The functionality of the modern blend of AI has some immensely powerful capabilities that offer a great deal of opportunity. LLMs also have some important flaws. Awareness of what AI is, what it’s capable of (and not capable of) is crucial to weighing opportunity cost of IT time. It’s simply too expensive to not be aware of what AI is.
This article explores the challenges and solutions in integrating Java with large language models (LLMs) for search. It details building a proof-of-concept for leveraging popular LLMs like SBERT and OpenAI, using Python-based tools to bridge gaps in Java compatibility. Learn how vector databases, FastAPI, and Chroma enable powerful search functionalities.
This article details a client success story with using RabbitMQ and MongoDB to Maintain Solr Indexes for high speed, cross data center updates.
This post breaks down how Mongo addresses the fundamental disparity in how to combine vector search results with lexical search results to maximize the benefits of each.
©2024 Innovent Solutions. All Rights Reserved.
