The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Building and Deploying Real-World RAG Applications with Ram Sriharsha - #669
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Jan 29, 2024 Ram Sriharsha, VP of Engineering at Pinecone and an expert in large-scale data processing, explores the transformative power of vector databases and retrieval augmented generation (RAG). He discusses the trade-offs between LLMs and vector databases for effective data retrieval. The conversation sheds light on the evolution of RAG applications, the complexities of maintaining fresh enterprise data, and the exciting new features of Pinecone's serverless offering, which enhances scalability and cost efficiency. Ram also shares insights on the future of vector databases in AI.
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LLMs and the Knowledge Layer
- Large language models (LLMs) excel at intelligence and orchestration but lack a robust knowledge layer.
- Vector databases provide this missing knowledge layer, enabling accurate and relevant information retrieval.
RAG and Search Expertise
- Chatbots based on Retrieval Augmented Generation (RAG) heavily rely on effective search and information retrieval.
- Experience in search and relevance is crucial for building successful, user-friendly chatbots.
Retrieval-Enhanced LLMs
- Combining LLMs with retrieval through vector databases enhances their performance.
- Retrieval improves LLMs even on knowledge they were trained on, exceeding fine-tuning.