Titans combines traditional LLM attention blocks with “neural memory ... This solves the generalization problem that other neural network architectures suffer from. To decide which bits ...

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of ...

The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, ...

Attention and Learning: With the limitation of energy and efficiency of the biological ... works best and helps CBSNN achieve the best accuracy of 52.85% under only around a third of computation cost ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

Tim Keary is a technology writer and reporter covering AI, cybersecurity, and enterprise technology. Before joining Techopedia full-time in 2023, his work appeared on VentureBeat,… The textbook ...

After casting his ballot in the presidential election on , Belarusian President Aleksandr Lukashenko told journalists whether ...

A new study published in the Journal of Affective Disorders shows that individuals with depression exhibit slower and less ...

The AI model that shook the world is part of a broad trend to squeeze more out of chips using what's called sparsity.

There are a lot of misconceptions out there about creativity. For instance, there is this idea that you must be a bit mad to ...

Jonathan EnudemeJonathan Enudeme Imagine finding yourself lost in a foreign land where no one speaks English or your native language. The streets are unfamiliar, and every turn leads you deeper into ...