congatec – a leading supplier of high-performance embedded computing products – and the Japanese AI experts at Hacarus today unveiled the world’s first embedded computing kit for Artificial Intelligence (AI) that uses Sparse Modeling technology. Sparse Modeling needs little training data to make highly accurate predictions. This is an advantage for vision-based inspection systems, among others, because the reject rate is naturally lower when manufacturing quality is high. With Sparse Modeling it is possible to create a new inspection model starting with 50 or even fewer images. This is significantly less than the 1,000 or more images required for traditional AI. The Sparse Modeling Kit, available from Hacarus, can be used stand-alone or as an add-on to existing inspection systems. Primary customers are vision system providers and system integrators. Another group of users includes machine and system builders who want to use vision-based AI in their devices but have been reluctant to do so up to now, because the wide variety of individual customer installations requires algorithms to be adapted, which was previously too costly.
“With Sparse Modeling, developers are able to build next-generation inspection systems that can be trained for individual requirements and can therefore function anywhere. There is no longer a need for optimal conditions, such as constant lighting. OEMs also gain greater flexibility to adapt to changing production processes, which is essential for the move to industrial IoT/Industry 4.0 controlled batch size production,” explains Christian Eder, Director of Marketing at congatec.
Essentially, Sparse Modeling is a data modeling approach that focuses on identifying unique characteristics. Simply put, Sparse Modeling interprets data similar to the human brain, instead of analyzing every single hair and every millimeter of a person.
