The rapid growth of Large Language Models (LLMs) has been a driving force in
transforming various domains, reshaping the artificial general intelligence landscape …

Training convolutional neural networks (CNNs) demands huge GPU memory consumption
and training time, leading to increased carbon emissions, and impacting sustainability. In …

A processor-implemented neural network method includes: generating a first output line of
an output feature map by performing a convolution operation between a first input line group …

Convolutional neural networks (CNNs) perform excellently in many image processing and
computer vision tasks. However, their complex structure and the vast number of parameters …

Embodiments of this application disclose a method for controlling a target object. The
method includes receiving an object control instruction, and obtaining interaction frame data …

G06F7/48—Methods or arrangements for performing computations using exclusively
denominational number representation, eg using binary, ternary, decimal representation …

Disclosed herein includes a system, a method, and a device for improving computational
efficiency of deconvolution by reducing a number of dot products. In one aspect, an input …

Exemplary embodiments maintain spatial locality of the data being processed by a sparse
CNN. The spatial locality is maintained by reordering the data to preserve spatial locality …

Embodiments relate to a neural processor that includes one or more neural engine circuits
and planar engine circuits. The neural engine circuits can perform convolution operations of …

A memory device includes a first word and a second word. The first word has a first subset of
a plurality of elements. The first subset of the plurality of elements each have a first set of …