Tag: #edge-ai
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 7 posts
On-Device and Edge AI — When AI Moves Inside the Device
AI inference, once confined to the cloud, is moving into smartphones, PCs, and embedded devices. This post examines the three drivers (latency, privacy, cost), the rise of NPUs and on-device LLMs, and the investment and
2026-06-18 · 19 min read #ai#edge-ai#on-device#npu#llmEdge AI and the NPU — On-Device Inference Accelerators
We lay out why edge AI runs inference on the device instead of the cloud (latency, privacy, cost) and the concept of the NPU that makes it possible. From Apple Neural Engine, Qualcomm, Edge TPU, and ARM Ethos to model co
2026-06-16 · 22 min read #edge-ai#npu#on-device#inference#quantizationEdge AI & TinyML 2026 — LiteRT / ExecuTorch / Edge Impulse / Jetson / Coral / Hailo / Sipeed K230 / llama.cpp / Phi-4 Deep-Dive Guide
A full-stack map of the 2026 Edge AI / TinyML ecosystem — the dual standard formed after TFLite Micro was rebranded as LiteRT and ExecuTorch reached GA, the TinyML cloud workflow created by Edge Impulse, the accelerator
2026-05-16 · 32 min read #edge-ai#tinyml#tflite-micro#litert#executorchEdge AI Complete Guide 2025: On-Device Inference, Model Optimization, TensorRT/ONNX/CoreML
Everything about Edge AI! On-device inference (TensorRT/ONNX Runtime/CoreML/TFLite), model optimization (quantization/pruning/knowledge distillation), hardware (NVIDIA Jetson/Apple Neural Engine/Qualcomm NPU), Federated
2026-04-13 · 21 min read #edge-ai#on-device#inference#tensorrt#onnxAI Hardware Accelerators Complete Guide: H100, TPU, Cerebras, and Edge AI Chips Compared
A comprehensive comparison guide covering NVIDIA H100 Tensor Core, Google TPU v5 systolic array, Cerebras WSE-3, AWS Inferentia 2, and Apple Neural Engine for AI hardware accelerators.
2026-03-17 · 17 min read #ai-hardware#h100#tpu#cerebras#edge-aiEmbedded Systems & IoT Complete Guide: From MCU to Edge AI
A comprehensive guide to embedded systems and IoT. Covers MCU programming, RTOS, communication protocols (I2C/SPI/UART/CAN), Raspberry Pi, ESP32, and Edge AI (TFLite/ONNX) with real code examples.
2026-03-17 · 16 min read #embedded-systems#iot#microcontroller#rtos#arduinoEdge AI and On-Device ML Complete Guide: TFLite, ONNX, Core ML, llama.cpp
A complete guide to running AI models on edge devices. Learn hands-on how to deploy optimized AI in mobile and edge environments using TensorFlow Lite, ONNX Runtime, Core ML, MediaPipe, llama.cpp, and Whisper.cpp.
2026-03-17 · 25 min read #edge-ai#on-device-ml#tflite#onnx#core-ml