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“AGI Meets the Real World—Toward Reasoning, Planning and Acting Beyond Book Intelligence,” a Presentation from Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University

Algorithms & Models, Edge AI and Vision Alliance, Summit 2026, Videos /

Eric Xing, President and Professor at Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University presents “AGI Meets the Real World—Toward Reasoning, Planning and Acting Beyond Book Intelligence” at the May 2026 Embedded Vision Summit. LLMs like OpenAI’s GPTs have fascinated the public with their astounding capabilities on… “AGI Meets the Real World—Toward […]

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In-Cabin Image Quality Testing

Automotive, Blog Posts, Image Engineering, Sensors and Cameras /

This blog post was originally published at Image Engineering’s website. It is reprinted here with the permission of Image Engineering. As the automotive industry continues its path toward full automation, one area of focus has become the in-cabin monitoring systems, often referred to as driver and occupant monitoring systems (DMS/OMS). These systems use cameras and sensors

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Perforated AI Releases Enhanced ResNet-18 Model on Hugging Face

Algorithms & Models, News, Perforated /

Perforated AI has released an enhanced version of ResNet-18 designed to approach the accuracy of larger vision models without imposing a comparable increase in model size or computational cost. The pretrained model is now available for evaluation and transfer learning on Hugging Face. The company’s technology adds artificial dendrites—additional computational structures inspired by biological neurons—to

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BrainChip Partners With Orama.AOI For AI-Fueled Defect Detection

Algorithms & Models, BrainChip, Industrial Vision (Computer Vision), News, Processors /

Assessing tire defects is another use case in the market for neuromorphic AI chip solutions LAGUNA HILLS, CA, UNITED STATES, August 13, 2026 /EINPresswire.com/ — A global leader in ultra-low power, fully digital, event-based neuromorphic AI, today announced a partnership with Atlanta-based Orama.AOI, which has retrained and optimized BrainChip’s Akida models using its industrial inspection

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“Self-Compression for Edge Inference,” a Presentation from Imagination Technologies

Algorithms & Models, Edge AI and Vision Alliance, Imagination Technologies, Summit 2026, Videos /

James Imber, Director of Research at Imagination Technologies presents “Self-Compression for Edge Inference” at the May 2026 Embedded Vision Summit. Self-compression is a quantization-aware training technique to reduce neural network size and optimize performance for edge inference. By learning optimal bit depths for weights and activations during training, self-compression achieves… “Self-Compression for Edge Inference,” a

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Why Model Zoos Fall Short in Production AI

Algorithms & Models, Blog Posts, ModelCat /

This blog post was originally published at ModelCat’s website. It is reprinted here with the permission of ModelCat. Artificial intelligence has advanced rapidly over the past decade, fueled in large part by the availability of pre-trained models and shared research. One of the most visible outcomes of this progress is the rise of the “model zoo”—collections

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“Introduction to Simultaneous Localization and Mapping: From Block Diagrams to Real Systems,” a Presentation from eInfochips (an Arrow company)

Algorithms & Models, Edge AI and Vision Alliance, eInfochips, Summit 2026, Videos /

Amit Gupta, Associate Director–Solution Architecture and Head of Robotics CoE at eInfochips (an Arrow company) presents “Introduction to Simultaneous Localization and Mapping: From Block Diagrams to Real Systems” at the May 2026 Embedded Vision Summit. Simultaneous localization and mapping (SLAM) is the core capability that allows robots and autonomous systems… “Introduction to Simultaneous Localization and

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Physical AI: Bridging Silicon, Software, and the Real World

Blog Posts, Processors, Robotics, Synopsys /

This blog post was originally published at Synopsys’s website. It is reprinted here with the permission of Synopsys.   AI is quickly emerging from its digital confines as something new: physical AI. This evolving incarnation pushes beyond the realm of information — code, text, images, video — and enables machines to sense, decide, and act in the

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Microchip Advances Edge AI Sensor Connectivity with Rev 2.0 PolarFire® FPGA Ethernet Sensor Bridge

Micron Technology, News, NVIDIA, Processors, Sensors and Cameras /

h3>Smaller, multi-camera platform enables scalable Ethernet architectures for NVIDIA Edge AI systems while lowering power, cost and integration complexity CHANDLER, Ariz., August 11, 2026 — The shift toward compact, high‑performance edge AI systems is redefining sensor connectivity, pushing developers to deliver power‑ and space‑efficient architectures that remain secure, scalable and future‑ready. To address these challenges, Microchip

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“Understanding Transformers: From LLMs to Context-Aware Multimodal Models,” a Presentation from Synopsys

Algorithms & Models, Edge AI and Vision Alliance, LLMs, Summit 2026, Synopsys, Videos /

Tom Michiels, System Architect at Synopsys presents “Understanding Transformers: From LLMs to Context-Aware Multimodal Models” at the May 2026 Embedded Vision Summit. Transformers have become the foundation of modern AI, reshaping how products are built and how businesses operate. In this talk Michiels explains why transformers replaced earlier models, what… “Understanding Transformers: From LLMs to

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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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