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Optimizing Generative AI for Edge Devices

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. How pruning, quantization and knowledge distillation help fit generative AI into resource-limited edge devices As of April 2023, one in three U.S. adults have used generative artificial intelligence (AI): Are you among them?1 When OpenAI unveiled ChatGPT […]

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Shining Brighter Together: Google’s Gemma Optimized to Run on NVIDIA GPUs

New open language models from Google accelerated by TensorRT-LLM across NVIDIA AI platforms — including local RTX AI PCs. NVIDIA, in collaboration with Google, today launched optimizations across all NVIDIA AI platforms for Gemma — Google’s state-of-the-art new lightweight 2 billion– and 7 billion-parameter open language models that can be run anywhere, reducing costs and

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An In-depth Comparison of LiDAR, Camera and Radar Technologies

This blog post was originally published at Outsight’s website. It is reprinted here with the permission of Outsight. This article explores the capabilities and limitations of each type of sensor, to provide a clear understanding of why LiDAR has emerged as a strong contender in the computer vision tech race. This article delves into the

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IoT for Dummies: Decoding the Language of Your Smart Building

This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. As smart home technology continues to evolve, our homes are becoming equipped with an increasing number of sensors, each capable of generating valuable data. From security systems and motion detectors to monitoring electricity and water usage, these

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Benchmarking Camera Performance on Your Workstation with NVIDIA Isaac Sim

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Robots are typically equipped with cameras. When designing a digital twin simulation, it’s important to replicate its performance in a simulated environment accurately. However, to make sure the simulation runs smoothly, it’s crucial to check the performance

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Quantization of Convolutional Neural Networks: Model Quantization

See “From Theory to Practice: Quantizing Convolutional Neural Networks for Practical Deployment” for the previous article in this series. Significant progress in Convolutional Neural Networks (CNNs) has focused on enhancing model complexity while managing computational demands. Key advancements include efficient architectures like MobileNet1, SqueezeNet2, ShuffleNet3, and DenseNet4, which prioritize compute and memory efficiency. Further innovations

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CES 2024 Showed that the Future of Cars will be Defined by AI

IDTechEx‘s new report, “Future Automotive Technologies 2024-2034: Applications, Megatrends, Forecasts“, highlights the biggest changes coming to cars over the next ten years. Electrification will change what powers cars, and automation will change how they are driven, but one of the biggest opportunities is connectivity and software definition, which will change how cars are monetized. This

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Generative AI in 2024: The 6 Most Important Consumer Tech Trends

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Qualcomm executives reveal key trends in AI, consumer technology and more for the future Not that long ago, the banana-peel-and-beer-fueled DeLorean in “Back to the Future” was presented as comedy. Yet today, 10% of cars are electric-powered.1

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Adapting Strategies: Industrial Machine Vision’s Response to Short-term Challenges

This market research report was originally published at the Yole Group’s website. It is reprinted here with the permission of the Yole Group. In 2023, the total machine vision market generated $6.9 billion in revenue. When will growth return? OUTLINE Industrial machine vision: a $7.8 billion market in 2029 compared to $6.9 billion in 2023.

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