Virtucom, Inc.’s Post

Today, I found time to review the "Introduction to On-Device AI" course offered by #DeepLearningAI and #Qualcomm, and I'd like to share my thoughts. 🔍 Course Overview: The course is well-structured, making it a great short crash course on #embeddedAI. It introduces the fundamentals of model training and deployment on edge devices, covering essential topics like model compilation, quantization, and profiling on CPU, GPU, and #NPU. The content primarily relies on the Qualcomm AI Hub and #Snapdragon chipsets, offering practical insights into their ecosystem. 💡 Key Takeaways - Model Preparation and Deployment: Solid foundation on the principles and practices. - Tools & Techniques: Model quantization and on-device performance profiling for CPU, GPU, and NPU. - Practical Insights: Providing a simple Android app for device integration and testing. 📈 Areas for Improvement: While the course content is informative, I wished for more depth and detail. I’m eagerly looking forward to a more comprehensive course from Qualcomm in the future. 👍 Recommendation: I recommend this course as a starting point for enthusiasts of practical AI. It’s perfect for getting your feet wet, but you'll need to explore further courses to build something truly hands-on. Excited to review more on-device AI content 🚀 #AI #EmbeddedAI #DeepLearning #AITraining #EdgeComputing #ArtificialIntelligence #AIHub

🚀 Exciting insights from embedded world Exhibition&Conference 2024! The privilege of tuning into a thought-provoking discussion between Patrick Hopper of Embedded Computing Design and MiTAC Computing Technology. They delved deep into the latest advancements in Edge AI Solutions. 🔗 Check out their full conversation here: https://lnkd.in/dka-gymZ Let's discuss: How do you see Edge AI transforming our tech landscape in the coming years? #ew24 #edgecomputing #ai

Looking back, I'm proud of the 'Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications' certification I earned in May 2021. After taking a step back to recharge, I'm now ready to dive back into the dynamic world of AI and Machine Learning. The advancements in computer vision and AI technology have been astounding, and I'm excited to continue learning and contributing to this ever-evolving field.🚀 #AI #MachineLearning #ComputerVision #TechJourney #LifelongLearning

Machine Learning engineers and scientists are often faced with the challenge of deploying their models on edge devices. The performance of machine learning models on edge devices is crucial for the success of edge computing. InferenceTime aims to provide a platform for collecting and analyzing performance metrics of machine learning models on edge devices. Our goal is to provide a platform that allows developers to collect and analyze performance metrics of machine learning models on edge devices, and to use this information to improve the performance of their models.

Hello connection! Excited to announce that I've completed the ML101: Machine Learning at the Edge course from Arm! 🎓 Learned valuable insights into deploying ML models on resource-constrained devices. 💻 Ready to leverage edge computing for innovative solutions! #MachineLearning #EdgeComputing #ArmEducation 🚀🔍💡

BeagleBoard is not new, but the organization’s latest offering, the BeagleY-AI board, is new. And it lets developers go to a completely new level, adding artificial intelligence, without breaking the bank. Watch the video with Richard Nass of Embedded Computing Design and Jason Kridner of BeagleBoard.org Foundation from embedded world Exhibition&Conference https://lnkd.in/efvDpV6H #ew24 #opensource #ai

Successfully completed a course on " Computer Vision with Embedded Machine Learning" in COURSERA. Thanks to #sruniversity.

California partners with Nvidia to bring artificial intelligence resources to colleges: ... Nvidia to help train California students, college faculty, developers and data scientists in artificial intelligence. The new initiative is part … http://dlvr.it/TBksQl

Tech and education leaders agree: In an age of AI, computer science education is more important than ever. See guidance for CS classrooms we've created in partnership with #TeachAI: teachai.org/cs. Let’s #TeachAI

We teach critical consumption and creation of AI when we teach it side by side with CS. I’ve had multiple people ask me if AI is the death of CS. No. Nope. Negative. It is one of the many reasons we must continue to teach CS, and we must continue to advocate for it to be taught K-12. An understanding of computer science will alway inform our understanding of technology in a way that simply teaching “digital literacy” or now “AI Literacy” never will.