Ask HN: Is Moore's Law over, or not?

Moore's law, strictly, is about the growth of transistor density. Koomey's law, strictly, is about the improvement in computation per unit energy.

Those are both interesting, but frequently people care about something different from either, which is something like "computation per second available in hardware of reasonable size, power consumption and cost". Call this "effective performance".

This can increase even if Moore fails (e.g., we find good ways to exploit parallelism, and build larger devices with more cores). It can fail to increase even if Moore holds (e.g., we can put more cores on a device of the same size, but we aren't good enough at exploiting parallelism so real performance doesn't improve).

It can increase even if Koomey fails (e.g., we find ways to make our hardware faster; there's a corresponding increase in power consumption but we are still able to cool things well enough so we just accept that). It can fail to increase even if Koomey holds (e.g., we can't make anything faster but we find a way to maintain existing speeds at lower power; very nice but no performance improvement unless power consumption is the current bottleneck).

It used to be that effective performance increased exponentially at a fairly consistent rate. This increase has slowed but not stopped; it's not obvious (to me, anyway) what we should expect it to do in the nearish future.

The consistent exponential increase in effective performance had a name, in popular discourse. It was called "Moore's law". It's unfortunate that strictly speaking it isn't what Moore was originally describing, leading to an ambiguity when people refer to "Moore's law" between a law about density and a law about effective performance.

(I unfortunately lack the ability to read minds, so I can't be sure what OP had in mind. But given the statement that "it has big implications for the advancement of AI technology", it looks to me more like effective performance than density.)

A general-purpose CPU requires that a program is transformed (via compilation or interpretation) into a set of basic instructions, ones that the processor knows how to handle. This means that almost every program requires many cycles to complete, even if the underlying logic itself could theoretically be done within a single cycle (or within no cycle at all!).

On the other end of the spectrum are FPGAs and ASICs, programmable or dedicated circuits that allow you to create specialized logic that corresponds directly to a specific need.

Bringing this back to the discussion at hand: Moore's law cares nothing about general-purpose CPUS, and is just focused on number of transistors on an IC doubling. With that said, transistors can only get so small (due to the laws of physics), and so one can presume we'll see an end to scaling eventually.

There are changes we can make to improve general-purpose CPU architecture, regardless of transistor count, and there are changes we can make to how we run programs (moving dedicated logic to dedicated circuits). Forcing any logic into a generic set of steps that run a in a loop will always be less efficient than wiring up the logic itself.

The questions has always been whether to wait for the machine to get faster or to create the dedicated logic yourself. The former has been true since the beginning of computation, and has been closely associated with Moore's law. With that said, it doesn't mean that the literal end of Moore's law is the end of computational efficiency gains.

Yeah, sure. Just give up on the thing you wanted to do and instead do something entirely different that is more parallelizable. That'll keep your CPU utilization high, but it won't actually accomplish your goal (presuming you were using software for some purpose other than maximizing CPU utilization).