Inspiration
Observing that we and everyone around me were becoming excessively dependent on AI for everyday tasks, we felt the need to create a tool that encourages a healthier balance. This project aims to help users optimize their AI usage while fostering their own creativity and skill development.
What it does
The AI Usage Tracker logs and analyzes your AI usage, providing insights to help you balance AI reliance with personal creativity and skill development. It tracks tasks, time spent, and the impact on creativity and productivity.
How we built it
We built the AI Usage Tracker using Python and Streamlit for the web application interface. we used Pandas for data manipulation and Matplotlib for visualizations. The data is stored in a CSV file, and the code was developed and tested in VS Code, with version control managed through GitHub.
Challenges we ran into
One challenge was ensuring seamless data handling and storage with CSV files. Another was creating an intuitive and user-friendly interface with Streamlit. Balancing real-time data updates and ensuring accurate calculations for AI dependence and productivity scores also proved challenging.
Accomplishments that we are proud of
- Effective Data Tracking: Successfully implemented a system to log and analyze AI usage, providing valuable insights into productivity and creativity.
- User-Friendly Interface: Designed an intuitive Streamlit application that makes data entry and visualization straightforward and accessible.
- Impactful Visualizations: Created meaningful charts and metrics that help users understand their AI usage patterns and set reduction goals.
- Project Deployment: Completed and shared the project on GitHub and Devpost, showcasing the application and its potential benefits to a wider audience.
What we learned
- Working on a real-world problem
- Integration of tools
- Database management
- User Experience Design
- Project Deployment
Log in or sign up for Devpost to join the conversation.