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:
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 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.
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.
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.”
August 1, 2014 — Arnoud Buzing, Director of Quality and Release Management
Today I’m happy to announce an update for Mathematica and the Wolfram Language for the Raspberry Pi that brings those new features to the Raspberry Pi. To get the new version of the Wolfram Language, simply run this command in a terminal on your Raspberry Pi:
sudo apt-get update && sudo apt-get install wolfram-engine
This new version will also be pre-installed in the next release of NOOBS, the easy setup system for the Raspberry Pi.
July 30, 2014 — Wolfram Blog Team
Kenzo Nakamura uses Mathematica to create Escher-inspired mathematical art. His trademark piece, Three-Circle Mandala, depicts a large circle covered by three smaller, repeating circles that form a Sierpinksi gasket.
When Nakamura began using Mathematica, he didn’t originally intend to use it for his artistic endeavors. He found the program by chance at a seminar while looking for the right tool to help him write his master’s thesis.
Now, in addition to using Mathematica for technical and operations research, Nakamura uses it to create Mathematica-derived visual illusions. Although his works are static drawings, their infinite properties create the illusion of movement.
Watch Nakamura discuss using Mathematica to create his drawings, and see a few of his creations.
(YouTube in Japanese)
July 22, 2014 — Wolfram Blog Team
Photography by Tracy Howl and Paul Clarke
Has our newfound massive availability of data improved decisions and lead to better democracy around the world? Most would say, “It’s highly questionable.”
Conrad Wolfram’s TEDx UK Parliament talk poses this question and explains how computation can be key to the answer, bridging the divide between availability and practical accessibility of data, individualized answers, and the democratization of new knowledge generation. This transformation will be critical not only to government efficiency and business effectiveness—but will fundamentally affect education, society, and democracy as a whole.
Wolfram|Alpha and Mathematica 10 demos feature throughout—including a live Wolfram Language generated tweet.
May 30, 2014 — Wolfram Blog Team
Donald Barnhart is a self-proclaimed mad optical scientist and independent business owner. He’s been developing optical design and analysis software in Mathematica since 1991, he’s the creator of the popular Optica software package, and he’s the developer of the first successful high-resolution holographic instrument that measures three-dimensional velocity fields in fluids.
Now Barnhart has another invention to add to his list of accomplishments: a totally new kind of photo album called the SlideOScope.
July 20, 2012 — Michael Trott, Chief Scientist
(This is the first post in a three-part series about electrostatic and magnetostatic problems involving sharp edges.)
Mathematica can do a lot of different computations. Easy and complicated ones, numeric and symbolic ones, applied and theoretical ones, small and large ones. All by carrying out a Mathematica program.
Wolfram|Alpha too carries out a lot of computations (actually, tens of millions every day), all specified through free-form inputs, not Mathematica programs. Wolfram|Alpha is heavily based on Mathematica, and many of the mathematical calculations that Wolfram|Alpha carries out rely on the mathematical power of Mathematica. And while Wolfram|Alpha can carry out a vast amount of calculations, it cannot carry out all possible calculations, either because it does not (yet) know how to do a calculation or because the (underlying Mathematica) calculation would take a longer time than available through Wolfram|Alpha. So for a detailed investigation of a more complicated engineering, physics, or chemistry problem, having a copy of Mathematica handy is mandatory.
But there is also the reverse relation between Mathematica and Wolfram|Alpha: Wolfram|Alpha’s knowledge, especially its data knowledge, allows it to carry out investigations and calculations that can substantially increase the power of pure Mathematica. And all of this is because Wolfram|Alpha’s knowledge is accessible through the WolframAlpha function within Mathematica.
August 26, 2011 — Maryka Baraka, Marketing Content Manager
Now that the Computable Document Format (CDF) is officially released, the real fun has begun. At least for me. Whether or not you plan to start using CDF in your own work anytime soon, you’ve got to admit, it’s pretty cool. From publishing textbooks and making complex information easy to understand to recreational games and everyday blogging, CDF truly makes it possible to communicate ideas in a more participatory way—as adopters of the format have already proven.
It has been exciting to see the tremendous interest in CDF following last month’s launch. Although CDF is a new advancement, it’s clear that the possibilities it presents resonate with authors and readers alike, and hence with publishers as well.