The Elegance of GPT: How Language Models Learn From Next-Token Prediction

GPT's training objective—predicting the next word—is deceptively simple, yet it enables AI systems to autonomously acquire grammar, reasoning, and coding conventions without explicit instruction. With scale (300 billion tokens), this single unsupervised task produces models capable of sophisticated language understanding and generation. This approach has become foundational to modern AI, demonstrating that remarkable depth emerges naturally from simplicity.