Objective
This phase aims to build and test a Minimum Viable Product (MVP) that effectively integrates AI-driven insights to address the identified problem. The focus is on creating a practical and scalable solution through iterative prototyping and testing, ensuring the MVP aligns with the challenge theme and problem definition from previous phases.
Activities
- MVP Development Using Low-Code AI Tools
Create an initial MVP using accessible low-code AI tools like Google AutoML, Microsoft AI Builder, or alternative application development platforms like Bubble or OutSystems: Checklist in Henrik’s challenge document appendices. These tools enable students to integrate AI without advanced coding, expediting the prototyping process while maintaining functional depth and relevance to the problem.
- Iterative Testing and Refinement with Design Thinking
Apply design thinking principles to guide iterative testing and refinement of the MVP. Emphasize usability and functionality, using data-driven insights to identify and address areas for improvement. This iterative process ensures the prototype remains user-centered and responsive to practical challenges.
- Feedback Collection from Peers and Mentors
Gather input from peers and mentors to enhance the MVP. Feedback should focus on technical aspects (AI integration, functionality) and user experience (usability, clarity). Students can refine their solutions by incorporating constructive critiques to meet real-world needs better.
Deliverable Requirements
The deliverable for this phase is an MVP Prototype accompanied by the following documentation:
- Technical Documentation:
- Model Structure: Describe the structure of the AI model(s) used, including details on architecture, algorithms, or modules.
- Data Sources: Outline the sources utilized, specifying data type, origin, and relevance to the problem. Indicate any preprocessing or data integration steps taken.
- AI Integration: Explain how AI is applied within the MVP, detailing how the chosen model and data enhance the solution’s effectiveness.
- Testing and Refinement Insights:
Summarize the outcomes of initial testing rounds, including any key challenges, improvements, or user feedback that shaped the refinement process. Highlight specific insights gained through testing and how these contributed to the final MVP iteration.
Formatting and Submission Guidelines
- Length and Structure: The MVP documentation should be concise, focusing on essential technical and testing information. There is no strict page limit, but clarity and coherence are critical.
- APA Citations: All data sources, references, and AI tools used in development and testing should be cited in APA format, both in-text and in a reference section.
- Appendices: Include additional visuals, diagrams, or test summaries as appendices, providing supplementary details without expanding the core documentation.
Like what you did the first time, I will give you the proposal and you need to build up a prototype this time. It dont has to be a comprehensive one, all it need just a simple chatbot model as a prototype to present. It should be basic level coding and only use open sourced materials. You can just do what I asked for chatgpt (screen shots attached below), just to give you an idea about it.
Requirements:
