This article was originally published at Hasty’s website. It is reprinted here with the permission of Hasty. This article will look at one of the most complex decisions for most organizations starting new AI projects. Should they buy or build the software they’ll use to develop their AI models? We’ll present arguments for both sides […]
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Manisha Agrawal, Product Marketing Manager at Texas Instruments, presents the “Build Smarter, Safer and Efficient Autonomous Robots and Mobile Machines” tutorial at the May 2022 Embedded Vision Summit. Automation is expanding rapidly from the factory floor to the consumer’s front door. Examples include autonomous mobile robots used in warehouses and last mile delivery and service
Luc Chouinard, AI Specialist and Design Architect at Teledyne Imaging, presents the “Deploying Visual AI on Edge Devices: Lessons From the Real World” tutorial at the May 2022 Embedded Vision Summit. Developing an AI-based edge device is complex, involving hardware, algorithms and software. It requires making many technology-selection decisions and balancing numerous trade-offs. In this
Ali Osman Örs, Director of AI ML Strategy and Technologies for Edge Processing at NXP Semiconductors, presents the “Intelligent Vision for the Industrial, Automotive and IoT Edge with the i.MX 8M Plus Applications Processor” tutorial at the May 2022 Embedded Vision Summit. Today’s edge-based ML solutions need a powerful multicore processor packed with features and
Jason Corso, CEO of Voxel51, presents the “Creating Better Datasets for Training More Robust Models in FiftyOne” tutorial at the May 2022 Embedded Vision Summit. Nothing hinders the success of computer vision and machine learning systems more than poor-quality data. Gone are the days of focusing only on the model while assuming the data is
21 Jul 2022 | Geneva | STMicroelectronics has released STM32Cube.AI version 7.2.0, the first artificial-intelligence (AI) development tool by an MCU (microcontroller) vendor to support ultra-efficient deeply quantized neural networks. STM32Cube.AI converts pretrained neural networks into optimized C code for STM32 microcontrollers (MCUs). It is an essential tool for developing cutting-edge AI solutions that make
On-device intelligence provides important benefits. This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our latest AI research to personalize and adapt models while keeping data private One size doesn’t fit all. The need for intelligent, personalized experiences powered by AI is ever-growing. Our devices are
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This video was originally published at Intel’s YouTube channel. It is reprinted here with the permission of Intel. In this episode, Stephanie Essin interviews Stewart Christie. He is an AI and IoT Evangelist at Intel who creates online developer courses (which you can go and take for free right now!). Outside of this, he also
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Carlos Garcia-Sierra, Product Manager for DeepStream at NVIDIA, presents the “Vision AI At the Edge: From Zero to Deployment Using Low-Code Development” tutorial on behalf of Alvin Clark, Product Marketing Manager at NVIDIA, at the May 2022 Embedded Vision Summit. Development of vision AI applications for the edge presents complex challenges beyond model inference, often
Akhil Docca, Senior Product Marketing Manager at NVIDIA, presents the “Accelerating the Creation of Custom, Production-Ready AI Models for Edge AI,” tutorial at the May 2022 Embedded Vision Summit. AI applications are powered by models. However, creating customized, production-ready AI models requires an army of data scientists and mountains of data. For businesses looking to
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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