Please describe your proposed solution

We propose Cardano Assistant, an open-source, AI-powered conversational interface tailored to the Cardano blockchain. By using state-of-the-art Large Language Models (LLMs), the assistant will function as a user-friendly plugin accessible via web browsers.

Natural Language Interaction

• Users can ask questions and receive answers about Cardano in plain language.
• Simplifies understanding of blockchain concepts and operations.

Educational Resource

• Provides explanations about Cardano's features, technology, and ecosystem.
• Helps new users learn how to use Cardano wallets, make transactions, and interact with decentralized applications (dApps).

Plugin Integration

• Easy integration as a plugin for web browsers.
• Open-source code encourages community contributions and enhancements.

Please define the positive impact your project will have on the wider Cardano community

Cardano Assistant will make Cardano more accessible, encouraging new users to join and participate. It will enhance user experience by simplifying complex operations, leading to greater community engagement, and potentially attracting more developers and projects to the platform.

What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

Team Capabilities:

Our team consists of four AI experts and blockchain enthusiasts with proven track records in academia and crypto development and up to 8 years of experience in relevant fields. Our work philosophy is best described by three principles:

1. Open: Achievements and work artifacts are open-sourced and published on a regular basis.

2. Transparent: Using clear documentation and academic rigor, we build trust and accountability. Whenever appropriate, we are happy to discuss our work with the academic community at top-tier blockchain and AI conferences around the globe.

3. Collaborative: Through collaboration with established industry peers from our earlier blockchain ventures, we gain regular feedback to continuously improve and adjust where required.

Validation:

Our team is composed of highly skilled developers with extensive experience in AI, ensuring we have the expertise to deliver the project. Further, the project will be fully open-source, allowing the community to review, contribute, and validate the code.

What are the key milestones you need to achieve in order to complete your project successfully?

Milestone 1: Milestone Outputs:

• Conduct Market Research:
• Analyze existing blockchain assistants and chatbots.
• Identify user needs and expectations within the Cardano community.
• Write Technical Design Document:
• Define the system architecture, including model selection, data flow, and integration points.
• Specify technical requirements for the plugin interface and backend systems.
• Identify Potential Challenges:
• Assess risks such as data privacy concerns, model biases, and technical limitations.
• Develop mitigation strategies for identified challenges.
• Develop a Project Plan:
• Outline timelines, resource allocation, and deliverables for each phase.

Acceptance Criteria:

• Final Research Report covering:
• Market Review: Comprehensive analysis of market needs and existing solutions.
• Technical Design Document: Detailed system architecture and specifications.
• Challenges: Identified risks with proposed mitigation strategies.
• Project Plan: Clear roadmap with timelines and resource allocation.

Evidence of Milestone Completion:

• Report summarizing the market review, technical design document, challenges, and project plan.

Milestone 2: Milestone Outputs:

• Choose Model Architecture:
• Select an appropriate LLM (e.g., GPT-based model) suitable for fine-tuning on Cardano-specific data.
• Collect Data, Including Cardano-Related Documentation:
• Gather data from official Cardano documentation, forums, FAQs, and educational resources.
• Clean and Preprocess the Dataset:
• Remove duplicates, correct errors, and format data for model training.
• Open-Source Data and Code Release:
• Publish the dataset (or links to data) and preprocessing code on GitHub.
• Documentation:
• Provide detailed instructions and explanations of the data collection and preprocessing processes.

Acceptance Criteria:

• Open-Source GitHub Repository containing:
• The dataset.
• The code used for data preprocessing.
• Documentation.of the code and scripts.

Evidence of Milestone Completion:

• GitHub Repository Link with the code, data, and documentation.

Milestone 3: Milestone Outputs:

• Fine-Tuned Model on the Collected Data:
• Train the selected LLM using the preprocessed Cardano-specific dataset.
• Test Model Performance:
• Evaluate the model's responses for relevance, and helpfulness.

Acceptance Criteria:

• Open-Source GitHub Repository updated with:
• Reference to the fine-tuned model.
• Updated code and documentation for the fine-tuning process.
• Performance Metrics:
• Documentation of testing results demonstrating satisfactory model performance.

Evidence of Milestone Completion:

• Link to the GitHub Repository with updated code, references and performance metrics.

Milestone 4: Milestone Outputs:

• Develop the Plugin Interface:
• Design and implement a user-friendly interface for the assistant.
• Ensure compatibility with major web browsers.
• Integrate Fine-Tuned Model with the Plugin:
• Connect the backend model to the frontend interface.
• Create User Documentation:
• Develop guides and tutorials on how to install and use the plugin.
• Open-Source Code Release:
• Publish the plugin code on GitHub.

