NVIDIA adds GPU resource controls and new local AI model support to RTX Spark laptops, expanding background agent management and on-device AI workflows.
Category: AI and Hardware
NPU stuck at 0%? Most AI apps, including Ollama and LM Studio, skip the NPU. Here’s what actually uses it and how to check yours.
Is 16GB RAM enough for machine learning in 2026? Yes for learning and classical ML, tight for big data, deep learning, and local LLMs.
AI image generation is slow on laptops from low VRAM, CPU fallback, laptop GPU limits, heat, and settings. Here’s how to find the cause and fix it.
More RAM only speeds up local AI if your model was spilling. Learn why bandwidth, dual-channel, and the GPU decide speed, and how to check.
AMD’s Ryzen AI Halo offers up to 192GB unified memory for large local AI models. See what the developer desktop means for AI laptop buyers.
Local AI slows down over time from growing context, memory spill, heat, and power limits. Here’s how to find which one and fix it.
AI tasks keep your CPU and GPU under sustained load, unlike normal use. Here’s why that heats up your laptop and whether it’s actually harmful.
Learn how NVIDIA PAIR routes local AI requests across compatible PCs and Macs, its hardware requirements, limitations, and setup process.