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from the let-the-chips-fall-where-they-may dept.
Submitted via IRC for AndyTheAbsurd
Recently, on a dazzling morning in Palm Springs, California, Vivienne Sze took to a small stage to deliver perhaps the most nerve-racking presentation of her career.
She knew the subject matter inside-out. She was to tell the audience about the chips, being developed in her lab at MIT, that promise to bring powerful artificial intelligence to a multitude of devices where power is limited, beyond the reach of the vast data centers where most AI computations take place. However, the event—and the audience—gave Sze pause.
[...] Newly designed chips, like the ones being developed in Sze's lab, may be crucial to future progress in AI—including stuff like the drones and robots found at MARS. Until now, AI software has largely run on graphical chips, but new hardware could make AI algorithms more powerful, which would unlock new applications. New AI chips could make warehouse robots more common or let smartphones create photo-realistic augmented-reality scenery.
Sze's chips are both extremely efficient and flexible in their design, something that is crucial for a field that's evolving incredibly quickly.
The microchips are designed to squeeze more out of the "deep-learning" AI algorithms that have already turned the world upside down. And in the process, they may inspire those algorithms themselves to evolve. "We need new hardware because Moore's law has slowed down," Sze says, referring to the axiom coined by Intel cofounder Gordon Moore that predicted that the number of transistors on a chip will double roughly every 18 months—leading to a commensurate performance boost in computer power.
(Score: 0) by Anonymous Coward on Monday May 13 2019, @05:57AM
How does it compare to a crow's brain? Compact and yet actually thinks. High IQ to watt ratio.
It's not merely a hardware problem. Most of those "AI" algorithms we use today are actually decades old, dumb and mediocre/crap. They work well enough now only because Google et all can get MILLIONS of samples to teach them the difference between a bus and a traffic light. See: https://www.technologyreview.com/s/608911/is-ai-riding-a-one-trick-pony/ [technologyreview.com]
That's practically brute-forcing the problem. In contrast many dogs or crows can tell the difference between a bus and a traffic light after just a handful of samples. No need for hundreds or thousands of samples. Also when they make mistakes, the mistakes show you that dogs and crows actually understand (and thus misunderstand) stuff, the AIs don't ( http://techland.time.com/2011/02/16/why-did-watson-think-toronto-is-a-u-s-city-on-jeopardy/ [time.com] ).
I suspect that as we learn more about various animals we'll find that even a mere fly is closer to thinking the way humans do compared to the current AIs in 2019. http://www.ox.ac.uk/news/2014-05-22-fruit-flies-show-mark-intelligence-thinking-they-act [ox.ac.uk]