[SOLUTION] Please describe your proposed solution.
Description:
In the ever-evolving landscape of software development, the dependence on AI tools like Github Co-pilot has become indispensable for developers. However, a notable gap exists – these tools are yet to be finely tuned to the unique languages and intricacies of the Cardano blockchain ecosystem. As a passionate AI developer and builder entrenched in the Cardano community, I’ve identified this challenge and I am excited to propose a solution – the Cardano Developer Co-pilot.
The Problem in Context:
Cardano, with its Haskell-based smart contracts in Plutus and Marlowe, has need for a specialized touch that mainstream AI tools lack. The existing solutions fall short when it comes to generating code that is not only syntactically correct but also aligned with the principles and nuances of the Cardano blockchain. This gap poses a bottleneck for developers eager to contribute to the Cardano ecosystem, hindering the speed and efficiency of smart contract development for developers in the ecosystem and creates bigger barriers to entry to new developers
The Solution:
Our proposed Cardano Developer Co-pilot is not just a tool; it’s a tailored companion for developers diving into the world of Haskell, Plutus, and Marlowe. Picture it as your trusty co-pilot on the coding journey, equipped with a deep understanding of the Cardano ecosystem. This AI assistant is not merely a code generator; it’s a learning partner, attuned to the unique requirements of Cardano development.
Why it Matters:
Efficient development is the lifeblood of progress, and with Cardano being at the forefront of blockchain innovation, the need for a dedicated co-pilot is paramount. Closing this gap will empower developers, reduce learning curves, and ultimately accelerate the growth of the Cardano ecosystem. By ensuring that the tools at our disposal align seamlessly with the Cardano languages, we pave the way for a more inclusive and vibrant developer community.
Implementation and Technical Features:
The Cardano Developer Co-pilot will be implemented using state-of-the-art natural language processing (NLP) and machine learning (ML) techniques. Our approach involves training the co-pilot on extensive datasets, ensuring it not only understands the syntax but also captures the essence of Cardano’s unique coding practices.
Key technical features include:
- Language Specialization: The co-pilot will be finely tuned to Haskell, Plutus, and Marlowe, (We will be starting with one language first) ensuring that generated code aligns with Cardano’s coding standards.
- Context Awareness: The AI will possess a deep understanding of the Cardano ecosystem, allowing it to generate code in context, taking into account the specific requirements of blockchain development.
- Learning and Adaptation: The co-pilot will continually learn from user interactions, evolving to meet the evolving needs of the Cardano developer community.
Tech Stack:
Our technology stack will leverage cutting-edge NLP libraries, machine learning frameworks, and the robust infrastructure necessary for the development of a sophisticated AI tool. We are committed to transparency and collaboration, welcoming community input to refine and enhance the Cardano Developer Co-pilot.
In essence, this proposal seeks not just to address a technical gap but to foster a more collaborative, efficient, and empowered Cardano developer community. Together, let’s embark on a coding journey where the co-pilot is as passionate about Cardano as the developers themselves.
USAGE:
The solution will be open-sourced so other developers in the ecosystem can adapt it in any format suitable to them, but for us we will make a simple interface where developers can simply access the solution, we will make the API available to the community and we will also develop it as a plugin on Chatgpt so as to reach a larger audience
[IMPACT] Please define the positive impact your project will have on the wider Cardano community.
Our proposed Cardano Developer Co-pilot isn’t just another fancy tool; it’s a game-changer for the community. Picture this: developers diving into Haskell, Plutus, and Marlowe with newfound ease, confidently crafting smart contracts like it’s second nature. Now that’s the kind of value we’re talking about.
Empowering Developers:
Imagine a world where developers, seasoned or just starting out, feel like they have a buddy in the coding trenches. Our co-pilot isn’t just about generating code; it’s about empowering developers to contribute effectively to the Cardano ecosystem. With a specialized touch for Cardano languages, the learning curve gets a bit less steep, and the possibilities for innovation broaden.
Accelerating Development:
Faster, more efficient coding means projects move at warp speed. The success of our co-pilot translates to quicker smart contract development. That’s not just a win for individual devs; it’s a boost for the entire Cardano community. The more we can streamline the development process, the faster we can bring exciting projects to life.
Fostering Collaboration:
You know what happens when tools are tailored to the community? Collaboration skyrockets. Our co-pilot isn’t an outsider; it’s part of the Cardano crew. By aligning with Cardano’s coding practices, it becomes a seamless addition to the developer toolkit, encouraging collaboration and knowledge-sharing within the community.
