Earthshot Factory aims to develop a cutting-edge software solution that integrates digital signals detection and analysis with an AI-driven workflow.

The primary goal is to create a system capable of identifying and interpreting various signals from digital data sources and analyzing them. This project will allow learners to apply their knowledge of signal processing, machine learning, and software development to build a robust and efficient system. The software should be able to autonomously detect anomalies, classify different types of signals, and provide actionable insights through an intuitive user interface. The project will involve designing algorithms for signal detection, training AI models for analysis, and integrating these components into a cohesive workflow.

The output should be a full-stack web application that allows the user to approve or reject the execution of the AI agent's recommended action.

- A functional software prototype that can detect and analyze signals using AI (whether large language models or otherwise).

- Documentation detailing the algorithms and AI models used, including their training and validation processes.

- A user interface that displays the detected signals and analysis results in an easy-to-understand format.

- A final report summarizing the project, including challenges faced and solutions implemented.

Access to OpenAI, Claude and Google API keys. Access to mentorship, guidance and support. Access to wireframes and relevant software required.