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🤯 On August 18, Lagrange announced the results of the launch of DeepProve-1, the first zkMl system that demonstrates complete LLM inference.
DeepProve-1 is the first zkML (zero-knowledge machine learning) system developed by Lagrange Labs that allows generating cryptographic proofs of complete inferences from large language models (LLMs) like GPT-2.
DeepProve-1.
Features and achievements:
First complete LLM inference proof, DeepProve-1 managed to generate a zero-knowledge proof for the complete inference of GPT-2, a large language model from OpenAI.
Verifiability in AI, introduces verifiability as a core feature in modern AI systems, extending this to full transformer architectures.
Support for complex structures, handles computation graphs with residual connections, parallel branches, and variable length inputs, typical in LLMs.
Applications and relevance:
security and privacy: Allows verifying the results of an LLM without revealing input data or model details, crucial for applications in defense, healthcare, finance, and infrastructure.
Auditability, facilitates the auditing of decisions made by LLMs without compromising data privacy or the intellectual property of the model.
Developments and future plans
Performance optimization: Lagrange Labs is working on improving cryptographic efficiency and parallelism to make DeepProve-1 more practical in production environments.
Extension to other LLMs, the next goal is to support models like Meta's LLAMA, one of the most adopted open-source LLMs.
DeepProve-1 is a significant advancement in verifiable AI, enabling cryptographic proofs of LLM inferences.
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