There is no law of the universe that says it has to be possible to generate human-level sapience with less than one kilogram of processing mass. In all likelihood we are never going to create a server with a whole city of intelligences in it, ever.
There is no law of the universe that says it has to be possible to generate human-level sapience with less than one kilogram of processing mass. In all likelihood we are never going to create a server with a whole city of intelligences in it, ever.
Natural selection is
- random
- blind - gradient descent is prone to getting stuck in local minima, has no foresight, no ability to go back to the drawing board, no "understanding" of what it's doing.
- not even optimizing for intelligence, except instrumentally - to the extent that increasing intelligence interferes with survival, it has to be sacrificed
- subject to hard constraints like the limits on size imposed by childbirth
A computer with five times the mass, five times the volume, and five times the power requirements of the human brain, that can run an uploaded copy of a human brain at merely half the speed of a human brain, would still render Pluto and Mercury trivial to colonise with machine intelligences.
And if it cost a $100k (inflation adjusted) to build, and lasted 80 years before you had to melt down the hardware and reforge from scratch, it would still be cheaper than Musk's target for a human to Mars.
Mere COVID disrupted that here; imagine what a few hundred million miles of space would do.
Much of the plastic supply chain starts as oil or gas. Wood is a major building component as well.
https://www.researchgate.net/publication/322275580_Electroly...
> Much of the plastic supply chain starts as oil or gas. Wood is a major building component as well.
If we really needed those things (why would we even want to use wood as a structural element on a space habitat?), we can build bioreactors from metal, glass, and water.
Oil and gas do occur non-biologically e.g. Titan, but they can also be made from algae grown in a transparent tube exposed to sunlight and provided with the necessary minerals and CO2, which is trivial to make.
IIRC the two limited resources if you needed biology and couldn't do it all with a clanking replicator are nitrogen and phosphate, everything else is easy to find basically everywhere.
The synapse is an incredibly complicated structure and there is a lot of 'computation' occurring within the butons. We're not very sure of all the processes that occur at this time. It's not just a 0/1 kinda thing. Also, our current computers aren't even running the hardware that a synapse is. The most analogous electrical structure to a synapse is a memristor, something we can't make at scale right now. The synapse is also not the only structure that causes computation to occur, many things effect the firing of a neuron and that modulation.
Great lower bound calculation though. I'd say that's the right ballpark number.
Another is that Neurons are incredibly slow. Lets say you can make a machine only half as intelligent as a Human but that can think 1 Million times faster, this is even a lowball since a neuron can fire at like 1Hz and modern CPUs operate in the GHz range.
>In all likelihood we are never going to create a server with a whole city of intelligences in it, ever.
Think this is a really bad take. If one assumes even a .1% improvement in "Machine Intelligence" per unit time then it is literally only a matter of time until you reach Human level and then pass it.
That's like saying "even if there's only a 0.1% improvement in materials strength per unit time eventually we'll have structures strong enough to bounce off an incoming rogue planet." There is an upper bound to computational performance per unit mass and unit energy. We're nowhere near it but it is there, lurking.
This comparison doesn't make much sense - computers have a very small number of cores, let's say 10, and brains have 86 billion neurons. 86 billion things operating at 1Hz is also in the GHz range. This is leaving aside the issue that a CPU cycle and a neuron firing are doing completely different sorts of work - comparing them is kind of nonsensical in the first place.
>This is leaving aside the issue that a CPU cycle and a neuron firing are doing completely different sorts of work - comparing them is kind of nonsensical in the first place.
Maybe, but the op comment was explicitly using raw transistor count to compare to Neuron count as a proxy for sapience.
Note that I am extremely skeptical of your 1T parameters claim - there is much much more to AGI than natural-looking natural language processing + image recognition.