Quick Look at Modulus Building on-chain Artificial Intelligence using ZKML.

Exploring Modulus Building's Revolutionary On-chain AI with ZKML A Brief Overview

Original Title: Introducing Modulus: Bring AI On-Chain

Author: Modulus Labs

Translation: Heilsman, ChainCatcher

Last night, Modulus Labs announced the completion of a $6.3 million seed round of financing, led by Variant and 1kx, with participation from Inflection, Bankless, Stanford, and others. Angel investors include the Ethereum Foundation, Worldcoin, Polygon, Celestia, and Solana.

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Modulus Labs uses ZKML combined with AI models’ ZK proofs to build a dapp that provides zero-knowledge proofs to verify the correct execution of AI models. The aim is to ensure that AI queries are not tampered with, paving the way for integrating AI into Web3 applications. It attempts to bridge the gap between the opacity of machine language models running on servers and the transparency of blockchain.

This article is a “self-introduction” released by Modulus Labs. To facilitate readers’ quick understanding, ChainCatcher has made appropriate edits and deletions to the original text:

We are helping dApp developers securely access tamper-resistant AI using the world’s only dedicated ZK prover for AI. This means smart contracts can now enjoy powerful AI capabilities without breaking the trustless ethos.

Stay tuned for the next few months as we:

• Achieve the largest-ever AI application on Ethereum through collaborations with Upshot, Worldcoin, Ion Protocol, and others;
• Open-source our prover “Remainder” – the world’s only specialized ZK prover built for AI;
• Launch the Modulus API, enabling every dApp to access powerful and expressive AI through ZK proofs;
• In fact, today we opened the waiting list for the “On-Chain AI” API.

TL;DR

• Problem: Currently, to enable dApps with powerful AI capabilities, they need to sacrifice decentralization security and take on centralized risks;
• Solution: Modulus uses zero-knowledge proofs to effectively verify AI providers are not manipulating their algorithms on-chain;
• Insight: Specialized ZK proofs built for AI offer extremely powerful AI functionality at a low cost for dApps;
• Result: Tamper-resistant AI-enhanced dApps surpass their peers in user experience while still adhering to the trustless ethos of the chain;
• Vision: As advanced AI is introduced into our legal, financial, medical, security, and education sectors, cryptographic accountability will uphold the pillar of our computing future.

AI Forcing People into “Faustian Bargains”

Artificial intelligence will fundamentally change our society. However, this “superpower” is almost useless for anyone building with blockchain technology. The reason is simple: the computational cost of AI operations is too high to run directly on the chain. This means that in order to integrate AI functionality into smart contracts, you have to trust that the AI can always run its model without manipulation.

But in a trustless encrypted environment, this is difficult to achieve. As Ronald Reagan once said, “Trust, but verify.”

ZK is the ultimategame changerforAI

To bring the magic of AI into blockchain without sacrificing decentralized security, we can rely on the verifiability of ZK.

When applied to AI, zero-knowledge cryptography allows us to verify if AI models are “correctly” executing without revealing the secrets behind the model. In other words, we use mathematics to check if AI results are manipulated in secret. By validating this “proof of correctness” on the chain, we can achieve security comparable to that of the blockchain at a fraction of the cost.

Thanks to mathematics, we can now know with cryptographic certainty that your AI co-pilot doesn’t have hidden code for tampering, your credit score isn’t biased by a prejudiced bank, and your social media information isn’t influenced by political bias. We call this “Accountable AI”.

But cutting-edge ZK cryptography isn’t free. In fact, despite saving funds through blockchain protocols, regular ZK proofs still add over 1000 times the cost to AI computations. In fact, during the past year of building the world’s first ZKML application, we’ve continuously encountered the same cost-performance ceiling. There’s no way to solve this problem: ZK + ML == Economic Violence.

That is, until we noticed that modern AI relies heavily on highly parallel processors, i.e., GPUs. If we make the same change in ZK proofs, we’ll greatly open up the design space of smart contracts.

With the support of “Remainder,” we’ve started building a community of developers and partners for the next generation AI-enhanced dApps. And we’re committed to bringing powerful AI functionality to specific use cases at scale.

To achieve this vision, we will be launching multiple ZKML applications in the coming months. For example, our first collaboration will be with NFT valuation leader, Upshot.

Upshot uses AI to provide extremely accurate and timely NFT prices (over 100 million evaluations per hour, with an average Mean Absolute Percentage Error (MAPE) of 3-10%). This opens up new financial markets for long-tail assets. However, using and subscribing to Upshot currently also means trusting that Upshot will never tamper with the prices.

Our ultimate goal is to deliver Upshot’s AI pricing on-chain without compromising blockchain security. This is achieved through integrating their machine learning oracle into the Modulus API. The result is a combination of AI superpowers and blockchain security, enabled by Modulus’ professional Zero-Knowledge proofs.

The Modulus Team

According to The Block, Modulus was born out of Stanford University. Co-founders Daniel Shorr and many other young people in their 20s during the pandemic couldn’t resist the allure of crypto, which led to the creation of Modulus.

According to the RootData Page, Daniel Shorr, co-founder and CEO of Modulus Labs, holds bachelor’s and master’s degrees from Stanford University; Nicholas Cosby is a co-founder of Modulus Labs and had previously studied programming at Coding Dojo; Ryan Cao is the CFO/CTO of Modulus Labs with a bachelor’s and master’s degree from Stanford University.

Daniel Shorr wrote: When Ryan, Nick, and I started Modulus over a year ago, we had a brilliant plan – to build something extremely difficult, with a level of strategic complexity that is truly mind-blowing! But our madness has a method. If we engage in things that people think are nearly impossible but approach them with absolute sincerity and seriousness – we will attract the most talented and friendly people in the world to work with us.

We will continue to update Blocking; if you have any questions or suggestions, please contact us!