaining to the precautions taken by officials prior to JFK's arrival. Theorists consider these possibilities along with how the world would have turned out had the great John F. Kennedynever been assassinated on that day.

Since its foundation, HSG has been a leader in Business Rule Management Systems Training and Consulting services by way of the Blaze Advisor Rule Engine.  Over the years we have provided such services to many of the worlds largest corporations and government institutions whose respective backgrounds include credit card processing, banking, insurance, health and medicine and more, much more.  Such training and consulting services have included:

Create a wrapper object model in either Java, .NET or XML

Identify and catalog business rules

Develop a rule architecture within Blaze Advisor that isolates rule repositories as they relate to functionality and corporate policies

Configure, develop and implement a variety of interfaces to the rule engine from disparate systems ranging from mainframe applications written in Cobol to UNIX/Windows applications using Enterprise Java Beans, Windows Services, Web Services, Fat Clients, Java Messaging Services and Web Applications.

Review and update code to boost efficiency either by way of

    Removing functions calls within conditional statements

    Ensuring that database calls are essential or can be rearchitected in some other manner

    Employing the rete algorithm where necessary

    Paring down extensively large class models

    Deploying such appliations in multi-threaded systems

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Call us if you:

    are in need of Blaze Advisor Expertise
    are developing SMEs in Blaze
    want to speak directly with an expert (no placement agencies)
    want an affordable alternative to FICO
    want to work with an industry leader

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”