Jerry Liu

Join Jerry Liu, the founder of LlamaIndex, as he shares his journey from roles at Uber and Quora to leading the RAG revolution in AI. He delves into the evolution of LlamaIndex, which enables better knowledge access through its innovative tree-index structure. Liu discusses the complexities of fine-tuning large language models and the importance of hands-on experience in optimizing performance. The conversation touches on the integration of structured and unstructured data, as well as the critical challenges in evaluating RAG systems, making it a fascinating listen for AI enthusiasts.

Join Jerry Liu, co-founder and CEO of Llama Index, as he discusses the innovative creation of this platform that links external data with large language models. He shares insights on the challenges of integrating private data, the importance of automation in decision-making, and the evolution of AI agents. Liu also dives into strategies for optimizing complex queries and highlights the transformative potential of AI in processing unstructured data. Get ready to explore how technology can revolutionize data management!

Jerry Liu, co-founder of LlamaIndex, dives into the captivating world of integrating private data with large language models. He reveals how LlamaIndex streamlines data ingestion and enhances query efficiency through innovative indexing techniques. The conversation covers prompt engineering intricacies and the transition from traditional querying to natural language processing. Plus, Jerry discusses evaluating model outputs and the exciting future of automated query interfaces, showcasing how LlamaIndex is set to revolutionize data interactions in AI applications.

Jerry Liu is the co-founder and creator of LlamaIndex (formerly known as GPT-Index), an interface that allows users to connect their data to LLM’s such as Chat-GPT. He has a B.S. in Computer Science from Princeton and has worked at companies such as Quora, Uber, and Robust Intelligence prior to starting LlamaIndex. Host: David Wu Twitter: @davidjhwu Audio Producer: Aaron Schumacher LinkedIn: Aaron Schumacher  Video Editor + Art: Saurin Kantesaria Instagram: saorange314 Social Media: Nikhil Kapur Time Stamps: 01:25 The path to starting LlamaIndex + initial ideas 07:09 LLMs like Chat-GPT vs traditional machine learning 10:00 4 steps of traditional machine learning 10:45 How do large LLMs change the game? 14:11 How does LlamaIndex help LLMs work with unstructured data? 18:08 How do you work with gigabytes of private data? 19:57 Organizing words and paragraphs by topic with embeddings 24:55 The importance of structuring data 26:00 3 key abstractions in LlamaIndex 29:25 Medical use cases for LlamaIndex 31:29 Increasing efficiency in medicine 33:25 An AI medical Research Assistant (Insight) 34:31 Other methods of connecting LLMs to data 36:55 What is langchain? 39:56 What work in the AI and LLM space excites you the most? 42:23 Do you ever feel scared about the developments of AI? 43:45 Llamas and Machine Learning 45:36 What do you think the future of AI in medicine will look like in 10-20 years? 47:24 What advice would you give to grad students, med students, and other early career professionals getting into AI and medicine?

Jerry Liu, Building LLM Tech, talks about Llama Index's mission in AI innovation challenges, effective communication with systems using Remix framework, tech tools for workflow efficiency, and Neo4j 5.15 updates in the graph community.

Jerry Liu, CEO of LlamaIndex, discusses the integration of diverse data formats with AI technologies, addressing challenges in data retrieval, analysis, and conversational memory. They explore topics such as Retrieval Augmented Generation (RAG), vector databases, AI model hallucinations, text extraction applications, and the role of LlamaIndex in the rapidly evolving field of AI-driven systems.

Jerry Liu, Co-founder and CEO of LlamaIndex, shares insights on Retrieval Augmented Generation (RAG) and LLMs in this podcast. They discuss the importance of good communication and documentation, the business aspects of LLM solutions, and the comparison of LlamaIndex with other tools. They also delve into the deep dive of RAG, the debate between RAG and fine-tuning, the importance of chunking size in RAG systems, and the relevance of prompt engineering in LLM development. The podcast concludes with a discussion on personal usage of AI tools and coding assistants.

Hey everyone! Thank you so much for watching the 37th episode of the Weaviate podcast! This episode discusses some of the ideas behind GPT Index. GPT Index presents really exciting ideas about how we use LLMs to index our data and then traverse these data structures. We began the podcast by discussing the origins of the tool and the ideas behind the Tree Index. We then discussed generalizing these trees to graphs and whether we are headed to the Knowledge Graph 2.0. Another really interesting topic we covered is the inference cost of building and traversing LLM indices like this! I really hope you enjoy this podcast I think these are some of the most cutting edge ideas in AI and Search! Check out GPT Index (now LlamaIndex here - https://gpt-index.readthedocs.io/en/l...) Chapters 0:00 Introduction 0:18 Origin Story of GPT Index 2:22 GPT Tree Index 5:53 Search Examples - Podcast Clips 11:22 Knowledge Graph 2.0? 16:05 LLM Writing Data to DB 20:18 Weaviate Classes and Index Hierarchy 23:53 Subindices vs. Tool Use 28:50 Inference Requirements for GPT Index 35:53 Design of GPT Index 37:40 Impact of Cheaper LLMs for this 40:02 Name Change for GPT Index? 42:04 Llama Hub 45:07 Relationship in Software Stack 48:15 Extension to Multimodal, e.g. Vision-Language

Jerry Liu, CEO and co-founder of LlamaIndex, discusses how companies are bringing their data to tailor large language models (LLMs) for their needs. Topics include working on LLMs versus autonomous systems, skill set and data preparation for LOMs, using databases for storing embeddings, capabilities of LMs in analyzing user questions, and exploring agents and specialized microservices in analytics engineering.

Clara Shih hosts founders/CEOs Aravind Srinivas, Jerry Liu, and Harrison Chase discussing AI tooling, tracking daily query counts, Langchain's connection to external data sources, Llama Index's private data applications, RAG vs. fine-tuning models, challenges in AI model responses, human contractors for model performance, future of education in AI era.