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2/Proof Aggregation in Multi-GPU setupProof Aggregation in MPI Environment: Began integrating proof aggregation functionality under a multi-GPU MPI environment. This aggregation not only coordinates distributed provers and combines partial results seamlessly, but also reduces the overall proof size, improving efficiency in both storage and verification.Stay tuned for more updates 🔥 ...

1/Multi-GPU AccelerationPolynomial Evaluation with NCCL: Completed multi-GPU acceleration for polynomial evaluation using NCCL. The implementation enables efficient parallel computation across multiple GPUs, significantly improving throughput and scaling performance for large proof workloads. ...

This week we delivered key improvements across ZKML and Expander. Here’s a breakdown of what was shipped. https://t.co/i6YGwdpNqH ...

5/Officially deprecated the GKR Square component. Removed redundant parts in the scratchpad that were tied to it, simplifying the codebase and reducing overall computational overhead.Stay tuned for more updates 🔥 ...

4/Introduced support for hints in the computation graph definition. This improvement reduces the number of witnesses required, streamlining execution and improving performance. ...

This week, the team delivered major updates in ZKML and Expander. Here’s an overview of the progress. https://t.co/qy21D9qzEl ...

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Google set the standard. Polyhedra zkML accelerates it.Together, this means faster adoption across fintech, consumer AI, and enterprises.The agent economy is coming — we’re here to make it verifiable. ...

Think of it as the missing trust primitive for AP2.Agents can pay, move money, and unlock services — all while proving compliance instantly. ...