
Ram Sriharsha
VP of Engineering at Pinecone, a vector database company. Expert in large-scale data processing, machine learning, and the application of vector databases to RAG.
Top 3 podcasts with Ram Sriharsha
Ranked by the Snipd community

65 snips
Jan 29, 2024 • 35min
Building and Deploying Real-World RAG Applications with Ram Sriharsha - #669
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.

22 snips
Oct 14, 2025 • 48min
The timelessness of vector databases | Pinecone’s Ram Sriharsha
Ram Sriharsha, CTO of Pinecone and expert on vector databases and AI infrastructure, dives into the vital role of vector databases in today's AI landscape. He emphasizes that search is central to AI, guiding listeners on starting with Retrieval-Augmented Generation (RAG) applications while implementing evaluation frameworks to manage AI hallucinations. Ram highlights the importance of curiosity and generalist engineers in leveraging AI effectively, urging leaders to build AI frameworks pragmatically and iteratively for better results.

21 snips
Aug 12, 2024 • 44min
#234 High Performance Generative AI Applications with Ram Sriharsha, CTO at Pinecone
Ram Sriharsha, CTO at Pinecone and a veteran in software engineering, dives into the fascinating world of generative AI applications. He discusses the problem of hallucinations in AI and how retrieval augmented generation can help. Ram explores practical uses for vector databases in chatbots, optimizing performance, and the importance of structured data. He also highlights the future of large language models and the crucial role of data engineering in enhancing AI efficiency. Get ready for a tech-packed conversation that uncovers the secrets of high-performance AI!


