What is the Closest We Have to AI (within normal human g range)?

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Discussion Overview

The discussion revolves around the concept of artificial intelligence (AI) and its closest analogs to human intelligence, particularly within the context of biological and artificial neural networks. Participants explore the feasibility of mapping human brain synapses and neurons to create artificial neural networks, as well as the mathematical frameworks that might be employed in this process.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests that a trained rat could be considered the closest analog to AI within the normal human "g" range.
  • Another participant expresses skepticism about the feasibility of mapping human neurons to create artificial neural networks, noting the analog nature of neurons and the complexity involved in simulating them.
  • Concerns are raised about the difficulty in determining whether an AI would function similarly to a human brain, suggesting that even a perfect simulation might only be as functional as a newborn baby.
  • A participant argues that current technology is far from being able to map every synapse in the human brain, emphasizing the limited understanding of brain function and the complexity of neuronal interactions.
  • It is mentioned that the brain's computing power is estimated to be equivalent to all the world's processors combined, multiplied by 16 million, highlighting its complexity.

Areas of Agreement / Disagreement

Participants express a range of views on the feasibility of mapping the human brain and creating AI that closely resembles human intelligence. There is no consensus on the closest analog to AI or the methods required for such mapping.

Contextual Notes

Limitations in current understanding of brain function and the complexity of neuronal interactions are noted, as well as the challenges in simulating brain activity accurately.

Friendly Immigrant
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What is the Closest We Have to AI (within normal human "g" range)?

Requesting info. please, thanks.

Also, second question: I heard something about scientists mapping every human synapses and neurons in the brain and then somehow transforming these into artificial neural nets. How do they do this, the mapping part and then converting it to identical artificial neural nets? What type of math equations do they use to represent the human brain and then apply this to chip circuits? Maybe I can just be directed to a link.

Thanks.
 
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Friendly Immigrant said:
Requesting info. please, thanks.

Also, second question: I heard something about scientists mapping every human synapses and neurons in the brain and then somehow transforming these into artificial neural nets. How do they do this, the mapping part and then converting it to identical artificial neural nets? What type of math equations do they use to represent the human brain and then apply this to chip circuits? Maybe I can just be directed to a link.

Thanks.


the closest we have? I would say a trained rat (rats are smart for animals)

as for the second one... that was a star trek episode.
 
I'm not sure how that neural net thing would work. Neurons are pretty analog, so even simulating one would be a lot of work. Also, it seems to me that it would be difficult to tell if the AI worked or not. It takes years of interactions with other people for our brains to collect enough information to know how to function and to think critically. Even if one was to simulate a brain perfectly, it may be as functional as a newborn baby.
 
Also, second question: I heard something about scientists mapping every human synapses and neurons in the brain and then somehow transforming these into artificial neural nets. How do they do this, the mapping part and then converting it to identical artificial neural nets? What type of math equations do they use to represent the human brain and then apply this to chip circuits?

Mapping every synapes with our current technology and understanding of the brain is far from possible. We actually know little about how the brain actually works. Really, just seeing what part of the brain is active when doing certain functions and determining that part of the brain has something to do with carring out that function is just about all we know how to do. As far as what goes on in the mircoscopic scale with individual neurons, we know, for the most part, the mechanics of how neurons send signals but not so much how neurons interprete these signals and act together as a whole.

The brain is the most complex structure that we know. It has been estimated that one average human brain has the computing power of all the world's processors put together, times 16 million.
 

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