Xconomist of the Week: Stephen Wolfram on Big Ideas & Companies

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the best possible tools I can, set myself up personally in the best possible situation, forget the idea of having everybody else help, and just have a blast figuring out a bunch of science for myself.”

So, 25 years ago, he started working on Mathematica, a symbolic programming language for scientific computing, via Champaign, IL-based Wolfram Research. “This time I was CEO of my own company, I didn’t take anyone else’s money,” he said, and things “worked out extremely well.” (Mathematica is a cash cow in the fields of education and algorithmic software development. Wolfram Research has been consistently profitable and currently employs about 700 people.)

Meantime, Wolfram moved to the Boston area and spent the ‘90s working on his book, A New Kind of Science (the details of which I can’t get into here), all in parallel with running Wolfram Research remotely. “The company continued to grow and prosper,” he said. “Despite some of my hopes that it would happen, there was no coup.”

If you’re thinking “crazy maverick genius,” you’re spot on—but it gets crazier. (Did I mention he’s saved every keystroke he’s typed in 22 years so he can analyze how to be more efficient?) Wolfram’s most recent project, called Wolfram Alpha, seeks to “take the knowledge of our civilization and make it computable, so that we can have something that automatically answers questions as well as or better than any human expert in any field,” he said. Basically, you can type in any query (on scientific, financial, economic, or other matters) and instead of giving you links like a search engine, Wolfram Alpha tries to compute the answer based on huge swaths of curated data, natural language processing, human experts, and 15 million lines of Mathematica code. (This sounds a bit similar to Paul Allen’s Project Halo, though there are big differences too.)

“I’ve worked on some pretty complicated projects and products over the years, but Wolfram Alpha is, from my point of view, kind of absurd,” Wolfram said.

In the spirit of understanding how and why to tackle such a huge idea, Wolfram shed some light. “Ever since I was a kid, I have been thinking about how to systematically organize knowledge and make it computable. I thought I’d have to solve the general problem of artificial intelligence. About every decade or so, I came back to that and always thought, ‘It’s just too hard.’ But from [A New Kind of Science] and thinking about the nature of intelligence, I realized I was not thinking about it correctly,” he said. “And that in some fundamental sense we already had everything we needed for computational knowledge, just from computation.”

What he means is he was able to tackle Wolfram Alpha because of decades’ worth of software framework built up at his company. Crucially, he also had the freedom—financially and intellectually—to pursue a big, risky project like this because of the company’s success to date. Of course, it takes a certain audacious mindset too.

“I think the single most important thing in that project, and in other impossible projects, is the simple point of believing that one can do the project,” Wolfram said. “Having the confidence, maybe the arrogance, to believe that … Next Page »

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Gregory T. Huang is Xconomy's Deputy Editor, National IT Editor, and Editor of Xconomy Boston. E-mail him at gthuang [at] xconomy.com. Follow @gthuang

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