6 ms·

It's also a power issue. The 4090 sounds like you're going to need a much, MUCH higher PSU than you currently use.. or it'll suddenly turn off as it uses 2-3x t

It's also a power issue. The 4090 sounds like you're going to need a much, MUCH higher PSU than you currently use.. or it'll suddenly turn off as it uses 2-3x the power. You'll need your own wiring to run your PC soon :-)

melenaboija 4y ago
I think it is a stupid question, but does the power consumption needed by processors to infer compared to human brains demonstrate that there is something fundamentally wrong for the AI approach or is it more physics related? I am not a physicist or biologist or anything like that so my intuition is probably completely wrong but it seems to me that for more basic inference operations (lets say add two numbers) power consumption from a processor and a brain is not that different. It’s like seeing how expensive it is for computers to infer for any NLP model, humans should be continuously eating carbs just to talk.
- googlryas 4y ago
  > but it seems to me that for more basic inference operations (lets say add two numbers) power consumption from a processor and a brain is not that different Sure it is - it is too hard to figure it out based on 2 numbers number, but lets multiply that by a billion - how much energy does it take a computer to add two billion numbers? Far less than the energy it would take a human brain to add them.
- agalunar 4y ago
  Around room temperature, an ideal silicon transistor has a 60 mV/decade subthreshold swing, which (roughly speaking) means that a 10-fold increase in current requires at least a 60 mV increase in gate potential. There are some techniques (e.g. tunneling) that can allow you to get a bit below this, but it's a fairly fundamental limitation of transistors' efficiency. [It's been quite a while since I studied this stuff, so I can't recall whether 60 mV/decade is a constant for silicon specifically or all semiconductors.]
- visarga 4y ago
  The AI is much faster than the brain, if you batch requests the cost goes down.
Dylan16807 4y ago
The RAM is not using all that much of the power, and I think that scales more on bus width than capacity.
PartiallyTyped 4y ago
I bought a 1500w psu soon after the previous crypto collapse for around $150, one of the best purchases I did.

melenaboija 4y ago

I think it is a stupid question, but does the power consumption needed by processors to infer compared to human brains demonstrate that there is something fundamentally wrong for the AI approach or is it more physics related? I am not a physicist or biologist or anything like that so my intuition is probably completely wrong but it seems to me that for more basic inference operations (lets say add two numbers) power consumption from a processor and a brain is not that different. It’s like seeing how expensive it is for computers to infer for any NLP model, humans should be continuously eating carbs just to talk.

googlryas 4y ago
> but it seems to me that for more basic inference operations (lets say add two numbers) power consumption from a processor and a brain is not that different Sure it is - it is too hard to figure it out based on 2 numbers number, but lets multiply that by a billion - how much energy does it take a computer to add two billion numbers? Far less than the energy it would take a human brain to add them.
agalunar 4y ago
Around room temperature, an ideal silicon transistor has a 60 mV/decade subthreshold swing, which (roughly speaking) means that a 10-fold increase in current requires at least a 60 mV increase in gate potential. There are some techniques (e.g. tunneling) that can allow you to get a bit below this, but it's a fairly fundamental limitation of transistors' efficiency. [It's been quite a while since I studied this stuff, so I can't recall whether 60 mV/decade is a constant for silicon specifically or all semiconductors.]
visarga 4y ago
The AI is much faster than the brain, if you batch requests the cost goes down.

Dylan16807 4y ago

The RAM is not using all that much of the power, and I think that scales more on bus width than capacity.

PartiallyTyped 4y ago

I bought a 1500w psu soon after the previous crypto collapse for around $150, one of the best purchases I did.