September 26, 2016 — Lizzie Griffiths, Wolfram Research Europe Ltd.
Bonjour la France! This October, we’re coming to you to introduce Mathematica 11. We will be running three conferences across France, starting October 4.
September 23, 2016 — Carlo Giacometti, Mathematica Algorithm R&D
I have always liked listening to music. In high school, I started wondering how it is that music seems to be so universally pleasing, and how it differs from other kinds of sounds and noises. I started learning to play guitar, and later at the University of Trieste, I learned about acoustics and signal processing. I picked up the guitar in high school, but once I began learning to program, the idea of being able to create and process any sound using a computer was liberating. I didn’t need to buy expensive and esoteric gear; I just needed to write some (or a lot!) of code. There are many programming languages that focus on music and sound, but complex operations (such as sampling a number from a special distribution, or the simulation of random processes) often require a lot of effort. That’s why the audio capabilities in the Wolfram Language are special: the ability to deal with audio objects is combined with all the knowledge and computational power of the Wolfram Language!
First, we needed a brand-new atomic object in the language: the Audio object.
September 19, 2016 — Conrad Wolfram, Strategic Director
Today I’m pleased to announce Wolfram Enterprise Private Cloud (EPC), which takes the unique benefits of the Wolfram technology stack—ultimate computation, integrated language and deployment—and makes them available in a centralized, private, secure enterprise solution.
In essence, EPC enables you to put computation at the heart of your infrastructure and in turn deliver a complete enterprise computation solution for your organization.
September 16, 2016 — Greg Hurst, Kernel Developer, Mathematica Algorithm R&D
Thirty-nine students from seven different countries attended our camp at Bentley University this summer. Students arrived at camp with some programming experience, but most had little or no familiarity with the Wolfram Language. Despite this, in nine short days they were all able to complete amazing projects.
September 7, 2016 — Stephen Wolfram
The Computational Future
Computational thinking is going to be a defining feature of the future—and it’s an incredibly important thing to be teaching to kids today. There’s always lots of discussion (and concern) about how to teach mathematical thinking to kids. But looking to the future, this pales in comparison to the importance of teaching computational thinking. Yes, there’s a certain amount of mathematical thinking that’s needed in everyday life, and in many careers. But computational thinking is going to be needed everywhere. And doing it well is going to be a key to success in almost all future careers.
Doctors, lawyers, teachers, farmers, whatever. The future of all these professions will be full of computational thinking. Whether it’s sensor-based medicine, computational contracts, education analytics or computational agriculture—success is going to rely on being able to do computational thinking well.
I’ve noticed an interesting trend. Pick any field X, from archeology to zoology. There either is now a “computational X” or there soon will be. And it’s widely viewed as the future of the field.
September 1, 2016 — Håkan Wettergren, Applications Engineer, SystemModeler (MathCore)
Explore the contents of this article with a free Wolfram SystemModeler trial.Rolling bearings are one of the most common machine elements today. Almost all mechanisms with a rotational part, whether electrical toothbrushes, a computer hard drive or a washing machine, have one or more rolling bearings. In bicycles and especially in cars, there are a lot of rolling bearings, typically 100–150. Bearings are crucial—and their failure can be catastrophic—in development-pushing applications such as railroad wheelsets and, lately, large wind turbine generators. The Swedish bearing manufacturer SKF estimates that the global rolling bearing market volume in 2014 reached between 330 and 340 billion bearings.
Rolling bearings are named after their shapes—for instance, cylindrical roller bearings, tapered roller bearings and spherical roller bearings. Radial deep-groove ball bearings are the most common rolling bearing type, accounting for almost 30% of the world bearing demand. The most common roller bearing type (a subtype of a rolling bearing) is the tapered roller bearing, accounting for about 20% of the world bearing market.
With so many bearings installed every year, the calculations in the design process, manufacturing quality, operation environment, etc. have improved over time. Today, bearings often last as long as the product in which they are mounted. Not that long ago, you would have needed to change the bearings in a car’s gearbox or wheel bearing several times during that car’s lifetime. You might also have needed to change the bearings in a bicycle, kitchen fan or lawn mower.
For most applications, the basic traditional bearing design concept works fine. However, for more complex multidomain systems or more advanced loads, it may be necessary to use a more advanced design software. Wolfram SystemModeler has been used in advanced multidomain bearing investigations for more than 14 years. The accuracy of the rolling bearing element forces and Hertzian contact stresses are the same as the software from the largest bearing manufacturers. However, SystemModeler provides the possibilities to also model the dynamics of the nonlinear and multidomain surroundings, which give the understanding necessary for solving the problems of much more complex systems. The simulation time for models developed in SystemModeler is also shorter than comparable approaches.
August 26, 2016 — Zach Littrell, Technical Content Writer, Technical Communications and Strategy Group
We are constantly surprised by what fascinating applications and topics Wolfram Language experts are writing about, and we’re happy to again share with you some of these amazing authors’ works. With topics ranging from learning to use the Wolfram Language on a Raspberry Pi to a groundbreaking book with a novel approach to calculations, you are bound to find a publication perfect for your interests.
August 22, 2016 — Ishwarya Vardhani, Educational Partnerships
Are you a teacher who’s been asked “Why am I learning this?”, “How is this going to help me in real life?” and other variations of this question by your students? I know that I faced this when I was teaching, and it can be tough to provide a satisfactory response. However, being able to address this issue is critical in the classroom. We believe that Wolfram|Alpha provides one way to do so.
The Wolfram Knowledgebase, our ever-growing repository of curated computable data, gives you instant access to trillions of data elements across thousands of domains. With Wolfram|Alpha, you can query these data points using natural language (plain English) right in your classroom.
By using real-world data, students have the opportunity to direct their learning toward areas that they care about. In the economics classroom, you can discuss GDP using data about real countries, data that is current and citable. Explore Wolfram|Alpha’s trove of socioeconomic data that will open multiple areas of inquiry in the classroom. A wonderful side effect that I’ve found with using a tool like Alpha is that it also teaches you to pose queries intelligently. Being able to carefully construct a problem is an integral step in the process of thinking critically.
Join us for a special training event on August 24 to learn more about using Wolfram|Alpha in the classroom. This session in the Wolfram|Alpha for Educators: Webinar Training Series will focus on the economics classroom. Previous sessions in this series focused on calculus and physics classrooms, and you can watch our past event recordings online.
August 17, 2016 — Zach Littrell, Technical Content Writer, Technical Communications and Strategy Group
3D printing. Audio. Machine learning. Neural networks. There are 555 completely new functions, major new areas of functionality and a vast deepening of core capabilities in Version 11 of the Wolfram Language and Mathematica. Continuing a three-decade tradition of aggressive innovation, Version 11 is filled to the brim with cutting-edge technology, and we’re excited to share with you how to put all these new features to use.
Join us for a special two-part webinar event, New in the Wolfram Language and Mathematica Version 11, on August 23, 2016, from 2–3:30pm EDT (6–7:30pm GMT) and August 30, 2016, from 2–4pm EDT (6–8pm GMT). Take the opportunity to explore the new features in the Wolfram Language and Mathematica with experts at Wolfram Research, then engage in interactive Q&A with the developers after the presentations.
August 12, 2016 — Bernat Espigulé-Pons, Consultant, Technical Communications and Strategy Group
There’s a Computed Pokémon nearby! Here is a Poké Spikey. This will help you catch ’em all! In this blog post I will share with you several data insights about the viral social media phenomenon that is Pokémon GO. First I will get you familiarized with the original 151 Pokémon that have now invaded our real world, and then I’ll show you how to find the shortest tour to visit your nearby gyms.