Landing AI today announced the launch of LandingEdge, a new deployment application within the company’s flagship platform, LandingLens. With LandingEdge, manufacturers will more easily deploy deep learning visual inspection solutions to edge devices on the factory floor to better and more consistently detect product defects.
Announced at Automate 2022, North America’s largest automation trade show and conference, LandingEdge extends the capability of LandingLens into even more manufacturing environments. LandingLens enables teams to build deep learning models. With the new edge capabilities, LandingLens customers will more easily integrate with factory infrastructure to communicate with cameras, apply models to images and make predictions to inform real-time decision making on the factory floor. If the factory is connected to the cloud, LandingEdge can update LandingLens with new data to continuously improve deep learning models.
LandingLens has also been enhanced to enable training of a deep learning model up to seven times faster than before. By reducing the time, it takes to train models, customers achieve fast and iterative AI processes and optimize model accuracy.
“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, Vice President of Outreach and Vision Technology at Landing AI. “They put ever more powerful tools in the hands of manufacturers and systems integrators to quickly implement inspection solutions that result in lower costs, increased productivity, and improve customer product satisfaction.”
The mission of Landing AI, under the leadership of AI pioneer Andrew Ng, is to bring the benefits of deep learning-based inspection to all industries with its pioneering data-centric approach in which the power of deep learning is unleashed even if companies have limited datasets. First unveiled in 2020, LandingLens provides Landing AI’s customers with the end-to-end automated inspection platform that enables manufacturing, quality, and AI teams alike to quickly and easily train, test, confirm, and deploy visual inspection solutions based on high-quality and verified data on the plant floor.
Deep learning is a key machine vision trend for 2022 and beyond in industrial automated inspection applications. But deep learning is not magic and does not automatically make it easy to program an inspection system. As with any vision application, the quality of the input data — the images — is essential to the quality of the output. This is particularly true for data used to train an algorithm. In addition, proper labeling is essential for the implementation of a deep learning inspection system.
