The robots are coming! The robots are coming!
Okay, Paul Revere, settle down. Yes, robots of various kinds and with various capabilities are in development. Many are already available, in some form or fashion, and deployed in industries from manufacturing to hospitality and security. And there has been more than a little hand-wringing and scaremongering about how robots, and automation in general, will affect jobs, the economy, and the nature of business itself.
Computer scientists, by and large, are not considered particularly artistic. When you spend your time in the world of bits and bytes, algorithms and loops, and nodes and edges, you may not think much about aesthetics. To the extent that you do, you might think, “How can I get a computer to create an image or a song or a poem by itself?”
As if we needed more evidence that machine learning is making its way out of the lab and into the hands of “regular” developers and their applications, along comes PyTorch, a Python open-source package developed at Facebook that enables neural network modeling, training, and testing, with a focus on deep learning and high performance.
The term “disruptive,” when applied to business in general and technology in particular, has become something of a buzzword since its original coinage by Harvard Business School professor Clayton Christiansen in the 1990s. Companies in all industries now claim to provide “disruptive” technologies or apply “disruptive” business models or processes.
At the end of 2017, speculators had run the value of a single Bitcoin to over $18,000—a far cry from the pennies that Bitcoins were trading for just a few years ago. But then the Bitcoin price fell back, almost as fast as it had risen, and at this writing has been trading in the $5,000–$10,000 range for several months. The buzz about cryptocurrencies in general and Bitcoin in particular has faded in tandem with Bitcoin’s trading price.
Ever since philosopher and mathematician René Descartes first set quill to paper to draw a line on his newfangled “Cartesian plane” in the 17th century, people have sought ever-cleverer ways to represent data in a pictorial format. The reasons are obvious: A graph, chart, gauge, or map can, at a glance, show important features and trends of a data set that you might miss by poring over tables of numbers. It’s the reason why Edward Tufte’s The Visual Display of Quantitative Information is still considered the bible of data visualization almost 40 years after its first release, and why firms large and small are demanding software “dashboards” showing the real-time health of their businesses.
