Update README.md

README.md

@@ -40,9 +40,7 @@ Traditional Large Language Models (LLMs) are incredibly knowledgeable but can so
 *   Personalized syllabus generation based on user goals and optional resources.
 *   Customizable teaching persona for the AI Explainer Agent.
 *   Interactive conversation manager to clarify learning objectives.
-*   Backend API built with Django and a frontend interface with React.
 *   Proper rendering of code and math formulas in explanations.
-*   SQLite database for easy setup.
 *   Designed for topics requiring deep thinking and understanding.
 
 ## How It Works (The Gist)
@@ -109,7 +107,7 @@ This project tackles these issues through a structured workflow:
 
 *   **Ideal Topics (based on experience):**
     *   Subjects requiring deep conceptual understanding where visual/audio aids are not primary (e.g., learning music theory concepts is okay, but learning an instrument is not ideal for this text-based version).and also not optimal for Topics where you need extreme precision from a preferred resource.
-    *   Examples: Increasing cognitive ability, learning Chess & Go strategies, understanding brain control concepts, developing a competitive spirit.
+    *   Examples: Increasing cognitive ability, learning Chess & Go strategies,  brain control
     *  **Technical Topics:** Revising classic machine learning, exploring advanced Reinforcement Learning (e.g., using Barto & Sutton as a resource and AI Studio(can handle large files) for syllabus creation) and  understanding codebases.
 *   **Performance:** Generally strong for conceptual/philosophical topics. For highly technical subjects, see "Improvements" below.
 *   **Resource Limitation:** Currently, resources can only be provided at the start of a conversation.