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I can honestly say that this post has revolutionized my thoughts on AI. Primarily this is because of what I perceive as the thesis statement, which is: "<AI>

by araes 12y ago

I can honestly say that this post has revolutionized my thoughts on AI. Primarily this is because of what I perceive as the thesis statement, which is: "<AI> is the construction of weighted tables (choices, data, meta relations, whatever) from large sets of <prior data> by <method>" This is kind of crazy, because I think it says you could make a Turing AI by using large datasets of prior life data for humans. In essence, "<my life> is the construction of weighted tables from large sets of <life experience> by <human learning>." For example, if you had an AI that could learn through text, you could have extensive transcribed conversation logs of people and then large time-activity logs to use as your inputs. If it could learn through video (IE, it could view images, understand objects, object relations, events in time, and assign will to the person behind actions / events) then you could instead just feed it huge video logs of people's lives. If you wanted a copy of a person, you could feed it only a single individual, and if you wanted a more general AI, then you could feed it cross sections of the population. In addition, there's a very cool meta aspect to the large dataset concept, in that it can be large datasets for when to use, or to feed data to, specialized sub-AI's. For example, you might have a math sub-AI that has been trained by feeding it massive sets of math problems (or perhaps it can learn math through the video life logs of a person?). If its then being used as a part of a larger piece, then you'd want to know when to use it to solve problems, or when to feed it experience inputs for further learning. In essence, its tables of categories for experience types, and then grown / paired sub-AI's for those types. I would wager that it is possible, right now, to create a chatbot that can pass Turing using the above by feeding it the equivalent of mass IRC chat or somesuch huge, human interaction by text dataset over a variety of topics. This would naturally need sub-AI's for mechanical things like grammar or parts of speech, and then possibly higher level meta-AI's for interpreting intent, orchestrating long form thought, or planning. In a way, its layers of AI based on level of thought abstraction. If it were a human, the high intensity portions of sub-AI would occupy space relative to intensity within reconfigurable co-processor zones (sight:visual cortex, sight:face recognition:occipital and temporal lobes, executive functions:frontal lobes, ect...)

sp332 12y ago
It doesn't explain any personality differences. Or chemical changes like whether a person is hungry, or drunk.
nopinsight 12y ago
Consider this simple sentence: "Jane grew up in an idyllic rural area." No current AI implementation, to my knowledge, can understand such a sentence nearly as well as humans do. A competent chatbot judge could suggest a novel situation, say a broken-winged black Pegasus appeared in Jane's hometown when she was seven, and ask pointed questions to find out if the interlocutor is a human or a bot. The issue with almost all current approaches to AI is that it is either purely symbolic or sub-symbolic. The current symbolic approaches cannot completely capture preconceptual experience human use to make sense of the world. When we hear "idyllic rural area", humans use our mental imagery and sensory experiences to help us understand the sentence much more deeply than the list of words suggests. The subsymbolic approach could potentially solve this issue, but it raises the problem of integrating all those complex, interacting parts, vision, auditory, motor control, conceptual thoughts, etc. into a unifying whole. More importantly, would we be able to control and direct the beast sufficiently well once it becomes reality? There is now some AGI (Artificial General Intelligence) research on integrating the two paradigms. If anyone is interested, a presentation is available here: http://ieet.org/index.php/IEET/more/goertzel20130531 http://ieet.org/index.php/IEET/more/goertzel20130531
- fizwhiz 12y ago
  To quote a great scene from the movie "Waking Life" [1] by Linklater: "When I say 'love', the sound comes out of my mouth and it hits the other person's ear, travels through this byzantine conduit in their brain, you know, through their memories of love, or lack of love, and they register what I'm saying and they say 'Yes, I understand'..but how do I know they understand because words are inert. They're just symbols. They're dead. You know, and so much of our experience is intangible. So much of what we perceive cannot be expressed, it's unspeakable. And yet, when we communicate with one another, and we feel we have connected and we think that we're understood, I think that we have a feeling of almost spiritual communion, and that feeling might be transient, but I think that's what we live for". [1] https://www.youtube.com/watch?v=pvnQu30kQ2c https://www.youtube.com/watch?v=pvnQu30kQ2c
- iandanforth 12y ago
  This is very well and succinctly put!
maaku 12y ago
What happens when you ask it to do something entirely novel, that it has never seen before?

by araes 12y ago

sp332 12y ago

It doesn't explain any personality differences. Or chemical changes like whether a person is hungry, or drunk.

nopinsight 12y ago

Consider this simple sentence: "Jane grew up in an idyllic rural area." No current AI implementation, to my knowledge, can understand such a sentence nearly as well as humans do. A competent chatbot judge could suggest a novel situation, say a broken-winged black Pegasus appeared in Jane's hometown when she was seven, and ask pointed questions to find out if the interlocutor is a human or a bot. The issue with almost all current approaches to AI is that it is either purely symbolic or sub-symbolic. The current symbolic approaches cannot completely capture preconceptual experience human use to make sense of the world. When we hear "idyllic rural area", humans use our mental imagery and sensory experiences to help us understand the sentence much more deeply than the list of words suggests. The subsymbolic approach could potentially solve this issue, but it raises the problem of integrating all those complex, interacting parts, vision, auditory, motor control, conceptual thoughts, etc. into a unifying whole. More importantly, would we be able to control and direct the beast sufficiently well once it becomes reality? There is now some AGI (Artificial General Intelligence) research on integrating the two paradigms. If anyone is interested, a presentation is available here: http://ieet.org/index.php/IEET/more/goertzel20130531 http://ieet.org/index.php/IEET/more/goertzel20130531

fizwhiz 12y ago
To quote a great scene from the movie "Waking Life" [1] by Linklater: "When I say 'love', the sound comes out of my mouth and it hits the other person's ear, travels through this byzantine conduit in their brain, you know, through their memories of love, or lack of love, and they register what I'm saying and they say 'Yes, I understand'..but how do I know they understand because words are inert. They're just symbols. They're dead. You know, and so much of our experience is intangible. So much of what we perceive cannot be expressed, it's unspeakable. And yet, when we communicate with one another, and we feel we have connected and we think that we're understood, I think that we have a feeling of almost spiritual communion, and that feeling might be transient, but I think that's what we live for". [1] https://www.youtube.com/watch?v=pvnQu30kQ2c https://www.youtube.com/watch?v=pvnQu30kQ2c
iandanforth 12y ago
This is very well and succinctly put!

maaku 12y ago

What happens when you ask it to do something entirely novel, that it has never seen before?