Software for Embedded Vision
Qualcomm Introduces a Full Suite of Robotics Technologies, Powering Physical AI from Household Robots up to Full-Size Humanoids
Key Takeaways: Utilizing leadership in Physical AI with comprehensive stack systems built on safety-grade high performance SoC platforms, Qualcomm’s general-purpose robotics architecture delivers industry-leading power efficiency, and scalability, enabling capabilities from personal service robots to next generation industrial autonomous mobile robots and full-size humanoids that can reason, adapt, and decide. New end-to‑end architecture accelerates automation
TI Accelerates the Shift Toward Autonomous Vehicles with Expanded Automotive Portfolio
New analog and embedded processing technologies from TI enable automakers to deliver smarter, safer and more connected driving experiences across their entire vehicle fleet Key Takeaways: TI’s newest family of high-performance computing SoCs delivers safe, efficient edge AI performance up to 1200 TOPS with a proprietary NPU and chiplet-ready design. Automakers can simplify radar designs and
Synopsys Showcases Vision For AI-Driven, Software-Defined Automotive Engineering at CES 2026
Synopsys solutions accelerate innovation from systems to silicon, enabling more than 90% of the top 100 automotive suppliers to boost engineering productivity, predict system performance, and deliver safer, more sustainable mobility Key Takeaways: Synopsys will support the Fédération Internationale de l’Automobile (FIA), the global governing body for motorsport and the federation for mobility organizations
Ambarella Launches a Developer Zone to Broaden its Edge AI Ecosystem
SANTA CLARA, Calif., Jan. 6, 2026 — Ambarella, Inc. (NASDAQ: AMBA), an edge AI semiconductor company, today announced during CES the launch of its Ambarella Developer Zone (DevZone). Located at developer.ambarella.com, the DevZone is designed to help Ambarella’s growing ecosystem of partners learn, build and deploy edge AI applications on a variety of edge systems with greater speed and clarity. It
ChatTag: Bringing ChatGPT Vision to Image Annotation in OpenFilter
This blog post was originally published at Plainsight Technologies’ website. It is reprinted here with the permission of Plainsight Technologies. Image annotation has always been one of those tasks that’s both essential and tedious. Whether you’re labeling thousands of product photos for a retail model or identifying components in industrial footage, manual annotation is time-consuming and
Chips&Media and Visionary.ai Unveil the World’s First AI-Based Full Image Signal Processor, Redefining the Future of Image Quality
The collaboration marks a breakthrough in real-time video, bringing software-upgradable imaging to the edge. 5th January, 2026 Seoul, South Korea and Jerusalem, Israel — Chips&Media, Inc. (KOSDAQ:094360) a leading hardware IP provider with more than 20 years of leadership in the multimedia industry, and Visionary.ai, the Israeli startup pioneering AI software for image processing,
The Architecture Shift Powering Next-Gen Industrial AI
This blog post was originally published at Arm’s website. It is reprinted here with the permission of Arm. How Arm is powering the shift to flexible AI-ready, energy-efficient compute at the “Industrial Edge.” Industrial automation is undergoing a foundational shift. From industrial PC to edge gateways and smart sensors, compute needs at the edge are changing fast. AI is moving
Nota AI Signs Technology Collaboration Agreement with Samsung Electronics for Exynos AI Optimization “Driving the Popularization of On-Device Generative AI”
Nota AI’s optimization technology integrated into Samsung Electronics’ Exynos AI Studio, enhancing efficiency in on-device AI model development Seoul, South Korea Nov.26, 2025 — Nota AI, a company specializing in AI model compression and optimization, announced today that it has signed a collaboration agreement with Samsung Electronics’ System LSI Business to provide its AI
Introducing Gimlet Labs: AI Infrastructure for the Agentic Era
This blog post was originally published at Gimlet Labs’ website. It is reprinted here with the permission of Gimlet Labs. We’re excited to finally share what we’ve been building at Gimlet Labs. Our mission is to make AI workloads 10X more efficient by expanding the pool of usable compute and improving how it’s orchestrated. Over the
Au-Zone Technologies Expands EdgeFirst Studio Access
Proven MLOps Platform for Spatial Perception at the Edge Now Available CALGARY, AB – November 19, 2025 – Au-Zone Technologies today expands general access to EdgeFirst Studio™, the enterprise MLOps platform purpose-built for Spatial Perception at the Edge for machines and robotic systems operating in dynamic and uncertain environments. After six months of successful
Enabling Autonomous Machines: Advancing 3D Sensor Fusion With Au-Zone
This blog post was originally published at NXP Semiconductors’ website. It is reprinted here with the permission of NXP Semiconductors. Smarter Perception at the Edge Dusty construction sites. Fog-covered fields. Crowded warehouses. Heavy rain. Uneven terrain. What does it take for an autonomous machine to perceive and navigate challenging real-world environments like these – reliably, in
The Role of Edge Computing in Video Intelligence
This blog post was originally published at Network Optix’ website. It is reprinted here with the permission of Network Optix. In many industries, decisions need to be made within seconds. Delayed responses can mean the difference between preventing an incident and simply reviewing it after the fact. Traditional video systems, which rely on transmitting data offsite
The Need for Continuous Training in Computer Vision Models
This blog post was originally published at Plainsight Technologies’ website. It is reprinted here with the permission of Plainsight Technologies. A computer vision model that works under one lighting condition, store layout, or camera angle can quickly fail as conditions change. In the real world, nothing is constant, seasons change, lighting shifts, new objects appear and
Why Openness Matters for AI at the Edge
This blog post was originally published at Synaptics’ website. It is reprinted here with the permission of Synaptics. Openness across software, standards, and silicon is critical for ensuring interoperability, flexibility, and the growth of AI at the edge AI continues to migrate towards the edge and is no longer confined to the datacenter. Edge AI brings
Bringing Edge AI Performance to PyTorch Developers with ExecuTorch 1.0
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. ExecuTorch 1.0, an open source solution to training and inference on the Edge, becomes available to all developers Qualcomm Technologies contributed the ExecuTorch repository for developers to access Qualcomm® Hexagon™ NPU directly This streamlines the developer workflow
NVIDIA Contributes to Open Frameworks for Next-generation Robotics Development
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. At the ROSCon robotics conference, NVIDIA announced contributions to the ROS 2 robotics framework and the Open Source Robotics Alliance’s new Physical AI Special Interest Group, as well as the latest release of NVIDIA Isaac ROS. This
Unleash Real-time LiDAR Intelligence with BrainChip Akida On-chip AI
This blog post was originally published at BrainChip’s website. It is reprinted here with the permission of BrainChip. Accelerating LiDAR Point Cloud with BrainChip’s Akida™ PointNet++ Model. LiDAR (Light Detection and Ranging) technology is the key enabler for advanced Spatial AI—the ability of a machine to understand and interact with the physical world in three
NVIDIA Blackwell: The Impact of NVFP4 For LLM Inference
This blog post was originally published at Nota AI’s website. It is reprinted here with the permission of Nota AI. With the introduction of NVFP4—a new 4-bit floating point data type in NVIDIA’s Blackwell GPU architecture—LLM inference achieves markedly improved efficiency. Blackwell’s NVFP4 format (RTX PRO 6000) delivers up to 2× higher LLM inference efficiency
