Weaviate Podcast Contextual AI with Amanpreet Singh - Weaviate Podcast #114!
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Feb 12, 2025 Amanpreet Singh, Co-Founder and CTO of Contextual AI, dives into the revolutionary world of Retrieval Augmented Generation (RAG) 2.0. He discusses the seamless integration of generative and retrieval models and the challenges of prompt engineering. Amanpreet emphasizes the necessity of continual learning and updates to model weights to resolve knowledge conflicts. The conversation also highlights the potential of reinforcement learning algorithms and the importance of domain-specific data. Buckle up for insights on the future of AI and specialized agents!
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RAG 2.0: Joint Optimization
- Retrieval Augmented Generation (RAG) systems face a challenge: retrievers lack feedback from generators.
- Jointly optimizing both components, as in RAG 2.0, enhances performance, mirroring advancements in computer vision and NLP.
Active Retrieval
- Active retrieval empowers language models to selectively retrieve information and fix errors, surpassing the limitations of static retrieve-and-read methods.
- LLMs can actively decide what to retrieve, improving information gathering.
Domain-Specific Language
- At Contextual AI, internal terminology like "hill climbing" has a specific meaning.
- New team members require time to understand specialized company jargon, similar to how language models need to adapt to enterprise data.