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VOOZH | about |
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VOOZH | about |
GPU computing has transformed industries, enabling applied deep learning advancements in autonomous vehicles, robotics, and molecular biology. The high-speed parallel processing capabilities offered by these machines accelerate the matrix multiplication computations required for processing and transforming massive amounts of data to train and make predictions (inference) with deep learning models comprised of layers of interconnected nodes (neural networks).
Training these neural networks and performing inference faster and cheaper is a high priority in AI research and development. With respect to GPU computing, this means understanding how to better optimize GPU performance.
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Melani is a Technical Writer at DigitalOcean based in Toronto. She has experience in teaching, data quality, consulting, and writing. Melani graduated with a BSc and Master’s from Queen's University.
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