Max Versace, CEO, Neurala, a deep learning neural network software company, and founding director of Neuromorphics Lab at Boston University. Read Max Versace's full executive profile here.
Manufacturing is changing. Often embracing the “what isn't broken shouldn't be touched” mindset, production lines are today forced to embrace more robotics, automation and artificial intelligence out of necessity. The Fourth Industrial Revolution is driven by labor shortages, reshoring, supply chain shortages and market and competitive pressure. However, the path to integration of new technologies such as AI in manufacturing is prone to misconceptions and challenges.
Take, for example, the case of a hypothetical company that builds packaging machines for consumer goods. Gathering relevant data, whether from cameras already built into machinery or from new cameras installed for the task, is just the tip of the iceberg. The quality and quantity of data play an essential role in AI's effectiveness, particularly in deep learning, which can be a resource-intensive endeavor.
Nothing is stationary—not even factory floors. Production runs and products vary and so does the environment where these goods are produced. It's therefore a misconception to assume that once AI is successfully deployed, it can operate indefinitely without further intervention.
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