The Barbell Effect of Machine Learning
If there is one technology that promises to change the world more than any other over the next several decades, it is arguably machine learning. By enabling computers to learn certain things more efficiently than humans and discover certain things that humans cannot, machine learning promises... Read more
Beyond the Black Box in Analytics and Cognitive
There is a growing crisis in the world of analytics and cognitive technologies, and as of yet there is no obvious solution. The crisis was created by a spate of good news in the field of cognitive technology algorithms: they’re working! Specifically, a relatively new and... Read more
The Power of Data Network Effects
In the furiously competitive world of tech startups, where good entrepreneurs tend to think of comparable ideas around the same time and “hot spaces” get crowded quickly with well-funded hopefuls, competitive moats matter more than ever.  Ideally, as your startup scales, you want to not only... Read more
Expected Value of the Diameter of a Tree
Description of the problem Gil Kalai asks the following problem: given a random tree on nn vertices asymptotically behaves like nn vertices by generating n=2n=2 to  Read more
Getting Started with Predictive Maintenance Models
This was originally posted on the Silicon Valley Data Science blog. In a previous post, we introduced an example of an IoT predictive maintenance problem. We framed the problem as one of estimating the remaining useful life (RUL) of in-service equipment, given some past operational history and historical run-to-failure... Read more
Are Your Predictive Models like Broken Clocks?
A wise philosopher (or comedian) once said, “Even a broken clock is right twice a day.” That same statement might also apply to some predictive models. Since prediction is about the future (usually), then random chance (like broken clockwork) may allow our model to be right occasionally (just... Read more
Why Machine Learning Is A Metaphor For Life
Seriously. Hear me out on this. The more I learn about ML, the more I see the number of similarities there are between life and machine learning concepts. Specifically, let’s think about neural networks. Let’s think of a neural net that has a bunch of input nodes... Read more
Which Gender Is More Likely To Trust Artificial Intelligence
Many people are very skeptical of the governments adoption of AI to take over management of its citizen services, but which gender is more comfortable with this decision? The answer to that question, by way of surveys, is men. More men than women feel more comfortable... Read more
Learning Effects, Network Effects and Runaway Leaders
There’s a new economic force at work in the machine learning revolution that is capable of generating increasing returns to scale, much as network effects did in the internet revolution. This force is automated learning, and its business impact comes in the form of learning effects:... Read more
A More Effective Approach to Unsupervised Learning with Time Series Data
Come see Anshuman Guha, Data Scientist from Spark Cognition Speak at ODSC West. Traditional Clustering Approaches In machine learning, the most traditional and popular methods of clustering are hierarchical clustering (similarity-based clustering) and k-means clustering (feature-based clustering). Hierarchical clustering, put simply, is grouping together points in a vector space... Read more