Oh god yes. This is going to be pretty simplified, but: The sheer compute required to run something like ChatGPT is mindboggling, we’re talking thousands of A100 GPUs ($10k a piece, each one has 80GB of VRAM) networked together, and probably petabytes of SSD storage for the DB. Most neutral networks require a bunch of GPUs working in parallel because they need a lot of very fast memory to hold all the data they sift through, and a lot of parallel compute to sift through that data as quickly as possible. That’s why GPUs are good for this - you can think of a CPU like a human, very versatile but there’s only so much one person can do at a time. Meanwhile GPUs are like bug swarms, a bunch of much simpler brains, but specialized, and they “make it up on volume”. It’s only because of advances in computing power, specifically in the amount of compute cores and VRAM on GPU dies, that the current level of AI became possible. Try downloading GPT4All and compare free models that run on your machine to the performance of ChatGPT - you’ll certainly see the speed difference, and if you ask the free ones for code or logic you’ll see the performance difference too.
This is all to say that superconducting traces and transistors mean no heat is generated by dumping power through them, so you can fit them closer together - even right next to and on top of each other, doesn’t matter, because they don’t need to be cooled. And, because you lose no power to heat, it can all go to compute instead, so it’ll be perfectly efficient. It’ll bring down the cost of everything, but specifically computer components, and thus OpenAI will be able to bring more servers online to improve the capabilities of their models.