The pandemic has shown how vulnerable our supply chains are. A small interruption can bring a supply chain to a halt, which in today’s fast-paced world, is simply not acceptable. Customers are always expecting their product to arrive on time when ordered, and any delay in the…

Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were…

This article was written by Carlos E. Perez.

In this post I will explore further the characteristics of Artificial Intuition with the goal of describing a set of patterns that can aid us in formulating novel architectures for Deep Learning. In a previous post, I introduced the idea that there are two…

This article was written by Matthew Hughes. 

CS 106A is Stanford University’s introductory programming course. The module – which is also available to view on YouTube – introduces the fundamentals of coding in an accessible way, and lays the foundations for…

Why developers prefer Google's Angular app development for their projects? Keep reading to find out!

Mobile app development is gaining popularity all over the world. Businesses are trying to incorporate this tech into their process in order to bridge the gap between the users and…

Across industries and enterprises, AI has been the key growth driver, and this is mainly due to the services offered under this technology umbrella. Every industry is now witnessing enhancements in business processes, costs, and efficiency due to AI's introduction in their field. Depending on the industry, AI offers something unique and has helped the key decision-makers to make fast and accurate decisions based on various implementation solutions.…

Consistent asset health across many levels from cell sites to regions is critical to ensure uninterrupted operations for telecom operators. However, proactively identifying anomalous patterns like equipment malfunction remains a major challenge. Drawing on Subex’s deep implementation experience, this paper describes the chief steps necessary to deploy successful pattern detection solutions. It also examines some high impact use cases for pattern detection that have systematically delivered…

The model-free, data-driven technique discussed here is so basic that it can easily be implemented in Excel, and we actually provide an Excel implementation. It is surprising that this technique does not pre-date standard linear regression, and is rarely if ever used by statisticians and data scientists. It is related to kriging and nearest neighbor interpolation, and apparently first mentioned in 1965 by Harvard scientists working on GIS (geographic information systems). It was referred…

In my previous post, What’s Driving the Future of Work and Professions?, I mentioned PESTLE as a helpful framework for classifying external forces that act on all of us and the companies for which we work.  In this article, I present a list of them for you to consider.  It’s not encyclopedic, but it’s a good…

Being an expert at developing and understanding ML, or Machine Learning algorithms, takes time and a lot of hard work. That’s why ML (machine learning) engineers are been seen constantly learning while at the job. If the learning stops, your professional growth stops. Many of us, especially the AI aspirants, think that watching tutorial videos on AI (artificial intelligence) modeling or ML algorithm development on YouTube…

I’ve been reading the interesting and soul-searching (from a data scientist perspective) book from Cathy O’Neil titled “Weapons of Math Destruction”, or WMD as used in the book.  The book provides several real-world examples of how Big Data and Data Science – when not properly structured – can lead to ethically-wrong unintended consequences. 

Chapter…

Over the years, I've had people ask me how a taxonomy differs from an ontology. The answer (or at least a reasonably simple answer) is that "a taxonomy is a tree shaped ontology".

It is worth digging  bit deeper to understand what that means, however:

Way back in the early 18th century, a Swedish biologist by the name of Carl Linnaeus…

Mobile applications based on machine learning are reshaping and affecting many aspects of our lives. Implementing machine learning on mobile devices faces various challenges, including computational power, energy, latency, low memory, and privacy risks. In this article, we…

This article was written on OpenAI. 

We’ve created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and…

Introduction and Motivation

It is becoming increasingly common for organizations to collect very large amounts of data over time, and to…

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…