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1
AI News / Re: AIRIS unsupervised one shot learning
« Last post by korrelan on Today at 10:33:29 pm »
I spent an hour and re-produced a simple version of the game editor AIRIS is using; I also implemented the same type/ method of AI.

Teaching the AI to understand a simple maze... to grab food and to wait at doors...



But it’s still driven by a simple list.

 :)
2
AI News / Re: Noam Chomsky Has Weighed In On A.I. Where Do You stand?
« Last post by danlovy on Today at 10:23:52 pm »
Thank you @Danlovy. I guess it is back to the drawing board?
I watched the horse video,  I'm not sure what I'm seeing.
3
AI News / Re: Noam Chomsky Has Weighed In On A.I. Where Do You stand?
« Last post by keghn on Today at 09:15:28 pm »
 Thank you @Danlovy. I guess it is back to the drawing board?
4
AI News / Re: Noam Chomsky Has Weighed In On A.I. Where Do You stand?
« Last post by danlovy on Today at 08:52:12 pm »
@danlovy really like to hear you  feed back on my work, or any one else?. But O.K. If you not interested in my work.
 Gong to write a big paper. Need get all the confusion out of my model.
 A CNN is a supervised detector. That is for a down and dirty trick ok. I have a unsupervised detectors.
 If use a Tensorflow CNN in a AGI system it need
to be paired with temporal data base when it activated. And a Generative NN to recreate rung the bell, or to say what
activated the CNN. 
 Down and dirty would record a snap shot and cut out the object that activated the detector NN. With a image editor.

Keghn -
I looked at the video and some of your links.  I'm confused and am having trouble understanding your approach.  Is there a summary link?
5
AI News / Re: Noam Chomsky Has Weighed In On A.I. Where Do You stand?
« Last post by danlovy on Today at 08:50:09 pm »
As with any human endeavor, truth usual resides somewhere in the middle.

My theory -
https://www.linkedin.com/pulse/industrial-strength-evolution-genetics-ai-dan-lovy/

Video version(s)
Episode 1 (27 min)


Episode 2( 10 min)


Episode 3 (3 min)


follow here:
http://danlovy.com/critter/
6
General Robotics Talk / Robot Vacuum Cleaners
« Last post by tekchamps on Today at 06:10:53 pm »
Who else thinks that robot vacuum cleaners are awesome? I couldn't find a thread about this topic so I decided to create one on my own. I found this article that talks about these kinds of <a href="https://tekchamps.com/best-robot-vacuum-cleaners-alexa-compatible-hands-free/" class="bbc_link" target="_blank">smart robots.[/url]</div>
7
AI News / Re: Noam Chomsky Has Weighed In On A.I. Where Do You stand?
« Last post by keghn on Today at 03:44:22 pm »
 @danlovy really like to hear you  feed back on my work, or any one else?. But O.K. If you not interested in my work.
 Gong to write a big paper. Need get all the confusion out of my model.
 A CNN is a supervised detector. That is for a down and dirty trick ok. I have a unsupervised detectors.
 If use a Tensorflow CNN in a AGI system it need
to be paired with temporal data base when it activated. And a Generative NN to recreate rung the bell, or to say what
activated the CNN. 
 Down and dirty would record a snap shot and cut out the object that activated the detector NN. With a image editor.



8
AI News / Re: AIRIS unsupervised one shot learning
« Last post by keghn on Today at 03:25:45 pm »
 For a beginning AGI, a above view is way too advance. Just like giving  the AGI the ability to chat right off the bat.
 A real AGI system would  be more like a FPV system or simulation. Later on the AGI would learn where it is in the
environment and how to communicate. 
 Human are not perfect. The have are born with primitive instinct to them get going. But later in life it hold them back.
 Animals and especially insects are have really good primitive instinct. Really good to get them up an running. But it pins
them as organic robot and they cannot exceed programming. 

AI2-THOR Interactive Simulation Teaches AI About Real World: 
https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/interactive-simulation-teaches-ai-about-real-world   



9
Neural networks are a kind of assembler for programming mind processes. I'm working on a replacement for neural networks that would have some interesting properties regarding to finding logic proofs. It is about bidirectional walking through a knowledge tree. Moving downwards would be finding solutions to problems, while moving upwards would be seeking what problem setups result with a specific solution. Today's artificial NN recognition process would be equivalent to moving upwards through a knowledge tree.
10
AI News / Re: AIRIS unsupervised one shot learning
« Last post by korrelan on Today at 02:12:52 pm »
Very well produced video and interesting AI.

If I was to speculate about the type of AI/ machine learning schema being used, I would say a reward driven variation of the same type as my pixel bot project uses.

http://aidreams.co.uk/forum/index.php?topic=10804.msg49555#msg49555

Or indeed my B-Bot demo…

http://aidreams.co.uk/forum/index.php?topic=12820.0

The point of the B-Bot was to demonstrate that complex behaviours can be exhibited by a very simple AI system when driven by the richness of the environment.

Anthropomorphism also plays a part, when we see a complex behaviour we tend to assume/ imply agency.

Actually the B-Bot just uses a simple list.  The pattern of what it sees is saved to a list along with an action, initially given by the human operator.  As the user moves around, they are basically teaching B-Bot to avoid walls and chase green objects. 

When you see this… do this… that’s it.

As the list grows there is a increasing chance that the bot can find a action related to what it’s currently ‘seeing’, it learns through experience.

AIRIS also seems to be using a ‘gods’ eye view of its environment; it would be interesting to see how it performed with a ‘bots’ eye view, where it couldn't ‘see’ over the walls etc.

Cool project.

 :)
Pages: [1] 2 3 ... 10

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by tekchamps (General Robotics Talk)
Today at 06:10:53 pm
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