> So the critical question is what exactly does AGI hardware look like

A Ryzen 5 should do. A lot of RAM is required.

On Thu, 11 Jul 2019 at 07:34, Alan Grimes via AGI <[email protected]>
wrote:

> I'm sure many of you are aware of this issue but I'll repeat it anyway
> because I had been allowing myself to get carried away thinking about
> what kind of hardware I'd throw at our resident genius' brain simulator.
> 
> The fundamental problem is this paradox:
> 
> A. We do not know what kind of hardware an AGI machine will require. It
> is still completely possible that it turns out to be nothing at all like
> the tensor cores you will find in a GV100.
> 
> B. It has been shown that specialized hardware can MASSIVELY accelerate
> AI (which may or may not = AGI) algorithms to the point where previously
> infeasible solutions become not only possible but commercially viable.
> 
> It is close to certain that any general purpose architecture, whether it
> be MIPS, Alpha, MMIX, ARM, Power, or even common x64 will do a perfectly
> medeocre job at doing whatever it turns out to be.
> 
> However, a specialized architecture will either be fantastic or absolute
> crap to the point of not being able to run it at all.
> 
> So the critical question is what exactly does AGI hardware look like and
> how much of it do we need to bridge the gap between what we can do with
> general purpose architectures.
> 
> I think GPUs and FPGAs can be considered relatively safe things to shop
> for. At least you can waste your life playing video games with a good
> GPU if it doesn't pan out for AGI work. =P
> 
> However, anything advertised as a deep learning accelerator -> BLEH
> because I think deep learning only has a few months of life left to it
> as a research paradigm and then the field is either SHIFT or WINTER.
> 
> --
> Clowns feed off of funny money;
> Funny money comes from the FED
> so NO FED -> NO CLOWNS!!!
> 
> Powers are not rights.
> 


-- 
Stefan Reich
BotCompany.de // Java-based operating systems

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