Microscaling (MX) data formats are designed to reduce computational and storage costs in deep learning applications by combining a per-block scaling factor with narrow floating-point and integer types for individual elements. This approach balances hardware efficiency, model accuracy, and user convenience. Empirical results from popular benchmarks demonstrate the practicality of MX data formats as a drop-in replacement for standard FP32 in AI inference and training, with minimal user friction. Notably, MX formats have enabled the training of generative language models with sub-8-bit weights, activations, and gradients, incurring only minor accuracy losses without requiring modifications to the training process.
“Chat with RTX” is an application that allows customization of a GPT large language model (LLM) with your specific content like documents and notes. This enables you to generate contextually relevant answers from a bespoke chatbot. The entire setup operates locally on RTX-enabled Windows PCs or workstations, ensuring quick and secure access to information.