Computational thinking is going to be a defining feature of the future—and it’s an incredibly important thing to be teaching to kids today. There’s always lots of discussion (and concern) about how to teach mathematical thinking to kids. But looking to the future, this pales in comparison to the importance of teaching computational thinking. Yes, there’s a certain amount of mathematical thinking that’s needed in everyday life, and in many careers. But computational thinking is going to be needed everywhere. And doing it well is going to be a key to success in almost all future careers.
Doctors, lawyers, teachers, farmers, whatever. The future of all these professions will be full of computational thinking. Whether it’s sensor-based medicine, computational contracts, education analytics or computational agriculture—success is going to rely on being able to do computational thinking well.
I’ve noticed an interesting trend. Pick any field X, from archeology to zoology. There either is now a “computational X” or there soon will be. And it’s widely viewed as the future of the field.
I’m thrilled today to announce the release of a major new version of Mathematica and the Wolfram Language: Version 11, available immediately for both desktop and cloud. Hundreds of us have been energetically working on building this for the past two years—and in fact I’ve personally put several thousand hours into it. I’m very excited about what’s in it; it’s a major step forward, with a lot of both breadth and depth—and with remarkably central relevance to many of today’s most prominent technology areas.
It’s been more than 28 years since Version 1 came out—and nearly 30 years since I started its development. And all that time I’ve been continuing to pursue a bold vision—and to build a taller and taller stack of technology. With most software, after a few years and a few versions, not a lot of important new stuff ever gets added. But with Mathematica and the Wolfram Language it’s been a completely different story: for three decades we’ve been taking major steps forward at every version, progressively conquering vast numbers of new areas. Continue reading »
I spend most of my time trying to build the future with science and technology. But for many years now I’ve also had two other great interests: people and history. And today I’m excited to be publishing my first book that builds on these interests. It’s called Idea Makers, and its subtitle is Personal Perspectives on the Lives & Ideas of Some Notable People. It’s based on essays I’ve written over the past decade about a range of people—from ones I’ve personally known (like Richard Feynman and Steve Jobs) to ones who died long before I was born (like Ada Lovelace and Gottfried Leibniz).
The Most-Used Mathematical Algorithm Idea in History
An octillion. A billion billion billion. That’s a fairly conservative estimate of the number of times a cellphone or other device somewhere in the world has generated a bit using a maximum-length linear-feedback shift register sequence. It’s probably the single most-used mathematical algorithm idea in history. And the main originator of this idea was Solomon Golomb, who died on May 1—and whom I knew for 35 years.
Solomon Golomb’s classic book Shift Register Sequences, published in 1967—based on his work in the 1950s—went out of print long ago. But its content lives on in pretty much every modern communications system. Read the specifications for 3G, LTE, Wi-Fi, Bluetooth, or for that matter GPS, and you’ll find mentions of polynomials that determine the shift register sequences these systems use to encode the data they send. Solomon Golomb is the person who figured out how to construct all these polynomials.
He also was in charge when radar was first used to find the distance to Venus, and of working out how to encode images to be sent from Mars. He introduced the world to what he called polyominoes, which later inspired Tetris (“tetromino tennis”). He created and solved countless math and wordplay puzzles. And—as I learned about 20 years ago—he came very close to discovering my all-time-favorite rule 30 cellular automaton all the way back in 1959, the year I was born. Continue reading »
Fifty years ago today there was a six-year-old at a kindergarten (“nursery school” in British English) in Oxford, England who was walking under some trees and noticed that the patches of light under the trees didn’t look the same as usual. Curious, he looked up at the sun. It was bright, but he could see that one side of it seemed to be missing. And he realized that was why the patches of light looked odd.
He’d heard of eclipses. He didn’t really understand them. But he had the idea that that was what he was seeing. Excited, he told another kid about it. They hadn’t heard of eclipses. But he pointed out that the sun had a bite taken out of it. The other kid looked up. Perhaps the sun was too bright, but they looked away without noticing anything. Then the first kid tried another kid. And then another. None of them believed him about the eclipse and the bite taken out of the sun.
Edited transcript of a talk given on March 4, 2016, at the Computer History Museum, Mountain View, California.
I normally spend my time trying to build the future. But I find history really interesting and informative, and I study it quite a lot. Usually it’s other people’s history. But the Computer History Museum asked me to talk today about my own history, and the history of technology I’ve built. So that’s what I’m going to do here. Continue reading »
Six and a half years ago we put Wolfram|Alpha and the sophisticated computational knowledge it delivers out free on the web for anyone in the world to use. Now we’re launching the Wolfram Open Cloud to let anyone in the world use the Wolfram Language—and do sophisticated knowledge-based programming—free on the web.
It’s been very satisfying to see how successfully Wolfram|Alpha has democratized computational knowledge and how its effects have grown over the years. Now I want to do the same thing with knowledge-based programming—through the Wolfram Open Cloud.
Last week we released Wolfram Programming Lab as an environment for people to learn knowledge-based programming with the Wolfram Language. Today I’m pleased to announce that we’re making Wolfram Programming Lab available for free use on the web in the Wolfram Open Cloud. Continue reading »
I think it was 1979 when I first met Marvin Minsky, while I was still a teenager working on physics at Caltech. It was a weekend, and I’d arranged to see Richard Feynman to discuss some physics. But Feynman had another visitor that day as well, who didn’t just want to talk about physics, but instead enthusiastically brought up one unexpected topic after another.
That afternoon we were driving through Pasadena, California—and with no apparent concern to the actual process of driving, Feynman’s visitor was energetically pointing out all sorts of things an AI would have to figure if it was to be able to do the driving. I was a bit relieved when we arrived at our destination, but soon the visitor was on to another topic, talking about how brains work, and then saying that as soon as he’d finished his next book he’d be happy to let someone open up his brain and put electrodes inside, if they had a good plan to figure out how it worked.
Feynman often had eccentric visitors, but I was really wondering who this one was. It took a couple more encounters, but then I got to know that eccentric visitor as Marvin Minsky, pioneer of computation and AI—and was pleased to count him as a friend for more than three decades. Continue reading »