This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
What I Built
LazyLearn AI is a study assistant prototype designed to help students prepare for exams more easily. It provides a simple interface for turning study notes into summaries, practice questions, flashcards, quizzes, and easy explanations.
The goal is to reduce repetitive study preparation and make revision easier.
Demo
https://amritakaur1717-collab.github.io/lazylearn-ai/
Code
https://github.com/amritakaur1717-collab/lazylearn-ai/tree/main
How I Built It
I built the project using HTML, CSS, and JavaScript for the frontend, with Python and Flask for the backend. The interface is designed to let students select a study task and submit their notes for processing.
The AI integration and testing are still in progress.
Why Does Open Innovation Matter?
Open innovation makes AI technology more accessible and gives developers the freedom to learn, experiment, and adapt tools to their needs. My goal is to integrate open-weight AI into LazyLearn AI so students can prepare study materials more efficiently.
The Lazy Payoff
LazyLearn AI aims to reduce the effort students spend creating revision materials manually. Instead of preparing summaries, questions, and flashcards separately, students will be able to generate study resources from their notes in one place.
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