...and then we'll just need to figure out how to make humans more creative.
AI
31–40 of 317 posts
Re: AI
#32how does this guy consistently write mini-Paul Graham essays?
Because he basically is mini-Paul Graham.
Really? The essay "Andrew Ng thinks there's one algorithm underlying all intelligence. Also, I hope we get conscious computers." is a mini Paul Graham essay?
No PG essay is so lacking in content or original ideas. Conscious computers? Who hasn't thought of conscious computers? http://en.wikipedia.org/wiki/History_of_artificial_intellige...
Re: AI
#33I believe human-level general intelligence (and beyond) is already inevitable, even if we don't make significant developments in "solving" intelligence. Projects that are already developing stuff like this (e.g. IBM Blue Brain) are just copying the human brain as closely as possible. Of course, this isn't as efficient as it could be (they simulate it all at the molecular level, so you can only get 1 neuron per CPU).…
Partially relevant link to resource helping engineers think in terms of biomimicry: http://www.asknature.org/
Re: AI
#34One thing that crosses my mind whenever I imagine creating a human level intelligence is that it takes humans YEARS of constant stimulation to begin to exhibit intelligent behavior... Sometimes I wonder if we'll have the algorithm may before we realize it...
Good point. How do you know if something works before you've put in the time to use it?
Re: AI
#35Critically speaking, this article doesn't add anything. I don't know why I read it. Can anyone explain why they upvoted?
What it adds is the simple point, "be optimistic about strong AI in the near future".
So an article that lacks all substance besides "be optimistic about AI" is front page material on HN?
Re: AI
#36Critically speaking, this article doesn't add anything. I don't know why I read it. Can anyone explain why they upvoted?
For me, "There are certainly some reasons to be optimistic. Andrew Ng, who worked or works on Google’s AI, has said that he believes learning comes from a single algorithm - the part of your brain that processes input from your ears is also capable of learning to process input from your eyes. If we can just figure out this one general-purpose algorithm, programs may be able to learn general-purpose things." is what was most interesting to me. The idea that there's a fairly simple algorithm to learning, applied in the brain, which produces at least the basic learning capability, and possibly consciousness.
Re: AI
#37Explain to me how a brain can evolve, and yet not understand how itself functions?
Why should it?
Because it thinks. It takes in information and performs an analysis on that data. Surely over the time it would take to evolve, my brain thinks that it should understand that more than anything?
It understands how every other organ works in explicit detail at the the molecular level.
The only thing my brain can imagine, is that my consciousness is disconnected somewhat from my brain. It's as though my consciousness is inside a machine that it barely understands the workings thereof. Like a dog riding in a car.
Re: AI
#38I believe human-level general intelligence (and beyond) is already inevitable, even if we don't make significant developments in "solving" intelligence. Projects that are already developing stuff like this (e.g. IBM Blue Brain) are just copying the human brain as closely as possible. Of course, this isn't as efficient as it could be (they simulate it all at the molecular level, so you can only get 1 neuron per CPU).…
I think that airplane analogy is really important for innovation in general. A lot of the activity often ascribed to progress really just amounts to someone building a lighter set of wings for the guy getting ready to jump off a building. (The counterargument, of course, being that that is progress--even if the lighter construction isn't too helpful in the current design it would be later on--but it's not the "macro" progress it's so often billed as.)
Anyway, it's just interesting to be reminded that context is important. Being able to distinguish between insanity and genius seems like it would be a super-power.
Re: AI
#39Interesting post. The way I look at it is from the perspective of a human baby. How do they become intelligent? They have the "sensors" to detect features and will be able to recognize their parents. A lot of things are then learned, like touching a hot stove and from getting a formal education. For a machine to be artificially intelligent it would have to learn from its environment but also take formal instruction.…
Not sure what set off the down votes but we can teach a computer to recognize characters for application in OCR. We also learned those characters from being taught in school and reading bad handwriting. We teach computers the same way. How are they supposed to magically recognize them especially since they didn't invent whatever language it is? Note that I'm referring to artificial general intelligence[0]. 0. http://…
This was back in the 1990s, but I worked in what was basically a data entry company, where the processing was a mixture of scanned forms (Scantron style) and human key entry. The project I was on was image scanning the forms for other purposes, so we had a neural net handwriting recognition system that we were comparing to human key entry at a large scale - millions of documents.
What we found was that human key entry significantly outperformed the neural nets, even when the data was carefully handwritten in constrained boxes. Humans were so far ahead of the heavily trained neural nets that the software was basically unusable at that point.
Of course, that was nearly 20 years ago, and things have probably moved on quite a bit. But you can still see the basic problem in Captcha-style validation on web pages. Computers just can't be trained to recognize distorted text that humans can read pretty easily.
Re: AI
#40I wonder what other credible contenders for "most overlooked technology" are.
I think "physical tamper evidence/tamper response" is one, along with hardware security functionality (crazy secure virtualization extensions, etc.) -- essentially competing with Intel not just on power but also on security features. Although Intel is leading in this area with TXT and now SGX.