Predictive maintenance has long been a topic of interest inindustry but implementing and scaling theoretical models into the real world hasproven to be fraught with challenges. However, by approaching the problem froma different angle, Senseye seeks to develop a scalable, general-purpose solutionthat can easily apply to the often less than ideal real-world data coming fromfactories. With intelligent use of AI models, predictive maintenance can be achievedwithout the use of the costly and difficult to scale bespoke models that havedominated the field for many years.In this final episode on predictive maintenance, hostSpencer Acain is joined by Dr. James Loach, Head of Research for SenseyePredictive Maintenance, to discuss Senseye’s unique approach, the struggles ofadopting predictive maintenance and AI in the real world, and what the futurefor AI holds.In this episode you will learn:·        General purpose decision support (1:06)·        Challenges of adoption (6:20)·        A rapidly changing world (10:02)