GPT 4: Superpower results with search
GPT-4 is pretty incredible, but like its predecessors, it has problems. Hallucinations and the lack of up-to-date information are typical of Large Language Models (LLMs), from PaLM and LLaMa, to ChatGPT (gpt-3.5-turbo) and GPT 4. In this video, we'll demonstrate how to supercharge GPT4 (and other language models) using OpenAI's ChatCompletion endpoint with the latest gpt-4 model and the Pinecone vector database. Augmenting the knowledge and abilities of GPT4 with up-to-date information about the LangChain Python library. 🔗 Code notebook: https://github.com/pinecone-io/examples/blob/master/learn/generation/openai/gpt-4-langchain-docs.ipynb 👾 Discord: https://discord.gg/c5QtDB9RAP 🎙️ Support me on Patreon: https://patreon.com/JamesBriggs 🤖 70% Discount on the NLP With Transformers in Python course: https://bit.ly/3DFvvY5 00:00 Why GPT-4 can fail - hallucinations 01:50 What we can do with retrieval augmentation 02:16 How retrieval augmentation works 07:41 Scraping docs for LLMs 10:01 Preprocessing and chunking text for GPT4 13:24 Creating embeddings with text-embedding-ada-002 14:58 Creating the Pinecone vector database 19:24 Retrieving relevant docs with semantic search 20:23 GPT-4 generated answers 23:44 GPT-4 with augmentation vs. GPT-4 without 25:34 Building powerful tools is almost too easy #artificialintelligence #gpt4 #openai #nlp #vectorsearch
