TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...

Abstract: The reversible residual neural network (RRNN) model is a bidirectional neural network model, which has recently gained attention in the design of various control methods in turntable servo ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

Abstract: In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of ...

The stability of the surrounding rock in the goaf of the mine is poor, which can easily cause collapse disasters in the mining area. This paper used orthogonal experiments and multi factor ...

1 Department of Computer Science, PUCC, Pondicherry University, Pondicherry, India. 2 Department of Computer Science, Pondicherry University, Pondicherry, India. An ancient fossil fuel, oil is a ...