Part 12/15:
A recurring theme in AI's progress is the importance of scale. Increasing the volume of data and computational resources has consistently led to performance leaps. For instance:
The "ImageNet moment" (2012) marked CNNs dominance in vision.
The GPT-3 revolution emerged from training on hundreds of billions of tokens.
Later, research like the Chinchilla paper emphasized optimal training data-to-parameter ratios.
Current models are trained on trillions of words, with newer research exploring synthetic data generation and multimodal models (combining images, text, and audio).