Google Machine Learning and Generative AI for Solutions Architects

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Advanced Generative AI Concepts and Use Cases

Now that we’ve covered the basics of generative AI (GenAI), it’s time to start diving deeper. In this chapter, we will cover more advanced topics in the field of GenAI. We’ll begin by learning about some techniques to tune and optimize generative models for specific domains or tasks. Then, we’ll dive into more detail on the important topics of embeddings and vector databases and how they relate to a relatively new pattern of using retrieval-augmented generation (RAG) to ground our large language model (LLM) responses in our own data. Next, we’ll discuss multimodal models, how they differ from standard, text-based LLMs, and the kinds of use cases they support. Finally, we will introduce LangChain, ...