September 17, 2020 — Hamza Alsamraee, Document & Media Systems
A few months before I accepted a Wolfram Research internship—around March—I was very fearful, and so was the majority of the world. We knew very little about the novel coronavirus, and the data was just not robust. In addition to the limited data we had, the scientific process necessarily takes time, so even that was not used to its full extent. In a world where not enough data can quickly become data overload, the question didn’t seem to be finding more data, but rather how can one extract useful and meaningful information from the available data?
A worldwide pandemic is definitely stressful, but a worldwide pandemic without accessible and computable information is much more so. Using Wolfram technologies in coordination with several internal teams, I created a Wolfram U course called COVID-19 Data Analysis and Visualization to try and cut through the informational fog and find some clarity. I saw this course as one that gives power to everyone to be able to look at data and gain insight. After all, data is knowledge, and knowledge is power.
September 15, 2020 — Cliff Hastings, Director, Sales & Strategic Initiatives
In March, my work life changed dramatically, as it did for many around the world. After working in an office environment for almost 25 years, I was told that I needed to work from home for the first time. So I took my laptop, power cord and extra battery home with the expectation that I’d be there for one to two weeks. The first couple of days were a mad dash with our IT department to ensure my VPN, softphone and main tools were set up correctly for remote work. They were great, and for the most part, I was working at 90% right away. The experience opened my eyes, as many of my sales employees work remotely, so I learned a lot about the positives (and, of course, the negatives) they often experience that I may not have appreciated in the past.
September 11, 2020
Brad Janes, Wolfram|Alpha Math Content Manager
Peter Falloon, Data & Semantics Engineering
Jeremy Stratton-Smith, Math Developer, Wolfram|Alpha Math Content
The WolframAlpha Chemistry Team
Wolfram|Alpha Notebook Edition was released nearly a year ago, and we’re proud to share what the team has been working on since. In addition to the improvements made to Wolfram|Alpha itself, new input and output suggestions were added. There were parsing fixes, additions to the Wolfram|Alpha-to-Wolfram Language translation and some of the normal improvements one would expect. There are also some bigger features and interesting new capabilities that we will explore in a bit more detail here.
If you haven’t checked out Wolfram|Alpha Notebook Edition in a while, we’d like to invite you to revisit. With education looking a little different for many people right now, this could be a great time to explore this exciting new way to interface with Wolfram technologies.
September 4, 2020 — Mads Bahrami, Community & Content Developer, Community Advancement
This roundup of Wolfram Community contributions features several different functions and tools related to current times, from the global pandemic to sustainable spaces and homeschool puzzles. Read on to see just a few creative examples from some of our favorite Community members and Wolfram Language wizzes.
September 2, 2020 — Arben Kalziqi, Education Evangelist, Education Partnerships
Schooling looks a little different in 2020. Whether it’s technical issues with the transition to online courses, decreased physical attendance or delayed and last-minute openings, we’re all feeling the pressure caused by the COVID-19 pandemic.
At Wolfram Research, we’ve been involved in education for decades and count millions of parents, teachers and students as both our customers and our friends. Because of this longstanding commitment to learning, we have content, experts and platforms at the ready to help parents and students who are looking for ways to augment their learning.
August 25, 2020 — Bob Sandheinrich, Development Manager, Document & Media Systems
While programming in the Wolfram Language, I am able to quickly and easily get results—one of the best aspects of writing code in a high-level language. The Wolfram Language is so easy to use that I have the freedom to pursue ideas on a whim, even if I know those ideas may not accomplish anything great or work toward a larger goal. In most cases, within a few minutes I figure out if the idea is a dead end. I also figure out if I am on the path to creating something useful or, better yet, fun.
August 18, 2020 — Jérôme Louradour, Machine Learning
A noteworthy achievement of artificial intelligence, since it is driven by artificial neural networks under the label deep learning, is the ability to create artistic works to generate images, text and sounds. At the core of this breakthrough is a basic method to train neural networks that was introduced by Ian Goodfellow in 2014 and was called by Yann LeCun “the most interesting idea in the last 10 years in machine learning”: generative adversarial networks (GANs). A GAN is a way to train a generative network that produces realistic-looking fake samples out of a latent seed, which can be some arbitrary data or random numbers sampled from a simple distribution. Let’s look at how to do so with some of the new capabilities developed for Mathematica Version 12.1.
August 14, 2020 — Devendra Kapadia, Manager of Calculus & Algebra, Algorithms R&D
Linear algebra is probably the easiest and the most useful branch of modern mathematics. Indeed, topics such as matrices and linear equations are often taught in middle or high school. On the other hand, concepts and techniques from linear algebra underlie cutting-edge disciplines such as data science and quantum computation. And in the field of numerical analysis, everything is linear algebra!
Today, I am proud to announce a free interactive course, Introduction to Linear Algebra, that will help students all over the world to master this wonderful subject. The course uses the powerful functions for matrix operations in the Wolfram Language and addresses questions such as “How long would it take to solve a system of 500 linear equations?” or “How does data compression work?”
Playing Cards with Alice and Bob: Using Secure Multi‑Party Computation and the Wolfram Language to Determine a Winner
August 6, 2020 — Arnoud Buzing, Director of Quality and Release Management
While catching up with my old friends Alice and Bob on Zoom a few days ago, I became intrigued by their recent card game hobby—and how they used the Wolfram Language to settle an argument. To figure out who gets to go first at the start of the game, they take one suit (spades) from a full deck, and each draws a card. Then, the person with the highest card value wins. Because they are using only one suit, there can be no ties. Simple, right?
July 30, 2020 — Rory Foulger, Instructional Designer & Technologist, Outreach & Communications
This year marked the ninth annual Wolfram High School Summer Camp, and it was a truly amazing experience. Forty-four students joined us remotely from around the world—from almost on the doorstep of Wolfram’s headquarters in Illinois to as far-flung as Kazakhstan, Germany, Russia, South Korea and India. They dedicated two weeks to learning the Wolfram Language, creating remarkably high-level independent projects and developing strong computational thinking skills. Our students had the opportunity to learn from subject experts from Wolfram Research, their mentors and teaching assistants (TAs) and, of course, our CEO Stephen Wolfram, who met with each student to discuss their projects.