In this interview, Edo Liberty discusses the concept of "true memory" for AI, differentiating it from cognitive skills and computational abilities. He positions the current state of AI knowledge as similar to where foundational models were before ChatGPT, noting that while there's been progress with Retrieval Augmented Generation (RAG) and other techniques, there's still a long way to go. Liberty emphasizes the need for breakthroughs in various components, including vector databases, embeddings, query processing, and infrastructure, to achieve end-to-end automated systems that truly understand and utilize memory effectively. He also touches on the evolution of Pinecone's architecture to handle different workload patterns and addresses the challenges of commoditization in the vector database space. Furthermore, Liberty raises questions about defining knowledge, ensuring accuracy, and dealing with contested information in AI systems, highlighting the importance of trustworthiness and ethical considerations in the development and deployment of AI technologies. He also shares a book that has inspired him as a leader and expresses both excitement and concern about the future of AI.
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