March 25, 2016 — Wolfram Blog Team
Mark your calendars now for the 2016 Wolfram Technology Conference! Join us October 18–21 at Wolfram headquarters in Champaign, Illinois, where we’ll be getting things off to an exciting start with a keynote address by Wolfram founder and CEO Stephen Wolfram on Tuesday, October 18 at 5pm.
Our conference gives developers and colleagues a rare opportunity for face-to-face discussion of the latest developments and features for cloud computing, interactive deployment, mobile devices, and more. Arrive early for pre-conference training opportunities, and come ready to participate in hands-on workshops, nonstop networking opportunities, and the Wolfram Language One-Liner Competition, just to name a few activities.
We are also looking for users to share their own stories and interests! Submit your presentation proposal by July 15 for full consideration. Last year’s lineup included everything from political data science to winning hackathon solutions to programming in the Wolfram Cloud… and literally almost everything in between. Review a sampling of the 2015 talks below, or visit our website for more.
Commanding the Wolfram Cloud—Todd Gayley
March 18, 2016 — Emily Suess, Technical Writer, Technical Communications and Strategy Group
Wolfram Community members continue to amaze us. Take a look at a few of the fun and clever ideas shared by our members in the first part of 2016.
How to LEGO-fy Your Plots and 3D Models, by Sander Huisman
This marvel by Sander Huisman, a postdoc from École Normale Supérieure de Lyon, attracted more than 6,000 views in one day and was trending on Reddit, Hacker News, and other social media channels. Huisman’s code iteratively covers layers with bricks of increasingly smaller sizes, alternating in the horizontal x and y directions. Read the full post to see how to turn your own plots, 3D scans, and models into brick-shaped masterpieces.
February 5, 2016 — Brian Wood, Technical Writer, Technical Communications and Strategy Group
“What are the odds?” This phrase is often tossed around to point out seemingly coincidental occurrences, and it’s normally intended as a rhetorical question. Most people won’t even wager a guess; they know that the implied answer is usually “very slim.”
However, I always find myself fascinated by this question. I like to think about the events leading up to a situation and what sorts of unseen mechanisms might be at work. I interpret the question as a challenge, an exciting topic worthy of discussion. In some cases the odds may seem incalculable—and I’ll admit it’s not always easy. However, a quick investigation of the surrounding mathematics can give you a lot of insight. Hopefully after reading this post, you’ll have a better answer the next time someone asks, “What are the odds?”
December 23, 2015 — Kathryn Cramer, Technical Communications and Strategy Group
With some impressive new features, new forums, and many new members, Wolfram Community has had a great year. As we approach the end of 2015, we wanted to share a few highlights from the last few months’ excellent posts on the Wolfram Community site.
Interested in drones? Check out these posts.
Connecting ROS to the Wolfram Language, Or Controlling a Parrot ArDrone 2.0 from Mathematica, by Loris Gliner, a student in aeronautical engineering.
Loris Gliner used his time in the Wolfram mentorship program to work out how to connect the Wolfram Language to the Linux Robot Operating System. He includes code examples and a video showing the flight of a Parrot ArDrone 2.0 controlled via the Wolfram Language.
November 5, 2015 — Christopher Carlson, Senior User Interface Developer, User Interfaces
The One-Liner Competition has become a tradition at our annual Wolfram Technology Conference. It’s an opportunity for some of the most talented Wolfram Language developers to show the world what amazing things can be done with a mere 128 characters of Wolfram Language code.
More than any other programming language, the Wolfram Language gives you a wealth of sophisticated built-in algorithms that you can combine and recombine to do things you wouldn’t think possible without reams of computer code. This year’s One-Liner submissions showed the diversity of the language. There were news monitors, sonifications, file system indexers, web mappers, geographic mappers, anatomical visualizations, retro graphics, animations, hypnotic dynamic graphics, and web data miners… all implemented with 128 or fewer characters.
The first of three honorable mentions went to Richard Gass for his New York Times Word Cloud. With 127 characters of Wolfram Language code, he builds a word cloud of topics on the current New York Times front page by pulling nouns out of the headlines:
September 21, 2015 — Arnoud Buzing, Director of Quality and Release Management
I drink too much coffee—it’s one of my few vices. Recently, my favorite espresso machine at the Wolfram Research headquarters in Champaign, Illinois, was replaced with a fancy new combination coffee and espresso maker. The coffee now comes in little pouches of various flavors, ranging from “light and smooth” to “dark and intense”. There even is a “hot chocolate” pouch and a way to make cappuccinos using both a “froth” pouch and an “espresso” pouch. Here is a picture of the new coffee selection:
May 13, 2015 — Stephen Wolfram
“What is this a picture of?” Humans can usually answer such questions instantly, but in the past it’s always seemed out of reach for computers to do this. For nearly 40 years I’ve been sure computers would eventually get there—but I’ve wondered when.
I’ve built systems that give computers all sorts of intelligence, much of it far beyond the human level. And for a long time we’ve been integrating all that intelligence into the Wolfram Language.
Now I’m excited to be able to say that we’ve reached a milestone: there’s finally a function called ImageIdentify built into the Wolfram Language that lets you ask, “What is this a picture of?”—and get an answer.
And today we’re launching the Wolfram Language Image Identification Project on the web to let anyone easily take any picture (drag it from a web page, snap it on your phone, or load it from a file) and see what ImageIdentify thinks it is:
May 7, 2015 — Robert Nachbar, Consultant
Spring is here, finally, and everyone around here is tired of snow this year! Some of the hardier flowers are up already, such as daffodils and hyacinths. So, naturally, I started thinking about when I could put in the more delicate annuals, or even my tomatoes. I don’t want them to be bitten by a late frost (we had one the other day!). And in the autumn, we want to know how late we can harvest before a frost might damage the produce.
Well, I could consult The Old Farmer’s Almanac for the last frost date, but how accurate is it for my specific locale? What about the variability? Might there be a trend to earlier dates due to global warming? To answer these questions, I need historical temperature data. The Wolfram Language has weather data available, so maybe I could do a little data mining and come up with our own planting chart, and you could for your town, too.
April 28, 2015 — Stephen Wolfram
My goal with the Wolfram Language is to take programming to a new level. And over the past year we’ve been rolling out ways to use and deploy the language in many places—desktop, cloud, mobile, embedded, etc. So what about wearables? And in particular, what about the Apple Watch? A few days ago I decided to explore what could be done. So I cleared my schedule for the day, and started writing code.
My idea was to write code with our standard Wolfram Programming Cloud, but instead of producing a web app or web API, to produce an app for the Apple Watch. And conveniently enough, a preliminary version of our Wolfram Cloud app just became available in the App Store—letting me deploy from the Wolfram Cloud to both mobile devices and the watch.
March 24, 2015 — Mariusz Jankowski
Recently, during a particularly severe patch of winter weather and much too much shoveling of snow off my driveway, I decided, with help from the Wolfram Language, to bring back memories of fairer weather by looking at commuting to work on a bicycle.
This past year, I finally succumbed to the increasingly common practice of recording personal activity data. Over the last few years, I’d noted that my rides had become shorter and easier as the season progressed, so I was mildly interested in verifying this improvement in personal fitness. Using nothing more than a smart phone and a suitable application, I recorded 27 rides between home and work, and then used the Wolfram Language to read, analyze, and visualize the results.
Here is a Google Earth image showing my morning bike route covering a distance of a little under 11 miles, running from east to west.