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/exampl...

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🤖 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