Acceptance Criteria:

• Functional Plugin:
• The plugin operates effectively, integrating the fine-tuned model.
• Compatibility:
• Works smoothly across intended platforms and devices.
• Documentation:
• User guides and technical documentation are available.
• Open-Source Availability:
• Plugin code is publicly accessible on GitHub.

Evidence of Milestone Completion:

• Plugin Files ready for installation.
• GitHub Repository Link containing the plugin code and documentation.
• Demonstration Video showcasing plugin functionality.

Final Milestone: Milestone Outputs:

• Testing with the Community:
• Collect feedback on usability, performance, and any encountered issues.
• Refine the Model and Plugin:
• Address bugs and enhance features based on user feedback.
• Finalize Documentation:
• Update user guides and technical documentation accordingly.
• Prepare Final Closeout Report and Video:
• Summarize project outcomes, lessons learned, and future recommendations.

Acceptance Criteria:

• Improved Plugin:
• Enhanced functionality and user experience based on feedback.
• Complete Documentation:
• All materials are updated and finalized.
• Closeout Materials:
• Final report and video summarizing the entire project.

Evidence of Milestone Completion:

• Updated Plugin reflecting refinements.
• Report on User Feedback summarizing testing results.
• Final Closeout Report and Video.

Who is in the project team and what are their roles?

Timo is a visionary entrepreneur with a deep expertise in robotics, artificial intelligence, and cloud engineering. He holds a Master’s degree in Robotics with a focus on AI applications and co-founded an AI-driven agricultural startup. Timo has published his work at a major conference, demonstrating his ability to merge academic research with real-world solutions. Timo is driven by his passion to unlock the pioneering potential in bringing AI solutions to the blockchain.

Samy is a professional with five years of blockchain development experience and nearly eight years in AI and machine learning. As a developer and researcher, Samy has worked on several DeFi protocols and published peer-reviewed articles in top-tier AI journals and conferences.

Chris is a seasoned software developer and entrepreneur, boasting over four years of specialized experience in blockchain and AI technologies. His in-depth research in AI and blockchain testifies his comprehensive knowledge of the DeFi ecosystem, establishing him as a knowledgeable figure within the community.

Phil is a former AI & Data scientist with a proven academic track record and several years of industrial experience. His professional career revolved around the robotics & aerospace industry, where he successfully integrated AI to tackle challenging problems. As a crypto-enthusiast, he now seeks to contribute to the next wave of blockchain innovation.

Future Recruitment: We plan to potentially recruit additional Cardano-experienced blockchain developers and UI/UX designers as needed to further scale our development efforts.

Please provide a cost breakdown of the proposed work and resources

Total Estimated Budget: 95,000 Ada

Cost Breakdown by Milestone

Milestone 1: Project Planning (1 month) - 20,000 Ada

• Costs Include:
• Market research expenses.
• Project management and planning.
• Technical design documentation.

Milestone 2: Model & Data Setup (1 month) - 15,000 Ada

• Costs Include:
• Data collection and preprocessing.
• Computational resources for data processing.
• Open-source code and data release.

Milestone 3: Fine-Tuning (1 month) - 15,000 Ada

• Costs Include:
• Computational resources for model training.
• AI engineering efforts for fine-tuning.
• Testing and evaluation of model performance.

Milestone 4: Plugin Development (2 months) - 25,000 Ada

• Costs Include:
• Development of the plugin interface.
• Integration of the model with the plugin.
• Security implementations.
• Documentation creation.

Milestone 5: Testing & Community Feedback (1 month) - 15,000 Ada

• Costs Include:
• Coordination of beta testing.
• Refinement based on community feedback.
• Finalization of documentation.
• Preparation of closeout materials.

Contingency Fund: 5,000 Ada

• Reserved for unforeseen expenses to ensure project completion.

No dependencies.

How does the cost of the project represent value for money for the Cardano ecosystem?

Investing 95,000 Ada in Cardano Assistant offers significant value for the Cardano ecosystem due to:

1. Enhancing Accessibility: Simplifies blockchain interactions, making Cardano more approachable for users of all technical levels.
2. Promoting Education and Adoption: Serves as an educational tool, helping users understand Cardano's features and technology, thereby encouraging broader adoption.
3. Open-Source Contribution:
4. Fully open-source, encouraging community collaboration and continuous improvement.
5. Provides a scalable foundation for future enhancements and integrations.