When a company like Nvidia invests heavily in the Industrial Internet of Things market like it has with the introduction of the Jetson brand of embedded processors, it turns a lot of people's heads. But will the company have the same type of impact it has had on industrial automation that it has on the datacenter universe by offering endless amounts of GPU horsepower to tackle the inferencing, machine language and computer vision applications installed on assembly lines? The smart money says eventually but it will take a while.
Nvidia has tried to demonstrate its commitment to the industrial embedded market and one of its goals is to revolutionize edge processing tasks for Artificial Intelligence in factories to make assembly lines more productive through improved quality control, predictive maintenance, autonomous vehicle operation and visual inspection among other things. Some industry watchers say generative AI is now gaining momentum in the industrial automation space.
But can you just imagine how Nvidia's overtures are going over with the people who operate assembly lines? Anecdotal evidence supports the theory that manufacturing technology adoption for industrial users occurs at a much slower pace than it does for datacenter users. Factory tech personnel eschew pie-in-the-sky productivity promises that leading-edge technology offers because they place more weight on safety, security, reliability and 24-hour uptime. New technology is often perceived as unnecessarily disruptive in a manufacturing environment, and it poses risk to the continuous flow of operations because it introduces challenges.
A deeper dive into the innovative technology that IIOT providers are promising for factories reveals some of the end-user benefits that may stir demand. Perhaps a small handful of industries will adopt the latest and greatest as soon as they are available, but every environment is different and so actual results may vary.
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