VisQueryPDF processes PDF files by splitting them into chunks, generating vector embeddings via OpenAI or compatible models, and storing those embeddings in a local vector store. Users can submit natural language queries to retrieve the most relevant chunks. Search hits are displayed with highlighted text on the original PDF pages and plotted in a two-dimensional embedding space, allowing interactive exploration of semantic relationships between document segments.

The DALL-E 2 Google Extension allows users to integrate OpenAI's DALL-E 2 image generation capabilities into Google Images. By incorporating AI-generated visuals alongside standard results, it transforms search experiences, inspiring creativity and enabling users to explore a myriad of visual styles and interpretations. Imagine searching for a concept and instantly finding unique art pieces that reflect that idea, making it an invaluable tool for artists, designers, and content creators.