Posts tagged "machine-learning"
5 posts tagged with machine-learning.
What Is Unified Memory? How It Differs From VRAM, and How Much You Need
Unified memory is one pool of RAM shared by the CPU and GPU. How it compares with VRAM, why it lets laptops run big AI models, and how much you need.
Can You Run Muse Spark Open Locally? Memory at Every Quantization
Muse Spark Open has 816 billion parameters and needs about 260 to 300 GB even at 2-bit. Memory for every quantization, and which machines can run it.
What Is Mixture of Experts? Why MoE Models Are Fast but Huge
A mixture-of-experts model uses only a few of its expert networks per token. How routing works, total vs active parameters, and why MoE still needs memory for every expert.
How AI Image Upscaling Beats Bicubic Interpolation
Old image upscaling guesses pixels with smooth math. AI upscalers like ESRGAN and Real-ESRGAN hallucinate plausible detail learned from millions of images. Here's the difference and where each fails.
How AI Background Removal Actually Works
From U-Net segmentation to modern transformer-based matting, we walk through how a single neural net can isolate a foreground subject in a photo, and why edges and hair are still the hard parts.