https://www.youngju.dev/blog 천천히 올바르게. AI Researcher & DevOps Engineer Youngju's tech blog. GPU/CUDA, LLM, MLOps, Kubernetes AI workloads, distributed training, and data engineering. ko fjvbn2003@gmail.com (Youngju Kim) fjvbn2003@gmail.com (Youngju Kim) Tue, 16 Jun 2026 00:00:00 GMT https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators.en https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators.en 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 compression, on-device LLMs, runtimes (TFLite/ONNX/CoreML), and cloud-edge hybrids, this is a developer starting guide. Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) edge-ainpuon-deviceinferencequantizationmobileaccelerators https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators.ja https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators.ja 推論をクラウドではなく機器で直接回すエッジ AI の理由(遅延・プライバシー・コスト)と、それを可能にする NPU の概念を整理します。Apple Neural Engine、Qualcomm、Edge TPU、ARM Ethos からモデル軽量化、オンデバイス LLM、ランタイム(TFLite/ONNX/CoreML)、クラウド-エッジのハイブリッドまで、開発者の始め方ガイドを収めました。 Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) edge-ainpuon-deviceinferencequantizationmobileaccelerators https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators https://www.youngju.dev/blog/gpu-cuda/2026-06-16-edge-ai-npu-accelerators 추론을 클라우드가 아니라 기기에서 직접 돌리는 엣지 AI의 이유(지연·프라이버시·비용)와, 이를 가능케 하는 NPU의 개념을 정리합니다. Apple Neural Engine, Qualcomm, Edge TPU, ARM Ethos부터 모델 경량화, 온디바이스 LLM, 런타임(TFLite/ONNX/CoreML), 클라우드-엣지 하이브리드까지 개발자 시작 가이드를 담았습니다. Tue, 16 Jun 2026 00:00:00 GMT fjvbn2003@gmail.com (Youngju Kim) edge-ainpuon-deviceinferencequantizationmobileaccelerators