One popular way to run AI locally has been to use multiple GPUs to access more memory and compute. While cloud frameworks like vLLM are well optimized for multiple GPUs thanks to their use in data centers, PC frameworks like llama.cpp and the ComfyUI implementation in PyTorch are not optimized for it. To solve this challenge, NVIDIA has collaborated with both llama.cpp and ComfyUI to enhance performance for RTX PCs with two equivalent GPUs. This enables you to run larger models and use the compute of both GPUs for better performance. llama.cpp now supports tensor parallelism (TP), fully utiliz
Build Personal AI Agents on Windows PCs with New Tools from Microsoft and NVIDIA | NVIDIA Technical Blog… With secure agent sandboxing, faster inference, multi-GPU scaling, and a maturing Windows AI platform, developers building on the over 100 million NVIDIA RTX PCs worldwide have the infrastructure to ship the next generation of AI applications. Learn more and start developing for NVIDIA RTX AI PCs . …
… This research uses the demo Blood Will Out , which features NVIDIA TTS and facial animation models with Meaning Machine Authored AI systems, to explore how narrative AI shapes player behavior. To learn more, check out the GDC session, What Good Are AI NPCs? …
… Policy updates happen live at sandbox scope as developer approvals are granted, with a full audit trail of every allow and deny decision. The policy engine enforces constraints on the agent’s environment across the filesystem, network, and process layers. …
… If profiling from the CLI, pick your platform based on where the CLI will be run. If using the GUI Full Version to view reports, do profiling, or do remote profiling, pick your platform based on the host PC architecture where the GUI will be run. …
… It expresses all roles in a single PodCliqueSet: apiVersion: grove.io/v1alpha1 kind: PodCliqueSet metadata: name: inference-disaggregated spec: replicas: 1 template: cliqueStartupType: CliqueStartupTypeExplicit terminationDelay: 30s cliques: - name: router spec: roleName: router replicas: 2 podSpec… …