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Robust AI Model That Constantly Learns New User Data

Artificial intelligence chatbots that can adjust to comprehend a user’s accent or smart keyboards that constantly update to more accurately guess the next word based on a user’s typing history can be made possible by personalized deep-learning models. A machine-learning model must constantly be adjusted with new data to accommodate this personalization. ....

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New techniques efficiently accelerate sparse tensors for massive AI models

New techniques efficiently accelerate sparse tensors for massive AI models
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Vivienne Sze , Taylor Swift , Zi Yu Xue , Joel Emer , Yannan Nellie Wu , Department Of Electrical Engineering , Mit Ai Hardware Program , Artificial Intelligence Laboratory , Research Laboratory Of Electronics , International Symposium On Microarchitecture , Electrical Engineering , Computer Science , Research Laboratory , Yannan Nellie Wu Phd ,

New techniques efficiently accelerate sparse

New computational techniques, “HighLight” and “Tailors and Swiftiles,” could dramatically boost the speed and performance of high-performance computing applications like graph analytics or generative AI. The work, from MIT and NIVIDIA, aims to accelerate sparse tensors for AI models by introducing more efficient and flexible ways to take advantage of sparsity. ....

Joel Emer , Yannan Nellie Wu , Zi Yu Xue , Taylor Swift , Vivienne Sze , Artificial Intelligence Laboratory , Research Laboratory Of Electronics , Department Of Electrical Engineering , Mit Ai Hardware Program , International Symposium On Microarchitecture , Electrical Engineering , Computer Science , Research Laboratory , Yannan Nellie Wu Phd ,