Johnson Electric Group and Cortica Group have formed joint venture company called Lean AI, a startup that aims to be a game changer in the quality inspection market by delivering an autonomous inspection system targeted at the manufacturing industry.
The new company will leverage Johnson Electric's vast knowledge and experience in manufacturing processes and Cortica's unique Autonomous AI Technology to revolutionise the visual inspection market.
Automating quality assurance in manufacturing through Autonomous AI will drive flawless quality and production while enabling simple and fast setup on the production line
"With the power of Cortica's Autonomous AI technology, and JE's vast knowledge of the market, Lean AI will deliver a product that reduces the cost of human error when it comes to quality inspection in manufacturing and address the vulnerabilities in the current market," said Karina Odinaev, CEO of Lean AI.
Austin Wang, senior vice president of Johnson Electric, said they are fully aware of the fundamental challenges in deploying an AI-based quality assurance software in the production environment – especially in terms of speed of deployment and reliability over time.
“However, Cortica’s autonomous AI technology can address a lot of these major headaches and allow for much faster and broader adoption.”
The Israel-based Cortica Group has developed Autonomous AI that simulates the natural processes of the mammal cortex. Its unsupervised approach to learning mimics the way the brain processes information: enabling machines to learn, collaborate and interact with the world without human input.
Wang also pointed out that Johnson Electric's deep experience in a wide range of manufacturing processes offers a unique platform for developing an AI-based quality assurance software for commercial use.
“The joint venture is also opening a new avenue for Johnson Electric to develop and market software offerings. It is therefore both a technological as well as business model innovation for us. There are also opportunities to apply the technology in predictive quality and expert systems as well. This is the second investment of Johnson Electric in Israeli technology, and we will continue to assess such relevant opportunities,” Wang said.
Seizing the opportunity in the global machine market
The newly-formed Lean AI hopes to tap into the growing global machine vision market, currently valued at US$11 billion, but is predicted to reach US$15.5 billion by 2026.
As these numbers continue to grow and AI technology advances, the opportunity for machine vision solutions to positively aid in manufacturers' earning potential with a reduction in defects gives way for a new system that will fundamentally change the industry's approach to quality assurance.
Today, supervised Deep Learning-Based Quality Assurance Systems can take weeks, up to months, to deploy. The existing systems are reliant on a data scientist or AI experts and require large manually tagged training sets with thousands of defect image examples. Requiring constant maintenance and re-training for the slightest variations, the system is unable to adapt to defects, new products, and new cameras.
Lean AI touts its technology surpasses existing challenges of prevalent supervised Deep Learning-Based Quality Assurance Systems with the power of unsupervised learning to process information within a fraction of a second, using unlabelled data, applies predictive quality assurance, and compiles data that increases the speed of deployment and scaling. As an open platform agnostic to camera, defect type and product, Lean AI can collaborate with any integrators, OEMs, and manufacturers of automation solutions.
"Cortica has developed self-learning AI that is fundamentally different from traditional deep learning systems. Autonomous AI Technology operates like a human brain - it's not a fixed system; instead, it continuously adapts itself to various scenarios and learns online in real-time. Its technology requires far less computing power, can be deployed at a fraction of the cost, and provides far superior performance outcomes," said Igal Raichelgauz, founder and chairman of Cortica. "Our technology is robust and generic and applicable within a multitude of signal domains such as visual, audio, time series and other domains; visual inspection is only the beginning. Autonomous AI technology is quickly becoming the benchmark for the industry."
