INT4 vs INT8 vs FP8 on Edge NPUs: The 2026 Quantization Trade-off
INT4, INT8, and FP8 quantization compared on edge NPUs in 2026: accuracy loss, latency, and memory trade-offs for vision and LLM workloads.
Hailo-10H vs Jetson Orin Nano (2026): Same CV Workload Tested
Hailo-10H vs Jetson Orin Nano head-to-head on the same computer-vision workload: TOPS/W, latency, framework support, memory and price. A 2026 edge-inference pick.
On-Device LLM Runtimes (2026): llama.cpp vs MLC vs ONNX
On-device LLM runtimes compared: llama.cpp vs MLC-LLM vs ONNX Runtime on edge SoCs - backends, quantization, throughput, memory and portability. 2026 decision guide.
Jetson Thor vs Hailo-10H vs Coral (2026): Edge Inference Pick
Jetson Thor vs Hailo-10H vs Google Coral for edge AI inference: TOPS/W, framework support, memory, price and the workload each wins. 2026 hardware decision guide.
Small Language Models on Device: Edge Inference Architecture (2026)
How to run small language models (SLMs) on-device: model sizing, distillation, quantization, NPU acceleration, memory budgets, and when a 1-8B SLM beats a cloud LLM.
NVIDIA Jetson + K3s: Edge AI Cluster Tutorial (2026)
A hands-on NVIDIA Jetson and K3s edge AI cluster tutorial: provision nodes, enable GPU scheduling, deploy a vision model, and run inference at the edge.
Industrial Machine Vision Defect Detection: Edge AI 2026
A reference architecture for industrial machine vision defect detection: edge AI inference, camera-to-PLC pipelines, model training, and MLOps on the factory floor.
Does Edge AI Actually Cut Cloud Costs? A Fact-Check
Fact-checking the claim that edge AI slashes cloud bills: where the savings are real, where they hide capital and ops costs, and the break-even math for 2026.
How Neuromorphic Chips Actually Work (2026)
Neuromorphic chips compute like a brain: spikes, not clocks. How spiking neural networks, memristors, and event-driven silicon work, and why they sip power.
Lights-Out Factories in 2026: What the Data Shows
A 2026 analysis of lights-out, autonomous factories — what edge AI and digital twins actually deliver, where the hype breaks, and the realistic adoption curve.