As somebody who works in Lithography, I can let you know that they have not been using visible light for a long time. All fine resolution lithography is designed around as close to a monochromatic light source as possible. Having a significant spread in the light spectrum was just not consistent to do much below the 1.0 um feature size. This is because of the diffraction spread is very dependent on the wavelength and the fact that the photons have different energies thus reacting differently (or not at all) in the photoresist on the wafer.
Thus broadband lithography gave way to g-line (465nm visible blue) which gave way to i-line (365nm Ultra-Violet); Next was deep UV (248nm), Now 193nm is still used in state of the art systems today with lots of tricks such as immersion (where the light goes into water before it hits the wafer to increase the NA of the system) and double patterning (splitting up the image into multiple images that are combined in the etch processes after). Extreme UV is 13.5nm light is the next step but it is a very difficult light source to work with and the systems outrageous sums of money even for this industry.
What you are completely correct about is the importance of connectivity. I went from working in a dying 1xx nm CMOS fab this year to a thriving 1.0+um fab that makes wireless components. The lithographic part of the process (and just cramming more and more transistors on a die) is not the key value to our customers; its the exotic materials that we use to target more and more bands of wireless connectivity. I expect there will always be a demand in the market for more and faster transistors for pure computation. Its unfortunately no longer where the market growth is; thus the ROI on developing these technologies is looking more and more risky for businesses. What I have found interesting is that just about everybody working on the high end of the industry is pretty confident that the transistors will work at the 5nm-7nm node so there is still an incentive to head in that direction for now. After that will require some radical re-thinking about the materials used in computational machines.