New Frontier Magazine

Edge Ai

2 articles

Editorial illustration for Pruning vs. Quantization vs. Distillation: How to Pick the Right Compression Technique for Your Edge AI Project
Artificial Intelligence

Pruning vs. Quantization vs. Distillation: How to Pick the Right Compression Technique for Your Edge AI Project

This article explores three key AI model compression techniques for edge deployments: pruning, quantization, and knowledge distillation. It details their mechanisms, trade-offs, and offers a decision framework to help developers choose the optimal method based on critical constraints like memory, latency, and accuracy.

Dr. Aris Thorne·October 18, 2026
Editorial illustration for TensorFlow Lite vs. OpenVINO vs. ONNX Runtime: Which Edge AI Framework Fits Your Project?
Artificial Intelligence

TensorFlow Lite vs. OpenVINO vs. ONNX Runtime: Which Edge AI Framework Fits Your Project?

Choosing an edge AI framework like TensorFlow Lite, OpenVINO, or ONNX Runtime depends on your project's hardware target, optimization needs, and portability requirements. Each framework offers distinct advantages for mobile, Intel-based systems, or cross-platform deployments.

Dr. Aris Thorne·October 14, 2026