See my responses to rest of the thread. Nobody understands or proposed a decent model of how an innate deep learning neural network was trained via evolution. Language acquisition in humans is in evolutionary terms an extremely recent phenomena, practically yesterday. Whatever the mechanism that processes language in humans, it was trained in very little number of evolutionary iterations, far less iterations compared to what chatgpt needs.
You might say that's not fair because we are comparing a pre-trained LLM with a blank slate newborn. But human hardware is also pre-trained by billions of years of evolution. We are hardwired to understand language and certain world concepts. It is not fair to compare hardware that is designed for language and reasoning to the hardware used for ChatGpt.
Another line of thinking: why does the amount of training matter? LLM and humans are completely different implementations.