The post Polyhedra and Berkeley RDI Launch Production-Ready zkML, Revolutionizing AI Trust appeared on BitcoinEthereumNews.com.

Berkeley RDI and Polyhedra have made a strategic collaboration to unveil a groundbreaking Production-Ready zkML. This production aims to mark a transformative leap in the fusion of AI and cryptographic verification. The organizations are now delivering a real-world application, four years after pioneering the concept. The application aims to empower AI developers to utilize zkML without requiring specific expertise in zero-knowledge proofs. The journey began in 2020 when Polyhedra’s research team, including Jiaheng Zhang, Dawn Song, and Yupeng Zhang published a paper in collaboration with Berkeley RDI. The paper was titled “Zero Knowledge Proofs for Decision Tree Predictions and Accuracy”, introducing a zkML, zero-knowledge machine learning. The concept of the paper aimed at building trust in AI by ensuring verifiable results while maintaining the privacy of underlying data and models. Polyhedra prioritizes trustless systems to minimize human error in technology incidents. The zkML model, at its core, allows the developers to prove the accuracy of AI model predictions on a specific data sample without exposing any sensitive information. zkML Polyhedra: Advancing Trust and Transparency in AI Through zero-knowledge proofs, a service provider can demonstrate that a specific output was genuinely produced by running a given model on an input. The zkML technology provides an effective solution to one of AI’s most pressing challenges, which are trust and transparency. The zkML model, by enabling verifiable computations, ensures that the results generated by AI models are accurate and trustworthy. This approach addresses concerns about the opaque nature of AI, where unverified outputs can lead to flawed decisions.  The CTO of the organization, Tiancheng Xie shared that: “We have spent the entire life of the company building systems that can operate without human intervention, that are verified by math, and are cryptographically secure.” Applications of zkML extend beyond inference verification, encompassing areas such…

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Filed under: News - @ November 19, 2024 11:17 pm