3 ms·

from purely storage prespective: right now you can buy 1Tb microSD card (1^12 bytes), which is about 7800x more than first 128Mb microSD card introduced in 2005

by lebed2045 5y ago

from purely storage prespective: right now you can buy 1Tb microSD card (1^12 bytes), which is about 7800x more than first 128Mb microSD card introduced in 2005, so x^15 = 7800 => x = 1.8 i,e 80% improvement a year (I know it's super vogue approximation but helps to get the order of magnitude). Extrapolate that for 17k Petabytes, and we get 1.8^y = 17000 => y = 17, so less than a century for sure. anothing thing, that likely for AI the topology of the brain wiring is more important than raw organic data

iaw 5y ago
I don't know if storage is the right metric, perhaps something closer to RAM is, or particularly VRAM. If that's the case then we have a bit farther than 17 years to go.
- sudosysgen 5y ago
  We have 1Tb RAM workstations, though.
- jiggawatts 5y ago
  Compared to modern digital electronics, the human brain is "very wide but very slow". The equivalent clockspeed is just tens of hertz, maybe a few hundred for some areas. High fidelity simulations of the signal waveforms might require only a few thousand samples per second! Contrast that to a typical modern computer, which has clocks a million times faster than that. Similarly, simulating a brain may not need high precision at all, and is likely amenable to various forms of compression. For example: a simulator could have a library of the behaviour of a million synapses, and simply interpolate between them to closely match each synapse in a brain scan. Hilariously, for extra efficiency, this kind of interpolation in a high dimensional space is something artificial neural networks are quite good at! I envision a path where ordinary "machine learning" is used to automatically model small sections of the brain, such a ganglia, axons, synapses, etc... Similarly, ML techniques can be used to match scans to the previously learned library of these models. The final thing might just be a hundred 8-bit "parameters" per synapse, and there's 125 trillion of those, so about 12.5 petabytes. That's a lot of data, but you can buy a server right now with 12 TB of memory! Assuming a 30% increase in capacity yearly (thanks Mr Moore), the goal is just 26 years away. Make an entry in your calendar: 2047 is the year we'll have human-equivalent AI...
tartoran 5y ago
Yes but not all parts have to be active simultaneously. Like our long term memories are stored on a long term type of media in the brain so could an artificial life agent store those on a different type of media, maybe it could be heavily compressed or self erasing over time
MeinBlutIstBlau 5y ago
We're not even counting the storage of memory, storage of connections between them, and dynamic growth of storage.

iaw 5y ago

I don't know if storage is the right metric, perhaps something closer to RAM is, or particularly VRAM. If that's the case then we have a bit farther than 17 years to go.

sudosysgen 5y ago
We have 1Tb RAM workstations, though.
jiggawatts 5y ago
Compared to modern digital electronics, the human brain is "very wide but very slow". The equivalent clockspeed is just tens of hertz, maybe a few hundred for some areas. High fidelity simulations of the signal waveforms might require only a few thousand samples per second! Contrast that to a typical modern computer, which has clocks a million times faster than that. Similarly, simulating a brain may not need high precision at all, and is likely amenable to various forms of compression. For example: a simulator could have a library of the behaviour of a million synapses, and simply interpolate between them to closely match each synapse in a brain scan. Hilariously, for extra efficiency, this kind of interpolation in a high dimensional space is something artificial neural networks are quite good at! I envision a path where ordinary "machine learning" is used to automatically model small sections of the brain, such a ganglia, axons, synapses, etc... Similarly, ML techniques can be used to match scans to the previously learned library of these models. The final thing might just be a hundred 8-bit "parameters" per synapse, and there's 125 trillion of those, so about 12.5 petabytes. That's a lot of data, but you can buy a server right now with 12 TB of memory! Assuming a 30% increase in capacity yearly (thanks Mr Moore), the goal is just 26 years away. Make an entry in your calendar: 2047 is the year we'll have human-equivalent AI...

tartoran 5y ago

Yes but not all parts have to be active simultaneously. Like our long term memories are stored on a long term type of media in the brain so could an artificial life agent store those on a different type of media, maybe it could be heavily compressed or self erasing over time

MeinBlutIstBlau 5y ago

We're not even counting the storage of memory, storage of connections between them, and dynamic growth of storage.