During the organized workshop together with cboost, two companies developed their individual use cases for AI in manufacturing, including a pitch on how to implement more AI in their organization.
Cboost is an engineering company and a social enterprise that provides high-tech consultancy and engineering services. Using robotics and artificial intelligence, they develop technological business solutions that improve processes and make them more sustainable.
Cboost’s multidisciplinary team of engineers and consultants mix and match technologies to create full-scale solutions. Services range from developing and integrating AI into machines to helping create digital strategies and training employees to use intelligent technology.
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3 takeaways from Laurens from cboost about how data and AI actually play a role in manufacturing
The accessibility, quality, and quantity of data used for training AI models is the number 1 factor determining successful implementation of AI.
The self-learning algorithms that power AI, particularly Neural Networks, are sometimes seen as autonomous and ambiguous fix-it-all machines. In reality, however, every implementation of the software requires careful network design specific to the task and tuning by experts.
Fueled by Sci-Fi and Pop Culture, Robotics and AI are often mentioned in the same breath. In the real world, however, these technologies have long been applied completely separately. Only very recently we start to see joint implementations of these technologies, with Smart Manufacturing and Smart Logistics being the pioneering industries.