Wider Reach
Our plan is to make this solution easily accessible to all and to make its API available to all and the plugins integrated into ChatGPT plugins, this will bring new reach to the Cardano developer community as more people begin to play with the tool to learn how to build their first Cardano Dapps
HOW WE WILL MEASURE IMPACT
Developer Adoption:
We will be keeping an eye on how many developers embrace the co-pilot for their Cardano projects. The more, the merrier. If it becomes a go-to companion, we know we’re on the right track. As such we will track:
Number of developers outside of our team who will participate in development using this tool
Speedier Development:
Time is money, right? We’re measuring success by the speed at which smart contracts are developed with our co-pilot. If we see projects moving from ideation to deployment faster than ever, that’s a win. As such we will track:
The deployment time it takes developers to turn in projects using our tool, and the amount in time savings as a result
[CAPABILITY & FEASIBILITY] 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?
As the CEO of Remostart and one who has been actively involved in the Cardano ecosystem since fund 9 and has actively onboarded hundreds of developers and entrepreneurs into the cardano ecosytem, I have witnessed first hand the challeges new developers face trying to understand Cardano programming languaged, this has made me worried many times and thought of creative means to help them, my closeness to developers and entreprenurs in my platform makes me see this problem first hand and has developed in me just the right amount of passion needed to execute this solution
But this is not the only reason why I am suited to deliver this project, here is another reason, my academic background is in Artificial Intelligence, I graduated with a first class in CSE(Artificial Intellgence), I have 8 research papers in AI domains bordering NLP, Computer vision, deep learning, Machine Learning, data mining etc. I have 2 AI-related patents applied and this experience and competence is what is needed to execute this project so you can trust me on my capacity to deliver.
Finally, I had a fund9-funded proposal which was executed and brought to completion on time, an F-10 projected that is well on time and meeting milestones as scheduled, this demonstrates that I can be trusted when it comes to managing funds properly and with integrity.
[Project Milestones] What are the key milestones you need to achieve in order to complete your project successfully?
Co-pilot Training Commencement
Description:
Launch the training phase for the Cardano Developer Co-pilot, focusing on Haskell or Plutus for the first iteration and phase of this project and Marlowe and Plutus in future iterations of this projetc. Establish a foundation for open-source adaptability.
Milestone Output(s):
- Curated dataset for training, openly accessible for the community.
- Initial machine learning models implemented and open-sourced.
- Prototypical API structure for community integration.
Acceptance Criteria:
- Approval from the Cardano developer community on the relevance and inclusivity of the training dataset.
- Transparent sharing of initial models and dataset for community scrutiny.
- Prototypical API structure accessible and documented for potential adaptability.
Language Specialization Achieved
Description:
Attain a high level of language specialization for the Co-pilot, ensuring generated code aligns with Cardano’s coding standards. Lay the groundwork for open-source collaboration.
Milestone Output(s):
- Co-pilot proficient in generating syntactically correct Haskell, Plutus, and Marlowe code.
- Open-source release of the Co-pilot’s language specialization models.
- Community feedback loop implemented for collaborative improvement.
Acceptance Criteria:
- Code generation passes basic syntax checks for each language, as validated by the community.
- Open-source release receives positive acknowledgment and contributions from the community.
- Iterative improvements based on community feedback through open-source channels.
Contextual Awareness Integration
Description:
Enhance the Co-pilot’s understanding of the Cardano ecosystem, ensuring it generates code in context. Foster open-source development practices.
Milestone Output(s):
- Co-pilot demonstrating an understanding of Cardano-specific use cases and scenarios.
- Improved code generation that considers the broader context of the language development
- Open-source release of contextual awareness models.
Acceptance Criteria:
- Co-pilot generates code that reflects an understanding of Cardano-specific development scenarios, validated through community input.
- Positive community sentiment regarding the contextual relevance of generated code.
- Iterative improvements based on user feedback through open-source collaboration.
Learning and Adaptation Mechanism
Description:
Implement a learning and adaptation mechanism for the Co-pilot, allowing it to evolve based on user interactions. Foster an open-source feedback loop.
Milestone Output(s):
- Co-pilot capable of learning from user feedback and adapting its code generation over time.
- Mechanism for users to provide feedback on generated code and suggest improvements, openly accessible.
- Open-source release of the learning and adaptation models.
Acceptance Criteria:
- Users observe improvements in code generation based on their feedback, contributing to an open-source collaborative improvement process.
- Positive community sentiment regarding the Co-pilot’s ability to adapt to evolving Cardano development practices.
- Transparent open-source feedback loop established for continuous improvement.
