Hackathon Ideas
Apply to the hackathon here.
OCY TRACK
Autonomous Research Agent
Description: Develop AI agents that autonomously retrieve, analyze, and summarize academic research or news articles on specific topics using OCY's RAG capabilities. Additional points, if your Agent understands what data it already has, doesn’t double store, categorises information found from a research point of view and does cycles of goal re-evaluation based on the knowledge found.
Evolving-RAG Agent
Description: Create and Agent that interact with users to requesting additional material. Then it adjusts its own knowledge through this material. Interesting possibilities can come from the side of directly allowing new information to twist the personality of the agent.
- Data-Driven Tokenization Agents
Description: Create agents that analyze user data, assess its value (e.g., insights from usage patterns or preferences), and automatically tokenize the data into tradable assets on Arbitrum or Base. Use Case: Enable users to monetize their data while maintaining ownership, creating a decentralized data marketplace.
- Intelligent Data-Coop Coordinators - Data DAOs
Description: Create agents that manage decentralized data cooperatives, where contributors pool their data and earn collective rewards through smart contract-governed profit-sharing. Use Case: Empower communities to monetize shared data for social or economic benefits.
ADCS Track
Side-note: Creative Data/AI Providers and unique Adapter creators will be rewarded separately.
Isolated agentic economies where each user controls their own Agent There is an extremely interesting use-case for agentic pvp, this could be in any vertical, but we will provide a few examples.
Isolated trading - There is a token, but only agents are allowed to trade it, say to participate each user needs to launch their own agent and add specification to how it acts. Then at certain event intervals agents access the oracle to make ai-driven decisions on how to act.
Isolated gamefi - Real users only setup the initial parameters of agents, then let them pvp with each other again requesting adcs for decision making.
- Dynamic Subscription-Based AI Services
Description: Agents provide real-time AI services (e.g., analytics, recommendations) on a subscription basis, with payments handled automatically via recurring Arbitrum/Base smart contracts. Use Case: Enterprises or individuals pay only for the AI insights they use, reducing upfront costs.
- Privacy-Preserving Data Sharing Agents
Description: Agents that mediate data sharing by encrypting and tokenizing user data, enabling secure and private transactions via Abritrum/Base smart contracts. Use Case: Protect user privacy while allowing controlled data sharing for AI applications.
Alternatively, you can create a tornado.cash type product by creating a mother agent SC and having users deploy their own pre-built SC as agents to where end state offload is managed by the mother agent and all TXs are handled by agents off-chain.
- Autonomous AI Research Bounty System
Description: Smart contract-powered bounties incentivize AI agents to retrieve and process data for specific research tasks. Rewards are issued when the task is verified as complete and valuable. Use Case: Universities, startups, or think tanks seeking decentralized AI research capabilities.
AI Agents / ai16z SUB-TRACK
Any Agents using ADCS or OCY.
ai16z Eliza sub-tracks - We are specifically interested in Agents:
Utilizing more mediums, from full access to devices to Virtual Machines / to WebOS
Having larger degrees of freedom, think outside of the box
With long-term reasoning/planning/action
That leverages SWARMS, such as this
Most importantly, make something interesting and exciting.
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