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, ...

Fine-tuning an AI model can feel a bit like trying to teach an already brilliant student how to ace a specific test. The knowledge is there, but refining how it’s applied to meet a particular ...