Parameters are values that guide how an
AI model processes information and generates responses. They are adjusted during
training while the model
learns from data, allowing it to identify
patterns and improve its performance in the tasks for which it was designed.
Parameters define how an
AI model analyzes and transforms the information it receives. In a computer vision model, for example, a combination of parameters can help distinguish shapes, colors, and edges in an image, allowing the system to recognize objects within it.
During
training, the model automatically adjusts millions or billions of these values to improve its accuracy. While a higher number of parameters tends to increase the model's capacity, it doesn't always guarantee better performance. Recent advances have enabled the development of more efficient models that achieve similar results with fewer parameters, optimizing the use of data and computational resources.