RAG and Kafka Flink to Prevent Hallucinations in GenAI
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Real-Time GenAI with RAG using Apache Kafka and Flink to Prevent Hallucinations

How do you prevent hallucinations from large language models (LLMs) in GenAI applications? LLMs need real-time, contextualized, and trustworthy data to generate the most reliable outputs. This blog post explains how RAG and a data streaming platform with Apache Kafka and Flink make that possible. A lightboard video shows how to build a context-specific real-time RAG architecture. Also, learn how the travel agency Expedia leverages data streaming with Generative AI using conversational chatbots to improve the customer experience and reduce the cost of service agents.
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Top 5 Trends for Data Streaming with Kafka and Flink in 2024

Do you wonder about my predicted TOP 5 data streaming trends with Apache Kafka and Flink in 2024 to set data in motion? Discover new technology trends and best practices for event-driven architectures, including data sharing, data contracts, serverless stream processing, multi-cloud architectures, and GenAI.
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Apache Kafka + Vector Database + LLM = Real-Time GenAI

Generative AI (GenAI) enables advanced AI use cases and innovation but also changes how the enterprise architecture looks like. Large Language Models (LLM), Vector Databases, and Retrieval Augmentation Generation (RAG) require new data integration patterns. Data streaming with Apache Kafka and Apache Flink processes incoming data sets in real-time at scale, connects various platforms, and enables decoupled data products.
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Data Streaming with Apache Kafka as Data Fabric for GenAI
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Apache Kafka as Mission Critical Data Fabric for GenAI

Apache Kafka serves thousands of enterprises as the mission-critical and scalable real-time data fabric for machine learning infrastructures. The evolution of Generative AI (GenAI) with large language models (LLM) like ChatGPT changed how people think about intelligent software and automation. This blog post explains the relation between data streaming and GenAI and shows the enormous opportunities and some early adopters of GenAI beyond the buzz.
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