AI

AI for Science: AI-Driven Knowledge Discovery

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B1 L3 R3119

This talk focuses on the latest progress in this area, often called AI for Science, and specifically on how AI is revolutionizing scientific exploration and the uncovering of fundamental physical laws.

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

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B1 L3 R3119

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.

From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs

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B9 L2 R2325

This talk introduces the Ball-Proximal Point Method, a new foundational algorithm for non-smooth optimization with surprisingly fast convergence, and Gluon, a new theoretical framework that closes the gap between theory and practice for modern LMO-based deep learning optimizers.
kaust-iit-collaboration-life-sciences-nanotechnology-research

KAUST collaboration to benefit life sciences and nanotechnology research

1 min read ·
KAUST and IIT unite to enhance research in life sciences, AI, robotics and nanotech, driving innovation through collaboration.

Aznaur Aliev

M.S. Student

Mhd. Emad Alolaby

Mohammed A Shukri

Technical Consultant at KAUST (King Abdullah University of Science and Technology).

Models, Methods, Applications: HPC in Medicine, Science, Engineering, and AI

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B3 L5 R5209

Abstract The accurate numerical prediction of complex processes in medicine, science, and engineering requires a well balanced interplay of mathematical models, numerical methods, and scientific software. In this talk, we discuss along different examples from engineering, earth-sciences, and medicine the various challenges in building predictive models. Our focus will be on the algorithmic aspects, i.e. on the numerical methods, -may it be finite elements or neural networks in the context of massive parallelism. We will present in particular parallel preconditioners for non-linear problems