Generative AI in practice: Concrete LLM use cases in Java, with the PaLM API By Guillaume Laforge

Large language models (LLMs) are a powerful new technology that can be used for a variety of tasks, including generating text, translating languages, and writing different kinds of creative content. However, LLMs can be difficult to use, especially for developers who are not proficient in Python, the lingua franca for AI. So what about us Java developers? How can we make use of Generative AI? This presentation will go through how to use LLMs in Java without the need for Python. We will use the PaLM API, provided by Google Cloud’s Vertex AI services, to perform a variety of tasks, such as searching through documentation, generating kids stories, summarizing content, extracting keywords or entities, and more. GUILLAUME LAFORGE Guillaume Laforge is Developer Advocate for Google Cloud, where he spreads the word to developers about the serverless compute space and service orchestration solutions. Guillaume is a Java Champion, a co-author of Groovy in Action, and a founding member of the French tech podcast Les CastCodeurs. Guillaume is the co-founder of the Apache Groovy programming language project, which he led under the umbrella of G2One (a Groovy/Grails startup where he was the VP Technology), then SpringSource, VMware, and the Pivotal spin-off. When the project joined to the Apache Software Foundation, he was the Chair of the Apache Groovy Project Management Committee (PMC). He is a member of the Micronaut Technology Advisory Board. He initiated the creation of the Grails web application framework, and founded the Gaelyk project, a lightweight toolkit for developing applications in Groovy for Google App Engine.