Generative AI on Google Cloud

Learn a comprehensive approach to building and deploying generative AI and large language models on Google Cloud, with a focus on language, images, and other modalities. Authors Mona Mona and Rajesh Thallam cover the latest launches from the Google Cloud Vertex AI platform, including PaLM2, Imagen, Codey, embeddings, Model Garden, and Generative AI App Builder.

AI developers, data scientists, and ML engineers will work with hands-on labs to implement these models in various business contexts, as well as with architecture blueprints for building and deploying generative AI applications for production use. You'll learn challenges and considerations associated with operationalizing these models using Google Cloud to adapt to business use cases and applications.

This guide helps you:

• Build generative AI use cases on Google Cloud and distinguish Google developer offerings from Google Cloud Enterprise offerings
• Explore the generative AI lifecycle with Vertex AI features: Model Garden, Vertex AI Studio, and Vertex AI Platform
• Train, fine-tune, and deploy Googleâ??s foundation models and open source models on the cloud
• Understand the importance of reinforcement learning with human feedback for aligning LLMs with human preferences
• Examine model architectures of data modalities such as images, code, audio, and multimodality
• Learn how generative AI changes or augments MLOps using Vertex AI Platform, including pipelines
• Understand the role of responsible AI when building generative AI applications on Google Cloud

Mona Mona is an AI/ML specialist for Google Public Sector.

Rajesh Thallam is an ML solutions architect who specializes in generative AI and LLMs at Google Cloud.