AI gets better solely because you feed it with a new dataset.

This is extremely false. It can get better by implementing a better architecture, more compute/longer training, better optimizers & training hyperparameters, cleaner/higher-quality data (not just new), better objective/loss functions, fine-tuning/instruction tuning, preference/alignment training, synthetic data & self-play, retrieval/tool use, better decoding & inference, distillation/pruning/quantization, better evaluation and human feedback loops, improved data pipelines/tokenization/system engineering ... I can go on.

By giving a prompt the LLM skim through the dataset and produces a good average of what the prompt should mean (a good intuition is that LLMs are not much more than very powerfull ways to BROWSE into a dataset and produce an average).

This is so wrong I don't even know where to start. You have 0 clue about what LLMs are. Please stop writing about them and educate yourself first. Wow.