4 ms·

I think maybe we might have been mis-reading Moore's Law for years, or rather, Moore himself might have mis-stated it. The radical changing reality that it des

I think maybe we might have been mis-reading Moore's Law for years, or rather, Moore himself might have mis-stated it. The radical changing reality that it describes is the number of transistors a person could economically employ at any one time to perform work on their behalf. So yes, physics and economics might provide us with a limit (or increasing slope of difficulty) for the construction of single chips, the practical effects of the Law continue unabated, at least as far as I can see. The average person continues to be able to employ more and more electronics to perform work for them. This is increasing geometrically. I'm not trying to dismiss either this DARPA guy or Moore, just point out that the specific details of Moore's Law may not be as important as we make them out to be. In my mind, the big obstacle we have now to continued growth is small-system, imperative thinking. Systems of the future will be massively parallel. I have no idea how long it will take the IT industry to truly transition, but that's the next big hurdle, not counting atoms inside a switch.

Detrus 13y ago
Yea I remember reading that DWAVE could tackle classical computing problems at 20 petaflops. All of Google today is 20 petaflops, across many cartoon colored datacenters. If you can produce small numbers of expensive computers that are more efficient than millions of cheap computers cobbled together, you are still advancing how much computational power each person has access to. But a significant problem with this approach is most real time video games aren't practical when the computer is far away.
- nullc 13y ago
  Latency isn't the only issue— do we want to be building a world where people are constantly trusting third parties to process their data privately and correctly? Certainly there are also cryptographic workarounds to those problems but their overheads are so high as to make the outsourced computation somewhat pointless.
danmaz74 13y ago
Except that, for most classes of problems, creating a software solutions that uses a massively-parallel system efficiently is much more difficult - and thus more expensive. This may be the real economic limit to using more transistors.

Detrus 13y ago

Yea I remember reading that DWAVE could tackle classical computing problems at 20 petaflops. All of Google today is 20 petaflops, across many cartoon colored datacenters. If you can produce small numbers of expensive computers that are more efficient than millions of cheap computers cobbled together, you are still advancing how much computational power each person has access to. But a significant problem with this approach is most real time video games aren't practical when the computer is far away.

nullc 13y ago
Latency isn't the only issue— do we want to be building a world where people are constantly trusting third parties to process their data privately and correctly? Certainly there are also cryptographic workarounds to those problems but their overheads are so high as to make the outsourced computation somewhat pointless.

danmaz74 13y ago

Except that, for most classes of problems, creating a software solutions that uses a massively-parallel system efficiently is much more difficult - and thus more expensive. This may be the real economic limit to using more transistors.