Build Intelligent Stores with Ultralytics YOLOv8 and Seeed Studio.

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Join us for Ultralytics Live Session 14 as we explore how to build intelligent stores with Ultralytics YOLOv8 and the NVIDIA Jetson Orin embedded device. Discover how Seeed Studio's hardware integrates with YOLOv8 for efficient deployment in retail environments. Dive into smart queue management and learn how computer vision can enhance customer experience in stores.

In this session, Ultralytics' Embedded Computer Vision Engineer Lakshantha Dissanayake, Edge AI Marketing Manager Elaine Wu, and Application Engineer Youjiang Yu from Seeed Studio will guide you through:
✅ Overview of Seeed Studio's NVIDIA Jetson hardware
✅ Streamlining YOLOv8 deployment on NVIDIA Jetson
✅ Live demonstration of queue management
✅ Future roadmap and Q&A session

We'll cover the technical aspects of deploying YOLOv8 models on Jetson devices, including performance benchmarks, multi-stream capabilities, and practical applications like people counting and heat maps. Learn how to leverage AI for better resource allocation and customer satisfaction in retail.

Don't miss out on the live demo and insights into future developments. Enhance your knowledge of AI and computer vision with real-world examples and expert tips.

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#Ultralytics #YOLOv8 #ComputerVision #AIinRetail #NVIDIAJetson #SeeedStudio #EdgeAI #SmartRetail #QueueManagement
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Awesome live session and super cool demos guys!!

glenn-jocher-ultralytics
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Given the immersive focus on integrating computer vision for retail, I'm curious: how does the deployment of YOLOv8 on NVIDIA Jetson hardware specifically enhance the accuracy and efficiency of real-time customer behavior analytics in stores? Could this approach offer a significant competitive edge over traditional methods in terms of data granularity and actionable insights?

os-EmilyW
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How do you think implementing YOLOv8 in retail stores might impact customer privacy, and are there ways to balance utility with privacy concerns?

m