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And on a related note, "better than humans", "comparable to human intelligence", and phrases like these since the early days of AI have always been a red herrin

by j1vms 10y ago

And on a related note, "better than humans", "comparable to human intelligence", and phrases like these since the early days of AI have always been a red herring. Not the least because these phrases do not imply what we are really comparing - better than all humans? some humans? How about just a person? What about just better than a 4-year-old? The criteria should have always been "faster / more efficiently", "more accurately", or "both" in comparing AI to human intelligence for a given task or activity. By this measure, AI had enduring production-ready successes since at least the 1980s. Let's say that was software that ran on post-VLSI hardware (1+ million transistors). Now, we have deep learning deployed on multiple GPUs each with a 15+ billion transistor count. True AI is starting to look philosophically like a mirage, not the least because we may not ever have a strict meaningful definition for intelligence. What we consider intelligence varies, evolves, changes shape, consistency and predictability even if we consider just one of the various people we interact with on a given day. As one of the latest, I think Brian Eno (https://news.ycombinator.com/item?id=12027055 https://news.ycombinator.com/item?id=12027055), like others before him who have formalized a similar approach to the matter of intelligence, is on the right track. This approach to deciding what constitutes True AI would do much to counter and eventually prevent the "AI effect".

ktta 10y ago
>And on a related note, "better than humans", "comparable to human intelligence", and phrases like these since the early days of AI have always been a red herring Well, I agree that it is not definitive, but it definitely gives us some insight on where AI techniques are, comparing with the 'average human'. Now I know even the term average human doesn't have a strict definition, but the scale of intelligence[0] is so vast compared to the dumbest and smartest human, all that we need to know from that is if the technology is better than humans or not. If it is not, then I'll not care much, but if it is, then you've got my attention. >Let's say that was software that ran on post-VLSI hardware (1+ million transistors). Now, we have deep learning deployed on multiple GPUs each with a 15+ billion transistor count. I think the problem lies with how we emulate intelligence. Will you be able to emulate me perfectly if you had not billions, but trillions of transistors? I'm assuming the answer is no, because, although we have all the power that the human brain (abstracting the neurons and other 'mechanical parts') has, we cannot simulate even a child's intelligence (now here I'm referring the ability to learn new things and communication, etc other abstract things etc, not computational ability). We need to know the technique just like we know have deep learning and are able to analyze pictures near-perfectly. >True AI is starting to look philosophically like a mirage Well, of course definitions vary. I think most people's (including mine) definition is that 'AI' (AGI, if you want to remove ambiguity) is surpassing human intelligence in the optimization area, like large scale optimizations like designing a spaceship, or curing cancer using techniques unknown to us right now. I remember reading that and considering his view very interesting. With our (normal) perspective we don't really see AI like people see it centuries ago. [0]: http://kruel.co/scale_of_intelligence.png http://kruel.co/scale_of_intelligence.png - I apologize for the poor quality picture; it was a quick google image search

by j1vms 10y ago

ktta 10y ago

>And on a related note, "better than humans", "comparable to human intelligence", and phrases like these since the early days of AI have always been a red herring Well, I agree that it is not definitive, but it definitely gives us some insight on where AI techniques are, comparing with the 'average human'. Now I know even the term average human doesn't have a strict definition, but the scale of intelligence[0] is so vast compared to the dumbest and smartest human, all that we need to know from that is if the technology is better than humans or not. If it is not, then I'll not care much, but if it is, then you've got my attention. >Let's say that was software that ran on post-VLSI hardware (1+ million transistors). Now, we have deep learning deployed on multiple GPUs each with a 15+ billion transistor count. I think the problem lies with how we emulate intelligence. Will you be able to emulate me perfectly if you had not billions, but trillions of transistors? I'm assuming the answer is no, because, although we have all the power that the human brain (abstracting the neurons and other 'mechanical parts') has, we cannot simulate even a child's intelligence (now here I'm referring the ability to learn new things and communication, etc other abstract things etc, not computational ability). We need to know the technique just like we know have deep learning and are able to analyze pictures near-perfectly. >True AI is starting to look philosophically like a mirage Well, of course definitions vary. I think most people's (including mine) definition is that 'AI' (AGI, if you want to remove ambiguity) is surpassing human intelligence in the optimization area, like large scale optimizations like designing a spaceship, or curing cancer using techniques unknown to us right now. I remember reading that and considering his view very interesting. With our (normal) perspective we don't really see AI like people see it centuries ago. [0]: http://kruel.co/scale_of_intelligence.png http://kruel.co/scale_of_intelligence.png - I apologize for the poor quality picture; it was a quick google image search