Beowulf Pioneer Lured From Cal Tech to LSU

An anonymous reader writes "Thomas Sterling, a pioneer of clustered computing, including /.'s beloved Beowulf cluster, has has accepted a fully-tenured professorship at Louisiana State University's Center for Computation and Technology, ditching his old post at Cal Tech. From TFA: "At LSU, he hopes to develop the next generation of high-performance computers that will give birth to true artificial intelligence. By making computer chips more efficient, Sterling believes he can change computing by "one to three orders of magnitude" that will transform how humans interact with technology.""

Comments

Ummm

[$RANDOMLUSER]

Isn't this the wrong week to be moving to Louisiana?

Re:Ummm

[tgd]

Real estate is probably going to be cheap.

Will throwing hardware at AI suffice?

[Lellor]

You can throw as much hardware as you want at the "problem" of AI, but in my opinion, that isn't the easiest route to achieving a breakthrough in AI - it would be like throwing hardware at a dog's brain - the dog would still think like a dog, only 1000 times faster. Sure, you might see improvement in "mechanical reasoning", and chess playing programs and the like, where most of the neccessary conclusions can be reached mechanically (mathematically), but that's about as far as it will go, I think. You won't get the dog to reach non-doggy (for example, human) conclusions by doing that.

The real key to AI lies in software, and superior algorithms. So far in AI, most of the progress has been on the mechanical side - expert systems using algorithms to match and discard possibilities until it finds the "correct" option. This is a good way of doing things for applications that expert systems are currently being utilized for, but to progress to the realm of true (self-aware) AI, scientists need to find out how it works in biological structures first. Once that has been established, computer scientists can try converting those (theoretical) signals into instructions, and plug those into new-generation algorithms.

Re:Will throwing hardware at AI suffice?

[Iphtashu Fitz]

The real key to AI lies in software, and superior algorithms.

Personally I think it'll require a huge paradigm shift in the way all digital computing is currently performed. Trying to force AI into a system run by a digital processor, whether it's an x86 or some other current-day architecture, results in pretty significant limitations. True intelligence isn't binary - there are an infinite number of shades of grey that come with it.

I don't think we'll see real AI until the next major advancement in computing hits, but I don't think anybody currently knows precisely what that'll be. It'll be something on the order of the transition from analog vacuum tubes to digital microprocessors.

Re:Will throwing hardware at AI suffice?

[Dachannien]

IMO, incredible amounts of computing power is a necessary, but not sufficient, condition for solving the AI "problem".

The real question is how much will be needed - how far down do we have to dig when simulating a biological intelligence? Will stopping at the algorithmic or procedural level suffice? Do we have to simulate neurons, and if we do, do we only need to simulate frequency-domain behavior, or do we have to go with a full-blown Hodgkin-Huxley-esque model of neuronal activity?

Or, perish the thought, is even that not sufficient, and do we have to start simulating intracellular or even molecular activity?

Re:This is a good thing?

[dvdeug]

Here's a guy saying he wants to create "true" artificial intelligence and we're all-of-a-sudden thinking its a good thing?

(A) It's been planned for 40 years now. It's a little late to be worrying about it.

(B) Those 40 years have got us OCR programs that can almost beat an 8-year old for quality, and voice recognition programs that have to be trained on a particular voice. An AI that is two orders of magnitude better is still probably not going to be able to make breakfest.

(C) There's six billion objects with natural intelligence that we let wander around with no supervision or real control. What's so scary about adding a few controlled supervised machine intelligences to the bunch?

(D) There's a lot of science fiction that is about the wonders of what we can do with technology, too. If you read the book "I, Robot", you'll get long discussions of why the irrational fear of robots doesn't help.