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CodiumAI has introduced a new enterprise platform that leverages Retrieval-Augmented Generation (RAG) for advanced, context-aware AI code generation. RAG is a promising AI use case that allows teams across various industries to utilize large language models (LLMs) with their own data. This technology combines retrieval-based methods with generative models, enabling organizations to produce specific code, tests, and reviews. The platform aims to transform natural language processing (NLP) by using a vector database and LLM to provide context-aware answers.
🚀 New Blog Alert! Discover how Retrieval Augmented Generation (RAG) transforms NLP by combining retrieval-based methods with generative models. Our latest blog covers: 🔍 RAG Basics: Learn how RAG uses a vector database and LLM for context-aware answers. 📈 Key Processes:… https://t.co/5lCs3PcMRm
Retrieval Augmented Generation (RAG) is one of the most promising AI use cases, as it enables teams across all industries to leverage the power of LLMs with their own data. But it's one thing to develop a prototype - another to use RAG in production. In our upcoming online… https://t.co/uv2kTrYYCG
Find out how CodiumAI's new enterprise platform leverages Retrieval-Augmented Generation #RAG for advanced contextual-aware #AIcode generation! 🧠✨ Read our latest blog to learn how we do organization-specific code, tests, and reviews: https://t.co/YMQo9h7x5j https://t.co/ouZGJfl8oJ
