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2024 Algorithm Improvements
Over the past year, we have reduced the data requirements 99% and the time by 97%
Emil Annevelink
Dec 2, 20242 min read


Scaling simulations to complex materials systems
Cropping allows us to generate training data from complex simulations to ensure the accuracy of 1000+ atom simulations
Emil Annevelink
Oct 30, 20243 min read


Why is uncertainty quantification necessary in machine learning?
Understanding and analyzing a system’s response to various inputs is central to any scientific or engineering R&D. Designing a new steel...
Emil Annevelink
Sep 25, 20244 min read


Eliminating hallucinations in machine learning models
Digitizing materials development requires materials models that can predict materials behavior accurately, quickly and cheaply. Digital...
Emil Annevelink
Aug 20, 20246 min read
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