OpenAI to Z Challenge

Project Overview - The project focuses on using deep learning and open AI to aid in archaeological site discovery, specifically in the Amazon rainforest [2][4][10] - The team developed a scalable system (AKOS) integrating open AI to enhance the system's intelligence [1] - The approach involves training classifiers on satellite images and lighter data to classify segments of the Amazon forest, dividing the region into 3x3 km tiles [2] - The team created an interactive website where users can explore potential sites in detail [3] Technical Approach - Deep learning is considered a valuable tool for discovering archaeological sites, especially in the Amazon [10] - GPT models are used as collaborators, assisting in decision-making by providing multiple solutions and discussing their strengths and weaknesses [12] - The team used GPT for summarization, providing detailed descriptions of potential spots to help archaeologists understand why the model chose them [16] Results and Findings - The model successfully identified potential discovery sites, which were confirmed through manual analysis based on archaeological knowledge [3][14] - The deep learning approach is scalable enough to scan the entire Amazon rainforest in a reasonable time [4] - Configuration changes improved the visibility of features, leading to the identification of over 100 potential sites [3] Future Plans - The team intends to make their work public to gather feedback and inspire further research [18] - They plan to improve their approach and share it with a broader community, potentially inspiring applications in other fields [18]