Summary

In this chapter, we dived into generative AI in Google Cloud, exploring Google’s native generative AI models, such as the Gemini, PaLM, Codey, Imagen, and MedLM APIs. We discussed the multiple versions of each model and some example use cases for each. Then, we introduced Vertex AI Studio and discussed open source and third-party models available on Google Cloud via repositories such as Vertex AI Model Garden and Hugging Face.

Next, we discussed vector databases in Google Cloud, covering various options available, such as Vertex AI Search and Conversation, Vertex AI Vector Search, BigQuery Vector Search, Spanner Vector Search, pgvector, and AlloyDB AI Vector Search, including some decision factors for choosing one solution over another. It is these kinds of decision points that are often most important in the role of a solutions architect, and the decisions will vary based on the specific needs of the customer or project, including the cost of each solution. I recommend...