You can still get all three, though you can only pick "cheaper" so many times before you fall off the mainstream product stack.
Two generations ago in 2019, the 3700X launched at $329. This generation, the 7600X launched at $299.
The 7600X has fewer cores, but they're about 50% faster individually and 25% faster total.
And it's N5 instead of N7.
The relative price of steel has remained flat, while the steel performance has greatly increased.
https://www.metalbulletinresearch.com/Article/3532290/Commod...
Between material science and cheaper compute, we can build higher tech parts and techniques.
The cycles/consumed/per/person/per/year is an exponential, what are some important points on that curve? When the computation to design something is on the order as the same amount of energy to create it?
https://cdn.mises.org/Less%20than%20Zero%20The%20Case%20for%... is an interesting book on the topic. (Ignore for a moment that it's hosted by mises.org..)
Some people think that deflation is bad for an economy. That's a bit confused.
What's bad for the economy is a fall in aggregate nominal spending. That one leads to recession and unemployment.
If prices fall, but total spending stays stable, that's fine.
We figure out how to turn atmospheric carbon into cheese. Take CO2 -> C12H22O11
Paying people to do nothing gives you nothing.
Full employment isn't an end in itself, but it's useful because it is typically related to things we do care about. Employing people to do nothing is like fiddling with the speedometer of your care in order to 'go faster'. Or relabeling your amplifiers to go to 11.
You can sort-of turn atmospheric carbon into cheese. Have grass capture the carbon, and a cow eat the grass. That's totally doable, just not viable or efficient if your goal is to capture carbon at scale.
(If your goal was to go carbon negative at all costs, you could instate a whooping big carbon tax, and let the economy figure it out.)
I think we already have a lot of high paying jobs in the economy that don't do much and pay people to do nothing (of value). We should absolutely spread that around.
I'm no expert in silicon scaling but from reading technical papers, my (naive) understanding is that transistor density has almost kept up but now that scaling comes with increasingly stringent design constraints which architects must make trade-offs over. Broadly speaking, things like "You can have 2x last gen's density but they can't all be fully powered on for very long." That's a greatly simplified example but much of what I've seen has been far "thornier" in terms of interacting constraints along multiple dimensions.
My sense is that in the 90s we usually got "denser, faster AND cheaper" with every generation. Now we're lucky to get one and even that comes with implementation requirements which can be increasingly arcane. My understanding is that different fabs are having to roll more of their own design libraries which embody their chosen sets of trade-offs per node. In addition to limiting overall performance and being harder to design, this apparently makes reusing or migrating designs more challenging. While certain headline metrics like node density may appear to be scaling as usual. The reality under the hood is more complex and far less rosy.