One goal in these architectures was to give each neuron its own digital representation. After a promising start in the 1980s, only a few of these approaches ...
Artificial neural networks (ANNs) represent a well-known solution for handling various pattern recognition problems. Soft- ware implementations of such ...
A new architecture achieves time-efficient execution of weighted sums, with a computation time superior to the time complexity of sequential von Neumann ...
Abstract: Execution of artificial neural networks, especially for online pattern recognition, mainly depends on time-efficient execution of weighted sums.
Nov 10, 2021 · This project addresses the weakness of modern AI thorough exploring novel memory architectures motivated by cognitive and computational insights.
Jul 12, 2018 · This blog would like to further highlight the importance and the recent industry developments of the intelligent memory architectures with new technologies.
Mar 19, 2020 · In this blog post, we'll discuss common memory systems that are used in the highest performance AI applications.
Jun 12, 2024 · This survey paper provides an overview and analysis of transformer-based models, reviewing various CIM architectures and exploring how they can address the ...
Jun 16, 2024 · The Hopfield network is a type of recurrent neural network that showcases associative memory in action. Memories are stored as stable states within the network.
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