

Vector Databases and the Power of RAG
14 snips Apr 26, 2024
Edo Liberty, CEO of Pinecone, discusses the challenges and potential of RAG technology in AI. He compares RAG to early transformers, highlighting its sharp edges but amazing capabilities. The conversation covers the evolution of infrastructure in machine learning, semantic search, and the future of AI knowledgeability.
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Early Big Data Challenges
- In 2003, Edo Liberty worked with hyperspectral microscopy images, which were gigabytes in size.
- Single images couldn't fit in desktop memory, highlighting the challenges of "big data" even with small datasets.
Deep Learning Skepticism
- Edo Liberty initially viewed deep learning with skepticism due to its lack of theoretical grounding.
- The "no overfitting" phenomenon, where deep learning models improved despite training on the same data, challenged established machine learning theory.
Pinecone's Origin
- Edo Liberty's decision to launch Pinecone in 2019 was driven by the rise of embeddings and the potential of early language models like BERT.
- He recognized the growing interest in vector search and the opportunity to build a dedicated solution.