Software for Embedded Vision
2026: The Year Intelligence Gets Physical
This article was originally published at Analog Devices’ website. It is reprinted here with the permission of Analog Devices. Artificial intelligence is entering a new phase where models interpret contextual data whilst interacting with the physical world in real time. At Analog Devices, Inc. (ADI), we call this Physical Intelligence: intelligent systems that can perceive, reason
Why Night HDR Is More Challenging Than Daytime HDR
This blog post was originally published at Visidon’s website. It is reprinted here with the permission of Visidon. High Dynamic Range (HDR) imaging has become a standard feature in modern cameras, from smartphones to automotive and surveillance systems. While daytime HDR is already a complex task, nighttime HDR introduces a completely different level of difficulty. The same
AI-Assisted Coding: The Next Step in Abstraction
I’ve been using AI-assisted coding for my work a lot recently, and I’ll admit, I wasn’t sure how I felt about it. Was I cheating? How do I know it’s right? Do I admit to using it? Looking at how software development has evolved over time helped answer those questions and led to a few
NVIDIA, T-Mobile and Partners Integrate Physical AI Applications on AI-RAN-Ready Infrastructure
News Summary: T-Mobile pilots NVIDIA RTX PRO 6000 Blackwell Server Edition AI infrastructure to demonstrate physical AI applications at the edge, complementing the AI-RAN Innovation Center’s distributed network Physical AI developers including Fogsphere, LinkerVision, Levatas, Vaidio and Siemens Energy are building reasoning and vision AI agents to the edge using the NVIDIA Metropolis Blueprint for
NVIDIA and Global Robotics Leaders Take Physical AI to the Real World
News Summary: Physical AI leaders across robot brain developers, industrial, and surgical robot giants and humanoid pioneers including ABB Robotics, AGIBOT, Agility, CMR Surgical, FANUC, Figure, Hexagon Robotics, KUKA, Medtronic, Skild AI, Universal Robots, World Labs and YASKAWA are building on NVIDIA technology to develop and deploy physical AI at scale. NVIDIA unveils new NVIDIA
Edge Container Registries Explained: How to Distribute Images Reliably at Scale
This blog post was originally published at Avassa’s website. It is reprinted here with the permission of Avassa. A mostly hidden piece of the container application puzzle is the image registry. If you’ve used Linux containers, you’ve come across one: it’s where container images are stored. Registries can be public (like Docker Hub) or private,
RTOS vs. Bare-Metal: Decision Matrix Tool for Projects Based on High-End Microcontrollers
This blog post was originally published at eInfochips’ website. It is reprinted here with the permission of eInfochips. Introduction When building a system with a powerful microcontroller (MCU) or microprocessor, such as an ARM Cortex-M4, M7, R5, RXv3, A15, or A53—one of the key decisions developers face is whether to use bare-metal programming or a
Conversations at the Edge with NXP
This blog post was originally published at Au-Zone’s website. It is reprinted here with the permission of Au-Zone. Are Single-Sensor Robots Obsolete? We think so, and we’re here to show you why. Au-Zone is proud to be featured in NXP Semiconductors’ Conversations at the Edge video series, a multi-part collaboration exploring innovation at the intersection of
Accelerating Product Development in the Era of Physical AI
This video was originally published at Peridio’s website. It is reprinted here with the permission of Peridio. The embedded world is undergoing its biggest transformation in a generation. AI workloads are now moving into the physical world — into cameras, robots, tractors, and drones — and edge devices are evolving into intelligent agents. Yet the
Why On-device AI Matters
This blog post was originally published at ENERZAi’s website. It is reprinted here with the permission of ENERZAi. Hello! I’m Minwoo Son from ENERZAi’s Business Development team. Through several posts so far, we’ve shared ENERZAi’s full-stack software capabilities for delivering high-performance on-device AI — including Optimium, our proprietary AI compiler that encapsulates our optimization expertise;
Upcoming Webinar on LLM-driven Driver Development
On March 19, 2026, at 1:00 pm EDT (10:00 am PDT) Boston.AI will deliver a webinar “Intelligent Driver Development with LLM Context Engineering ” From the event page: Developing even simple sensor drivers can consume valuable engineering time, requiring manual transcription of registers from datasheets into code—an error-prone and repetitive process. In this webinar, you’ll
HCLTech unveils VisionX 2.0, a next-gen multi-modal AI Edge Platform with NVIDIA
Noida, India, February 20, 2026 — HCLTech, a leading global technology company, today unveiled VisionX 2.0, an upgraded version of its multi-modal AI edge platform. This platform delivers real-time intelligence, enhanced safety and operational efficiency at scale for mission-critical industrial environments. VisionX 2.0 builds on HCLTech’s award-winning Intelligent Secure Edge capabilities, integrating advanced computer vision, vision language
Ambarella to Showcase “The Ambarella Edge: From Agentic to Physical AI” at Embedded World 2026
Enabling developers to build, integrate, and deploy edge AI solutions at scale SANTA CLARA, Calif., — Ambarella, Inc. (NASDAQ: AMBA), an edge AI semiconductor company, today announced that it will exhibit at Embedded World 2026, taking place March 10-12 in Nuremberg, Germany. At the show, Ambarella’s theme, “The Ambarella Edge: From Agentic to Physical AI,”
Production-Ready, Full-Stack Edge AI Solutions Turn Microchip’s MCUs and MPUs Into Catalysts for Intelligent Real-Time Decision-Making
Chandler, Ariz., February 10, 2026 — A major next step for artificial intelligence (AI) and machine learning (ML) innovation is moving ML models from the cloud to the edge for real-time inferencing and decision-making applications in today’s industrial, automotive, data center and consumer Internet of Things (IoT) networks. Microchip Technology (Nasdaq: MCHP) has extended its edge AI offering
Accelerating next-generation automotive designs with the TDA5 Virtualizer™ Development Kit
This blog post was originally published at Texas Instruments’ website. It is reprinted here with the permission of Texas Instruments. Introduction Continuous innovation in high-performance, power-efficient systems-on-a-chip (SoCs) is enabling safer, smarter and more autonomous driving experiences in even more vehicles. As another big step forward, Texas Instruments and Synopsys developed a Virtualizer Development Kit™ (VDK) for the
Into the Omniverse: OpenUSD and NVIDIA Halos Accelerate Safety for Robotaxis, Physical AI Systems
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. NVIDIA Editor’s note: This post is part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advancements in OpenUSD and NVIDIA Omniverse. New NVIDIA safety
Driving the Future of Automotive AI: Meet RoX AI Studio
This blog post was originally published at Renesas’ website. It is reprinted here with the permission of Renesas. In today’s automotive industry, onboard AI inference engines drive numerous safety-critical Advanced Driver Assistance Systems (ADAS) features, all of which require consistent, high-performance processing. Given that AI model engineering is inherently iterative (numerous cycles of ‘train, validate, and
Production Software Meets Production Hardware: Jetson Provisioning Now Available with Avocado OS
This blog post was originally published at Peridio’s website. It is reprinted here with the permission of Peridio. The gap between robotics prototypes and production deployments has always been an infrastructure problem disguised as a hardware problem. Teams build incredible computer vision models and robotic control systems on NVIDIA Jetson developer kits, only to hit
