A Technical Analysis of Model Compression and Quantization Techniques for Efficient Deep Learning

I. The Imperative for Efficient AI: Drivers of Model Compression A. Defining Model Compression and its Core Objectives Model compression encompasses a set of techniques designed to reduce the storage Read More …

The Edge Advantage: A Comprehensive Analysis of Sub-7B Small Language Models for On-Device Deployment

The Paradigm Shift to Compact AI: Defining the SLM Landscape From Brute Force to Finesse: The Evolution Beyond LLMs The trajectory of artificial intelligence over the past half-decade has been Read More …