How SWE-Serve Exposes the Gap Between Local Tests and Live Serving
1mês
- Publicado
- Coletado
An AI coding agent’s patch can pass tests yet fail when the server loads a real model and handles requests. Evaluating changes to inference-serving software...
O overfeed.news indexa e aponta. Publicamos um trecho curto — o artigo completo fica em NVIDIA Technical Blog.
Mais de NVIDIA Technical Blog
Entre para seguir esta fonte
Validating GPU Platforms with Runtime AI Inventory via the NVIDIA DSX AI Factory
As teams deploy and scale AI workloads using NVIDIA Dynamo, Kubeflow, or Slurm, tracking what actually runs requires visibility beyond the platform...
Running AV Reasoning Models Within Onboard Compute and Latency Limits
Autonomous vehicle (AV) developers need reasoning models that can operate within the compute and latency constraints of an onboard system. Larger models provide...
Manage Kubernetes Clusters for GPU Infrastructure with NVIDIA Kubernetes Engine
NVIDIA is announcing two open source projects for building and operating managed Kubernetes services on GPU infrastructure—NVIDIA Kubernetes Engine (NVKE) and...
Start and Restore GPU Workloads in Seconds with NVIDIA Snapshot
NVIDIA Snapshot, a new open-source component of the NVIDIA DSX AI Factory Platform, makes initialized GPU workloads reusable across inference...