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I don't think Flops is the adequate metric for measuring how close we are to AGI. The number of neurons firing does matter, but what matters even more is how t

I don't think Flops is the adequate metric for measuring how close we are to AGI. The number of neurons firing does matter, but what matters even more is how they all are connected. I personally think once we get adequate algorithms and data structures out there, the metric will switch to numbers of lookup operations performed, and floating point operations will just be a multiplicative constant in front of the whole complexity formula.

BobbyJo 4y ago
This. There is information encoded in the relative connections of neurons, so a neuron firing doesn't represent a single flop, it represents something more like a flop + a routing table lookup + n number of other flops where n is the number of destination neurons spiked. Depending on how much information is encoded in the table lookup, and how many destination neurons are effected, a single neuron firing can represent many many flops. This is all armchair speculation, but I'd be willing to be my life that a flop is well below the floor of actual computation happening from a single neuron firing.
- lostmsu 4y ago
  I don't believe there's a "routing table lookup" in a single neuron firing. Once it fires all downstream neurons get signal.
  - BobbyJo 4y ago
    The neuron itself and its downstream counterparts are what I was considering the table lookup. In computers the address a value is stored at doesn't encode information. Only the value held at the address matters. Not so with neurons. How the connections form and who they are connected to represent compound operations. Like passing a value through separate preconfigured pipelines.
- pyinstallwoes 4y ago
  I agree. There is also information when it's not firing, the pause between is information itself, almost infinite which is odd to think about. It seems similar to music/geometric shape. Queries by frequency filtering through the geometry of the neurons activating access to some thought-space.
slaymaker1907 4y ago
I personally think we don't know how to build anything close to AGI and doubt more computational power will help. Not that I think we can't figure out how to build these structures eventually, but we just don't right now. Even if we figure out how to simulate human brains, there is a gap between simulation and understanding the simulation well enough to modify it in useful ways.

BobbyJo 4y ago

This. There is information encoded in the relative connections of neurons, so a neuron firing doesn't represent a single flop, it represents something more like a flop + a routing table lookup + n number of other flops where n is the number of destination neurons spiked. Depending on how much information is encoded in the table lookup, and how many destination neurons are effected, a single neuron firing can represent many many flops. This is all armchair speculation, but I'd be willing to be my life that a flop is well below the floor of actual computation happening from a single neuron firing.

lostmsu 4y ago
I don't believe there's a "routing table lookup" in a single neuron firing. Once it fires all downstream neurons get signal.
- BobbyJo 4y ago
  The neuron itself and its downstream counterparts are what I was considering the table lookup. In computers the address a value is stored at doesn't encode information. Only the value held at the address matters. Not so with neurons. How the connections form and who they are connected to represent compound operations. Like passing a value through separate preconfigured pipelines.
pyinstallwoes 4y ago
I agree. There is also information when it's not firing, the pause between is information itself, almost infinite which is odd to think about. It seems similar to music/geometric shape. Queries by frequency filtering through the geometry of the neurons activating access to some thought-space.

slaymaker1907 4y ago

I personally think we don't know how to build anything close to AGI and doubt more computational power will help. Not that I think we can't figure out how to build these structures eventually, but we just don't right now. Even if we figure out how to simulate human brains, there is a gap between simulation and understanding the simulation well enough to modify it in useful ways.