Category Archives: Miscellaneous

I contributed to an article titled “The Effects of COVID-19 on Business Collaboration” in the October 2021 edition of the online Pure AI web site. See https://pureai.com/articles/2021/10/04/covid-business-collaboration.aspx. A group of Microsoft analysts investigated how work collaboration patterns at their company … Continue reading →

I was working on a project that uses Azure Functions. An Azure Function is an example of (the wildly misnamed) “serverless technology”. An Azure Function lives in the Cloud, accepts HTTP requests, and gives an HTTP response. I hadn’t used … Continue reading →

I watched an episode of an old TV Western show called “Maverick” recently. The episode was titled “Rope of Cards” (1958). Bret Maverick, played by actor James Garner (1928-2014) is a roguish gambler has all kinds of adventures in the … Continue reading →

I stumbled across an interesting idea called energy distance. Energy distance is a number that is a measure of the distance between two distributions. There are many other ways to define the distance between two distributions. The Kullback-Leibler divergence is … Continue reading →

I noticed an example where great technology is rendered useless because of a lack understanding of human psychology. My story takes place in Las Vegas. I was there speaking at a conference. Before I explain, it’s important to know that … Continue reading →

I was sitting in an airport recently, waiting to board a plane to fly to a conference. I wanted to make use of the time so I decided to review the different colormaps for use with Python matplotlib 3D surface … Continue reading →

I was chit-chatting with a colleague a couple of days ago and the topic of kernel density estimation (KDE) came up. The first hurdle when trying to understand KDE is figuring out exactly what kind of problem the technique solves. … Continue reading →

The Jensen-Shannon distance measures the difference between two probability distributions. For example, suppose P = [0.36, 0.48, 0.16] and Q = [0.30, 0.50, 0.20]. The Jenson-Shannon distance between the two probability distributions is 0.0508. If two distributions are the same, … Continue reading →

Many years ago I was quite interested in mathematical percolation theory. But over the past 10 years or so I haven’t seen many new research papers published on the topic. This figure illustrates some of the main ideas of percolation: … Continue reading →

If you have 70 people in a room, what is the probability that two or more of them have the same birthday? Most people guess something like 70/365 = 0.19 or 19%. But amazingly, the probability is 0.9990 — almost … Continue reading →