TECHNOLOGIES

“HiFi iQ: Enabling Voice AI and Immersive Audio for Smart Home, Mobile and Automotive,” a Presentation from Cadence

Amol Borkar, Group Director of Product Management and Marketing—Tensilica DSPs, Silicon Solutions Group (SSG) at Cadence presents “HiFi iQ: Enabling Voice AI and Immersive Audio for Smart Home, Mobile and Automotive” at the May 2026 Embedded Vision Summit. Voice is quickly becoming the primary interface for consumer and enterprise devices,… “HiFi iQ: Enabling Voice AI […]

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Why Vision LLMs Force A Rethink Of Edge AI Hardware

This blog post was originally published at Expedera’s website. It is reprinted here with the permission of Expedera. As vision-centric large language models move on-device, performance measured in raw TOPS is no longer enough. Architectures need to be built around real workloads, memory behavior, and sustained utilization, especially at the edge. Vision LLMs are changing

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“What We Learned Porting to OpenCV 5 with Claude Code,” a Presentation from Boston.AI

Mark Antonelli, CTO at Boston.AI presents “What We Learned Porting to OpenCV 5 with Claude Code” at the May 2026 Embedded Vision Summit. OpenCV 5 introduces significant architectural changes to improve vision performance and better utilize modern hardware. In addition to support for new features like vision-language models, there are… “What We Learned Porting to

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Gemma 4 on Arm: Accessible, Immediate, Optimized On-device AI to Accelerate the Mobile App Experience

Gemma 4 on Arm brings fast, privacy-preserving, power-efficient AI directly onto Android devices, helping developers deliver richer real-time app experiences to billions of users without relying on the cloud.   This blog post was originally published at Arm’s website. It is reprinted here with the permission of Arm. Real-time assistance, seamless communication, and greater personalization are now baseline expectations for billions of smartphone

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Building High-Performance Data Paths: New Evaluation Platforms for AI and Vision Systems

Bringing AI and vision designs to life starts with reliable data movement. Learn how our latest evaluation kits help engineers prototype imaging and networking paths early, reduce design risk and move from concept to working system faster.   Microchip released two evaluation platforms designed to help developers prototype and benchmark data-intensive systems much earlier in

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“Accelerating Deep Learning Models on AMD Adaptive SoCs with the AMD Vitis AI Workflow,” a Presentation from AMD

Thomas Zerbs, Technical Marketing Engineer, Adaptive and Embedded Computing Group at AMD presents “Accelerating Deep Learning Models on AMD Adaptive SoCs with the AMD Vitis AI Workflow” at the May 2026 Embedded Vision Summit. In this presentation, we provide a practical end-to-end overview of the AMD Vitis™ AI workflow for… “Accelerating Deep Learning Models on

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Samsung Foundry and Cadence: Accelerating Chiplet Solutions for Physical AI

This blog post was originally published at Samsung Semiconductor’s website. It is reprinted here with the permission of Samsung Semiconductor. Artificial Intelligence (AI) is rapidly expanding beyond digital environments and into the physical world. AI-driven systems that give machines the ability to perceive, comprehend, learn from, and respond to real-time environments are quickly moving from

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Analog Devices to Acquire Empower Semiconductor, Expanding its Next-Generation High-Density Power Portfolio for the AI Era

Key Takeaways: Addresses a critical challenge in AI – delivering high-density, energy-efficient compute as power and thermal demands limit system scale Further advances ADI’s position as a leading strategic, system-level grid-to-core power partner for hyperscalers and AI silicon developers Expands ADI’s total addressable market in AI compute power delivery with Integrated Voltage Regulator (IVR) and

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“Accelerating Physical AI with ROCm: High-Performance ML on AMD Embedded iGPUs,” a Presentation from AMD

Alok Gupta, Senior Technical Marketing Manager at AMD presents “Accelerating Physical AI with ROCm: High-Performance ML on AMD Embedded iGPUs” at the May 2026 Embedded Vision Summit. Discover how AMD’s ROCm software stack unlocks data center-class ML performance on embedded integrated GPUs, enabling diverse AI workloads from CNNs and transformers… “Accelerating Physical AI with ROCm:

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The Software Gap Holding AI Back: What Semiconductor Leaders Can Learn From the EV Transition

This blog post was originally published at HTEC’s website. It is reprinted here with the permission of HTEC. The story of EV adoption contains a warning that semiconductor companies would be wise to take seriously. When the automotive industry made the leap from combustion engines to electric drivetrains, it discovered that a transformative technology is not enough on its own. The

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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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