Summary:  If you’re planning your AI/ML business strategy watch out for the confusion in categories and overly risky ratings given by some research and review sources.  Read the research, then consult with your own data scientists for a better evaluation of risk. It’s likely not as bad as you think. 

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The amount of data generated today is astonishing. Research published by Seagate reports that by 2025, around 175 Zettabytes of data will be generated on an annual base. The colossal sets of collected, analyzed, monitored, and stored data is only…

Introduction

The quarterly earnings call is a critical event for publicly traded companies. Each call serves multiple purposes. It is both an important source of information for investors and an opportunity for a company to present a narrative of operational performance, financial health, and strategic vision in their own terms. It’s also an ideal opportunity for executives seeking to manage and optimize outcomes.

The advent of AI makes it plausible for…

In this blog, I will be discussing some distinct types of data involved in feedback. The types that I will be covering are as follows: 1) structural; 2) event; 3) quantitative; 4) contextual; and 5) systemic. In 2014, I recall reading a number of blogs about three types of data: prescriptive, descriptive, and predictive. There was a data scientist apparently on tour lecturing extensively about these three types. I don't recall the individual's name. Well, prescription, description, and…

Thermometers and scales to measure weight appeared in retail outlets long ago. Blood pressure monitors perhaps came later. Pedometers and heart-rate monitors seem more recent - possibly closer to my time. I saw several devices while doing this blog intended to electronically record among other things hours of sleep; these are designed to be worn on the body all the time. A couple of weeks ago, I bought something to give the heart rate and blood oxygen saturation level. I consider it a real…

In this post, I discuss the basic characteristics of code that I have personally used to extract online data - in a process these days often called data-mining.  I intend to cover some general features.  Those that wish to do so can also compile the coding samples.

Over the years, I have programmed in a number of computer programming languages including Visual Basic, Perl, Python, and LISP (AutoLISP).  The coding samples on this blog are written in Java, my language of…