Please describe your proposed solution.
In the dynamic world of Decentralized Finance (DeFi), trading freedom can lead to compulsive behaviors resembling gambling addiction. HarmonyAI addresses this challenge by empowering users with informed decision-making and providing mental health support. We aim to promote responsible trading practices, preventing financial and emotional distress in the DeFi ecosystem.
Introduction to Secure DFL - The basic framework for our solution:
Secure DFL (Secure Decentralized Federated Learning) is a privacy-preserving machine learning framework. It leverages the security and immutability of blockchain technology for decentralized federated learning. Internally integrated with encryption technologies such as Differential Privacy (DP), Secure Multi-Party Computation (SMPC), GPG, etc., it ensures user privacy, allowing users to train models without exposing personal information. The feasibility of this framework is demonstrated in the demo, which also provides a user-friendly interactive interface: https://github.com/HXSu/DFL-Framework.
The Secure DFL framework, which has undergone experimentation, provides a solid technological foundation for our solution. Our framework seamlessly integrates state-of-the-art deep learning models and serves as a good benchmark for Blockchain-AI developers. It has two modes of operation as explained on the GitHub page. This work was detailed in two publications at IEEE Blockchain and Beyond conference last November. The latest work addresses practical real-world considerations while porting to the Cardano blockchain - first via MIlkomeda sidechain feasibility and in the future via native Plutus implementation as in this proposal.
In collaboration with our esteemed partner, HugoByte Network Labs, we are excited to unveil their profound expertise in providing decentralized infrastructure for AI. Their dedicated support will play a crucial role in optimizing our model's effectiveness.
In tandem with our valued partner, The Love Hope Company, we are thrilled to announce their commitment to offering extensive technical expertise in the realm of mental health care. Their dedicated support will play a pivotal role in enhancing the effectiveness of our model. Additionally, they will spearhead a beta test for our platform, ensuring a robust and refined solution that aligns seamlessly with the evolving landscape of mental health support. This collaborative effort underscores our collective commitment to delivering a cutting-edge and impactful solution for the well-being of our users.
Secure Federated Learning on Cardano:
Secure DFL, a blockchain-based framework on Cardano, enables collaborative model training without sharing raw data. Participants, identified as nodes, undergo a secure and scalable process. Features like Secure Multi-party Computation (SMPC), secure storage in IPFS, and privacy-preserving learning, including differential privacy measures, ensure confidentiality. SMPC Collaborative Model Aggregation allows nodes to jointly compute an aggregated model while preserving individual privacy. This innovative approach fosters trust in the decentralized chatbot ecosystem, offering a secure, scalable, and privacy-centric environment for language model training on Cardano.
<u>Proof of Implementation on Testnet:</u>
Our proposal includes a tangible demonstration of our solution through a robust implementation on the Cardano EVM testnet via Milkomeda. The provided link (https://explorer-devnet-cardano-evm.c1.milkomeda.com/address/0x4C2BA0815Cc6AFBdaB5E476D1e93db12Efe10A5B/transactions#address-tabs) showcases the deployment of our smart contract, capturing crucial transactions and operations that validate the functionality and effectiveness of our solution.
Node Registration: The testnet transactions include operations related to node registration, demonstrating the seamless onboarding process for participants in our decentralized infrastructure. This ensures that the network is open and accessible for all potential contributors.
Model Distribution: The recorded transactions on the testnet reflect the distribution of machine learning models, a critical aspect of our solution. This process is fundamental to the continuous learning and improvement of our chatbot's responses, enhancing its efficacy over time.
Status Change: Internal transactions on the testnet also capture status changes within the system. These transitions signify the dynamic nature of our decentralized infrastructure, showcasing the adaptability and responsiveness of the chatbot to evolving conditions.
Evaluation Reward: One of the key components of our solution is the incentivization mechanism, and the testnet transactions provide evidence of evaluation rewards. This ensures that participants in the network are appropriately recognized and rewarded for their contributions to the overall success of the HarmonyAI project.
By offering this transparent view into our testnet implementation, we aim to provide voters with a concrete demonstration of the real-world applicability of our solution. The testnet operations serve as a testament to the viability and functionality of our decentralized chatbot infrastructure on the Cardano platform.
The current proposal to scale it to a solution involves four main components:
Solution Features and Enhancements:
- Additional enhancements or improvements compared to the testnet implementation.
- Scalability features to accommodate native Plutus implementation.
User Interface and Experience:
- An intuitive design for a seamless user experience.
- Ensuring accessibility for individuals with varying technical backgrounds.
Security Measures:
- Security protocols in place to protect user data and maintain the confidentiality of mental health interactions.
- Any additional security features implemented to safeguard against potential threats.
Community Engagement and Support:
- Plans for community engagement, feedback mechanisms, and support channels.
- A strategy for building and nurturing a community around the solution, encouraging user participation and contribution.
Collaborations Strengthening HarmonyAI:
LoveHope Partnership:
- Objective: Collaborating with Chennai-based mental health startup LoveHope for enhanced mental health support.
- Benefits: Shared vision, expanded reach, and leveraging innovative technology.
- Mutual Support: HarmonyAI supports LoveHope’s mission, and LoveHope provides valuable insights.
Metazord Collaboration:
- Institute Overview: Partnering with Metazord, a blockchain institute in India.
- Shared Interest: Both entities share a common interest in advancing blockchain technology.
- Collaborative Role: Metazord contributes to the technical development of HarmonyAI.
- Educational Initiatives: Joint workshops and training programs planned to educate and share knowledge.
These collaborations contribute to HarmonyAI's success, fostering a positive impact on mental health and the broader blockchain ecosystem.
Overall Impact:
HarmonyAI aims to address the challenges of timely support and limited availability of mental health professionals by leveraging advanced federated learning technologies on the Cardano blockchain. Our solution provides a private and always-available decentralized application (DApp) in the form of a chatbot, offering convenient and confidential mental health support to users.
By utilizing federated learning, HarmonyAI ensures the privacy and security of user data while enabling continuous learning and improvement of the chatbot's responses. This approach allows for personalized and effective support, even in the absence of direct human intervention.
Our project will engage mental health professionals, data scientists, and blockchain experts to develop and deploy the HarmonyAI infrastructure. We will collaborate with mental health organizations and communities to gather valuable insights and ensure the relevance and effectiveness of our solution.
The unique aspect of HarmonyAI is its integration of advanced technologies with the decentralized nature of Cardano. This combination enables scalable and secure mental health support, providing accessibility to individuals worldwide. By leveraging Cardano's ecosystem, we contribute to the growth and adoption of blockchain solutions for real-world applications, emphasizing the importance of privacy, data sovereignty, and innovation in the Cardano community.