# 'AI-at-scale' method accelerates atomistic simulations for scientists

**URL:** <https://community.materialssquare.com/t/ai-at-scale-method-accelerates-atomistic-simulations-for-scientists/1045>\
**Category:** News\
**Created:** [December 13, 2024, 6:47pm UTC](https://community.materialssquare.com/t/ai-at-scale-method-accelerates-atomistic-simulations-for-scientists/1045 "2024-12-13T18:47:56Z")\
**Posts on this page:** 1\
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**Author:** ![gabriele1](https://yyz1.discourse-cdn.com/flex003/user_avatar/community.materialssquare.com/gabriele1/32/20_2.png) [@gabriele1](https://community.materialssquare.com/u/gabriele1)\
**Post date:** [December 13, 2024, 6:47pm UTC](https://community.materialssquare.com/t/ai-at-scale-method-accelerates-atomistic-simulations-for-scientists/1045/1 "2024-12-13T18:47:56Z")

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Researchers from UC Berkeley and Lawrence Berkeley National Laboratory have introduced a novel AI-driven method, Efficiently Scaled Attention Interatomic Potential (EScAIP), to accelerate atomistic simulations. This machine learning approach significantly reduces computational memory needs by over fivefold and speeds up simulations by more than ten times compared to traditional models. By leveraging techniques similar to those used in large language models, EScAIP can efficiently process extensive datasets without relying heavily on explicit physical constraints, enabling accurate predictions of atomic interactions. The model is a breakthrough for simulating complex molecular and material systems, with applications spanning chemistry, materials science, and drug discovery, offering a scalable and resource-efficient tool for researchers.

For more details, please continue reading the full article under the following link:

> **['AI-at-scale' method accelerates atomistic simulations for scientists](https://techxplore.com/news/2024-12-ai-scale-method-atomistic-simulations.html)**
>
> Quantum calculations of molecular systems often require extraordinary amounts of computing power; these calculations are typically performed on the world's largest supercomputers to better understand real-world products such as batteries and...

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In general, if you enjoy reading this kind of scientific news articles, I would also be keen to connect with fellow researchers based on common research interests in materials science, including the possibility to discuss about any potential interest in the Materials Square cloud-based online platform ( [www.matsq.com](http://www.matsq.com) ), designed for streamlining the execution of materials and molecular modelling simulations!

Best regards,

Dr. Gabriele Mogni  
Technical Consultant and EU Representative of Virtual Lab Inc., the parent company of the Materials Square platform  
Website: [Home | Virtual Lab Inc.](http://www.virtuallab.co.kr/en/)  
Email: gabriele@simulation.re.kr

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