Community Integration and Adoption
Description:
Facilitate seamless integration of the Co-pilot into the Cardano developer community, encouraging widespread adoption. Develop a simple interface and integrate as a plugin on ChatGPT for broad accessibility.
Milestone Output(s):
- Co-pilot accessible through user-friendly interfaces and integrated into popular development environments.
- Open-source release of a simple interface and plugin integration for ChatGPT.
- Community engagement events, tutorials, and documentation to promote Co-pilot adoption.
Acceptance Criteria:
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Positive feedback from developers regarding the ease of integration into their workflows.
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Increased usage metrics indicating a growing number of developers using the Co-pilot.
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Successful community events and tutorials with active participation and positive feedback on ChatGPT integration
[RESOURCES] Who is in the project team and what are their roles?
UBIO OBU: The CEO of Remostart, is a blockchain and AI researcher, his academic background is in Artificial Intelligence. Ubio has about 4 years of experience in researching, his research works have cut across different fields, from AI, to IoT, Agriculture, environment, blockchain, HR, human behaviors etc. He currently has about 7 research paper publications in reputable journals like the American Institute of Physics, and IEEE, etc, he has 2 patents under application and a Copyright on a book titled “Research writing for beginners”.
Ubio is a Microsoft Winsider Recipient, KECTIL leadership fellow, and a SingularityNet Ambassador.
Ubio will be in charge of the AI development and resource management
https://www.linkedin.com/in/ubio-obu-71927276/
Ediyangha Otogho: Full-stack software and Blockchain developer with 8 years of of software development experience and 3 years blockchain development experience. Ediyangha has won several hackathons and techatrons and was the chief technology officer behind Send funds, a fintech solution building a Bharatpe for Africa. Funfact Ediyangha can code efficiently in more than 7 programming languages. For this project he will be the blockchain and fullstack developer
https://www.linkedin.com/in/edinyanga-ottoho-02801517a/
https://www.github.com/EdinyangaOttoho
Yash Ambekar : B.Tech-Computer Engineering, Full stack Developer, 7 years experience in Software development, a Smart India hackathon winner, with about 3 Research paper publications. In this project he will coordinate the front end developer especially the UI/UX aspects.
Daniel Effiom: He is a co-founder at RemoStart, a Reconciliation analyst at ETransact international PLC. With 5 years experience in data analysis, process monitoring and operational procedures. He has managed several projects for RemoStart and ETransact and is why he will be the project and product manager for this project.
https://www.linkedin.com/in/daniel-effiom-a2b377199/
[BUDGET & COSTS] Please provide a cost breakdown of the proposed work and resources.
Co-pilot Training Commencement (20,000 ADA):
- Dataset curation: 5,000 ADA
- Machine learning implementation: 7,000 ADA
- API prototyping: 8,000 ADA
Language Specialization Achieved (40,000 ADA):
- Advanced training models: 20,000 ADA
- Open-source release preparation: 10,000 ADA
- Community feedback loop setup: 10,000 ADA
Contextual Awareness Integration (30,000 ADA):
- Specialized training for contextual understanding: 15,000 ADA
- Open-source release and documentation: 10,000 ADA
- Iterative improvements based on community feedback: 5,000 ADA
Learning and Adaptation Mechanism (40,000 ADA):
- Development of learning mechanisms: 15,000 ADA
- Open-source release and documentation: 15,000 ADA
- Transparent open-source feedback loop: 10,000 ADA
Community Integration and Adoption (40,000 ADA):
- Interface development and integration: 20,000 ADA
- ChatGPT plugin development: 15,000 ADA
- Community events, tutorials, and documentation: 5,000 ADA
Contingency and Miscellaneous (5,000 ADA):
- Reserve for unforeseen expenses or adjustments: 5,000 ADA
Total Budget: 170,000 ADA
[VALUE FOR MONEY] How does the cost of the project represent value for money for the Cardano ecosystem?
Our budgeting for the Cardano Developer Co-pilot is like crafting a fine dish – it’s about the right ingredients in the right proportions. The costs align with the expertise required for specialized development, training, and community engagement using global standards as the team is decentralized and not in one country. We’re transparent and open-source, with costs reflecting fair compensation for skilled work. The contingency fund is our safety net, and overall, the budget is a thoughtful investment in the Cardano community’s growth. It’s not just about spending money; it’s about investing in a future where the Co-pilot becomes an invaluable asset to Cardano developers, bringing genuine value to every ADA spent.
Refer below to the average cost of building LLMs and you will see our ask is 20-30% of what the average ask is
https://blog.truefoundry.com/economics-of-large-language-models/