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.
April 18, 2012 — Vitaliy Kaurov, Academic Director, Wolfram Science and Innovation Initiatives
A number of you have written us asking about interface design, Dynamic structures, and general starting tips for creating Wolfram Computable Document Format (CDF) files. I will present three examples of CDF files that will provide some insight into good practices. You should also read the recent Mathematica Q&A Series blog post about delivering CDF to your websites and blogs with the help of the CDF Web Deployment Wizard. This enables users to showcase their Mathematica projects online and share them with the global community. Let’s have a look at some features that make CDF great, rising well above other platforms. For a more extensive list, please see the CDF comparison table.
We will start with a short program that numerically solves the challenging problem of constrained global optimization by finding the minimum on a limited surface region. Think of finding the lowest point of an area of a mountain range. Dragging the 2D slider on the interface below automatically changes the surface geometry, and the CDF engine quickly recomputes the new minimum. This is reflected in the updated positions of the red dot. Drag and rotate the 3D graphics with the mouse to get a different view. Hold Ctrl while dragging to zoom (Command on a Mac) or hold Shift and drag to pan.
March 25, 2010 — Adam Berry, Senior Kernel Developer
It happens to everyone—you spend forever digging around in your filesystem for the dataset you need to finish your work. But you can’t remember the name or enough about the contents to be able to search for it. Searching is wasted time, time that would be far better spent on productive tasks.
What users like myself really need is for our tools to reflect the way we actually work, and that’s where project-based workflows in tools like Wolfram Workbench come in.
When working with Mathematica, we need notebooks—some will contain rough work and some will be presentation material. We may also need some data and other forms of output, such as HTML for final delivery. So let’s walk through setting up a project, and some of the features that can enhance your workflow and improve your productivity.
February 25, 2010 — Wolfram Blog Team
Wolfram|Alpha‘s mission—to make all systematic knowledge immediately computable by anyone—is a major software engineering effort. With millions of lines of code and hundreds of team members, a sophisticated code-base manager is essential in making the project possible. Enter Wolfram Workbench.
Wolfram Workbench 2, the recently released version of Wolfram’s state-of-the-art software engineering and deployment tool, is used at all levels of the Wolfram|Alpha project, from data curation and quality assurance to documentation and framework development. With its leading code-editing, navigation, and project-management tools, Workbench is a scalable solution that is necessary for building and growing Wolfram|Alpha.
In this video, two Wolfram|Alpha developers describe Workbench‘s invaluable role in the project.
February 17, 2010 — Wolfram Blog Team
Wolfram Workbench 2 is out today. New in Version 2 is the ability to create and integrate documentation for your Mathematica applications, as well as a host of improvements to code editing, navigation, and more.
Workbench is an Eclipse-based integrated development environment (IDE) with a powerful suite of tools to help you quickly create innovative, next-generation applications from concept to completion. You can work with any Eclipse-supported language, making Workbench a very efficient organizational tool. It’s a powerful tool for small projects as well as large scale applications. How do we know? It is one of our key tools in the development of Mathematica, Wolfram|Alpha, and other Wolfram technologies.
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