You can spend a small amount of die space on something that will yield 10x performance benefits for some things, and you can spend a lot of die space on somethi

You can spend a small amount of die space on something that will yield 10x performance benefits for some things, and you can spend a lot of die space on something that will only yield a general 5% improvement. Which you choose depends on a lot of factors. In other words, the relationship between the "things on the chip" and general performance, or specific application performance, is not a strictly linear relationship. The 20 series Nvidia GPUs with RTX were a good example. RT cores were added and took up significant die space, people said "why not more CUDA cores", but given the design of consumer GPUs it's extremely unlikely that just replacing those with more CUDA cores would have had a proportional uplift. In Nvidia's case, they realized RT cores were a better bet and served their customer bases (industrial graphics, gaming) better than just more raw numbers. As it stands, specialization like this is a key element of new designs on leading edge processes. You're going to see more of it, not less. > I guess that’s why they pay the people at apple the big bucks because they must know best. Well I don't know about "best", they almost certainly know ~infinitely more about their customers and workloads than random people like us do, I can at least say that much.