[jfoutz]

This is hard to parse. All software that can be represented as if and goto (and some sort of assignment i suppose)?

when, while and do are just if and goto.

alpha go is all just if and goto. I'm not sure what you're looking for or alluding to.

Is there some other operation that isn't just if and goto? because i think any function you come up with, i can just make a big table of inputs that result in specific outputs.

Heck, decrement and jump if zero is enough. I'm not convinced at all that specific operations are limiting us somehow. Could you elaborate?

[jtbayly]

I believe what he's saying is that we don't "think" in if/then statements. So true AI will never be intelligent-like if you judge intelligence as thinking like us.

[vntok]

What do you mean? Neurons work exactly like if/then statements. If (input > level) {transmit information}

[jtbayly]

Ummm.... no. You might be able to make the case that a neuron can be simulated with a very complex set of if-then statements, but that assumes that we can know everything about the state of a dozen inputs, which we can't. At any rate, the brain is not a computer: https://aeon.co/essays/your-brain-does-not-process-informati...

[xj9]

i like that this essay puts the complexity of the brain into perspective, but the distinction between a computer and an organism is kind of arbitrary. brains are physical systems that can be modeled mathematically. if you can create a mathematical model of a thing, you can execute that model on a computer. a brain isn't a classical computer, but that doesn't mean that a computer can't simulate a brain.

we currently lack the ability to recreate a brain-like entity, but the subtext that i am reading here is that the complexity of the brain is such that accurately modelling a brain in mathematical terms is impossible. the "brain-as-computer" model may not be accurate, but everything that exists can be expressed in mathematical (and therefore compute-able) terms.

i doubt that cyberbrains will run on anything that we recognize as a general-purpose cpu. gpu micro-architecture is already a significantly more efficient option for performing nn computations. as our grasp on this stuff improves, more specific silicon is being developed to make it even more efficient.

[jtbayly]

I don't think it's arbitrary. You even distinguished in this comment between a brain and a simulation of a brain. Steel is a physical system that can be modeled mathematically. Accurately simulating steel doesn't make steel.

[a_crc]

Agreed. I think radioactive decay is an even better example of a well modeled physical system that defies simulation. A simulation of an ounce of decaying uranium won't tell you which atoms will decay in which order in a physical chunk. Ergo, somethings defy simulation.

[vntok]

output = if (input > locally_stored_threshold) input * locally_stored_weight else 0

This is not very complex and accurately models neurotransmission. What's missing here is the vastness of connections from a particular neuron towards thousands or more other neurons, but the inherent function is definitely not complex.

* weight being either 1 if you adopt a continous modelization (multiple serial input provide multiple serial output) or a float if you prefer the discrete modelization (sum of input to sum of output)

[mathiasben]

the idea of creating a pre-determined program which will be followed is limiting. creating AI will require methods we can't yet conceptualize.

[jfoutz]

Are you sure? evolution is pretty darn simple. just not trying the same solution twice is a pretty big speedup.