Agentic AI Capabilities
Jerry discusses the evolving capabilities of agentic AI, emphasizing the importance of chaining reasoning calls and retaining memory for enhanced performance. He highlights the potential of combining tools like vector and SQL databases to automate workflows. The conversation also explores the intriguing concept of code generation, where AI can write and execute its own programs, hinting at a step towards artificial general intelligence.In this clip
From this podcast

Gradient Dissent - A Machine Learning Podcast
Revolutionizing AI Data Management with Jerry Liu, CEO of LlamaIndex
Related Questions
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode Vector Databases and the Power of RAG and the clip Evolution of AI, as well as in the episode with Cohere co-founder Nick Frosst on building LLM apps for business and the clip Model Evaluation Insights?
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business, in the episode Holistic Evaluation of Generative AI Systems // Jineet Doshi // #280 and the clip Evaluating RAG Systems?
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data as discussed in the episode Building LLM-Based Applications with Azure OpenAI with Jay Emery - 657 and the episode with Cohere co-founder Nick Frosst on building LLM apps for business?