A new generation of Scientific AI combined with GPU-accelerated simulation is redefining what is computationally feasible
Exploring chemical and materials design spaces has traditionally been constrained by experimental cost, computational limits, and data fragmentation. A new generation of Scientific AI, combined with GPU-accelerated simulation, is redefining what is computationally feasible.
This webinar explores how generative technologies and the Virtual + Real (V+R) approach allow scientists to move seamlessly between molecular design, predictive modeling, and real-world validation. We will highlight how GPU-accelerated computing architectures enable large-scale atomistic simulation, rapid property prediction, and AI model training — expanding the range of solvable problems in chemical R&D. Learn how the same scientific AI can apply a digital traceability that extends from R&D to manufacturing, enabling simulation & optimization of production processes in a virtual environment before real world implementation - effectively scaling lab ideas to mass production through a real time, physic-based virtual factory.
Watch now to learn how integrating AI, simulation, and high-performance computing can accelerate discovery, reduce uncertainty, and unlock new opportunities for innovation.
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