How much computing power is needed at the edge? How much memory and storage are enough for AI at the edge? Minimum requirements are growing as AI opens the door to innovative applications that need more and faster processing, storage, and memory.
The investment reflects BOWE's strategic view of robotics in the future of automation and is a vote of confidence in MOV.AI's innovative approach to robot software.
There are many ways of combining these three technologies, but a handful of applications stand out today. They reveal some key benefits of AR, VR and robots working together.
With advancements in artificial intelligence (AI) and 5G network connectivity, smart-road infrastructure technology offers the promise of being added to many different roads, bridges, and other transit systems across the U.S.
Learn How To Protect Your Business with AI for Visual Inspection - Pleora Webinar Live April 6, 2022
This webinar will discuss how two manufacturers - a distillery and an electronics assembly operation - are using camera-based visual inspection to protect their brand and make manual processes repeatable, consistent, and traceable.
In general, the more data an artificial intelligence device can capture, the better it will perform. This fact may influence some businesses to use specific robots and autonomous machines that are designed to be compatible with their existing technologies.
Research is shedding light on how autonomous systems can foster human confidence in robots. Largely, the research suggests that humans have an easier time trusting a robot that offers some kind of self-assessment as it goes about its tasks.
The lettuce's outer, or 'wrapper', leaves will be mechanically removed to expose the stem. Machine vision and artificial intelligence are then used to identify a precise cut point on the stem to neatly separate the head of lettuce.
Private 5G Connectivity and AI Technologies Accelerate the Transformation From Automation to Autonomy
This article looks at private 5G (known as P5G) and how it supports advanced and emerging technologies, including AI cameras, enabling manufacturers to drive more functionality closer to the edge.
DeepMap, Metropolis, and ReOpt improve performance for fleets of autonomous mobile robots amid expectations for nearly 6x increase in robot sites by 2025.
Any policy that slows down the use of automation will cause operational inefficiencies. This is the last thing we need considering the global supply chain crisis.
The demand for AI-driven robotics is increasing in operations like those in manufacturing and warehouse settings to help organizations with data and analytics that identify problems in real time, improve decision making, and perform tasks more efficiently.
Like transformative technologies that came before, the ethics of AI is coming under increased scrutiny, giving birth to regulations and policies constraining the scope of its application.
While most manufacturing companies have begun to explore the next step in automation technology -- artificial intelligence (AI) and machine learning (ML) -- a large gap exists between where they want their organizations to be with AI technology and where they are.
IoT and mobile app development are two such prospects that industry analysts believe can reshape our lives in significant ways. Collectively, these technologies are expected to dominate the future and bring a never-seen change in enterprises across the niches.
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Agile and powerful Matrox Design Assistant® X takes the gymnastics out of vision application development. The flowchart-based software removes the need for coding; it's equally adept with simple application development or solving complex vision projects. Get a leg up with traditional vision tools to inspect, locate, measure, and read in images and 3D scans, plus deep learning tools