Independent Research in AI Safety & Decentralized Systems
Economic protocol for post-scarcity civilization. Non-static, dynamic reputation-based system that measures, decays, and circulates contributions.
A distributed systems perspective on neural network compression. Achieves 8-12x compression through layer consensus mechanisms with Byzantine fault tolerance.
Mathematical foundations for decentralized market infrastructure. Formal proofs and advanced cryptographic constructions.
From Financial Markets to Distributed Intelligence: An 8-year research journey exploring consensus as a fundamental primitive across domains.
Theoretical foundations and practical applications of advanced prompt engineering methodologies in artificial intelligence systems.
AI safety framework for financial systems. Decomposes complex behaviors into verifiable primitive operations for guaranteed safety.
Advanced techniques for error bounds and mitigation strategies in zero-knowledge systems. Critical for scalable privacy.