How a Global Energy Company Adopts ML & AI with Nicholas Osborn - #150

Cognitive Assets

Nicholas Osborn from AES Corporation shares insights into the company's use of cognitive assets for predictive maintenance and asset tuning. He explains how these efforts have led to significant improvements, such as anomaly detection in facilities and asset tuning, drawing parallels to Google's data center efficiency improvements 1. Nicholas highlights the broad scope of cognitive assets, emphasizing their role in enhancing operational efficiency 2.

Cognitive assets is a bit of a broad category for us, where we look at a number of prediction type capabilities there and really looking at that, anomaly detection in a facility, predicted maintenance and those sort of things.

--- Nicholas Osborn

These advancements underscore the potential of machine learning in optimizing energy operations.

   

Safety Data

AES Corporation's exploration of AI for safety assessments faced challenges, as Nicholas Osborn describes their attempts to analyze safety data through language processing. Despite initial setbacks, the team utilized tools from Cortical to analyze cultural survey responses, aiming to benchmark statements and identify safety triggers 3. Nicholas also mentions the company's efforts to engage employees with machine learning tools, fostering hands-on experience through various platforms 4.

We used the tool from cortical, and we did a number of different analyses, but what we were looking to do is benchmark those statements against 60 other statements that we had.

--- Nicholas Osborn

These initiatives highlight the complexities and potential of AI in enhancing workplace safety.