April 20, 2017 — Stephen Wolfram
After a Decade, It’s Finally Here!
I’m pleased to announce that as of today, the Wolfram Data Repository is officially launched! It’s been a long road. I actually initiated the project a decade ago—but it’s only now, with all sorts of innovations in the Wolfram Language and its symbolic ways of representing data, as well as with the arrival of the Wolfram Cloud, that all the pieces are finally in place to make a true computable data repository that works the way I think it should.
April 11, 2017 — Swede White, Media & Communications Specialist
It’s National Pet Day on April 11, the day we celebrate furry, feathered or otherwise nonhuman companions. To commemorate the date, we thought we’d use some new features in the Wolfram Language to map a dog walk using pictures taken with a smartphone along the way. After that, we’ll use some neural net functions to identify the content in the photos. One of the great things about Wolfram Language 11.1 is pre-trained neural nets, including Inception V3 trained on ImageNet Competition data and Inception V1 trained on Places365 data, among others, making it super easy for a novice programmer to implement them. These two pre-trained neural nets make it easy to: 1) identify objects in images; and 2) tell a user what sort of landscape an image represents.
April 7, 2017 — Håkan Wettergren, Applications Engineer, SystemModeler (MathCore)
Vibration measurement is an important tool for fault detection in rotating machinery. In a previous post, “How to Use Your Smartphone for Vibration Analysis, Part 1: The Wolfram Language,” I described how you can perform a vibration analysis with a smartphone and Mathematica. Here, I will show how this technique can be improved upon using the Wolfram Cloud. One advantage with this is that I don’t need to bring my laptop.
March 16, 2017 — Stephen Wolfram
A Minor Release That’s Not Minor
I’m pleased to announce the release today of Version 11.1 of the Wolfram Language (and Mathematica). As of now, Version 11.1 is what’s running in the Wolfram Cloud—and desktop versions are available for immediate download for Mac, Windows and Linux.
What’s new in Version 11.1? Well, actually a remarkable amount. Here’s a summary:
March 2, 2017 — Håkan Wettergren, Applications Engineer, SystemModeler (MathCore)
Until now, it has been difficult for the average engineer to perform simple vibration analysis. The initial cost for simple equipment, including software, may be several thousand dollars—and it is not unusual for advanced equipment and software to cost ten times as much. Normally, a vibration specialist starts an investigation with a hammer impact test. An accelerometer is mounted on a structure, and a special impact hammer is used to excite the structure at several locations in the simplest and most common form of hammer impact testing. The accelerometer and hammer-force signals are recorded. Modal analysis is then used to get a preliminary understanding of the behavior of the system. The minimum equipment requirements for such a test are an accelerometer, an impact hammer, amplifiers, a signal recorder and analysis software.
I’ve figured out how to use the Wolfram Language on my smartphone to sample and analyze machine vibration and noise, and to perform surprisingly good vibration analysis. I’ll show you how, and give you some simple Wolfram Language code to get you started.
January 31, 2017 — Michael Gammon, Blog Coordinator
If aliens actually visited Earth, world leaders would bring in a scientist to develop a process for understanding their language. So when director Denis Villeneuve began working on the science fiction movie Arrival, he and his team turned to real-life computer scientists Stephen and Christopher Wolfram to bring authentic science to the big screen. Christopher specifically was tasked with analyzing and writing code for a fictional nonlinear visual language. On January 31, he demonstrated the development process he went through in a livecoding event broadcast on LiveEdu.tv.
January 24, 2017 — Jeremy Sykes, Publishing Assistant, Wolfram Media
Jeremy Sykes: To celebrate the release of Hands-on Start to Wolfram Mathematica and Programming with the Wolfram Language (HOS2), now in its second edition, I sat down with the authors. Working with Cliff, Kelvin and Michael as the book’s production manager has been an easy and engaging process. I’m thrilled to see the second edition in print, particularly now in its smaller, more conveniently sized format.
January 3, 2017 — John Moore, Marketing and Technical Content Team Lead
It’s been a busy year here at the Wolfram Blog. We’ve written about ways to avoid the UK’s most unhygienic foods, exciting new developments in mathematics and even how you can become a better Pokémon GO player. Here are some of our most popular stories from the year.
December 28, 2016 — Kathryn Cramer, Technical Communications and Strategy Group
When looking through the posts on Wolfram Community, the last thing I expected was to find exciting gardening ideas.
The general idea of Ed Pegg’s tribute post honoring Martin Gardner, “Extreme Orchards for Gardner,” is to find patterns for planting trees in configurations with constraints like “25 trees to get 18 lines, each having 5 trees.” Most of the configurations look like ridiculous ideas of how to plant actual trees. For example:
December 16, 2016 — Robert Cook, Senior Consultant, Wolfram Technical Services
The UK’s National Health Service (NHS) is in crisis. With a current budget of just over £100 billion, the NHS predicts a £30 billion funding gap by 2020 or 2021 unless there is radical action. A key part of this is addressing how the NHS can predict and prevent harm well in advance and deliver a “digital healthcare transformation” to their frontline services, utilizing vast quantities of data to make informed and insightful decisions.
This is where Wolfram comes in. Our UK-based Technical Services Team worked with the British NHS to help solve a specific problem facing the NHS—one many organizations will recognize: data sitting in siloed databases, with limited analysis algorithms on offer. They wanted to see if it was possible to pull together multiple data sources, combining off-the-shelf clinical databases with the hospital trusts’ bespoke offerings and mine them for signals. We set out to help them answer questions like “Can the number of slips, trips and falls in hospitals be reduced?”