Scratching the scary reality of that sounds like it’s from a s-f novel. But it’s not.
We are used to thinking of intelligent life, as an inevitable consequence of evolution. But the Anthropic Principle should warn us to be wary of such arguments. It is more likely that evolution is a random process, with intelligence as only one of a large number of possible outcomes. It is not clear that intelligence has any long-term survival value. Bacteria, and other single cell organisms, will live on, if all other life on Earth is wiped out by our actions. There is support for the view that intelligence, was an unlikely development for life on Earth, from the chronology of evolution. It took a very long time, two and a half billion years, to go from single cells to multi-cell beings, which are a necessary precursor to intelligence. This is a good fraction of the total time available, before the Sun blows up. So it would be consistent with the hypothesis, that the probability for life to develop intelligence, is low. In this case, we might expect to find many other life forms in the galaxy, but we are unlikely to find intelligent life.
A bit dated, but nevertheless fantastic lecture by Stephen Hawking on artificial intelligence and the likelihood of intelligent life in the universe.
Humans will never stop being valuable to companies, because their judgement — their ability to make sense of quantitative data in a qualitative way — will remain valuable. Cohen says: “Don’t hire a computer to do a human’s job. We’re never going to have a ‘find the bad guy’ button, and we’re never going to find a ‘make money’ button. It will only work as long as the button doesn’t change human behaviour, and the thing with human behaviour is that it changes fast.
“Once you realise its limitations, you realise we’re not going to be out of a job.”
‘They will never beat us in chess!’
Once a FOOMing intelligence is smart enough to understand its own design and can redesign itself at will, motivational signals are vulnerable to the strategy employed by robot 0x2A: the simplest solution to any motivational problem is to tinker with the motivational signals themselves. If this leads to a serious disconnect between external and internal reality, it amounts to death by Occam’s Razor.
Interesting concept obscured by unnecessary acronyms.
While Siri will humorously show you nearby ravines or abandoned mines when asked “how can I hide a body?” or can find local escort services when looking for “sex,” the paucity of responses in the area of pregnancy and birth control have raised concerns that Siri is programmed to be “pro-life.”
This officially marks a moment when an artificial intelligence entered political debate. More to come.
Some quick comments on using Siri in practice—for things other than asking it to open the pod bay doors. Siri’s voice recognition is very impressive, and the scope of what it understands is very good given the difficulty of what it’s doing. But it has a lot of difficulty with certain sorts of names—Irish names, for example, which often are not written as pronounced.
Notes from using Siri in real situations. I’m highly impressed by what I’ve read so far on Siri’s technical sophistication, but that may not be enough to achieve the quality that would satisfy users. Siri attempts to emulate a real human assistant and that places the bar for an AI extremely high.
You might wonder why aren’t there any robots that you can send in to fix the Japanese reactors,” said Marvin Minsky, who pioneered neural networks in the 1950s and went on to make significant early advances in AI and robotics. “The answer is that there was a lot of progress in the 1960s and 1970s. Then something went wrong. [Today] you’ll find students excited over robots that play basketball or soccer or dance or make funny faces at you. [But] they’re not making them smarter.
From the discussion on the current state of AI research and the direction it should take.
Over on a forum called teamliquid, a user by the name of Lomilar posted a fairly long thread about a program he had written that optimized build orders for the zerg race in starcraft. He eventually cleaned up his code and posted the code to googlecode. The program is called EvolutionChamber (a clever name, as it’s the name of one of the buildings in the game), and it uses genetic algorithms to find build orders.
This I had to see.
This is actually quite revolutionary. Genetic algorithms were used to generate Starcraft 2 build orders and one builds discovered quickly gained traction on battle.net and totally changed the situation on the ladder.
It’s not as with AI playing chess against humans – here it is still the human that implements AI’s strategy. It sounds much more like using steroids in physical sports. And it’s very tempting – the build is dreadfully effective.
So we have developed technology for cars that can drive themselves. Our automated cars, manned by trained operators, just drove from our Mountain View campus to our Santa Monica office and on to Hollywood Boulevard. They’ve driven down Lombard Street, crossed the Golden Gate bridge, navigated the Pacific Coast Highway, and even made it all the way around Lake Tahoe. All in all, our self-driving cars have logged over 140,000 miles. We think this is a first in robotics research.
From now on Skynet can officially drive cars.
Great talk on our current dependency on software with gloomy bottom line: humans don’t have to wait AI to become irrelevant. While the talk itself is very sound, the proposed solution is less likely that the end of civilization.