Tengyu Ma, AI optimization researcher and founder of Voyage AI, discusses the rise of RAG architecture in enterprise. They dive into evolving foundational data, context windows, managing latency budgets, and the role of academia in AI growth. Tengyu predicts RAG as the most cost-effective data retrieval system, highlighting its accuracy and speed.

Tengyu Ma, Co-Founder of Voyage AI and Assistant Professor at Stanford University, discusses embedding model training, contrastive learning theory, fine-tuning models for Langchain documentation, challenges in serving embeddings API, and optimizations for query inference and batch embeddings on the Weaviate Podcast.