When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

What separates a mediocre large language model (LLM) from a truly exceptional one? The answer often lies not in the model itself, but in the quality of the data used to fine-tune it. Imagine training ...