LLMs don't "memorize" concepts like humans do. They generate output based on token patterns in their training data. So instead of having to be trained on every possible problem, they can still generate output that solves it by referencing the most probable combination of tokens for the specified input tokens. To humans this seems like they're truly solving novel problems, but it's merely a trick of statistics. These tools can reference and generate patterns that no human ever could. This is what makes them useful and powerful, but I would argue not intelligent.