Train your edge: Landing AI adds LandingEdge deployment application for edge devices
AI pioneer Andrew Ng’s Landing AI is expanding its capabilities to enable manufacturers to deploy deep learning visual inspection solutions to industrial edge devices. LandingEdge, now part of the LandingLens platform, enables real-time monitoring that will help industrial manufacturing, quality, and AI teams to make quick decisions by training deep learning models, testing them on edge devices, and retraining the models with new datasets.
Through the introduction of LandingEdge, customers have the flexibility to integrate new capabilities with industrial infrastructure to communicate with edge devices, according to the company. This will also give industrial engineering teams the ability to apply complex deep learning models to the incoming data and make informed predictions for operational efficiency. Provided that the existing infrastructure is connected to the cloud, Landing AI’s LandingEdge can update the AI models continuously with new datasets improvising the accuracy of the algorithms.
“These products mark huge steps in bringing deep learning solutions to the factory floor that are easily integrated to perform an automated inspection for a broad range of applications,” said David L. Dechow, VP of Outreach and Vision Technology at Landing AI. “They put more powerful tools in the hands of manufacturers and systems integrators to quickly implement inspection solutions that result in lower costs, increased productivity, and improved customer product satisfaction.”
LandingLens is an end-to-end automated AI visual inspection platform that enables engineers to collaboratively train, test, and deploy deep-learning models based on verified data from edge devices deployed in the industrial environment. The platform is a data-centric MLOps platform which indicates that the platform focuses on data instead of the AI software or code and gives an efficient way for manufacturers to train AI models. Some of the key benefits of the platform are data management, which includes a variety of tools to help the team understand the defects, and model iteration, which is about flexibility to remove the complexity of training models with open-source code and a custom environment.
“LandingLens helps improve inspection accuracy and reduce false positives,” said the company in the product brochure. “The end-to-end platform standardizes deep learning solutions that reduce development time and scale projects easily to multiple facilities across the globe. Our focus remains on our customers and continual product innovation to solve the real-world problems of the manufacturing audience.”
Article Topics
Andrew Ng | deployment | edge AI | edge devices | Landing AI | model training
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