Principles of Large Language Models

Statements 1 and 2 are correct. LLMs operate as advanced probabilistic systems that analyze text patterns to compute statistical distributions, predicting the most probable next word in a sequence based on prior context. Their underlying training architecture uses mathematical loss functions and optimization algorithms to reduce prediction errors across datasets. Statement 3 is incorrect because LLMs frequently duplicate or amplify systemic biases present in their training data, meaning they do not produce completely objective or unbiased outputs.