Software for Embedded Vision
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
Robotics Builders Forum offers Hardware, Know-How and Networking to Developers
On February 25, 2026 from 8:30 am to 5:30 pm ET, Advantech, Qualcomm, Arrow, in partnership with D3 Embedded, Edge Impulse, and the Pittsburgh Robotics Network will present Robotics Builders Forum, an in-person conference for engineers and product teams. Qualcomm and D3 Embedded are members of the Edge AI and Vision Alliance, while Edge Impulse
On-Device LLMs in 2026: What Changed, What Matters, What’s Next
Editor’s note: Vikas Chandra is one of the keynote speakers for the 2026 Embedded Vision Summit. Check out his upcoming keynote “Scaling Down is the New Scaling Up here. The Embedded Vision Summit runs May 11-13, 2026 in Santa Clara, California. In On-Device LLMs: State of the Union, 2026, Vikas Chandra and Raghuraman Krishnamoorthi explain
Voyager SDK v1.5.3 is Live, and That Means Ultralytics YOLO26 Support
Voyager v1.5.3 dropped, and Ultralytics YOLO26 support is the big headline here. If you’ve been following Ultralytics’ releases, you’ll know Ultralytics YOLO26 is specifically engineered for edge devices like Axelera’s Metis hardware. Why Ultralytics YOLO26 matters for your projects: The architecture is designed end-to-end, which means no more NMS (non-maximum suppression) post-processing. That translates to simpler deployment and
Free Webinar Highlights Compelling Advantages of FPGAs
On March 17, 2026 at 9 am PT (noon ET), Efinix’s Mark Oliver, VP of Marketing and Business Development, will present the free hour webinar “Why your Next AI Accelerator Should Be an FPGA,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: Edge AI system developers often
