To mark the second anniversary of the launch of Wolfram|Alpha, I did an interactive webcast:

Here’s a transcript of my introduction:

[Note: here is what I wrote for Wolfram|Alpha’s first anniversary a year ago.]

So, as of today, Wolfram|Alpha has officially been out in the wild for two years.

And I’m happy to say, it’s doing really well.

You know, I’d been thinking about building Wolfram|Alpha for more than 30 years.

And I’ve been working to build the stack of ideas and technology to make it possible for nearly that long.

At the beginning, I was not really sure that Wolfram|Alpha was going to be possible at all.

And I think if I look a year ago from now my main conclusion was that after a year out in the wild, we’d proved that, yes, Wolfram|Alpha was indeed possible.

Well, now that we’re two years out, I think my conclusion is: Wolfram|Alpha is even a lot more important than I thought it was.

This effort to make all our knowledge computable is really something very fundamental, that’s sort of inevitably going to be needed just all over the place.

So what have we been up to this year?

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Wolfram|Alpha is making possible a whole new very interesting and very powerful kind of computing. And with the release today of version 2.0 of the Wolfram|Alpha API, it’s going to be considerably easier for a broad range of software developers to take advantage of it.

I’m happy to say that it seems as if Wolfram|Alpha is pretty useful to humans—for example through the wolframalpha.com website. But it also turns out that Wolfram|Alpha is extremely useful to programs. And in fact, even today, the number of requests coming to Wolfram|Alpha each second from programs often exceeds by some margin all the requests coming directly from humans.

The reason for this popularity is really pretty simple: Wolfram|Alpha completely changes the economics of a lot of programming. You see, these days a remarkable number of programs rely on having some kind of knowledge. And traditionally, the only way to get knowledge into a program was for the programmer to painstakingly put it there.

But with Wolfram|Alpha in the picture, it’s a different story. Because built into Wolfram|Alpha is already a huge amount of computable knowledge. And if a program is connected to Wolfram|Alpha, then it can immediately make use of all that knowledge.

Whether one’s building a website or a mobile app or desktop software or an enterprise application, the point is that one can use Wolfram|Alpha as a “knowledge-based computing” platform—so that having all sorts of computable knowledge becomes effectively free from an engineering point of view.

How does a program communicate with Wolfram|Alpha? It uses the Wolfram|Alpha API. (These days, API is pretty much a term on its own, but it comes from “Application Program Interface”.)

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Today we’re releasing the first three of a planned series of “course assistant” apps, built using Wolfram|Alpha technology.

The long-term goal is to have an assistant app for every major course, from elementary school to graduate school. And the good news is that Wolfram|Alpha has the breadth and depth of capabilities to make this possible—and not only in traditionally “computational” kinds of courses.

The concept of these apps is to make it as quick and easy as possible to access the particular capabilities of Wolfram|Alpha relevant for specific courses. Each app is organized according to the major curriculum units of a course. Then within each section of the app, there are parts that cover each of the particular types of problems relevant to that unit.

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I spent a decade of my life writing *A New Kind of Science*. Most of that time was devoted to discovering the science in the book. But another part was spent figuring out how to present the science in the best possible way—using words and pictures.

It took a lot of technology to do that presentation. On the software side, the biggest part was using *Mathematica* to create elaborate algorithmic diagrams—thousands of them. But then came the question of how to actually deliver everything. And back in 2002 when *A New Kind of Science* was published, the only real possibility was to print a book on paper, using the very best printing technology of the time.

The actual print production process was quite an adventure—going right to the edge of what was possible. But in the end we got many compliments on the object we produced. And from that time to this, that 5.5 lb (2.5 kg) lump of paper has been the definitive representation of my decade-plus of intellectual work.

But today I’m excited to be able to say that there’s something new and in some ways even better: a full version on the iPad.

Today (June 23, 2010) would have been Alan Turing‘s 98^{th} birthday—if he had not died in 1954, at the age of 41.

I never met Alan Turing; he died five years before I was born. But somehow I feel I know him well—not least because many of my own intellectual interests have had an almost eerie parallel with his.

And by a strange coincidence, *Mathematica*‘s “birthday” (June 23, 1988) is aligned with Turing’s—so that today is also the celebration of *Mathematica*‘s 22^{nd} birthday.

I think I first heard about Alan Turing when I was about eleven years old, right around the time I saw my first computer. Through a friend of my parents, I had gotten to know a rather eccentric old classics professor, who, knowing my interest in science, mentioned to me this “bright young chap named Turing” whom he had known during the Second World War.

One of the classics professor’s eccentricities was that whenever the word “ultra” came up in a Latin text, he would repeat it over and over again, and make comments about remembering it. At the time, I didn’t think much of it—though I did remember it. Only years later did I realize that “Ultra” was the codename for the British cryptanalysis effort at Bletchley Park during the war. In a very British way, the classics professor wanted to tell me something about it, without breaking any secrets. And presumably it was at Bletchley Park that he had met Alan Turing.

