Generative AI and Long-Term Memory for LLMs (OpenAI, Cohere, OS, Pinecone)

Generative AI is what many expect to be the next big technology boom, and being what it is — AI — could have far-reaching implications far beyond what we'd expect. One of the most thought-provoking use cases of generative AI belongs to Generative Question-Answering (GQA). Now, the most straightforward GQA system requires nothing more than a user text query and a large language model (LLM). We can test this out with OpenAI's GPT-3, Cohere, or open-source Hugging Face models. However, sometimes LLMs need help. For this, we can use retrieval augmentation. When applied to LLMs can be thought of as a form of "long-term memory" for LLMs. 🌲 Pinecone article: https://www.pinecone.io/learn/openai-... 📌 Notebook: https://github.com/pinecone-io/exampl... 🤖 AI Dev Studio: https://aurelio.ai 🎉 Subscribe for Article and Video Updates!   / subscribe     / membership   👾 Discord:   / discord   00:00 What is generative AI 01:40 Generative question answering 04:06 Two options for helping LLMs 05:33 Long-term memory in LLMs 07:01 OP stack for retrieval augmented GQA 08:48 Testing a few examples 12:56 Final thoughts on Generative AI