Predictive maintenance has long been a topic of interest in

industry but implementing and scaling theoretical models into the real world has

proven to be fraught with challenges. However, by approaching the problem from

a different angle, Senseye seeks to develop a scalable, general-purpose solution

that can easily apply to the often less than ideal real-world data coming from

factories. With intelligent use of AI models, predictive maintenance can be achieved

without the use of the costly and difficult to scale bespoke models that have

dominated the field for many years.

In this final episode on predictive maintenance, host

Spencer Acain is joined by Dr. James Loach, Head of Research for Senseye

Predictive Maintenance, to discuss Senseye’s unique approach, the struggles of

adopting predictive maintenance and AI in the real world, and what the future

for 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)