Apple's latest research shows that the performance of a visual model is positively correlated with the amount of its parameters and the amount of pre-training data. This study verified the rule of "the more parameters, the stronger the performance" through the autoregressive image model, and successfully expanded the model capacity to billions of parameters while maintaining its good performance in downstream tasks. This breakthrough provides important theoretical basis and new research direction for the performance improvement and optimization of future image models, and also lays a solid foundation for further development in the field of artificial intelligence.
Researchers from Apple have verified the rule of "the more parameters, the stronger the performance" of the visual model through the autoregressive image model, further proving that as the capacity or amount of pre-training data increases, the model can continue to improve performance. The researchers verified that the model capacity can be easily expanded to billions of parameters, and at the same time has good performance on downstream tasks, providing new research directions and ideas for future image model performance improvement and optimization.This research result is of great significance, pointing out the direction for the development and application of future image models, and heralding the imminent advent of higher-performance and more powerful image models. I believe that in the near future, we will see more innovative applications based on the results of this research.