How do large language models get so large?

AI models consist of large numbers of parameters, with larger models generally performing better. Language models and image diffusion models have different components, including tokenizers, embedding models, and predictors. Quantization can compress models, trading off quality for reduced memory usage. Storing and deploying large AI models presents challenges, with various solutions available depending on specific needs and infrastructure.