Charles Packer, lead author of MemGPT at UC Berkeley, discusses the concept of explicit memory management in GPT models, the use of prompts to handle memory limitations, interrupts in retrieval augmented generation (RAG), achieving ideal running speed in high parameter models, fine-tuning MemGBT for long conversations, search actions pagination, role-playing language models, and the future integration of memory in chatbot platforms.