The whole world seems set on a course to take everyone into a highly automated and artificially intelligent future. The influence of Artificial Intelligence (AI) in smart manufacturing is growing rapidly. As written in our recent AI in Manufacturing report, the trend for a broader adaption of AI in manufacturing is fueled by internal and external factors. Such as demand for greater variety, traceability, flexibility, production efficiency, speed, faster market dynamics and lower operational costs. For example, manufacturing risks can be reduced by using AI solutions that learn and detect patterns and anomalies in the production process. At the same time, demand for higher quality of products is ensuring that AI solutions are used to achieve the last production mile at significantly lower costs.
AI chips, as the term suggests, refers to a new generation of microprocessors which are specifically designed to process artificial intelligence tasks faster, using less power. That's obvious, you might think, but some might wonder what the difference is between an AI chip and a normal chip when all chips of all kinds process only zeros and ones - after all, even a typical, classic processor is capable of performing AI tasks.
Graphics processing units (GPUs) are particularly good for AI-related tasks and therefore form the basis for many of the AI chips developed and offered today. Without going too deep, one can say that a general microprocessor is a universal system, and AI processors are embedded with logic gates and highly parallel computing systems that are more suitable for typical AI tasks, such as image processing, machine vision, machine learning, deep learning, artificial neural networks, and so on.
This is the reason why IPC manufacturers today no longer just enter into partnerships with the well-known chip manufacturers but also increasingly cooperate with specialized AI chip/board manufacturers, such as Advantech with NVIDIA. Advantech has developed an AI IPC product line, that not only focuses on industrial and production applications, but also develops products for transport and smart city applications.
As GPU computing becomes increasingly important in industry applications, like machine vision, 3D imaging, machine learning, big data analysis and other artificial intelligence applications, more and more end users, manufacturers and system integrators require GPU cards or other hardware AI chip solutions to be installed in the devices to take advantage of high speed and parallel computing power.
Important for industrial applications is a strict validation of the entire controller, IPC or edge device to ensure the thermal, mechanical and electrical requirements. This also applies to GPU cards. The whole unit must also meet the relevant industrial antivibration and high-temperature operating requirements. As AI in machinery and the corresponding hardware will increasingly gain importance, ARC will continuously watch, write and share the latest news with you. For more info, please contact ARC Advisory Group at Contact Us.