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.

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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.

A few lines of Wolfram Language code creates and deploys an Apple Watch app

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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.

Morning commute to work

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March 17, 2015 — Arnoud Buzing, Director of Quality and Release Management

Recently Stephen Wolfram announced the Wolfram Data Drop, which is a great new tool to upload any type of data from any type of device. I’ll show how you can use the Wolfram Data Drop with a weather station you build using some basic hardware and a few lines of code. Once completed, your device will take temperature measurements every second for 60 seconds, and upload their average value to the Wolfram Data Drop every minute. This will give you 60 data points per hour and 1,440 data points per day. With this data you can use Wolfram Programming Cloud to understand how the temperature changes over time. You can find the exact times in a given day when the temperature was the highest or lowest, when the temperature changed the fastest, and maybe even use the data to make predictions! Can you beat your local weather station and make a prediction that is better?

confused weatherman

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March 12, 2015 — Stephen Wolfram

Pictures from Pi Day now added »

This coming Saturday is “Pi Day of the Century”. The date 3/14/15 in month/day/year format is like the first digits of And at 9:26:53.589… it’s a “super pi moment”.

3/14/15 9:26:53.589... a "super pi moment" indeed

Between Mathematica and , I’m pretty sure our company has delivered more π to the world than any other organization in history. So of course we have to do something special for Pi Day of the Century.

Pi Day of the Century with Wolfram: 3.14.15 9:26:53

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March 4, 2015 — Stephen Wolfram

Where should data from the Internet of Things go? We’ve got great technology in the Wolfram Language for interpreting, visualizing, analyzing, querying and otherwise doing interesting things with it. But the question is, how should the data from all those connected devices and everything else actually get to where good things can be done with it? Today we’re launching what I think is a great solution: the Wolfram Data Drop.

Wolfram Data Drop

When I first started thinking about the Data Drop, I viewed it mainly as a convenience—a means to get data from here to there. But now that we’ve built the Data Drop, I’ve realized it’s much more than that. And in fact, it’s a major step in our continuing efforts to integrate computation and the real world.

So what is the Wolfram Data Drop? At a functional level, it’s a universal accumulator of data, set up to get—and organize—data coming from sensors, devices, programs, or for that matter, humans or anything else. And to store this data in the cloud in a way that makes it completely seamless to compute with.

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February 27, 2015 — Vitaliy Kaurov, Technical Communication & Strategy

Martin Handford can spend weeks creating a single Where’s Waldo puzzle hiding a tiny red and white striped character wearing Lennon glasses and a bobble hat among an ocean of cartoon figures that are immersed in amusing activities. Finding Waldo is the puzzle’s objective, so hiding him well, perhaps, is even more challenging. Martin once said, “As I work my way through a picture, I add Wally when I come to what I feel is a good place to hide him.” Aware of this, Ben Blatt from Slate magazine wondered if it’s possible “to master Where’s Waldo by mapping Handford’s patterns?” Ben devised a simple trick to speed up a Waldo search. In a sense, it’s the same observation that allowed Jon McLoone to write an algorithm that can beat a human in a Rock-Paper-Scissors game. As Jon puts it, “we can rely on the fact that humans are not very good at being random.”

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January 30, 2015 — Jenna Giuffrida, Content Administrator, Technical Communications and Strategy Group

This weekend marks the culmination of blood, sweat, and, oh yes, tears (Deflategate, anyone?) from months of struggle: Super Bowl XLIX.

For those of you who are interested, Wolfram|Alpha possesses a wealth of sports stats so that you can get all the cold, hard facts about the Patriots and the Seahawks.

Patriots vs. Seahawks

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December 15, 2014 — Wolfram Blog Team

It’s the holiday season, and Wolfram is gearing up for bright lights and winter weather by holding a new Tweet-a-Program challenge. To help us celebrate the holidays, tweet your best holiday ornament-themed lines of Wolfram Language code. As with our other challenges, we’ll use the Wolfram Language to randomly select winning tweets (along with a few of our favorites) to pin, retweet, and share with our followers. If you’re a lucky winner, we’ll send you a free Wolfram T-shirt!

If you need some help getting into the holiday spirit, check out these examples:


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December 3, 2014 — Adriana Rose, Business Development, Partnerships

Get ready, get set… code! It’s the time of year to get thinking about programming with the Hour of Code.

For many years, Wolfram Research has promoted and supported initiatives that encourage computation, programming, and STEM education, and we are always thrilled when efforts are taken by others to do the same., in conjunction with Computer Science Education Week, is sponsoring an event to encourage educators and organizations across the country to dedicate a single hour to coding. This hour gives kids (and adults, too!) a taste of what it means to study computer science—and how it can actually be a creative, fun, and fulfilling process. Millions of students participated in the Hour of Code in past years, and instructors are looking for more engaging activities for their students to try. Enter the Wolfram Language.

Built into the Wolfram Language is the technology from Wolfram|Alpha that enables natural language input—and lets students create code just by writing English.

W|A using natural language

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