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This kind of behavior in single celled organisms leads me to believe that there is a fair amount of complex logic handled by individual neurons in the brain, th

This kind of behavior in single celled organisms leads me to believe that there is a fair amount of complex logic handled by individual neurons in the brain, that is currently not being modeled in the state of the art neural networks. The bottom line, I guess is our understanding of biological intelligence has a long way to go and correspondingly AI also has a long way to go before it can hope to simulate intelligence. It also means we may need a lot more computing power to simulate a complex intelligence if each neuron has its own complex set of behaviors that need to be simulated.

solipsism 7y ago
This kind of behavior in single celled organisms leads me to believe that there is a fair amount of complex logic handled by individual neurons in the brain, that is currently not being modeled in the state of the art neural networks A highschool biology textbook could have told you the same. Each neuron is an incredibly complex systems of pumps, channels, and pathways. There are many kinds of inhibition and excitation, both chemical and electrical. There's reuptake, active gene regulation causing dynamic protein synthesis, etc etc etc. Individual neurons can be multiple feet long. Every cell in your body is much, much more complex than we could ever imagine. our understanding of biological intelligence has a long way to go and correspondingly AI also has a long way to go before it can hope to simulate intelligence. That seems to assume mimicking the specifics of biology is necessary for progress. It's an open question, but that idea seems a bit silly to me.
- mlyle 7y ago
  The hard part is that we don't know the order of the problem. We know a neuron and synapse count for humans, but we don't know if that's minimal for intelligence. We don't know how complicated of a model of a neuron we need to get by with an equivalent number of neurons/synapses. Or what the tradeoff is-- how many more neurons we need for a simpler model, if that's even possible. Can we run smaller numbers of neurons to have a "slow" AGI? Does the fact that computers can operate the connections and weightings quicker earn us anything? And then you have the people like Penrose who argue there must be some quantum magic somehow being used by the neurons to perform quantum consciousness computation stuff. I mean, I suspect what you imply is right: we can get by with something much less than an exhaustive model of the human brain. But I can't make a rigorous argument for it, let alone how much less. P.S. There's a certain irony to be replying to someone named "solipsism" advancing this argument ;)
deleted 7y ago
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jcims 7y ago
Totally agree. There are a hundred trillion atoms in the average human neuron. It might take what is presently considered a large ML model just to emulate the behavior of a single one.
jbotz 7y ago
Take a look at the video "Inner life of a cell". It's a CGI visualization that shows the complexity of the molecular machinery in a cell. Even if you already have a good idea, this video is likely to expand your perspective.
- jbotz 7y ago
  This "expansion in perspective" leads me to an intersting speculation: If we could quantify the relative complexity of living organisms, we might find that the difference in complexity between the simplest ancient proto-bacteria and something modern like the leucocyte in the video, or a modern single-cellular eucaryote, is greater than the difference in complexity between the simplest animals with a nervous system and us. On the face of it this might seem absurd (although watching a video like "Inner life of a cell" gives us a hint at how that might be true), but after all evolution has worked on cells for billions of years, and whereas the evolution of multicellular organisms with nervous systems has only been going on for about 600 million years! Just some food for thought...

This kind of behavior in single celled organisms leads me to believe that there is a fair amount of complex logic handled by individual neurons in the brain, that is currently not being modeled in the state of the art neural networks. The bottom line, I guess is our understanding of biological intelligence has a long way to go and correspondingly AI also has a long way to go before it can hope to simulate intelligence. It also means we may need a lot more computing power to simulate a complex intelligence if each neuron has its own complex set of behaviors that need to be simulated.

solipsism 7y ago

This kind of behavior in single celled organisms leads me to believe that there is a fair amount of complex logic handled by individual neurons in the brain, that is currently not being modeled in the state of the art neural networks A highschool biology textbook could have told you the same. Each neuron is an incredibly complex systems of pumps, channels, and pathways. There are many kinds of inhibition and excitation, both chemical and electrical. There's reuptake, active gene regulation causing dynamic protein synthesis, etc etc etc. Individual neurons can be multiple feet long. Every cell in your body is much, much more complex than we could ever imagine. our understanding of biological intelligence has a long way to go and correspondingly AI also has a long way to go before it can hope to simulate intelligence. That seems to assume mimicking the specifics of biology is necessary for progress. It's an open question, but that idea seems a bit silly to me.

mlyle 7y ago
The hard part is that we don't know the order of the problem. We know a neuron and synapse count for humans, but we don't know if that's minimal for intelligence. We don't know how complicated of a model of a neuron we need to get by with an equivalent number of neurons/synapses. Or what the tradeoff is-- how many more neurons we need for a simpler model, if that's even possible. Can we run smaller numbers of neurons to have a "slow" AGI? Does the fact that computers can operate the connections and weightings quicker earn us anything? And then you have the people like Penrose who argue there must be some quantum magic somehow being used by the neurons to perform quantum consciousness computation stuff. I mean, I suspect what you imply is right: we can get by with something much less than an exhaustive model of the human brain. But I can't make a rigorous argument for it, let alone how much less. P.S. There's a certain irony to be replying to someone named "solipsism" advancing this argument ;)

deleted 7y ago

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jcims 7y ago

Totally agree. There are a hundred trillion atoms in the average human neuron. It might take what is presently considered a large ML model just to emulate the behavior of a single one.

jbotz 7y ago

Take a look at the video "Inner life of a cell". It's a CGI visualization that shows the complexity of the molecular machinery in a cell. Even if you already have a good idea, this video is likely to expand your perspective.

jbotz 7y ago
This "expansion in perspective" leads me to an intersting speculation: If we could quantify the relative complexity of living organisms, we might find that the difference in complexity between the simplest ancient proto-bacteria and something modern like the leucocyte in the video, or a modern single-cellular eucaryote, is greater than the difference in complexity between the simplest animals with a nervous system and us. On the face of it this might seem absurd (although watching a video like "Inner life of a cell" gives us a hint at how that might be true), but after all evolution has worked on cells for billions of years, and whereas the evolution of multicellular organisms with nervous systems has only been going on for about 600 million years! Just some food for thought...