April 1, 2020 — Alec Titterton, CBM Content Development Manager, European Sales
With many schools transitioning to remote learning for the remainder of the school year, educators face the challenge of maintaining the same quality of education as in-person lessons. Here’s a collection of the resources offered by Wolfram Research and others to help educators in an e‑learning environment.
March 17, 2020 — Ishwarya Vardhani, Education Partnerships Manager, Partnerships
Communities the world over are bracing themselves for impact from the novel coronavirus COVID-19. Many school districts in particular have already suspended sessions for several weeks to come—and understandably, parents and educators feel anxious about navigating at-home learning (among the variety of other concerns brought about by a pandemic!).
Professionally, a large part of what I do at Wolfram involves working with educators, students and organizations, and empowering them with the technology to think computationally. I know of several parents with older kids who are now at home, enrolled in schools that are not completely prepared to provide online instruction. While the internet is awash with curricula, it can be a challenging task to assess the quality, relevance and usefulness of each course, given the amount of what is out there.
For decades now at Wolfram, we’ve been committed to the creation of cutting-edge technology and resources for classrooms. Let’s take a look at our wealth of free online resources for quality education while at home.
February 12, 2020 — Ed Pegg Jr, Editor, Wolfram Demonstrations Project
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.
January 23, 2020 — Jofre Espigule-Pons, Document & Media Systems
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.
December 12, 2019 — Ishwarya Vardhani, Education Partnerships Manager, Partnerships
Happy Hour of Code! There’s no better reason to start learning or continue honing your programming skills than the Hour of Code, an annual celebration of computer science during Computer Science Education Week. While we like to think that every hour is a great hour to code, we look forward to the Hour of Code event as an opportunity to come together and share some of our best Wolfram Language resources for students. Since its 2013 launch, the Hour of Code has been an immense success, introducing valuable programming skills to millions of students. So with this year’s Hour already underway, let’s take a look at the ways you can get started!
November 13, 2019 — Jesse Friedman, Software Engineer, Engine Connectivity Engineering
Two weeks ago, I had the pleasure of returning as a commentator for the fourth annual Livecoding Championship, a special event held during the 2019 Wolfram Technology Conference. We had such an incredible turnout this year, with 27 total participants and 14 earning at least one point! Conference attendees and Wolfram staff competed for the title of Livecoding Champion, with seven questions (plus one tiebreaker!) challenging their speed, agility and knowledge of the Wolfram Language. It was a high-spirited battle for first place, and while I had prepared “answer key” solutions in advance, I always look forward to the creativity and cleverness that competitors demonstrate in their wide range of approaches to each question.
By popular request, in addition to revisiting the questions, I’ll walk you through how competitors reached their solutions and earned their points, as a kind of “study guide” for next year’s aspiring champions. So hold on to your keyboards—we’re going in!
November 7, 2019 — Paritosh Mokhasi, Kernel Developer, Algorithms R&D
My student days learning fluid dynamics were all about studying complicated equations and various methods of simplifying and manipulating these equations to get some kind of a result. Unfortunately, this left very little to the imagination when it came to getting an intuitive feel for how a fluid would behave in different situations. When I took my first experimental fluid dynamics course, I got to see how one would use different visualization techniques to understand qualitatively the behavior of the flow. These visualizations gave me a way of creatively looking at a flow, and, as an added bonus, they looked stunning. All these experiments and visualizations were being carried out inside a wind tunnel.
October 24, 2019 — Stephen Wolfram
Wolfram Notebooks on the Web
We’ve been working towards it for many years, but now it’s finally here: an incredibly smooth workflow for publishing Wolfram Notebooks to the web—that makes possible a new level of interactive publishing and computation-enabled communication.
You create a Wolfram Notebook—using all the power of the Wolfram Language and the Wolfram Notebook system—on the desktop or in the cloud. Then you just press a button to publish it to the Wolfram Cloud—and immediately anyone anywhere can both read and interact with it on the web.
It’s an unprecedentedly easy way to get rich, interactive, computational content onto the web. And—together with the power of the Wolfram Language as a computational language—it promises to usher in a new era of computational communication, and to be a crucial driver for the development of “computational X” fields.
September 17, 2019 — Brian Wood, Lead Technical Writer, Document and Media Systems
Our interactive Multiparadigm Data Science (MPDS) course has been up at Wolfram U for over a month now, and we’re pretty satisfied with the results so far. Hundreds of people have started the course—including students from our first Data Science Boot Camp, who joined us at Wolfram headquarters for a three-week training camp. Thanks to the success of the boot camp, we have also had several projects submitted for advanced MPDS certification, which will soon be available within the interactive course.
But what exactly does it mean to be a practitioner of MPDS? And how might the multiparadigm approach improve my computational projects? To find out, I decided to try this free course for myself.
September 5, 2019 — Daniel Lichtblau, Symbolic Algorithms Developer, Algorithms R&D
A Year Ago Today
On September 5 of last year, The New York Times took the unusual step of publishing an op-ed anonymously. It began “I Am Part of the Resistance inside the Trump Administration,” and quickly became known as the “Resistance” op-ed. From the start, there was wide‐ranging speculation as to who might have been the author(s); to this day, that has not been settled. (Spoiler alert: it will not be settled in this blog post, either. But that’s getting ahead of things.) When I learned of this op-ed, the first thing that came to mind, of course, was, “I wonder if authorship attribution software could….” This was followed by, “Well, of course it could. If given the right training data.” When time permitted, I had a look on the internet into where one might find training data, and for that matter who were the people to consider for the pool of candidate authors. I found at least a couple of blog posts that mentioned the possibility of using tweets from administration officials. One gave a preliminary analysis (with President Trump himself receiving the highest score, though by a narrow margin—go figure). It even provided a means of downloading a dataset that the poster had gone to some work to cull from the Twitter site.
The code from that blog was in a language/script in which I am not fluent. My coauthor on two authorship attribution papers (and other work), Catalin Stoean, was able to download the data successfully. I first did some quick validation (to be seen) and got solid results. Upon setting the software loose on the op-ed in question, a clear winner emerged. So for a short time I “knew” who wrote that piece. Except. I decided more serious testing was required.