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Self driving cars were serious research more than 10 years ago. https://en.wikipedia.org/wiki/DARPA_Grand_Challenge Several vehicles finished the 2005 course. The one that finished first won a $2 million prize.
Yes but it wasn't even remotely seen as possible by the masses for decades to come. It's already here now.
"Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind" -- Stanford Study Panel, comprised of seventeen experts in AI from academia, corporate laboratories and industry, and AI-savvy scholars in law, political science, policy, and economics
Understanding robotics does not mean you understand exponential growth, it's very very hard to understand even for those who believe they do. http://assets.motherjones.com/media/2013/05/LakeMichigan-Fin... 5 years ago it was thought to take decades to beat a human in Go. Just 10 years ago self driving cars was something you joked about. We consistently overestimate progress in the short run and underestimate in the l…
You can't overestimate the economic pressures on progress as well.
Remember in 2007 when everybody thumbed their noses at hybrid and electric vehicles in the US? Ford was still pumping out record numbers of their behemoth Excursion model.
Then the economy crashed, and people suddenly needed a fuel efficient car and then they all traded in their SUV's for what? Toyota Prius' which were an after thought a few years prior - in the span of 18 months, Toyota couldn't keep them on the lot.
I can see one or more catastrophic disasters where there is a sudden need for AI to rescue the human race in some capacity. Think nuclear war, environmental disaster, biological catastrophe, etc.
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What immediately follows is rather sobering, too: "No machines with self-sustaining long-term goals and intent have been developed, nor are they likely to be developed in the near future."
This is the major problem with the line of reasoning. A tiger doesn't need to be self aware or have intent to be dangerous.
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Understanding robotics does not mean you understand exponential growth, it's very very hard to understand even for those who believe they do. http://assets.motherjones.com/media/2013/05/LakeMichigan-Fin... 5 years ago it was thought to take decades to beat a human in Go. Just 10 years ago self driving cars was something you joked about. We consistently overestimate progress in the short run and underestimate in the l…
"I believe that a world-champion-level Go machine can be built within 10 years" - Deep Blue architect, 2007. http://spectrum.ieee.org/computing/software/cracking-go
Of course there were people who believed that Go would be able to beat humans. Just as today there are people who believe that AI can be a treat.
But it wasn't a majority of people who believed Go would be able just as it isn't a majority who believes AI can be a threat.
I.e. just because the majority believe something doesn't mean it will be so (or vice versa)
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This is the major problem with the line of reasoning. A tiger doesn't need to be self aware or have intent to be dangerous.
Pretty sure the tiger has intent on eating something...
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Yes but it wasn't even remotely seen as possible by the masses for decades to come. It's already here now.
Cool! I wasn't aware. Where I can go buy one?
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"I believe that a world-champion-level Go machine can be built within 10 years" - Deep Blue architect, 2007. http://spectrum.ieee.org/computing/software/cracking-go
You are missing the point completely. Of course there were people who believed that Go would be able to beat humans. Just as today there are people who believe that AI can be a treat. But it wasn't a majority of people who believed Go would be able just as it isn't a majority who believes AI can be a threat. I.e. just because the majority believe something doesn't mean it will be so (or vice versa)
The big change in AI is that it now makes money. AI used to be about five academic groups with 10-20 people each. The early startups all failed. Now it's an industry, maybe three orders of magnitude bigger. This accelerates progress.
Technically, the big change in AI is that digesting raw data from cameras and microphones now works well. The front end of perception is much better than it used to be. Much of this is brute-force computation applied to old algorithms. "Deep learning" is a few simple tricks on old neural nets powered by vast compute resources.
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Understanding robotics does not mean you understand exponential growth, it's very very hard to understand even for those who believe they do. http://assets.motherjones.com/media/2013/05/LakeMichigan-Fin... 5 years ago it was thought to take decades to beat a human in Go. Just 10 years ago self driving cars was something you joked about. We consistently overestimate progress in the short run and underestimate in the l…
"I believe that a world-champion-level Go machine can be built within 10 years" - Deep Blue architect, 2007. http://spectrum.ieee.org/computing/software/cracking-go
Earlier quoted context omitted.
Understanding robotics does not mean you understand exponential growth, it's very very hard to understand even for those who believe they do. http://assets.motherjones.com/media/2013/05/LakeMichigan-Fin... 5 years ago it was thought to take decades to beat a human in Go. Just 10 years ago self driving cars was something you joked about. We consistently overestimate progress in the short run and underestimate in the l…
"I believe that a world-champion-level Go machine can be built within 10 years" - Deep Blue architect, 2007. http://spectrum.ieee.org/computing/software/cracking-go