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yeonseok-zeticai

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On device AI with mobile hardware utilizations

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๐Ÿš€ Revolutionary Method to Convert YOLOv8 to On-Device AI with mobile NPU utilizations

Attention AI developers and engineers!
Discover how ZETIC.MLange can effortlessly transform YOLOv8 models into on-device AI with mobile NPU utilizations. ๐ŸŽ‰

๐Ÿ’ก We highlight the power of mobile NPU, showing how it outperforms CPU in processing speed. The results speak for themselvesโ€”NPU-driven execution is faster, smarter, and more efficient.
* Real-time demos are no easy feat but with ZETIC.MLange, weโ€™ve made it possible!

๐ŸŽฅ Watch the video to see how weโ€™re revolutionizing on-device AI.
: https://youtu.be/LkP3JDTcVN8?si=6Ha5vHA-G7jZE9oq

๐ŸŒŸ Our team has successfully implemented YOLOv8 as on-device AI using ZETIC.MLange. This innovative approach enables high-performance object detection across various manufacturers mobile devices.

๐Ÿ” Curious about the details? We've shared a comprehensive guide on our blog. Check it out through the link below!
๐Ÿ“š Blog link: https://zetic.ai/blog/implementing-yolov8-on-device-ai-with-zetic-mlange

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