MIT News – Artificial intelligence In late 2019, after years of studying aviation and aerospace engineering, Hector (Haofeng) Xu decided to learn to fly helicopters. At the time, he was pursuing his PhD in MIT’s Department of Aeronautics and Astronautics, so he was familiar with the risks associated with flying small aircraft. But something about […]Continue reading

AWS Machine Learning Blog In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Pre-trained language models (PLMs) are undergoing rapid commercial and enterprise adoption in the areas of productivity tools, customer service, search and recommendations, […]Continue reading

MIT News – Artificial intelligence In order for natural language to be an effective form of communication, the parties involved need to be able to understand words and their context, assume that the content is largely shared in good faith and is trustworthy, reason about the information being shared, and then apply it to real-world […]Continue reading

MIT News – Artificial intelligence In fields such as physics and engineering, partial differential equations (PDEs) are used to model complex physical processes to generate insight into how some of the most complicated physical and natural systems in the world function. To solve these difficult equations, researchers use high-fidelity numerical solvers, which can be very […]Continue reading

MIT News – Artificial intelligence In late November, faculty, staff, and students from across MIT participated in MIT Generative AI Week. The programming included a flagship full-day symposium as well as four subject-specific symposia, all aimed at fostering a dialogue about the opportunities and potential applications of generative artificial intelligence technologies across a diverse range […]Continue reading

AWS Machine Learning Blog In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision (CV), natural language processing (NLP), and recommendation systems. However, the increasing cost associated with training and fine-tuning these models poses a challenge for enterprises. This cost is […]Continue reading

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