LlamaIndex Webinar: Long-Term, Self-Editing Memory with MemGPT

Long-term memory for LLMs is an unsolved problem, and doing naive retrieval from a vector database doesn’t work.

​The recent iteration of MemGPT (Packer et al.) takes a big step in this direction. Taking the LLM as an OS analog, the authors propose “virtual context management” to manage both memory in-context window and in external storage. ​Recent advances in function calling allow these agents to read and write from these data sources, and modify their own context.

​We're excited to host Charles Packer, lead author of MemGPT. Charles presents an excellent overview of the project, gives a demo, and we also do a Q&A session in the middle and towards the end.

Timeline:
00:00 - 24:20 Presentation
24:20 - 41:18 Demo
41:18 Q&A