Editorial: The emergence of AI in additives development, TAPPI Journal March 2025

 


Machine learning holds immense potential to sift through enormous datasets in the hope of uncovering insights buried deep within. But what is all too easy to overlook in all the enthusiasm is that these tools are not magic. They do not work well with just any dataset. These new tools work best with large, high-quality, cleaned, and wellorganized data pools. This reality can create a dilemma: in the early stages of developing genuinely innovative solutions to the complex problems our industry faces, such datasets are often unavailable — and without them, we must rely on traditional investigator-driven research.

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Author: Scott Rosencrance and Anthony Petty II
Editorial: The emergence of AI in additives development, TAP
ABSTRACT: The continuing evolution of artificial intelligence (AI) and its penetration into the core of the world of papermaking were undeniable at TAPPICon 2024 and especially within the content presented and sponsored by TAPPI’s Papermaking Additives Committee. On one side of the spectrum, there were traditional methods of chemical development and application grounded in natural intelligence, while on the other, there was the emerging presence of algorithmic decision-making and machine learning within the development cycle. The latter technology is brimming with the kind of promise that could reshape how additives are conceived, developed, and applied, turning what was once a matter of trial and error into something far more precise and previously out of reach.
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