News, Views & Insights
Today we celebrate the arrival of the 36th (x.x) version of the Wolfram Language and Mathematica: Version 14.1. We’ve been doing this since 1986: continually inventing new ideas and implementing them in our larger and larger tower of technology. And it’s always very satisfying to be able to deliver our latest achievements to the world.
Today we celebrate a new waypoint on our journey of nearly four decades with the release of Version 14.0 of Wolfram Language and Mathematica. Over the two years since we released Version 13.0 we’ve been steadily delivering the fruits of our research and development in .1 releases every six months. Today we’re aggregating these—and more—into Version 14.0.
In June 2019, Stephen Wolfram announced the Wolfram Function Repository, a curated repository of functions that can be employed immediately in the Wolfram Language. Since then, the Repository has grown to include more than 1,000 functions in over 20 categories.
Functions included in the Repository range from those that are more general and utilitarian in nature to others with very specific applications. As with all Wolfram Language functions, Repository documentation pages contain examples showing how to use the functions. We’re featuring a few of the functions submitted to the Repository so far that showcase the variety of functions our users have built.
We all know Wolfram|Alpha is great for solving calculations and math problems, but not everyone knows about the full breadth of useful data it provides. I entered college as a biology major and was quickly overwhelmed with the amount of information I had to memorize. Class lectures moved at a fast pace, and often my notes had gaps in them where I hadn’t finished writing down what the professor was saying before she moved on. I was up late at night making flashcards for tests and searching desperately through Yahoo! Answers, trying to find information like what exactly the alimentary system does (hint: it “functions in food ingestion and digestion; absorption of water and nutrients; secretion of water, acids, enzymes, buffers and salts; waste excretion; and energy storage”—thanks, Wolfram|Alpha!).
Thinking back on those late-night study sessions, I would have saved a lot of time if I had properly used Wolfram|Alpha as a study tool. Because I was a biology major, many of the areas in which I most frequently sought information were related to scientific fields such as chemistry, but Wolfram|Alpha can be a valuable resource in so many more areas. Here are 15 applications of Wolfram|Alpha in topics beyond mathematics. I hope you will find these to be useful both inside and outside the classroom!
The sparse ruler problem has been famously worked on by Paul Erdős, Marcel J. E. Golay, John Leech, Alfréd Rényi, László Rédei and Solomon W. Golomb, among many others. The problem is this: what is the smallest subset of so that the unsigned pairwise differences of give all values from 1 to ? One way to look at this is to imagine a blank yardstick. At what positions on the yardstick would you add 10 marks, so that you can measure any number of inches up to 36?
Another simple example is of size 3, which has differences , and . The sets of size 2 have only one difference. The minimal subset is not unique; the differences of also give .
Part of what makes the sparse ruler problem so compelling is its embodiment in an object inside every schoolchild's desk—and its enduring appeal lies in its deceptive simplicity. Read on to see precisely just how complicated rulers, marks and recipes can be.
When 20 presidential candidates duke it out on the debate stage, who wins? Americans have been watching a crowded and contentious primary season for the 2020 Democratic nomination for president. After the debates, everyone’s talking about who got the most talk time or attention, which exchanges were most exciting or some other measure of who “won” the night—and who might ultimately clinch a victory at the caucuses. So I decided I’d do a little exploration of the debates using the entity framework, text analytics and graph capabilities of the Wolfram Language and see if I could come up with my own measure of a “win” for a debate, based on which candidate was most central to the conversation.
Today, the world around us is being captured by imaging devices ranging from cell phones and action cameras to microscopes and telescopes. With ever-increasing generation of images, image processing and automatic image analysis are used in a wide range of individual, academic and industry applications.
We are excited to announce Introduction to Image Processing, a free interactive course from Wolfram U, which makes cutting-edge image processing simple with graphical and visual examples that demonstrate how image operations work. It includes 14 video lessons, each lasting 20 minutes or fewer, and 5 short quizzes, as well as a certificate for finishing all course materials. Topics range from how to control brightness and contrast or crop and resize images, to advanced topics including segmentation, image enhancement, feature detection and using machine learning to perform modern image processing—no machine learning knowledge necessary!
Who has not encountered a stink bug? Perhaps the better question is not if, but when. I remember well my first interactions with stink bugs—partly because of their pungent, cilantro-like odor, but also because in my native Catalan language they are called Bernat pudent ("stinky Bernat") and Bernat is my twin brother's name.
So when I encountered the stink bug again when visiting Champaign, Illinois, for the 2019 Wolfram Technology Conference, it brought up a lot of fond childhood memories. This time, however, two things had changed: the frequency of encounters with the stink bug seemed exponentially greater, and I now had the Wolfram Language to more fully (and computationally) satisfy my curiosity about this reviled insect and its growing impact on our ecosystem. So to get a better picture of the arrival and spread of this invasive bug across the US, I used available observation data and the Wolfram Language to make a map of sightings over the past two decades.
It’s been another busy few months on Wolfram Community! If you’ve kept up with the latest posts, you may have noticed that many are live, interactive notebooks embedded directly from the Wolfram Cloud. Take advantage of this feature for your next post on the Community: when authoring your post, use the "Add Notebook" button in the post editor. Learn more about embedding Wolfram Cloud notebooks directly on your website from the Wolfram Notebook Embedder documentation (or download the JavaScript library directly).
We’ve gathered some of our favorite Wolfram Community posts showing the variety of applications made possible with the Wolfram Language.
Looking to fulfill your New Year's resolution of learning new data science skills? Join Wolfram U for Wolfram Technology in Action: Data Science, a three-part web series demonstrating a range of data science applications in the Wolfram Language. These 90-minute sessions feature recorded talks from the 2019 Wolfram Technology Conference, along with live presentations by Wolfram staff scientists, application developers, software engineers and Wolfram Language users who apply the technology every day to their business operations and research.
Newcomers to Wolfram technology are welcome, as are longtime users wanting to see the latest functionality in the language.
Yellowstone National Park has long been known for its active geysers. These geysers are a surface indication of subterranean volcanic activity in the park. In fact, Yellowstone is actually the location of the Yellowstone Caldera, a supervolcano: a volcano with an exceptionally large magma reservoir. The park has had a history of many explosive eruptions over the last two million years or so.
I’ve found that the United States Geological Survey (USGS) maintains data on the various volcanic calderas and related features, which makes it perfect for computational exploration with the Wolfram Language. This data is in the form of SHP files and related data stored as a ZIP archive. Thanks to the detail of this available data, we can use the Wolfram Language and, in particular, GeoGraphics to get a better picture of what this data is telling us.