Moore’s law has been unsustainable for 20 years, I remember Pentium 4’s with 4ghz. But that hasn’t seemed to matter in terms of real day to day performance improvements. This article makes some great points about the scaling cost and reduced market opportunity for there to be more than 2 or 3 makers in the market, but that’s a trend we’ve seen in every market in the world, to be honest I’m surprised it took this long to get there.

As interesting as this breakdown of the current state of things is, it doesn’t tell us much we didn’t know or predict much about the future, and that’s the thing I most wanted to hear from an expert article on the subject, even if we can take it with a large pinch of salt.

  Roughly every two years, the density of transistors that can be fit onto a silicon chip doubles.

No. Moore's law is not about density. It's just about the number of transistors on a chip. Yes, density increases but so does die size. Anyways, in Moore's own word:

  The complexity for minimum component costs has increased at a rate of roughly a factor of two per year.

http://cva.stanford.edu/classes/cs99s/papers/moore-crammingm...

More parallelism. Less clock. More l1 cache per CPU and less disk stalls. Are there plenty of tricks in the sea, when clockspeed goes flat?

Dual ported TCAM memory isn't getting faster and we've got to 1,000,000 prefixes in the internet and ipv6 are 4 times bigger. Memory speed is a real issue.

There are a lot of people working on all the mentioned problems - and on many many more.

Re garage invention: lithography is probably too big an issue for that. It's important to keep in mind that we're currently producing a lot of transistors with today's tech. Any alternative would have to match that (eg stamping technologies).

(I work on lithography optics)

Current GPUs have a comparable number of transistors (92.2 billion in the current NVidia Blackwell according to https://chipsandcheese.com/p/blackwell-nvidias-massive-gpu) to the number of neurons in human brains (about 90 billion according to Wikipedia). Brains consume less energy and do more, though transistors beat them on density. This suggests there are alternative pathways to performing computation that will scale better.

Is there also a law for how much more difficult it becomes to sustain Moore's law?

Ultimately, there's a cap. For as far as I know, the universe is finite.

> Roughly every five years, the cost to build a factory for making such chips doubles, and the number of companies that can do it halves.

So we may have Apple and NVidia as the only ones that can afford to build a fab. Edit, correction, Microsoft is the current number 2 company by market cap.

> In a transistor, the voltage of the gate lying on top of the channel controls the conductivity of the channel beneath it, either creating an insulator or “depletion region”, or leaving the silicon naturally conductive.

That's... not how this works at all. Eventually the depletion region where the positive or negative charge carriers (for p or n doped silicon) deplete far enough and then at the threshold voltage inversion happens when the opposite sort of charge carrier start to accumulate along the oxide and allow conduction. By surrounding the channel there's less space for a depletion region and so inversion happens at lower voltages, leading to higher performance. Same as people used to do with silicon on oxide.

The Wikipedia article has nice diagrams:

https://en.wikipedia.org/wiki/MOSFET

> Roughly every two years, the density of transistors that can be fit onto a silicon chip doubles. This is Moore’s Law.

that... isn't the moore law, it is about count / complexity, not density. and larger chips are a valid way to fullfill it.

https://hasler.ece.gatech.edu/Published_papers/Technology_ov...

https://www.eng.auburn.edu/~agrawvd/COURSE/E7770_Spr07/READ/...

the law delivered enough headroom that systems moved on. once compute got cheap to rent and scale ,there was less pressure to push frequency or density every cycle. so focus shifted. the gains kept coming ,just not in the same shape.

> Another possibility that has long been on my personal list of “future articles to write” is that the future of computing may look more like used cars. If there is little meaningful difference between a chip manufactured in 2035 and a chip from 2065, then buying a still-functional 30-year-old computer may be a much better deal than it is today. If there is less of a need to buy a new computer every few years, then investing a larger amount upfront may make sense – buying a $10,000 computer rather than a $1,000 computer, and just keeping it for much longer or reselling it later for an upgraded model.

This seems improbable.

50-year-old technology works because 50 years ago, transistors were micron-scale.

Nanometer-scale nodes wear out much more quickly. Modern GPUs have a rated lifespan in the 3-7 year range, depending on usage.

One of my concerns is we're reaching a point where the loss of a fab due to a crisis -- war, natural disaster, etc. -- may cause systemic collapse. You can plot lifespan of chips versus time to bring a new fab online. Those lines are just around the crossing point; modern electronics would start to fail before we could produce more.

factor in power usage reduction, and it still works

Has "Moore's Law" been consistent since it reared its head, or has it been constantly tweaked to suit the narrative of it still being correct?

I've always wondered what the classic Moore's-law curve looks like when you take the FLOPs per constant dollar, totaled across the whole R&D/manufacturing/operation process. Sure, you can keep investing more and more into increasingly cutting-edge or power-hungry processes, but at some point it isn't worth the money, and money will generally be the ultimate limiting factor. Not that we'll ever really get these numbers, alas.