Machine AI TechnologyMachine AI including deep learning and neural networks, are the next generation of software enhancements supporting and improving performance of traditional machine vision methods. Combining the two software principles allows for complex and quite often ‘inconsistent’ applications to be developed without hundreds of software programming hours, but rather time invested in training ‘models’ for good and bad, continually improving the system capability.
Vision AI offer industry capabilities in design and technical skillsets required to implement cutting edge application architecture.
We do not oversell Machine AI and it’s capabilities, just like machine vision there are fundamental design principles required for the system and hardware selection. Implementing AI systems requires intrinsic planning with a client willing to understand the process and methods required to build effective datasets during normal operation.
At this stage, Machine AI technologies generally compliment traditional machine vision systems.
Machine AI CapabilitiesArtificial intelligence and specifically deep learning and CNNs (neural networks) are getting more and more powerful, enabling learning on visual information to train machine systems to interpret data in a way somewhat resembling how a human eye works.
AI solutions can serve very specific requirements, and enables an increasing number of applications that weren’t possible before. Moreover, the performance of existing applications can be significantly improved. Especially in the field of data classification, deep learning is a very efficient technology. Many industries and sectors are already benefiting from the new opportunities, such as agriculture, mechanical engineering, pharmaceuticals, logistics, etc.
How Is It Different?Data labeling is an essential task for many Deep Learning projects. During labeling, the user adds the information to the system about how the problem is solved correctly. Depending on the method, this will determine the solution reliability.
