Komunitas-Super

Regular readers may know my enthusiasm for the work of Stephen Wolfram, British-born prime mover of the Mathematica mathematics suite. I've never got deep into Mathematica but his book A New Kind of Science (NKS for short) about cellular automata is one of the most interesting I have read in the past decade, bristling with ideas, though it has been received with scorn and anger by many.

One of the central themes is how complexity can arise from very simple rules; he is describing cellular automata, basically a mathematics of growth, but you can get the idea from the fact that our perception of colour, and by extension of all natural beauty and all visual art, stems from just three sets of sensors in our eyes.

So naturally my interest was aroused by our report yesterday that Wolfram has applied his work on both Mathematica and NKS to create a new search engine called Wolfram Alpha, which will launch in May.

He writes in his blog: "Fifty years ago, when computers were young, people assumed that they'd quickly be able to handle all these kinds of things. And that one would be able to ask a computer any factual question, and have it compute the answer. But it didn't work out that way. Computers have been able to do many remarkable and unexpected things. But not that."

Some years ago, he says, he realised that he had the tools to do it. "With Mathematica, I had a symbolic language to represent anything--as well as the algorithmic power to do any kind of computation. And with NKS, I had a paradigm for understanding how all sorts of complexity could arise from simple rules."

Search engines can efficiently search for terms and phrases in that text. "But we can't compute from that. And in effect, we can only answer questions that have been literally asked before. We can look things up, but we can't figure anything new out."

One approach to the problem is the semantic web, using tagging to describe data "to somehow automatically understand the natural language that exists on the web."

"But armed with Mathematica and NKS I realized there's another way: explicitly implement methods and models, as algorithms, and explicitly curate all data so that it is immediately computable."

This also addresses the problem of how to answer questions couched in natural language. "We're still very far away from having computers systematically understand large volumes of natural language text on the web," Wolfram writes. "But if one's already made knowledge computable, one doesn't need to do that kind of natural language understanding."

He says his new search site will "with one simple input field that gives access to a huge system, with trillions of pieces of curated data and millions of lines of algorithms."