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 Cut Cloud Costs? 2026 Fact-Check
Does edge AI cut cloud costs? Only above roughly 30-50 GB/day per device. See verified egress, hardware and fleet-ops math, updated November 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.
On-Device SLM Inference: A 2026 Edge GPU Benchmark
A 2026 benchmark methodology for small language models on edge GPUs — latency, tokens/sec, memory, and cost for Phi, Gemma, and Qwen on Jetson-class hardware.
Edge MLOps Pipelines for Industrial IoT: 2026 Production Architecture
Production-grade edge MLOps pipeline for industrial IoT — training, packaging, OTA delivery, drift detection, and rollback under network constraints.
Time-Series Forecasting at the Edge: 2026 Production Patterns
Production patterns for time-series forecasting at the edge — Chronos-Bolt, TimesFM, TFT, quantization, and real-world latency budgets.
NVIDIA Jetson Thor: Humanoid Robot Compute Architecture
NVIDIA Jetson Thor architecture for humanoid robots — the compute stack, VLA model serving, real-time partitioning, power envelope, and where it fits.