I'd argue this why we need innovation in the software architectures of the data processing systems that utilise our compute power. If we are running out of road on how much more powerful we can make microchips, then we should look at the software architectures as the area that needs to evolve. We haven't really done any major innovation in things such as data indexing since the '60's.
There is another factor, hardware optimization. If you look at word processing, there is no need to optimize the software because the workload is not increasing. Indeed, more WP is done now in browsers with inefficient language than is done by the pure apps written in C.
However, that WP (whether browser or app) will have AI added. This will use inferencing built into the SOC (look at all the mystery silicon already on an Apple A15) which runs several orders of magnitude more efficiently than software on the CPU or even on a GPU. This is what Moore's law is mostly fueled by now. Special acceleration. The leading edge innovation is going to require this, and the chips have plenty of room for it. Making that advance saves power (it is starting to eat into legacy functionality as well as new) and is not blocked by physics. It just needs manufacturing quality to keep improving so that larger chips are cost effective (as well as welcoming improvements in density and device power).
In the near term we are not near the limits. Next 5 years has mapped out improvements in size and energy efficiency of process, as well as reducing defect rates. In 5 years will another 5 years of improvements seem obvious? Perhaps. The kind of improvements needed will likely change, due to acceleration, and the current wave of bringing memory closer to computation.
I'd argue this why we need innovation in the software architectures of the data processing systems that utilise our compute power. If we are running out of road on how much more powerful we can make microchips, then we should look at the software architectures as the area that needs to evolve. We haven't really done any major innovation in things such as data indexing since the '60's.
There is another factor, hardware optimization. If you look at word processing, there is no need to optimize the software because the workload is not increasing. Indeed, more WP is done now in browsers with inefficient language than is done by the pure apps written in C.
However, that WP (whether browser or app) will have AI added. This will use inferencing built into the SOC (look at all the mystery silicon already on an Apple A15) which runs several orders of magnitude more efficiently than software on the CPU or even on a GPU. This is what Moore's law is mostly fueled by now. Special acceleration. The leading edge innovation is going to require this, and the chips have plenty of room for it. Making that advance saves power (it is starting to eat into legacy functionality as well as new) and is not blocked by physics. It just needs manufacturing quality to keep improving so that larger chips are cost effective (as well as welcoming improvements in density and device power).
In the near term we are not near the limits. Next 5 years has mapped out improvements in size and energy efficiency of process, as well as reducing defect rates. In 5 years will another 5 years of improvements seem obvious? Perhaps. The kind of improvements needed will likely change, due to acceleration, and the current wave of bringing memory closer to computation.