The presentation was a great overview of how to build a production-ready generative AI application on Google Cloud. I was delighted by the high quality of the Jupyter notebooks, which provided a hands-on way to learn about the different concepts. It was particularly helpful to see the real-world example of a restaurant website that uses generative AI to enhance customer engagement. This presentation was part of Google Cloud On Air, which is a great resource for learning about the latest developments in cloud computing.
Here are the key takeaways:
Vertex AI is a powerful platform for building generative AI applications. It provides access to Google’s Gemini models, as well as a variety of other foundation models and tools for prompt engineering, model customization, evaluation, and deployment. Prompt engineering is crucial for getting the most out of generative AI models. The presentation provided a helpful walkthrough of how to design effective prompts that elicit the desired responses from a model. Model evaluation is not a solved problem, but Vertex AI provides a variety of tools to help with the process. We learned about the different methods for evaluating models, including online and offline evaluation, pointwise and pairwise evaluation, and computation-based and auto-rated evaluation. Agent Builder is a powerful tool for augmenting generative AI models with real-time data and actions. We saw how to use Agent Builder to create a generative agent that can answer questions about a restaurant’s menu and book reservations. The presentation was clear, concise, and well-organized, and the live demonstration of the restaurant website was very helpful. I feel like I have a better understanding of the key steps involved in building a generative AI application on Google Cloud.