Processors

Upcoming Tech Talk Explores How to Solve Tomorrow’s AI Problems Today with Edge Co-processors

Next Tuesday, July 15, 2025 at 8:00 am PT (11:00 am ET), Alliance Member company Cadence will deliver the free tech talk “Solving Tomorrow’s AI Problems Today with Cadence’s Newest Processor.” From the event page: The AI industry is undergoing a profound transformation, with evolving workloads demanding processors that deliver unparalleled efficiency, flexibility, and performance. […]

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Andes Technology’s AutoOpTune Applies Genetic Algorithms to Accelerate RISC-V Software Optimization

Andes AutoOpTune™ v1.0 accelerates software development by giving software developers the ability to automatically explore and choose the compiler optimizations to achieve their performance and code-size targets. Hsinchu, Taiwan – July 10, 2025 – Andes Technology, a leading provider of high-efficiency, low-power 32/64-bit RISC-V processor cores and a Founding Premier member of RISC-V International, today

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Optimizing Your AI Model for the Edge

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Key takeaways: We talk about five techniques—compiling to machine code, quantization, weight pruning, domain-specific fine-tuning, and training small models with larger models—that can be used to improve on-device AI model performance. Whether you think edge AI is

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Cadence Demonstration of Waveguide 4D Radar Central Computing on a Tensilica Vision DSP-based Platform

Sriram Kalluri, Product Marketing Manager for Cadence Tensilica DSPs, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Kalluri demonstrates the use of the Tensilica Vision 130 (P6) DSP for advanced 4D radar computing for perception sensing used in ADAS applications. The Vision 130 DSP is

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Cadence Demonstration of a SWIN Shifted Window Vision Transform on a Tensilica Vision DSP-based Platform

Amol Borkar, Director of Product Marketing for Cadence Tensilica DSPs, presents the company’s latest edge AI and vision technologies at the 2025 Embedded Vision Summit. Specifically, Borkar demonstrates the use of the Tensilica Vision 230 (Q7) DSP for advanced AI and transformer applications. The Vision 230 DSP is a highly efficient, configurable, and extensible processor

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US Export Controls on AI Chips Boost Domestic Innovation in China

AI chips for data centers, rely on international collaboration in design, manufacturing, and distribution, however the US has cornered China by restricting this collaboration. These AI processors see increasing demand in data centers, but this comes with high energy consumption and capital costs. The discussion around advanced chips for artificial intelligence, driven by billions in

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Aizip Demonstration of Its Personal Offline AI Assistant for Biking on a Cadence Tensilica HiFi DSP Platform

Nathan Francis, Head of Business Development at Aizip, demonstrates the company’s latest edge AI and vision technologies and products in Cadence’s booth at the 2025 Embedded Vision Summit. Specifically, Francis demonstrates the capabilities of his company’s small language model capable of running on a bike computer. You can’t assume internet connectivity when biking in the

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DeGirum Demonstration of Its PySDK Running on BrainChip Hardware for Real-time Edge AI

Stephan Sokolov, Software Engineer at DeGirum, demonstrates the company’s latest edge AI and vision technologies and products in BrainChip’s booth at the 2025 Embedded Vision Summit. Specifically, Sokolov demonstrates the power of real-time AI inference at the edge, running DeGirum’s PySDK application directly on BrainChip hardware. This demo showcases low-latency, high-efficiency performance as a script

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Best-in-class Multimodal RAG: How the Llama 3.2 NeMo Retriever Embedding Model Boosts Pipeline Accuracy

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Data goes far beyond text—it is inherently multimodal, encompassing images, video, audio, and more, often in complex and unstructured formats. While the common method is to convert PDFs, scanned images, slides, and other documents into text, it

Best-in-class Multimodal RAG: How the Llama 3.2 NeMo Retriever Embedding Model Boosts Pipeline Accuracy Read More +

BrainChip Demonstration of LLM Inference On an FPGA at the Edge using the TENNs Framework

Kurt Manninen, Senior Solutions Architect at BrainChip, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Van Manninen demonstrates his company’s large language models (LLMs) running on an FPGA edge device, powered by BrainChip’s proprietary TENNs (Temporal Event-Based Neural Networks) framework. BrainChip enables real-time generative AI

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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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