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Customers have a huge investment in WebSphere ND infrastructure including installation, development, deployment, management, support, and 3rd party products. At the same time there are significant new workloads. Mobile is driving very high transaction rates using new device types. New applications often require extremely fast response times. The Cloud economy based on Restful services is rapidly expanding the very nature of applications. Meanwhile, teams need to improve efficiency and drive higher density on their platforms. In this session we will show you how to evolve your WebSphere ND environment to manage new workloads while preserving your existing investment. See how to add Liberty servers into ND. Explore how Intelligent Management and the ODR extend ND to support Restful services. Examine the benefits of a caching tier to improve response time and availability. See how to add Worklight into your ND environment to provide mobile device and application support. Explore continuous delivery and devOps options for WebSphere ND.
AAI-2075 Evolving an IBM WebSphere Topology to Manage a Changing Workloa
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Retrieval augmented generation (RAG) is the most popular style of large language model application to emerge from 2023. The most basic style of RAG works by vectorizing your data and injecting it into a vector database like Milvus for retrieval to augment the text output generated by an LLM. This is just the beginning. One of the ways that we can extend RAG, and extend AI, is through multilingual use cases. Typical RAG is done in English using embedding models that are trained in English. In this talk, we’ll explore how RAG could work in languages other than English. We’ll explore French, Chinese, and Polish.
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