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.
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.
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?"
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?
For more on Wolfram’s summer education programs, read our post about the Wolfram Summer School.
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.
For more on Wolfram’s summer education programs, read our post about the Wolfram Summer Camp.
The 18th annual Wolfram Summer School has just thrown its graduation party in High Fidelity, a virtual world augmented with spatial audio. Students and faculty sang together during karaoke with a DJ and jukebox, chatted away mixing techspeak and humor, said farewells and had a ball celebrating the completion of the program. Due to the COVID-19 pandemic, we chose to make our summer programs more accessible to the students and faculty from all corners of the world—this year from 25 countries and all populated continents.
Explore the contents of this article with a free Wolfram System Modeler trial. Have you ever thought about making your own musical instruments? What about making mathematical models of your instruments? Whether you're someone looking for a cost-effective alternative, a minimalist with dreams of maximalist sounds or a Wolfram Language enthusiast curious about sound design, you can build a virtual version of a modular synthesizer using Wolfram System Modeler.
As Conrad Wolfram writes in his new book, education in computational thinking and quantitative problem solving are largely absent from today’s mathematics curricula. With the current crisis changing education practice in many ways, what better time to try out a sample of our new curriculum? It’s a curriculum fit for learners who want to be better prepared for an AI age where computers can be used to their full potential.
It’s a beta release, a first sample manifestation of what can be deployed in a self-study mode to implement The Math(s) Fix. We’re stretching what can be done in a browser to the limit, so please be patient with refresh times. The content and intended learning outcomes are the key points to look out for; you can see how we’ve merged the learning of general "thinking" outcomes and computation outcomes with real contexts in accessible problems.
Wikidata is a large, community-curated repository of freely usable data. Version 12.1 of the Wolfram Language introduced dedicated functionality to access Wikidata. We came up with a new kind of entity: a fundamental building block called ExternalIdentifier, which I’ll explain in more detail shortly.
The first half of 2020 has brought with it another exciting batch of publications. Wolfram Media has released Conrad Wolfram's The Math(s) Fix. Keep an eye out for the upcoming third edition of Hands-on Start to Wolfram Mathematica later in 2020.