How Irrelevant Retrieval Leads to Hallucination in RAG Models
Introduction Retrieval-Augmented Generation (RAG) models combine retrieval and generative technologies to improve natural language understanding and generation. These models use huge external databases to find relevant info, which they then use to create accurate and context-appropriate responses. However, RAG models face a big problem called “hallucination,” where they produce outputs that aren’t based on facts […]
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Integration of Spring AI with Knowledge Graphs
Today’s rapidly evolving technological environment has created a need to integrate artificial intelligence (AI) into corporate Infrastructure. there is an increasing need for these systems to understand and process vast amounts of structured data. This is where knowledge graphs come into play, offering a structured way to represent and interpret data that reflects real-world relationships. […]
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Vector Database: Addressing Latency Issues in AI-Powered Search
In the fast-paced world of artificial intelligence (AI), speed is everything. Imagine asking a question and waiting several seconds for an answer—frustrating, right? This delay, known as latency, is a major hurdle in AI-powered search systems. It can turn user experiences sour and diminish the effectiveness of AI applications, especially in real-time scenarios where every […]
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Fine-Tuning Large Language Models (LLMs) with Transfer Learning in a Spring Data Pipeline
Large Language Models (LLMs) like GPT-4 have transformed the landscape of natural language processing (NLP making it possible to create smart apps that can understand and write text like human. But to make these models work best for specific business needs, they often need extra training on data from that field. This process called transfer […]
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Spring AI and Large Language Models (LLMs) Integration
Integrating Spring AI with Large Language Models (LLMs) combines the power of intelligent text generation with the robust architecture of Spring. While LLMs like GPT-4 excel at generating and understanding human-like text, Spring AI enhances this capability by providing a solid, scalable framework for deploying and managing these models within enterprise applications. This integration allows […]
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Generative AI: Reliable Recommendations with Knowledge Graphs
How can organizations ensure that AI-driven recommendations are accurate, trustworthy, and contextually relevant? Generative AI is transforming how we generate and interpret data, These models, fueled by neural networks and deep learning, can generate sophisticated outputs, but their reliability remains a critical concern. missing out on accurate recommendations is not an option. Remember, successful recommendations […]
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