Modulus: Zero-Knowledge Machine Learning for Decentralized Protocols
Investing in a new paradigm for building onchain apps
It’s a consensus viewpoint that AI is changing the world.
But arguably the one realm where we haven’t seen major new AI-enabled applications has been blockchains. At least, not yet. That’s because the bar for putting ML models onchain is higher than in traditional software settings—blockchains act as global trust and transparency machines, and the ability to verify the computation influencing user actions is critical to their functioning. To date, this has been difficult to do with AI: most ML models are run in opaque servers, with black box algorithms tweaked by relatively unchecked operators. And in a world where verification presides over trust assumptions, current ML mechanisms don’t meet the cut.
Modulus is bridging this gap. Its focus is on zero-knowledge machine learning (zkML): ML models with provably correct computation, regardless of whether the computation was processed in an open environment or a private, centralized server. The result? AI agents and ML models can now begin to serve as natural extensions of smart contract logic. Specifically, we believe zkML can help unlock more advanced decentralized protocols by minimizing the need for human governance over complex, dynamic functions.
Modulus’ first experiments—an onchain trading bot and a zk-enabled chess engine—are two early examples of this new paradigm. Another use case may involve something like a lending protocol tapping AI to manage loan collateralization ratios (something often coordinated by humans) while leveraging zk proofs to ensure the model is running as specified.
Overall, our expectation is that many more innovative applications will emerge, especially as developers become more acquainted with Modulus’ technology and the feedback loops compound.
That’s why we’re excited to lead Modulus’ seed round. The co-founders are Stanford alums Daniel Shorr and Ryan Cao, and big data engineer Nick Cosby. They’re joined by leading cryptographer Giorgos Zirdelis. The team’s marriage of expertise in AI research, bleeding-edge cryptography, and product engineering makes them uniquely well-suited to tackle this emerging frontier. We expect this team to continue shipping innovative applications, and we couldn’t be more thrilled to back them on their journey.
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