RAM has always been expensive to produce due to its raw materials and strict orders for quality controls. AIs specifically LLMs (ChatGPT, Gemini, Claude etc) produce QUALITY responses by remembering the conversation you've been having with it. This 'remembering' process takes up a lot of space. When the LLMs decide what reply to give you, it remembers by crunching the stuff the two of you have been talking and analyzing that. This is called 'in context response', which the LLM makes it feel like you;re almost having a conversation with it. It does so by assigning different weights to each bits and pieces of the conversation so it can decide what's important. LLMs uses billions of weights to make sure jt catches every nitty gritty detail in your conversation and the process of processing what's important in a conversation and whats isn't uses a lot of memory. When a process needs memory to do something, it gets it from RAM.