At the recent NEARCON 2023 event, Ilya Polosukhin presented a model for developing the NEAR ecosystem with AI, which includes the following items:
AI Governance: Agent Roles
- AI Agent: Community Manager
Inputs: Has all context of the ecosystem
Functions: Greet new members, respond to frequent question
- AI Agent: Developer Relations
Inputs: Dev documentation and previous questions
Functions: Respond to frequent questions and given examples of how to use various APIs
- AI Agent: Data Analyst
Inputs: Query on-chain data with indexed database
Functions: Answer question about ecosystem state, data, and more
- AI Agent: Legal Assistant
Inputs: Legal documents and current regulations
Functions: Provide first contract drafts and help review contracts
We can already see how AI simplifies a lot of operational processes, and if we directly integrate it into the NEAR ecosystem, it will unlock the technical potential of the NEAR Protocol at full capacity.
So we have an initiative to create AI Community Manager, AI Developer Relations and AI Adviser for Proposals, each of which can enhance the current activities of the community, developers and DAO Council in NEAR (Next, we describe in detail exactly how AI improves the ecosystem)
Functionality of our AI products:
- AI Community Manager will be engaged in:
- Greeting and introducing new members to all activities in the community, all tasks will be tracked automatically and adjusted from within the community.
- General and narrow-profile answers to participants’ questions about the ecosystem. AI Community Manager will automatically adjust to updates of existing applications on the network to always give a clear and correct answer.
- Creation of quests/tasks /quizzes for the community and a full analysis of the conducted activity for the chat moderators.
- AI Developer Relations will be engaged in:
- Assistance in the formation of technical specifications based on the subtleties of dApps development in the NEAR network.
- Support in writing elements for applications on the NEAR network using all available tools.
- A handy knowledge base of the tools available in the NEAR network to familiarize developers with all the nuances of writing an application.
- Advices for servicing existing projects.
- A superficial primary audit of an application.
- AI Adviser for Proposals:
- For the project: Assistance in writing the structure of the proposal, which will initially be sharpened for NDC metrics.
- For the project: Assist in the drafting of the proposal, taking into account advice from Councils and NDC metrics.
- For Councils: Analyze the proposal against the NDC metrics and calculate the approximate impact the proposal may have on the ecosystem.
- For Councils: Help assess the submitted reports to ensure they align with the NDC V1 indicators outlined in the proposal.
Implementation of AI Agents:
AI Community Manager: Telegram chat-bot; Near.Social;
AI Developer Relations: Near.Social;
AI Adviser for Proposals: NEAR Forum; Near.Social;
Duration: 3 months starting November.
November: AI Community Manager
December: AI Developer Relations
January: AI Adviser for Proposals
Designer: To create the visual elements of the AI widget and ensure a user-friendly interface that aligns with the NEAR aesthetic.
Tester: To rigorously test the AI widget and agents across multiple scenarios to ensure reliability and effectiveness.
AI Developer: To develop the AI algorithms, train the models, and integrate the widget into the BOS platform by NEAR.
Development team: top-notch professionals with experience in: AI generation, dataset creation and neural network training, ability to work with WEB tools to implement UI/UX, knowledge of NEAR frameworks to implement AI Agents on BOS and Near.Social.
The development team has some experience in building and training neural networks, creating datasets and parsing data, for further development and integration of AI in the form of chatbots and widgets. We are working on optimizing and improving current AI solutions such as Quex AI AGENT to implement our own solution with all the above stated features.
We are committed to developing solutions that not only improve the performance of existing systems, but also provide scalability to handle future growth and development.
QA, Debugger and Operation Team:
- Integration testing: Testing the interaction between different modules and systems to identify errors in their interrelationships.
- User interface (UI) testing: Checking the usability and intuitiveness of the applications user interface.
- Stress testing: Evaluating the performance of the application under high loads and large number of transactions.
- Update and migration testing: Checking the data update and migration processes to ensure that they are smooth and error-free. Acceptance testing: Fina
This proposal aligns with current NEAR community visions, focusing on the intersection of technology and user engagement, as well as with NDC V1 principles, by promoting the goal of bringing innovative solutions to the NEAR/AURORA ecosystems, attracting users and developers.
Requested Funds Allocation:
Development (AI Developer): $3,000
Design and User Experience (Designer): $500
Testing and Quality Assurance (Tester): $1,000
Project Management and Oversight: $500
TOTAL: $5.000 per month