Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866911954511069184 |
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| author | Chertkov, Michael |
| author_facet | Chertkov, Michael |
| contents | The paper reflects on the future role of AI in scientific research, with a special focus on turbulence studies, and examines the evolution of AI, particularly through Diffusion Models rooted in non-equilibrium statistical mechanics. It underscores the significant impact of AI on advancing reduced, Lagrangian models of turbulence through innovative use of deep neural networks. Additionally, the paper reviews various other AI applications in turbulence research and outlines potential challenges and opportunities in the concurrent advancement of AI and statistical hydrodynamics. This discussion sets the stage for a future where AI and turbulence research are intricately intertwined, leading to more profound insights and advancements in both fields. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_17993 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence Chertkov, Michael Machine Learning Statistical Mechanics Artificial Intelligence Fluid Dynamics The paper reflects on the future role of AI in scientific research, with a special focus on turbulence studies, and examines the evolution of AI, particularly through Diffusion Models rooted in non-equilibrium statistical mechanics. It underscores the significant impact of AI on advancing reduced, Lagrangian models of turbulence through innovative use of deep neural networks. Additionally, the paper reviews various other AI applications in turbulence research and outlines potential challenges and opportunities in the concurrent advancement of AI and statistical hydrodynamics. This discussion sets the stage for a future where AI and turbulence research are intricately intertwined, leading to more profound insights and advancements in both fields. |
| title | Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence |
| topic | Machine Learning Statistical Mechanics Artificial Intelligence Fluid Dynamics |
| url | https://arxiv.org/abs/2403.17993 |