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Comment by roenxi | Hacker News Reader

The computational power of the hardware is getting really close to what a human brain is capable of (on an exponential scale, anyway). If "nowhere close" means not in the next 5 years then sure.

Over the medium term I'm not sure AI researchers are the best people to ask. They are completely dependent on how much power the electrical engineers give them - I doubt there is a deeper understanding what a doubling or quadrupling of computer power will do than any programmer learning about neural networks.

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> The computational power of the hardware is getting really close to what a human brain is capable of

Why do you say that? AFAIK computing architecture and brain architecture are completely different. How would you even begin to compare their power?

Well, Wikipedia was my source [0] and it links http://hplusmagazine.com/2009/04/07/brain-chip/ as its source.

Google has TPU that are off from the estimated power required to simulate a brain by a factor of 3, so technology is reaching the ballpark. Given that brains were evolved, the part that does symbolic thinking is probably "easy to stumble on" in some practical sense.

[0] https://en.wikipedia.org/wiki/Computer_performance_by_orders...

Faster hardware will help, but I'm not convinced that it's the answer. OpenAI Five used on the order of 2000 years of experience to train their agent. There are clearly still huge algorithmic gains to be had.

Given how we've managed to improve on nature in other domains (see solar cell efficiency, for example), I think that if we can figure out how intelligent organisms manage to learn so quickly we can likely beat nature's efficiency.

> I doubt there is a deeper understanding what a doubling or quadrupling of computer power will do than any programmer learning about neural networks.

Sure they do. They just hook up four times as much compute power or simulate whatever they want to do in four times as much time. A slow AGI would still be an AGI. But we do not see anything like that if we use four times as much power as in the control. It is still nowhere near.

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