Summary:  Let’s start by clarifying the difference between RPA (Robotic Process Automation) and IA (Intelligent Automation).  Then we’ll show why AI/ML inside Intelligent Automation is the secret sauce that really makes this work.

As we’ve tracked the adoption of AI/ML across industries…

Summary: This is a discussion of social injustice, real or perceived, promulgated or perpetuated by machine learning models.  We propose a simple solution based on wide spread misunderstanding of what ML models can do.

This is a discussion of social injustice, real or perceived, promulgated or perpetuated by…

Summary:  Digital Twins is a concept based in IoT but requiring the skills of machine learning and potentially AI.  It’s not completely new but it is integral to Gartner’s vision of the digital enterprise and makes the Hype Cycle for 2017.  It’s a major enabler of event processing as opposed to traditional request processing.

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Summary:  As a profession we do a pretty poor job of agreeing on good naming conventions for really important parts of our professional lives.  “Machine Learning” is just the most recent case in point.  It’s had a perfectly good definition for a very long time, but now the deep learning folks are trying to hijack the term.  Come on folks.  Let’s make up our minds.

As a profession we do a pretty poor job of agreeing on good naming conventions…

Summary:  The data science press is so dominated by articles on AI and Deep Learning that it has led some folks to wonder whether Deep Learning has made traditional machine learning irrelevant.  Here we explore both sides of that argument.

On Quora the other day I saw a question from an aspiring data scientist that asked – since all the…

Summary:  Are there large, sustainable career opportunities in AI and if so where?  Do they lie in the current technologies of Deep Learning and Reinforcement Learning or should you focus your career on the next wave of AI?

If you’re a data scientist thinking about expanding your career options into AI you’ve got a forest and…

Summary:  What are the earliest seeds of artificial intelligence?  To whom do we owe thanks for starting us down this path?  Many modern researchers to be sure, but the earliest is Leonardo Torres of Spain, in about 1914.

As data scientists it’s very cool to be at the forefront in this age of techno-optimism.  Since the awakening of the digital age calculated by economic researchers to have begun about 1994, a wave of increased productivity has…

Summary:  Which of these terms means the same thing:  AI, Deep Learning, Machine Learning?  Are you sure?  While there’s overlap none of these is a complete subset of the others and none completely explains the others.

Take this quiz.

Which of the following are substantially the same things?

A. AI

B. Deep Learning

C.  Machine Learning

(Select your answer)

1.  A and B

2.  B and C

3.  A and…