On-screen robots tend to rise up and crush their puny human masters with alarming regularity.
“I decided to log every single incidence of artificial intelligence or robots in the history of cinema,” Adam Rutherford, a British geneticist and author who served as AI consultant on the recent film “Ex Machina”, tells CNET’s Crave blog. “I think I calculated that 65 percent of them end up being a threat, and the rest of them are just servile.” Read more
“Another big trend at work: The Renault robots are ‘collaborative,’ designed to work in proximity to people. Older types of factory robots swing their steel arms with such force that they can bludgeon anyone who strays too close. Using sonar, cameras or other technologies, collaborative robots can sense where people are and slow down or stop to avoid hurting them.” Read more
“Machines can do some surprising things. But what you really want to know is this: Will your job be around in the future?…The researchers admit that these estimates are rough and likely to be wrong. But consider this a snapshot of what some smart people think the future might look like.” Read more
“Without human beings making the decision to kill, the concern is that killing will happen indiscriminately, slowly lowering the bar for the use of violent force. Once death happens by algorithm, what’s the incentive to preserve life? ‘Humans must ultimately bear moral responsibility and face the horror of war squarely, not outsource it to machines.’” Read more
“It’s a nice thought that humans could one day create a superintelligent artificial intelligence, and that intelligence takes a look at us, says “thanks, creator,” and blasts off into space, never to be heard from again. Or maybe the AI moves to the deserts or the Arctic or some other uninhabited place, and we live together peacefully. But it seems like such an outcome is unlikely.” Read more
“But instead of having to figure out which leg is broken and how, or doing any sort of self-analysis at all, the robot simply starts trying a whole bunch of different gait behaviors through ‘intelligent trial and error,’ converging on something that works by exploring an enormous pregenerated set of potentially effective motions in about two minutes.” Read more
As a rule, robots have to learn through explicit instruction, whether it’s through new programming, watching videos or holding their hands. UC Berkeley’s BRETT (Berkeley Robot for the Elimination of Tedious Tasks) isn’t nearly that dependent, however. The machine uses neural network-based deep learning algorithms to master tasks through trial and error, much like humans do. Ask it to assemble a toy and it’ll keep trying until it understands what works. In theory, you’d rarely need to give the robot new code — you’d just make requests and give the automaton enough time to figure things out.
A long interview from Esquire on transhumanism, AI, life extension, my campaign, and thoughts on the future.