A few years later, I heard scattered mentions of Alan Turing in various British academic circles. I heard that he had done mysterious but important work in breaking German codes during the war. And I heard it claimed that after the war, he had been killed by British Intelligence. At the time, at least some of the British wartime cryptography effort was still secret, including Turing’s role in it. I wondered why. So I asked around, and started hearing that perhaps Turing had invented codes that were still being used.

I’m not sure where I next encountered Alan Turing. Probably it was when I decided to learn all I could about computer science—and saw all sorts of mentions of “Turing machines”. But I have a distinct memory from around 1979 of going to the library, and finding a little book about Alan Turing written by his mother, Sara Turing.

And gradually I built up quite a picture of Alan Turing and his work. And over the 30 years that have followed, I have kept on running into Alan Turing, often in unexpected places. More »

The creation of large data repositories has been a key historical indicator of social and intellectual development—and indeed perhaps one of the defining characteristics of the whole progress of civilization.

And through our work on Wolfram|Alpha—with its insatiable appetite for systematic data—we have gained a uniquely broad view of the many great data repositories that exist in the world today.

Some of these repositories are maintained by national or international agencies, some by companies and other organizations, and some by individuals. A few of the repositories are quite new, but many date back 40 or more years, and some well over a century. But there is one thing in common across essentially every great data repository: a core of diligent and committed people who have carefully shepherded its development.

Curiously, though, few of these people have ever met their counterparts in other domains of data. And in our work on Wolfram|Alpha we are almost certainly the first group ever to have had the pleasure of getting to know such a broad range of leaders of great data repositories.

And one of the things that we have discovered is that there is much in common in both the methods used and the issues faced by these data repositories. So as part of our contribution to the worldwide data community we have decided to sponsor a data summit to bring together for the first time the leaders of today’s great data repositories.

The Wolfram Data Summit 2010 will be held in Washington, DC on September 9–10.

Years ago I wondered if it would ever be possible to systematically make human knowledge computable. And today, one year after the official launch of Wolfram|Alpha, I think I can say for sure: it *is* possible.

It takes a stack of technology and ideas that I’ve been assembling for nearly 30 years. And in many ways it’s a profoundly difficult project. But this year has shown that it *is* possible.

Wolfram|Alpha is of course a very long-term undertaking. But much has been built, the direction is set, and things are moving with accelerating speed.

Over the past year, we’ve roughly doubled the amount that Wolfram|Alpha knows. We’ve doubled the number of domains it handles, and the number of algorithms it can use. And we’ve actually much more than doubled the amount of raw data in it.

Things seem to be scaling better and better. The more we put into Wolfram|Alpha, the easier it becomes to add still more. We’ve honed both our automated and human processes, progressively building on what Wolfram|Alpha already does.

When we launched Wolfram|Alpha a year ago, about 2/3 of all queries generated a response. Now over 90% do.

So, what are some of the things we’ve learned over the past year? More »

There’s a lot going on in the Wolfram|Alpha project these days—and this week there’s a remarkable convergence of events.

Late last week we introduced the Wolfram|Alpha Webservice API, allowing outside developers to call Wolfram|Alpha from their websites or application programs.

Then yesterday we released the first mobile implementation of Wolfram|Alpha, in the form of an iPhone app.

Tomorrow, we’re doing something completely different: Wolfram|Alpha Homework Day—a 14-hour live webcast event for students and educators.

Oh, and starting on Thursday is the International *Mathematica* User Conference, which will show many advances in the core *Mathematica* technology on which Wolfram|Alpha is based.

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So what’s been happening with Wolfram|Alpha this summer? A lot!

At a first glance, the website looks pretty much as it did when it first launched—with the straightforward input field. But inside that simple exterior an incredible amount has happened. Our development organization has been buzzing with activity all summer. In fact, it’s clear from the metrics that the intensity is steadily rising, with things being added at an ever-increasing rate.

Wolfram|Alpha was always planned to be a very long-term project, and paced accordingly. We pushed very hard to get it launched before the summer so that we could spend the “quiet time” of our first summer steadily enhancing it, before more people start using it more intently in the fall.

Two really great things have happened as a result of actually getting Wolfram|Alpha launched. The first is that we’ve discovered that there’s a huge community of people out there who want to help the mission of Wolfram|Alpha. And we’re steadily ramping up our mechanisms for those people to contribute to the project. More »

It’s now a week since we officially launched Wolfram|Alpha into the world.

It’s been a great first week.

Approaching 100 million queries. Lots of compliments.

But for me the most striking thing is how many people want to help Wolfram|Alpha succeed.

Making the world’s knowledge computable is a huge undertaking.

And it’s wonderful to see all the help we’re being offered in doing it.

We’ve worked hard to construct a framework. But to realize the full promise of computable knowledge, we need a lot of input and support. More »