Qualcomm

Qualcomm Unveils Snapdragon Ride Flex – the Automotive Industry’s First Scalable Family of SoCs to Simultaneously Support Digital Cockpit and Advanced Driver Assistance Systems

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Highlights: Snapdragon Ride Flex SoC (System-on-Chip) product family is built on Qualcomm Technologies’ leadership in Digital Cockpit and Advanced Driver Assistance Systems (ADAS) compute platforms Snapdragon Ride Flex SoC supports mixed-criticality workloads, allowing for digital cockpit, ADAS and automated driving (AD) capabilities to be co-implemented on the same hardware Snapdragon Ride Flex SoC is pre-integrated […]

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VVDN Technologies Demonstration of Its Various Reference Platforms

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Kalpeshkumar Chauhan, Senior Director and Technology Evangelist for Vision and IoT at VVDN Technologies, demonstrates the company’s latest edge AI and vision technologies and products at the December 2022 Edge AI and Vision Innovation Forum. Specifically, Chauhan demonstrates the company’s various reference platforms, developed in partnership with other Alliance Member companies. VVDN has strong relationships

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Leading Research Delivers AI Firsts

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Qualcomm AI Research establishes firsts in AI across research and proof-of-concept. At Qualcomm, we have a culture of innovation. We take pride in researching and developing fundamental technologies that will change the world. It’s also in our

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Qualcomm Launches Snapdragon AR2 Designed to Revolutionize AR Glasses

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Highlights: The Company unveils the world’s first purpose-built headworn augmented reality platform, Snapdragon® AR2 Gen 1, as part of its extended reality (XR) portfolio. The groundbreaking multi-chip architecture achieves 50% lower power consumption and 2.5x better AI performance1, to enable high-performance, sleek AR glasses. Snapdragon AR2 is in various stages of development with OEMs including

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Snapdragon 8 Gen 2 Defines a New Standard for Premium Smartphones

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Highlights: Snapdragon® 8 Gen 2 Mobile Platform to revolutionize flagship smartphones for truly extraordinary experiences Snapdragon Smart enables groundbreaking AI experiences like faster natural language processing with multi-language translation and revolutionary INT4 support Snapdragon Sight™ technology additions include new Cognitive ISP to power real time semantic segmentation for photo and video capture, delivering breakthrough customized

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Exploring AIMET’s Quantization-aware Training Functionality

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. In Exploring AIMET’s Post-Training Quantization Methods, we discussed Cross-layer Equalization (CLE), Bias Correction, and AdaRound in AIMET. Using these methods, the weights and activations of neural network models can be reduced to lower bit-width representations, thus reducing

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Qualcomm Scales Flagship Experiences to More Consumers with Introduction of Snapdragon 6 and 4 Gen 1

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Enabling Illuminating Capture, Advanced Connectivity Features, and Next-Generation Artificial Intelligence Highlights: Snapdragon 6 Gen 1 and Snapdragon 4 Gen 1 Mobile Platforms provide advanced technology solutions for the mid-tier and mass-volume segments. Snapdragon 6 Gen 1 Mobile Platform provides brilliance beyond expectation, fueling dynamic experiences. Commercial devices powered by Snapdragon 6 are expected to be

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Exploring AIMET’s Post-Training Quantization Methods

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Usually, when you’re presented with three options, such as powerful, efficient, and low cost, you’re also faced with the conundrum where you’re only allowed to pick one or two. Machine learning (ML) practitioners developing neural networks for

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Enabling On-device Learning at Scale

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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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Neural Network Optimization with AIMET

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models’ size and complexity while taking advantage of hardware acceleration for inference. For these

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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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