Remember when the world feared the supercomputer? We had HAL 9000 in 2001: A Space Odyssey, Skynet in The Terminator and the evil Master Control Program in Tron — all ready to squash the human race with their ability to make cold, calculating decisions without all that pesky morality.

But since the Y2K scare, 21st-century humanity seems have gotten over its worries about a future digital Armageddon. In fact, Houston's own Rice University has become a hotbed of supercomputing in the past decade and recently announced the acquisition of its fifth mega-machine — an ultrafast IBM Blue Gene/P.

CultureMap spoke with Gary Kidney, who directs academic and research computing at Rice, for a little more on the university's need for speed.

"The supercomputer is basically just a bunch of CPUs, like you'd have in your PC or Macintosh, all linked together," he explained. Think of thousands of Macs working on a single computation. Complex problems are solved in seconds rather than months and allow researchers to simulate theoretical situations like the future of Earth's climate or the collision of galaxies.

While technology has come a long way since IBM's Deep Blue defeated chess master Garry Kasparov in 1997, this notion of parallel computing — the simultaneous processing of multiple calculations — has changed little.

"The computers themselves are pretty much the same as they were 15 years ago," he said. "What's changed is our ability to connect them together into larger clusters, allowing for more parallel computations."

This increased ability has allowed for recent major advances in bioengineering as well as human voice recognition, as demonstrated by IBM's Watson and its clean sweep on Jeopardy! in 2011. When Rice's Blue Gene is fully operable by mid-April, researchers plan to concentrate on energy, geophysics, bioscience and cancer research.

But CultureMap had one more question. Just how close are we to artificial intelligence?

"If you're ever going to achieve the capability or the intelligence of the human brain — and whether that's even feasible or not is still in question — you need the ability to do multiple calculations in parallel, the ability to exchange information at lightning speed, and a massive database to store and serve it up when it's needed."

For today's scientists, Kidney noted, artificial intelligence works best with fairly straight-forward scenarios and tasks. Rice researcher James McLurkin, for example, is working with AI to program a team of robots to locate people after an earthquake by mapping and predicting possible patterns of destruction.

So much for the robot apocalypse in 2012. . . For now, supercomputers appear to be on the side of humans.