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Nil Foundation Teams Up with Taceo to Verify Machine Learning Models on Ethereum.

The Nil Foundation and Taceo are forging a path to validate machine learning models on Ethereum’s Layer 1 using zkLLVM and zero-knowledge proofs, enabling trusted ML operations within smart contracts.

Validating Machine Learning Models on Ethereum: The Partnership of Nil Foundation and Taceo

In an innovative alliance, the Nil Foundation is joining forces with research heavyweight Taceo. Their goal? To devise a software pipeline focused on the validation of machine learning (ML) models on Ethereum's Layer 1 mainnet, employing zero-knowledge methods.

Machine learning, an offshoot of artificial intelligence, empowers computers to enhance task accomplishments through learning, predominantly by dissecting data to discern patterns. By aiming to make ML models verifiable on the Ethereum blockchain, this collaboration sets the stage for ML executions within smart contracts, sidelining the requirement for external trust.

At the heart of this collaborative pursuit lies the Nil Foundation's groundbreaking tool - zkLLVM. Launched in February, this compiler facilitates the validation of data in software ecosystems without the bedrock of trust, courtesy of ZK proofs. A unique feature? It can validate ML computations across a spectrum of mainstream development tongues, such as C++, Rust, and JavaScript/TypeScript. This becomes indispensable, especially in the cryptographic and blockchain arenas where confirming computations sans data disclosure is paramount.

By incorporating zero-knowledge proofs, there’s potential to authenticate ML operations and correlate training datasets. This paves the way for the fusion of provable ML within decentralized applications, with implications stretching over varied sectors like DeFi, privacy, and even nascent domains like healthcare.

Both entities are neck-deep in the developmental phase of the pipeline, with an anticipated release of zkLLVM’s preliminary results concerning ML models slated for Q4 2023.

Elaborating on the significance of this initiative, Taceo commented, "The convergence of machine learning into decentralized apps necessitates the provability and security of ML models, more so when they interact with smart contracts on platforms like Ethereum."

Starting 2023 on a high, the Nil Foundation successfully secured a whopping $22 million in funding, championed by Polychain Capital.

As the boundaries of blockchain and artificial intelligence continue to blur, collaborations like that between the Nil Foundation and Taceo exemplify the endless possibilities lying ahead. With tools like zkLLVM, the fusion of machine learning and Ethereum appears not just viable, but poised to redefine decentralized applications' landscapes.