Software

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 […]

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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

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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

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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

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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

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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

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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

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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

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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

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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

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