Cardinal Peak’s Post

Are you working on performance-critical applications like image processing or machine learning? Then you need to harness the power of RISC-V Vector Extensions! But wait, developing and testing on RISC-V hardware can be a pain, right? Not anymore! Cloud-V provides a cloud-based RISC-V development environment, letting you seamlessly leverage Vector Extensions without the hassle of physical hardware. Click here: https://lnkd.in/dz25qGg7 1. Shows you how to optimize the "llama.cpp" benchmark using RISC-V Vector Extensions 2. Guides you through the process on Cloud-V, demonstrating its ease of use 3. Unveils the performance gains achievable with Vector Extensions What's in it for you? 1. Significant speedups for your vectorized applications ️ 2. Reduced development time and effort ⏳ 3. A smooth and efficient Cloud-V experience ☁️ Ready to unlock the full potential of RISC-V Vector Extensions? Read this blog post now! https://lnkd.in/dz25qGg7 Sign up for Cloud-V and start developing faster today! https://cloud-v.co/ Join the RISC-V revolution with Cloud-V!

Connect 4 Strategy with Computer Vision -- never lose In this blog, I guide you through the process of creating a model to recognize game pieces and predict optimal moves, highlighting how Roboflow is helping make the world programmable. Read the full blog to see a step-by-step implementation here: https://lnkd.in/eHbgd7ve

#SmartManufacturing is here to stay. And thankfully, building and tracking production-grade anomaly detection models for Industry 4.0 has never been easier! This article explores a new integration between Comet and Anomalib: an end-to-end solution that includes cutting-edge #algorithms, visualizations, optimization and inference deployment code with Intel’s OpenVINO toolkit. #Industry40

#SmartManufacturing is here to stay. And thankfully, building and tracking production-grade anomaly detection models for Industry 4.0 has never been easier! This article explores a new integration between Comet and Anomalib: an end-to-end solution that includes cutting-edge #algorithms, visualizations, optimization and inference deployment code with Intel’s OpenVINO toolkit. #Industry40

YOLOv7 OnnxRuntime Performance 💡 Computer Vision ✅ Research and Development YOLOv7 is amongst the State of the art object detection models, but it faces issues in speed as compared to other variants of YOLO (i.e. YOLOv8). ONNX Runtime is an open-source runtime engine that executes machine learning models in the ONNX format with high performance and cross-platform compatibility. By converting the YOLOv7 PyTorch model to the onnx model, it's provides 🚀 Increase In Speed ✅ Cross platforms Integration (i.e TensorFlow, TensorFlow Lite) By performing different experiments I noticed, onnx model Inference time is half that YOLOv7 Pytorch model Inference time. Due to its cross-platform integration, onnxruntime is always preferred in different types of deployment. There are other ways too to optimize YOLOv7, which include: ✅ TensorRT Optimization for Jetson Nano (YOLOv7) ✅ TensorFlow Lite Conversion for Android Applications Its use cases are not limited, but it's helpful for different industries: 🟢 Retail 🟢Transportation 🟢Health 🟢 Security 🟢Construction #computervision #machinelearning #deeplearning #objectdetection #researchanddevelopment #tensorflow #brainmachine

Amazing work on vector similarity in recommender systems! 🌟Did you know that the recommendation engine at Amazon produces 35% of the company's revenue? It is impossible to emphasize the value of efficient vector similarity. It's not only about making product recommendations; it's also about designing a customized user experience that may have a big impact on a business's bottom line. I can't wait to see how your work evolves! #VectorSimilarity #RecommenderSystems #DataScience

🚀 **Introducing YOLO-World: A Leap in Open-Vocabulary Object Detection** Earlier I had the opportunity to work with the YOLO architecture previously, and I felt truly excited when I first learned about 'YOLO-World'. It's an interesting concept, and I'd recommend looking into it to learn more." In the realm of object detection, the YOLO (You Only Look Once) architecture has long been a pioneering force. Traditionally, models like Faster R-CNN, SSD, and YOLO were bound by a predefined set of object categories, limiting their adaptability to diverse scenarios beyond their training data. Enter YOLO-World, a groundbreaking advancement in open-vocabulary object detection. This innovation showcases that even lightweight detectors, such as those from the YOLO series, can achieve exceptional performance in open-vocabulary settings. ### Key Advancements and Applications: - **Performance:** YOLO-World maintains nearly the same accuracy as leading zero-shot detectors but boasts an incredible 20x speed improvement and 5x reduction in size. - **Versatility:** YOLO-World opens doors to myriad of applications, including real-time object detection and tracking on edge devices, video processing and analytics, and auto-labeling data for custom vision model training. This development marks a significant stride towards faster, more cost-effective, and widely accessible open-vocabulary object detection. YOLO-World is not just a step forward in technology; it's a leap into a more dynamic and adaptable future. you can check this out here. https://lnkd.in/gHa4WXEE #yolov8 #Ultralytics #deeplearning #transformers

Vector databases are a hot topic because they support retrieval augmented generation (RAG) for LLM's, but vector databases are also extremely useful in today's recommender systems. This post describes how Milvus, an open source vector database, integrates nicely with Merlin, a GPU accelerated recommender system. https://lnkd.in/gnftkMBe

The next level of Machine Vision has arrived! 🚀 👁️🗨️ Say hello to the next generation of Machine Vision -  the MX-G2000 by Datasensing! Combining the power of IMPACT software and DataSensing’s PEKAT AI software, this revolutionary machine vision processor is here to redefine possibilities! 💡 The MX-G2000 merges deep-learning algorithms with robust rule-based methods, empowering you to Do MORE. 💰 Maximize your ROI with training and inference running directly on the embedded GPU, saving you MORE. 🛠️ Forget about programming headaches - the MX-G2000 eliminates the need for it in the majority of applications, making it easy to Do It With EASE. ⏱️ Need speed? The MX-G2000 delivers unrivaled computing power, enabling you to Do It FASTER. 🔐 Safety first! Run your training and inference directly on the MX-G2000 Vision Processor for peace of mind, ensuring you can Do It SAFELY. 🔍 Ready to explore the incredible inspections you can achieve with the MX-G2000? Reach out to elliTek, Inc. today to unlock the possibilities! #MachineVisioin #MXG2000 #FutureTech #DeepLearning #IMPACTSoftware #PEKATSoftware