Summary: Creating AI models involves five interconnected stages: data preparation, model training, model validation, model tuning, and model deployment. Data is crucial, and preparation includes categorization and filtering. Model training involves choosing the right foundational model and tokenizing data. Model validation assesses real-world performance, while tuning optimizes responses. Finally, model deployment releases the AI into the world, with opportunities for continuous improvement. Advances in deep learning and foundation models have streamlined the process, making it more accessible for various applications, from chatbots to universal solutions.