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In-depth information about the edge AI and vision market, applications, technologies, products, and trends.

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Aerospace and Defense

Upcoming Event on AI Transformation

KOTRA Silicon Valley will host “Physical AI Superconnect 2026,” on June 24, 2026, from 10:00 am to 8:00 pm PDT at the Computer History Museum in Mountain View, California. The event will feature insightful presentations, technology exhibits, matchmaking and networking. From the event page: ​M.AX: A New Era of Manufacturing AI Transformation ​​Physical AI Superconnect

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Algorithms & Models

Synetic Debuts LYNX Computer Vision SDK at the 2026 Embedded Vision Summit

New SDK helps teams add real-time vision capabilities to robotics, industrial automation, security and edge AI systems with faster deployment, flexible integration and continuous model improvement REDMOND, Wash. — May 11, 2026 — Synetic, Inc., a provider of computer vision and synthetic data solutions for real-world AI systems, today announced the debut of LYNX, a

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News

Renesas Completes Acquisition of Irida Labs to Expand Vision AI Software Capabilities and Accelerates System-Level Vision Solutions

TOKYO, Japan ― Renesas Electronics Corporation (TSE:6723, “Renesas”), a premier supplier of advanced semiconductor solutions, today announced that a subsidiary of Renesas has completed the acquisition of Irida Labs, a Greece-based company specializing in embedded software for AI-powered visual perception systems. The acquisition strengthens Renesas’ edge AI embedded processing offerings, a key secular growth area for Renesas. It also enables system-level solutions that integrate physical AI and software to power camera and machine

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Market Analysis

Blog Posts

Key Trends Shaping the Semiconductor Industry in 2026

This blog post was originally published at HTEC’s website. It is reprinted here with the permission of HTEC.   The hardware boom is slowing down. What comes next is a software, power, and inference problem—and most of the industry isn’t ready for any of it. AI chips are now 0.2% of all chips manufactured, but

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Market Analysis

Humanoid Robots 2026-2036: Technologies, Markets, and Opportunities

Maturity of commercialization of humanoid robotics by application. For full data, refer to IDTechEx’s research on “Humanoid Robots 2026-2036: Technology, Market, and Opportunities” This blog post was originally published at IDTechEx’s website. It is reprinted here with the permission of IDTechEx. Automotive industry, logistics, home-use, key players and suppliers, AI chip, battery, actuator, motor, screw, tactile

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Consumer

Evaluating Waveguide Technologies for AR Smart Glasses

The difference in optical efficiency at wider FOV for the same technology type for several commercial waveguides. Data was normalized to the narrow FOV product, with arrows representing the reduction in efficiency for wide FOV waveguides developed by the same company. A clear reduction in optical efficiency for waveguides of the same technology at wider

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Blog

Blog Posts

ChiPy: Bridge Neural Networks and C++ on Silicon — Full Inference Pipelines with Zero CPU Round-Trips

This blog post was originally published at Quadric’s website. It is reprinted here with the permission of Quadric. The ChiPy DSL is Quadric’s Python framework for building complete on-chip pipelines. Using YOLOX-M as a case study, we show how backbone inference, box decoding, and NMS run entirely on the Chimera GPNPU — no host CPU intervention,

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Blog Posts

The New Baseline for Human-Centric Devices Starts with Always-On Edge AI Audio: Introducing the Synaptics® Astra™ SR80 Series

This blog post was originally published at Synaptics’ website. It is reprinted here with the permission of Synaptics. The devices we wear, carry, and live with are becoming our most personal AI companions—and that demands they be always aware, always private, and always delivering exceptional audio. The Astra™ SR80 Series delivers always-on Edge AI processing and

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Blog Posts

What is a spatial filter, and how does it enhance Depth Quality in ToF Cameras?

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Time-of-Flight (ToF) cameras generate depth maps by measuring the phase shift between emitted near-infrared light and its reflection. Each pixel records the shift, which is then converted into distance information. But raw depth maps tend to contain

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