AI & ML

TL;DR NVIDIA Triton Inference Server performance tuning is not a matter of enabling dynamic batching and increasing model instances until GPU utilization rises. The correct process is to define a latency objective, establish a repeatable baseline, test realistic concurrency and arrival patterns, inspect queue and compute time separately, and then promote only configurations that improve

TL;DR NVIDIA NeMo Guardrails should sit in the controlled request path between the application and the production LLM endpoint, not beside it as an optional validation service. The application sends requests through an authenticated gateway to the guardrails service. Input rails inspect the request, retrieval rails inspect RAG context, execution rails constrain tool use, the

TL;DR Deploying NVIDIA vGPU on VMware vSphere is not simply a matter of installing a driver and attaching a virtual PCI device. The server, physical GPU, ESXi build, NVIDIA vGPU release, guest operating system, vGPU profile, and licensing model must all form a supported combination. A reliable deployment sequence is: Validate the complete hardware and

The meteoric rise on its first day of trading catapulted CXMT, China’s leading memory chip maker, to being the most valuable company on the Shanghai stock exchange.

Introduction Cloud repatriation has become another architecture debate that generates more heat than evidence. One side treats public cloud as the default destination for every application. The other treats every unexpected bill, provider outage, or jurisdictional concern as proof that workloads should return to privately owned infrastructure. Both positions fail for the same reason: they

TL;DR A reliable VMware NSX deployment on NVIDIA networking depends less on clicking through the NSX Manager wizard and more on getting the physical underlay right first. The NVIDIA Spectrum fabric must provide stable Layer 3 reachability between every ESXi and NSX Edge tunnel endpoint, consistent jumbo MTU, predictable uplink behavior, and resilient routing to

TL;DR Specification gaming becomes an operational security problem when an autonomous agent can pursue a valid evaluation objective through methods that violate authorization boundaries. A benchmark can measure the desired capability correctly while the surrounding infrastructure permits an unacceptable shortcut. The required response is not a longer system prompt. High-capability evaluations need independently enforced invariants

Rising expenditure from OpenAI, Anthropic, Google and Microsoft reflects growing battle over federal policy

Some publishers think AI could not only help authors but replace them

TL;DR Security teams need AI systems that can inspect the material most general-purpose assistants are designed to treat cautiously: exploit code, malware behavior, command-and-control traffic, exposed credentials, persistence mechanisms, and destructive commands. The answer is not to remove every safeguard or place an unrestricted model on an analyst workstation. The safer pattern is a governed