🤖DeAI Co-Research Day @ DevCon : Attribution Is What We Need w/Story, Gensyn, Eigenlayer, Sentient
Dear decentralized AI researchers,
Join us for an exclusive, shilling-resistant, tech-focused co-research that dives deep into the cutting-edge of DeAI attribution mechanisms.
🛠️ Expected Technical Contributions Reference
Jialin Li, co-founder of Hetu Protocol, Sung Kah Kay Assistant Professor @ NUS | Research lead @ Advaita Labs - Real-time Attribution Tracking in DeAI Field
Allen Chuang @ Story - Data integrity & Trust in AI
Wes Floyd, core member of DevRel @ Eigenlayer | proven track of ML/AI
Ben Fiedling, co-founder @ Gensyn - Attribution Verification of Computing Power Supply
Vitaly Kleban, researcher @ Cyber Fund
Mitrasish Mukherjee, Cofounder & CTO @ Spheron
Eric Cai, CEO @ Entrova , ex Head of Big Data @Binance
Yi, co-founder & CEO @ Codatta - Attribution and valuation in high-quality data flow
Ram, core contributor @ OpenLedger - Role of Verifiable Data in Decentralized AI
Chi Zhang Cofounder & CEO at ZettaBlock | ex-Databricks, AI PhD@Berkeley -Smart indexing , portable AI memory.
Hang Yin, co-founder & CTO @ Phala Network - Temper-proof Attribution Guaranteed by TEEs
And more on the road
⏰ Co-Research Structure
2:00 PM - 2:15 PM: 🎉 Opening & Group Formation
DeAI landscape open questions listed
Group assignments
Discussion guidelines
2:15 PM - 2:30 PM : Keynote : Attribution Is What We Need - Jialin Li, co-founder of Hetu Protocol, Assistant Professor @ NUS | Research lead @ Advaita Labs
2:30 PM - 3:45 PM: 💡 EXCLUSIVE Parallel Group Discussions
3:45 PM - 4:30 PM: 📢 Group Sharing
10 minutes per group to present key insights
Visual documentation of core findings
4:30 PM - 5:00 PM: ❓ Open Q&A & Wrapping Up
Cross-group technical discussion
Common challenges identification
Potential collaboration exploration
🎯 Expected Outcomes
🔄 Enhanced exchange between different technical approaches
🤝 Exploration of potential technical collaborations
📝 Generation of high-quality technical discussion documentation
🎯 Groups & Topics
Group A: Technical Verification Mechanisms
Core Discussion Topics:
Comparative analysis of verification approaches (opML, zkML, TEE-based solutions)
Implementation challenges in on-chain AI computation verification
Performance optimization in verification systems
Real-time verification and monitoring methods
Trade-offs between security and computational efficiency
Group B: Resource Attribution & Incentive Design
Core Discussion Topics:
Resource contribution measurement and verification
Quality assessment frameworks for decentralized resources
Dynamic incentive mechanisms design
Fraud prevention in resource attribution
Sustainable tokenomics for resource providers
Group C: Cross-chain Attribution Challenges
Core Discussion Topics:
Standardization of cross-chain attribution protocols
Privacy preservation in cross-chain scenarios
Cross-chain identity and rights management
Interoperability of attribution systems
Consistency maintenance across chains
Group D: Model Ownership & Collaborative Training
Core Discussion Topics:
Attribution frameworks in federated learning
Rights management for derivative models
Open-source contribution tracking mechanisms
Collaborative training governance
IP rights in decentralized AI development