CS50's Fundamentals of AI - Lecture 5 - Generating (live, unedited)

This CS50 lecture explores generative AI, focusing on how AI can produce new content like text, images, and audio. The lecture details text generation, explaining how language models predict the next token in a sequence to answer questions or fulfill prompts. Speaker 1 describes strategies for refining language models, including adding specificity and precise instructions to prompts, and using reinforcement learning from human feedback to train reward models. The discussion covers retrieval augmented generation, using embeddings and vector databases to incorporate external data sources like emails into AI responses. Image generation techniques are examined, including generative adversarial networks, variational autoencoders, and diffusion models, alongside speech synthesis methods like concatenative synthesis and neural network-based approaches.