watsonx

Learn about using Granite models and watsonx for enterprise AI with Java. Understand the importance of openness, interoperability, and long-term support in AI adoption. Granite models provide an open foundation for AI, while watsonx delivers enterprise governance and lifecycle management. The combination of Quarkus, LangChain4j, Jakarta EE, and Red Hat OpenShift AI provides a complete story for confident AI adoption. This approach aligns AI adoption with the principles that made Java successful, ensuring investments remain valuable over time.

Learn how the Java ecosystem is adapting to the AI era and how IBM and Red Hat are investing to secure its future.

Integrates IBM watsonx Assistant with Guardium Key Life Cycle Manager to manage keys, check server health, verify backups, and retrieve user details.

This framework is effective for business process automation, research tasks requiring multiple perspectives, and creative collaboration scenarios where diverse expertise needs coordination.

Learn how to evaluate SQL query generation with a robust benchmarking method that handles SQL complexity, semantic diversity, and result validation.

Use Caikit to serve Hugging Face AI models that are consumed by your application.

Convert Maximo Java code to Python automation scripts with AI. Streamline customization, reduce downtime, and enhance efficiency with automated code conversion.

Learn how to shorten AI factsheet links in IBM OpenPages using rich text format, improving user experience and simplifying AI governance in watsonx.

Integrate IBM watsonx with IBM Docling and open source CrewAI to automate document analysis with highly intelligent agents

The article discussed RAG systems, highlighting the benefits, challenges, and optimization strategies for RAG systems by using IBM watsonx capabilities.