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代理工具

GitHub Copilot Usage API No Longer Guarantees Legacy Agent Field; Dashboards Must Switch to Cloud Agent Metric

The compatibility period for `used_copilot_coding_agent` in GitHub Copilot usage reports expired on August 1. Integrations should migrate to `used_copilot_cloud_agent`. The two fields previously returned the same Boolean value, but the legacy field is no longer guaranteed after the deadline, potentially causing enterprise adoption reports to silently undercount usage.

GitHub Repo

Open Secure AI Alliance Launches, with NVIDIA Advancing Agent Testing, Tracing, and Auditing Tools Through NOOA

NVIDIA, the Linux Foundation, Hugging Face, Microsoft, and other organizations have formed the Open Secure AI Alliance to address vulnerabilities in agents and AI software with open models and tools. Its first concrete contributions include NVIDIA’s NOOA framework, but the alliance has yet to announce common specifications, governance processes, or a delivery timeline.

推論系統

Fast Gemma Verified Build Breaks 510 Tokens per Second on a Single A10G by Combining Sliding-Window Attention and MTP

VIDRAFT has published the highest- performing verified configuration from the Fast Gemma Challenge, pushing Gemma 4 E4B to 510.58 tokens/s on a single NVIDIA A10G while holding perplexity at 2.3930. The result comes from stacking multiple inference optimizations, but the test uses a single stream, fixed hardware, and a private prompt set, so it should not be equated directly with production throughput.

硬體

NERC’s Computational Load Level 3 Reporting Deadline Arrives, Requiring AI Data Centers to Be Included in Dynamic Models and Disturbance Recording

The North American Electric Reliability Corporation requires transmission planning and system operations entities to report by August 3 on seven computational load measures covering models, stability studies, commissioning, and dynamic disturbance recording. This is not a generic energy-policy declaration; it requires the second-scale load shedding and power oscillations of AI data centers to become part of power-grid engineering models.

AI 基礎設施

Etched Unveils Rack-Scale Inference Architecture, Challenging GPUs with Low-Voltage Compute and Cluster-Shared Memory

Etched’s first N4P inference chips have entered rack-level validation. The system uses low-voltage compute arrays and cluster-scale memory to address throughput and latency bottlenecks, respectively. The company claims sparse MoE workloads can sustain more than 80% of peak FLOPs, but has yet to publish reproducible model, power, or end-to-end performance data.