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  • How AI Physics is Transforming Technology and Engineering: Innovations . . .
    AI physics is transforming the way we approach technology and engineering, unlocking new possibilities in everything from quantum computing to renewable energy
  • AI meets physics: a comprehensive survey - Springer
    Uncovering the mechanisms of physics is driving a new paradigm in artificial intelligence (AI) discovery Today, physics has enabled us to understand the AI paradigm in a wide range of matter, energy, and space-time scales through data, knowledge, priors, and laws
  • AI Physics Connects Technology and Theoretical Physics - Rescale
    AI physics leverages machine learning algorithms to simulate, predict, and optimize physical phenomena Neural networks and other AI models can aid in solving complex differential equations, predicting quantum mechanical behaviors, and even optimizing experimental setups
  • Physics and AI: A physics community perspective - iop. org
    How can physics inform national and international AI strategies, and how can physics better articulate opportunities to accelerate physics discovery and innovation through use of AI as part of ‘AI for Science’ approaches?
  • Scientists use generative AI to answer complex questions in physics . . .
    Researchers used generative AI to develop a physics-informed technique to classify phase transitions in materials or physical systems that is much more efficient than existing machine-learning approaches The work was led by researchers at MIT and the University of Basel
  • Physics - How AI and ML Will Affect Physics
    Can AI ML revolutionize doing theoretical physics by finding ideas and concepts such as the general theory of relativity or the Schrödinger equation? Most physicists I talk to firmly believe that this would be impossible
  • AI Expands Potential for Discovery in Physics
    Fangwei Si, the Cooper-Siegel Assistant Professor of Physics, aims to understand living systems in a quantitatively precise way With a background in physics, mechanical engineering and biology, he applies physical concepts and tools to study bacterial cells
  • AI for Physics and Physics for AI - Frontiers
    Researchers are encouraged to submit papers exploring the theoretical foundations of machine learning, innovative approaches to overcoming overfitting, methods for robust uncertainty quantification, and frameworks for enhancing causality and explainability in AI systems


















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