For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...
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Deep learning regularization: Prevent overfitting effectively explained
Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...
DeepSeek has published a technical paper co-authored by founder Liang Wenfeng proposing a rethink of its core deep learning ...
During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
AI systems may not need vast amounts of training data to begin behaving more like the human brain, according to new research ...
A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...
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