Polyhedra collaborates with Berkeley RDI to launch the first verifiable zero-knowledge proof system for large language models (LLM). Just as HTTPS established security for internet communication, this system builds a verification infrastructure for the AI field. The system can efficiently verify AI performance and compliance without disclosing the model or data, achieving speeds 20,000 times faster than previous methods. It is now possible to quickly verify large language models including Llama 3-8B. Key highlights include: - Polyhedra's innovative technology: Zero-Knowledge Machine Learning (zkML) technology is akin to the HTTPS protocol on the internet, allowing the verification of AI system performance and compliance without leaking model or data details, thus protecting privacy. - Exceptional performance: Expander significantly enhances verification efficiency, with single-thread verification speeds 20,000 times faster than existing methods, supporting VGG-16 at 2.2 seconds per image and Llama-3 at 150 seconds per token. - Developer-friendly: The zkPyTorch compiler seamlessly integrates with PyTorch, providing developers with simple and easy-to-use tools. Application scenarios: - AI service quality assurance - AI training data compliance - Fair data automated trading market - AI Agent responsibility allocation - AI Agent compliance - Financial services compliance verification This system not only addresses compliance challenges in AI model verification but also offers a new solution for AI security and trustworthiness.

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