Over the years, I have been asked many times about my opinions on free and open-source software. Sometimes the questions are driven by comparison to some promising or newly fashionable open-source project, sometimes by comparison to a stagnating open-source project and sometimes by the belief that Wolfram technology would be better if it were open source.At the risk of provoking the fundamentalist end of the open-source community, I thought I would share some of my views in this blog. While there are counterexamples to most of what I have to say, not every point applies to every project, and I am somewhat glossing over the different kinds of “free” and “open,” I hope I have crystallized some key points.
How does it feel to be an intern at Wolfram?
Most undergraduate college students chase opportunities for internships in New York, Miami, Seattle and particularly San Francisco at very young but large high-tech companies like Uber, Pinterest, Quora, Expedia and similar internet companies. These companies offer the best salaries, perks, bosses, coworkers, catered lunches and other luxurious amenities available in such large cities. You would seldom hear about any of these people pursuing opportunities in small, lesser-known towns like Ames, Iowa, or Laramie, Wyoming—and Champaign, Illinois, where Wolfram Research is based, is one of those smaller towns.
Many students want to go into computer science, as it’s such a rapidly developing field. They especially want to work in those companies on the West Coast. If you’re in a different field, like natural science, you might think there’s nothing beyond on-campus research for work experience. At Wolfram Research, though, there is.
The Mathematics Genealogy Project (MGP) is a project dedicated to the compilation of information about all mathematicians of the world, storing this information in a database and exposing it via a web-based search interface. The MGP database contains more than 230,000 mathematicians as of July 2018, and has continued to grow roughly linearly in size since its inception in 1997.In order to make this data more accessible and easily computable, we created an internal version of the MGP data using the Wolfram Language’s entity framework. Using this dataset within the Wolfram Language allows one to easily make computations and visualizations that provide interesting and sometimes unexpected insights into mathematicians and their works. Note that for the time being, these entities are defined only in our private dataset and so are not (yet) available for general use.
One of the many beautiful aspects of mathematics is that often, things that look radically different are in fact the same—or at least share a common core. On their faces, algorithm analysis, function approximation and number theory seem radically different. After all, the first is about computer programs, the second is about smooth functions and the third is about whole numbers. However, they share a common toolset: asymptotic relations and the important concept of asymptotic scale.
By comparing the “important parts” of two functions—a common trick in mathematics—asymptotic analysis classifies functions based on the relative size of their absolute values near a particular point. Depending on the application, this comparison provides quantitative answers to questions such as “Which of these algorithms is fastest?” or “Is function a good approximation to function g?”. Version 11.3 of the Wolfram Language introduces six of these relations, summarized in the following table.