Sunday 18 March 2012

5 Things I Learned About the Future from Stephen Wolfram

wolframsxsw1.jpgLots of the knowledge dropped at South By Southwest Interactive is vertical. In the sense that tech people use that word, "vertical" means focused on a particular market or problem and all its implications from top to bottom. Talks tend to be about the business of this or that, or the makers of one app will talk about how they did it.

A precious few talks are horizontal, though. They consider the challenges and opportunities in tech across all disciplines. On Sunday, Stephen Wolfram performed that role in his talk, "Computation and Its Impact on the Future." In his view, we're at the dawn of an age of computing that's as important as the agricultural and industrial revolutions, if not more so. Here are five key takeaways.

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Nature Is A Computer

wolframsxsw2.jpgOne of the first slides Wolfram showed us was an image of the output of his beloved rule 30. It's from his set of "cellular automata," arrays of cells with only two states that change state over time following basic rules. They demonstrate that you don't need a complicated program to produce fabulously complex bodies of information.

Wolfram thinks of computation as a new kind of science. Once you realize how well patterns of information describe the shapes and functions we see in nature, you start to see how the rules - or programs - that produce those patterns are fundamental. It might be that the whole universe can be described by one program. "Even among the first few thousand possible programs," Wolfram said," there are a few that are not obviously not our universe."

Once you observe the intricacy that can emerge from such basic functions as rule 30, the natural evolution of this complex universe begins to seem more possible. "This is nature's secret," Wolfram told us. Take life on Earth for example. Genes need only to encode the right kinds of simple rules to express amazing diversity. This Conus textile shell has a beautiful pattern reminiscent of rule 30.

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Programming Is Easy

wolframsxsw4.jpgFortunately, when you see things the way Wolfram does, that means programming is easy. Since simple rules can produce complex results, creating those rules becomes a matter of simply observing the world and understanding the way it operates. Science!

That's the thinking behind Mathematica the programming language Wolfram created. It powers Wolfram Alpha, the "computational knowledge engine" that takes users' natural language questions, assembles some Mathematica programs and computes graphical, interactive answers.

Mathematica is full of basic mathematical and scientific rules. They're the primitives of the language. While San Francisco software developers toil to write the best mobile photo apps from scratch, Wolfram demonstrated Mathematica to us on stage by writing photo filtering software off the top of his head with a few lines of Mathematica code.

How? All it takes is an understanding of the properties of light, graphs and digital image formats, and those are all baked into the language.

Data Are Good For Our Health

We can take the science of computation up a notch if we have more data. That's why Stephen Wolfram has been collecting personal data about himself for decades. He wanted to understand his patterns and habits better, so he started tracking his typing, emailing, phone calls, walking and more. He's started to apply his own tools to his personal dataset, and it has taught him some illuminating lessons.

But we'll take this much further in the future. Wolfram argues that computation on personal data is the future of medical diagnosis. The way medicine works now, we take measurements, compare it to the literature and produce a diagnosis. "Naming it is not the key thing," though.

The key is to understand the context of our health condition by watching our bodily trends over time. Then we can know on a personal basis how to react medically to a particular state. We can do that by constantly collecting medical data about ourselves and computing new solutions.

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Computers Belong In The Classroom

It's easy to believe that the Internet is destroying our brains. You know, just like the calculator did </sarcasm>. Now that answers are constantly, instantaneously available, we don't have to keep them in our heads anymore. Conventional wisdom tends to assert that this makes us dumber, but Wolfram argues the opposite.

"Education today is based on the industrial age," he told us at SXSW, "not on our coming computing age." According to Wolfram, the power afforded to students by computers should take education to a higher level. Instead of rote memorization of facts and abstract rules, teachers can now give students increasingly hard real-world problems to solve. They have powerful tools at their disposal to do the math for them; what they need to learn is how to use them.

"You don't need professors to tell us generic facts," Wolfram said. "You need humans to apprentice to."

Humans Still Matter

To Wolfram, computation is as important a human innovation as agriculture or manufacturing, "maybe bigger." Yes, the whole universe might be computing all around us, but the human discovery of how to do it on purpose is a pivotal step.

The line isn't as clear between "intelligence" and computation as we'd like to think, Wolfram says. A simple rule that's computationally sophisticated could trick us. Wolfram doesn't believe in general artificial intelligence, only more computation specialized to our kinds of problems. Since we, too, are specialized for our own problems, we're improving ourselves by getting better at computation.

Wolfram talked about how, in times of historical upheaval, people tend to turn to the wisdom of the ancients to figure out what to do next. "For the future," he said, "I have this suspicion that we're going to be The Ancients." By reorienting our civilization around computing, we're on to something big, and it's still the very beginning.

Image 1 by Nonenmac via Creative Commons

Image 2 by Maksim via Creative Commons

Image 3 by Rling via Creative Commons

Image 4 by Quchen in the public domain

Image 5 via Stephen Wolfram

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