New edge to cloud connectivity offers scalable advanced analytics and a unified, AI‑ready production data foundation. Industrial customers can optimize their operations, reduce costs and increase productivity. Siemens Industrial Edge and FFT DataBridge connect shopfloor and plant data directly to the Databricks Platform – with no IoT middleware required.

BitFlow Claxon Frame Grabbers accelerate AI-Driven machine vision systems with NVIDIA GPU performance. Full CoaXPress 2.0 throughput and direct GPU integration put real-time AI Inference within reach of vision engineers.

New Cisco research details how Industrial AI is moving into physical operations. The report provides a data-driven view into how industrial organizations are adopting AI, challenges companies face and the emerging opportunities as AI becomes embedded in physical systems, infrastructure and workflows.

OPC UA for standardized, secure communications, MQTT as a lightweight, publish/subscribe protocol ideal for IoT and edge devices and AI to leverage data from OPC UA and MQTT-enabled devices to deliver predictive maintenance, real-time quality control and adaptive learning is a powerful combination.

To capture the ROI of “thinking” robots and capitalize on agentic AI-powered robots, leaders should recast this shift as an information and decision rights transformation, not a hardware refresh.

Long-term strategic partnership between Nvidia and Dassault Systèmes aims to establish a shared industrial architecture for mission-critical artificial intelligence across industries.

To scale Physical AI, the next leap is the development of a Multimodal Large Language Model (MLLM), an AI model capable of understanding and reasoning across multiple input types including text, images, video, audio, LiDAR, and more.

NVIDIA is working with manufacturing and robotics leaders to drive reindustrialization using Physical AI.

Industrial edge computing processes data locally within industrial environments, enabling real-time analytics and machine control. It’s used in predictive maintenance, robotics, and quality assurance by reducing latency and enhancing automation.

In a recent blog post, IOTech’s Chief Technology Officer, Brad Corrion, shared his perspective on how “2026 will be the year that AI is deployed at the Edge”.