Enabling AI Models for Use in Smart Contracts: Partnering with Giza

Einar Braathen

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Published in

The CoinFund Blog

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5 min read

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14 hours ago

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We are excited to announce that CoinFund has led a $3 million dollar round in Giza, a company working toward enabling AI models for blockchain smart contracts.

Large tech companies have historically dominated the production of cutting edge machine learning models due to the significant resources required. These resources include vast amounts of data for training, high-performance computing infrastructure, and specialized expertise in machine learning. This concentration of resources and expertise has led to an environment where only a few entities have the capacity to develop and maintain such complex AI systems.

However, over the last 18 months there has emerged a counter-trend with tremendous progress being made by open source communities within AI innovation. We have seen the democratization of model design by HuggingFace, decentralized computation networks for training like GenSyn, open GPU availability via decentralized computation networks like Akash, and step-function improvements such as LoRA from Microsoft, which now allows fine-tuning at a fraction of the cost and time.

Even so, an increasing number of enterprises, governments, and individuals are restricting their usage of proprietary AI models due to privacy and safety concerns. Simultaneously, neural networks are becoming increasingly important and being tested in healthcare, law, art, asset management, security, and nearly every other field of human industry. How can we trust closed companies with our data? In a world saturated with models, can we trust that a proprietary model is actually running the correct computation that we requested? In other words, how do we get verifiable onchain inference? The stakes are high.

As AI has moved at blistering pace this year, the web3 community has been exploring how to make AI models accessible to trustless smart contracts. AI is one of the most important technologies of our generation, and it is paramount to work towards an open and democratized AI ecosystem, through decentralization and transparency. It’s likely that the push for open source innovation in AI will move the space toward open web3 infrastructure over time. One of the key primitives of this trend is making AI model inference available onchain, as this will dramatically expand the design space of smart contracts, enabling use cases like asset management, fraud protection, dynamic pricing, and more.

Giza’s network uses zero-knowledge proofs to verify that AI model inference has been run correctly offchain, making the verified output available for use in a smart contract. Their technology transpiles the common ONNX format, an open source format for storing machine learning models, allowing model outputs to be computed and referenced onchain. Smart contracts can now interact with AI models directly and use them as triggers for actions and verification. For example, imagine a crypto wallet which can now use facial recognition as a security factor. The Giza team recently announced their first product, Orion, a transparent, verifiable, and wholly open-source inference framework, readily accessible for community contribution and use.

One of the inherent challenges of building at the intersection of web3 and AI is that teams need a deep understanding of both AI models and web3 primitives. Fran Algaba, Giza’s CEO, has led MLOps teams at some of the world’s largest companies since 2017. While tinkering with onchain inference, he met Cem Dagdelen and Renç Korzay through the Madrid web3 community. Cem and Renç have been web3 builders since 2018 and shared the same vision for the future of Web3 AI, having experimented with web3 primitives at Curve Labs. Combining cryptonative backgrounds with production machine learning expertise, the trio joined forces in late 2022 and are now actively expanding the team.

We are incredibly grateful and excited to partner with Giza to lead their pre-seed round and help build the Open Economy for AI. For further context on our view of the intersection of AI and web3, please see our post from September 2022.

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