July 19, 2017 — Stephen Wolfram
The Philosophy of Chemicals
“We’ve just got to decide: is a chemical like a city or like a number?” I spent my day yesterday—as I have for much of the past 30 years—designing new features of the Wolfram Language. And yesterday afternoon one of my meetings was a fast-paced discussion about how to extend the chemistry capabilities of the language.
At some level the problem we were discussing was quintessentially practical. But as so often turns out to be the case for things we do, it ultimately involves some deep intellectual issues. And to actually get the right answer—and to successfully design language features that will stand the test of time—we needed to plumb those depths, and talk about things that usually wouldn’t be considered outside of some kind of philosophy seminar.
January 3, 2017 — John Moore, Marketing and Technical Content Team Lead, Technical Communications & Strategy Group
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.
November 4, 2016 — Zach Littrell, Technical Content Writer, Technical Communications and Strategy Group
Here are just a handful of things I heard while attending my first Wolfram Technology Conference:
- “We had a nearly 4-billion-time speedup on this code example.”
- “We’ve worked together for over 9 years, and now we’re finally meeting!”
- “Coding in the Wolfram Language is like collaborating with 200 or 300 experts.”
- “You can turn financial data into rap music. Instead, how about we turn rap music into financial data?”
As a first-timer from the Wolfram Blog Team attending the Technology Conference, I wanted to share with you some of the highlights for me—making new friends, watching Wolfram Language experts code and seeing what the Wolfram family has been up to around the world this past year.
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.
April 16, 2015 — Stephen Wolfram
The Wolfram Cloud Needs to Be Perfect
The Wolfram Cloud is coming out of beta soon (yay!), and right now I’m spending much of my time working to make it as good as possible (and, by the way, it’s getting to be really great!). Mostly I concentrate on defining high-level function and strategy. But I like to understand things at every level, and as a CEO, one’s ultimately responsible for everything. And at the beginning of March I found myself diving deep into something I never expected…
Here’s the story. As a serious production system that lots of people will use to do things like run businesses, the Wolfram Cloud should be as fast as possible. Our metrics were saying that typical speeds were good, but subjectively when I used it something felt wrong. Sometimes it was plenty fast, but sometimes it seemed way too slow.
We’ve got excellent software engineers, but months were going by, and things didn’t seem to be changing. Meanwhile, we’d just released the Wolfram Data Drop. So I thought, why don’t I just run some tests myself, maybe collecting data in our nice new Wolfram Data Drop?
A great thing about the Wolfram Language is how friendly it is for busy people: even if you only have time to dash off a few lines of code, you can get real things done. And in this case, I only had to run three lines of code to find a problem.
First, I deployed a web API for a trivial Wolfram Language program to the Wolfram Cloud:
![In[1]:= CloudDeploy[APIFunction[{}, 1 &]]](https://blog.stephenwolfram.com/data/uploads/2015/04/cloud-bug-hunting-in1.png "In[1]:= CloudDeploy[APIFunction[{}, 1 &]]")
February 9, 2015 — Jenna Giuffrida, Content Administrator, Technical Communications and Strategy Group
We are once again thrilled by the wide variety of topics covered by authors around the world using Wolfram technologies to write their books and explore their disciplines. These latest additions range from covering the basics for students to working within specialties like continuum mechanics.
October 16, 2014 — Jenna Giuffrida, Content Administrator, Technical Communications and Strategy Group
Summer has drawn to a close, and so too have our annual internships. Each year Wolfram welcomes a new group of interns to work on an exciting array of projects ranging all the way from Bell polynomials to food science. It was a season for learning, growth, and making strides across disciplinary and academic divides. The Wolfram interns are an invaluable part of our team, and they couldn’t wait to tell us all about their time here. Here are just a few examples of the work that was done.
April 16, 2014 — Wolfram Blog Team
Professor Malcolm Levitt is Head of Magnetic Resonance at the University of Southampton and a leader in the field of magnetic resonance research. In the early 2000s, he began programming SpinDynamica—a set of Mathematica packages that run spin dynamical calculations—to explore magnetic resonance concepts and develop experiments.
SpinDynamica is an open-source package that Professor Levitt continues to work on as a hobby in his spare time, but the SpinDynamica community also contributes add-ons to bring additional functionality to researchers.
Professor Levitt graciously agreed to answer a few of our questions about his work, Mathematica, and SpinDynamica. He’s hopeful that as word spreads, others will submit add-ons that enhance the core functionality of SpinDynamica.
April 10, 2014 — Wolfram Blog Team
It probably comes as no surprise that Wolfram has been asked to participate in a number of hackathons recently, including the upcoming HackIllinois. There’s a natural fit between our pioneering, agile approach to technology development and the growing hackathon phenomenon, in which coders come together for a short but intensive time—either individually or in teams—to create new and unique software or hardware applications.
Last month while at SXSW 2014, Wolfram helped provide support for Slashathon, the first-ever music-focused hackathon. Hosted by Slash from Guns N’ Roses, the winning hack will be used to help release Slash’s new album. Wolfram provided mentoring for the competition in the form of onsite coding experts and technology access.
November 14, 2012 — Jon McLoone, Director, Technical Communication & Strategy
Update: See our latest post on How the Wolfram Language Measures Up.
I stumbled upon a nice project called Rosetta Code. Their stated aim is “to present solutions to the same task in as many different languages as possible, to demonstrate how languages are similar and different, and to aid a person with a grounding in one approach to a problem in learning another.”
After amusing myself by contributing a few solutions (Flood filling, Mean angle, and Sum digits of an integer being some of mine), I realized that the data hidden in the site provided an opportunity to quantify a claim that I have often made over the years—that Mathematica code tends to be shorter than equivalent code in other languages. This is due to both its high-level nature and built-in computational knowledge.
Here is what I found.
Mathematica code is typically less than a third of the length of the same tasks written in other languages, and often much better.
Newer Posts