Week 19 - Invention, Intellectual Property, And Income

This week’s core task is to systematically define the intellectual property strategy, licensing approach, sharing mechanisms, and potential pathways to financial sustainability for the final project – AI Horse BOOK. The following is a comprehensive elaboration from four dimensions.

1. Invention and Intellectual Property Positioning

The project is positioned as a non‑patented, open‑source‑first educational innovation tool. It is built entirely upon the existing open‑source ecosystem, and all designs can be reproduced in common digital fabrication laboratories (e.g., Fab Labs). It is primarily intended for youth STEM education scenarios. Therefore, we do not seek any patent protection; instead, we proactively adopt open licenses to promote knowledge sharing and community collaboration.

The specific licensing scheme is divided by output type as follows:

Output Type	License	Description
Hardware (mechanical structures, 3D models), PCB designs, system documentation, and teaching materials	Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 International (CC BY‑NC‑SA 4.0)	Allows others to copy, modify, and redistribute, provided they give appropriate credit, do not use for commercial purposes, and distribute derivative works under the same license.
Firmware / source code (including the underlying graphical programming blocks)	MIT License	Grants maximum freedom of use, including commercial integration, with the only requirement being retention of the copyright notice – ideal for educational remixing and secondary development.

2. Project Positioning and Target Audiences

The initial design goal of AI Horse BOOK is to provide a low‑threshold, highly interactive, multi‑modal practice platform for youth STEM education. It integrates core functions such as AI speech recognition and dialogue, remote control, mechanical motion driving, music playback, and graphical block‑based programming, supporting a complete learning chain from hardware assembly to software coding.

Although originally designed for after‑school programmes, science clubs, and makerspaces, its application is not limited to these settings. Potential users include:

• STEM/ICT teachers in primary and secondary schools, as well as vocational institutions

• Extracurricular technology education organisations and youth centres

• Charitable foundations, NGOs, and community groups running science‑popularisation activities

• Practitioners in Fab Labs, makerspaces, and other open fabrication laboratories

• University students or hobbyists interested in AI + robotics introductory education

For all these groups, the project offers a directly referenceable complete example – from hardware assembly and circuit design to AI interaction logic and graphical programming framework – all of which can be customised and scaled as needed.

3. Functionality Demonstration and Technical Validation

The core functions have been validated in a prototype during Week 15: Interface and Application Programming.

The accompanying video demonstrates the following two key scenarios:

• AI voice dialogue: through local or cloud‑based speech recognition, the system achieves natural language interaction with users, executing actions or providing feedback based on spoken commands.

• Remote‑controlled mechanical motion: using a mobile phone or gamepad, users can remotely control the horse‑shaped robot’s walking, head turning, tail wagging, and other movements, showcasing the synergy of mechanical transmission and electronic control.

The stable performance of these two functions confirms the feasibility of the system architecture and lays a solid technical foundation for the subsequent development of course content.

4. Scaling and Financial Sustainability Strategy

At this stage, the project is self‑financed by the individual, using equipment and materials provided by the host Fab Lab, without external capital. Therefore, we are not rushing to develop a full business plan. Instead, we adopt a “small steps, user‑co‑creation” strategy, prioritising the following tasks:

1. Small‑scale pilot (Phase 1)

• Collaborate with teachers from 3–5 partner schools and expert makerspace educators for real classroom trials.

• Collect feedback to validate the effectiveness of the teaching process, and refine hardware usability and software stability.

• Goal: develop 10 structured lessons through real‑world teaching scenarios, each focusing on a specific topic (e.g., “Understanding Motor Drivers”, “Voice Command Programming”, “Sensor Feedback Loops”). Students should be able to follow the lessons to independently complete the entire exploration from assembly to programming, ultimately gaining an intuitive understanding of AI and mechanical control.

2. Manufacturing standardisation (in parallel with the pilot)

• Complete small‑batch trial production (initially 10 complete kits), establishing standardised assembly procedures, a Bill of Materials (BOM), and testing specifications.

• Ensure consistent quality and reproducibility for each unit, preparing for future larger‑scale production.

3. Funding pathways (medium‑term)

• Self‑funding + grants: continue using personal resources while actively applying for small educational innovation grants (e.g., from local science and technology bureaus or education foundations).

• Crowdfunding platforms (next stage): after the course content and product have matured, launch a campaign on platforms like Kickstarter (or domestic equivalents) to raise initial capital through pre‑sales of kits plus course packages, while simultaneously validating market demand.

4. Long‑term vision

If the pilot proves successful, we envisage a dual‑track model: an open‑source community edition (freely shared) and an institutional custom edition (offering teacher’s manuals, online training, and technical support for a fee). Revenue from custom services will sustain ongoing iteration, ensuring the project’s long‑term financial viability.

Conclusion:

From its inception, AI Horse BOOK has embraced openness, sharing, and education as its core values. By choosing permissive licenses for intellectual property and maintaining a prudent, pragmatic approach to commercialisation, we believe that through genuine user co‑creation and iterative testing, this project can truly serve as a bridge between young learners and AI, while also contributing a valuable reference to the global educational maker community.