The project aims to create tools that support neurodivergent users, including a typing telemetry tool to detect possible signs of SEN and a thought tracking tool to automatically filter and sort conversations into groups and links ideas through connections.
The idea is inspired by the user's personal experience with ADHD and autism, and the goal is to build tools that can help people in ways the user didn't receive help themselves.
The tools should have features that effectively support neurodivergent users, such as adapting to individual thought processes and providing reminders to stay on track.
Assessment tools for neurodivergent traits, such as the Conners Adult ADHD Rating Scales and the Autism Quotient (AQ) test, are typically used in clinical settings and require individuals to answer questions in a self-report or observer-report format.
However, these tests have limitations, such as the potential for masking or coping strategies to influence self-reporting, and the challenge of assessing personal experiences of the same issue.
The breakthrough in LLM memory could lead to reduced costs for training and running AI models, making them more accessible and affordable for various applications, including this project.
The user's personal experience and perspective can bring a unique insight into developing these tools, and the goal is to create tools that can empower neurodivergent users and provide them with the support they need.