Making AI Come to Life in Heavy Industry – with Nikunj Mehta of Falkonry

Matthew DeMello

Matthew is Senior Editor at Emerj, focused on enterprise AI use-cases and trends. He previously served as podcast producer with CrossBorder Solutions, a venture-back AI-enabled tax solutions firm. Prior, Matthew served three years at the World Policy Institute as a news editor and podcast producer.

Making AI Come 
to Life in Heavy 

While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.

Several potential ROI-adding use cases exist for AI and machine learning in steel manufacturing. A casual search in a reputable database (e.g., Researchgate or similar) will reveal various works published by SMEs within the industry. 

Many of the reported use cases revolve around machine learning. Because steelmaking involves complex scientific processes (e.g., physics) and the combination of science and technology (e.g., metallurgy), many correlations and variables need to be made fully transparent and understood. 

Machine learning can ingest large data stores and uncover said correlations and variables. Teams can then use thi...

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