Category: Edge AI & Robotics
-
Whisper.cpp vs Faster-Whisper: WER Accuracy Test on LibriSpeech
Tested whisper.cpp vs faster-whisper on LibriSpeech: 4.71% vs 4.42% WER. Here's exactly where quantization drops accuracy and which to deploy on edge.
-
TFLite & ONNX Mobile Setup: 2x Speed Left on Table
Default TFLite and ONNX configs waste 2-8x performance. Here's the exact setupโdelegates, threads, quantizationโthat closes the gap on ARM devices.
-
TFLite Inference Fails on Android: 5 ONNX Mobile Fixes
Fix TFLite Android crashes with ONNX Runtime โ 5 solutions for dynamic shapes, quantization bugs, GPU failures, and memory leaks with real benchmarks.
-
ONNX INT8 vs FP16: 3x Latency Drop on Jetson Orin Nano
YOLOv8n INT8 cut latency from 47ms to 15ms on Jetson Orin Nano โ but small-object mAP dropped 5.7%. Real tradeoff numbers with power benchmarks.
-
TFLite vs ONNX Mobile: 5 ARM Devices, 12ms Gap
TFLite vs ONNX benchmark on 5 ARM devices reveals 12ms latency gapโone framework dominates power efficiency while the other surprises on speed
-
ROS2 Nav2 vs Custom DWA: 47ms Latency Drop on AMRs
Compare Nav2 vs custom DWA for AMR navigation: discover how switching planners cut latency by 47ms and improved real-time obstacle avoidance.
-
Federated Learning vs Centralized: 3 Reasons Edge Fails
Federated Learning vs Centralized: Discover why edge training struggles with convergence, hardware limits, and security risks in real-world ML systems.