NEW Pinecone Assistant

The video introduces the new Pinecone Assistant, a tool for building AI assistants that can be enhanced with knowledge from PDF documents to provide accurate and up-to-date information. It demonstrates how to create an AI research assistant in Python, upload PDF documents to the assistant for processing, and interact with it to ask questions and receive informative responses supported by references to the provided knowledge.

The video discusses the new Pinecone Assistant, a tool that allows users to easily build AI assistants and enhance them with additional knowledge from documents. The Pinecone Assistant aims to reduce hallucinations in AI, provide up-to-date information, and answer questions specific to user’s needs by incorporating knowledge from PDF documents. The tutorial walks through using Pinecone Systems in Python by installing necessary prerequisites and authenticating the Pinecone API key within a notebook. The video demonstrates creating an AI research assistant, adding metadata for tracking, and starting the assistant to interact with it.

To make the assistant functional, knowledge in the form of PDF documents needs to be provided. The video shows how to download recent AI papers, extract file paths, and upload them to the assistant using the Pinecone API. The status of the uploaded files is checked to ensure processing completion, allowing users to move forward with interacting with the assistant. Once the documents are processed, users can start chatting with the assistant to ask questions and receive accurate responses grounded in the provided knowledge.

The tutorial includes examples of interacting with the assistant by asking questions about topics like ‘Mixture 8X 7B,’ ‘sparse Mixture of Experts model,’ and ‘Mamba 2 model.’ The assistant provides detailed responses with references to the specific PDF documents used to generate the answers, enhancing credibility and allowing users to delve deeper if desired. The video showcases the use of markdown display to present the assistant’s responses in a structured and readable format, making it easier for users to understand and follow the information provided.

A chat function is implemented to facilitate ongoing conversations with the assistant by storing the chat history and formatting messages for interaction. Users can continue asking questions and receiving informative responses from the assistant on various topics related to AI and deep learning models. The Pinecone Assistant offers a user-friendly and efficient way to leverage AI technology for acquiring knowledge, understanding complex concepts, and staying updated in the field of artificial intelligence. The video concludes with the process of deleting the assistant to free up storage space, highlighting the ease of managing and utilizing the Pinecone Assistant for tailored AI assistance.