In general that is true. Also for ddr5 systems AMD threadripper and Ryzen can give more bang for the buck, than official intel products, in terms of hardware specs. However, for Math Kernel Library (MKL) applications which for particular applications is still the best mathematical library in the world and many softwares use it by default. Unfortunately also older versions. In dependence of MKL AMD can be slow or extra headache, needing to recompile things, with other flags, there are fewer users, smaller community, and therefore its more difficult to find helpfull support. The library was developed by intel, and they made it in a way to have an advantage over competitors. So i think for now, MKL+ Intel CPU is still the 'better' choice for a lot of scientific computation.
Not necessarily because it's really better, but extra programming and debugging efforts are also cost that go in the overall consideration of what hardware to buy. Similarly with NVIDIA GPU's and CUDA, all big libraries Pytorch, Tensoflow are faster and easier with NVIDIA gpus. Even if their products are or will become less hardware cost-efficient, they will not lose the lead so fast. And unfortunately for users, (not investors) that will probably make the price difference larger, w.r.t competitors larger. By buying their (intel and Nvidia) stuff eventually on the long run we will be paying for that growing monopoly gap. Except of course when buying ES cpu's. So maybe its even ethically a well-justifiable choice. Also considered early 12900 cpu, those with the round intel logo have surprisingly have AVX512 if e-cores are disabled. But honestly, they remain just 8 p-cores, memory and pcie channels made me look towards ES Xeons.
