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Comparing Synthetic Data Platforms: Synetic AI and NVIDIA Omniverse

This blog post was originally published at Synetic AI’s website. It is reprinted here with the permission of Synetic AI. This blog post compares Synetic AI and NVIDIA Omniverse for synthetic data generation, focusing on deployment-ready computer vision models. Whether you’re exploring simulation tools or evaluating dataset creation platforms, this guide outlines key differences and […]

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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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Stereo ace for Precise 3D Images Even with Challenging Surfaces

The new high-resolution Basler Stereo ace complements Basler’s 3D product range with an easy-to-integrate series of active stereo cameras that are particularly suitable for logistics and factory automation. Ahrensburg, July 10, 2025 – Basler AG introduces the new active 3D stereo camera series Basler Stereo ace consisting of 6 camera models and thus strengthens its position as

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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 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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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

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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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BrainChip Demonstration of Its Latest Audio AI Models in Action At the Edge

Richard Resseguie, Senior Product Manager at BrainChip, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Van Resseguie demonstrates the company’s latest advancements in edge audio AI. The demo features a suite of models purpose-built for real-world applications including automatic speech recognition, denoising, keyword spotting, and

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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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