Right, we needed compute on a large and fast scale to make LLMs actually work. But the basic principles are quite simple: train on a huge dataset for long enough, using some fairly simple ML maths but across a very large dimensional space, and then out the other side you get something that can competently use language, and is capable of doing useful work. This is somewhat surprising, no?