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 ...
In this special guest feature, Arvin Hsu, Senior Director of Data Science and Machine Learning for GoodData, discusses that despite the two terms being used interchangeably, deep learning and machine ...
Artificial intelligence is everywhere these days, but the fundamentals of how this influential new technology work can be difficult to wrap your head around. Two of the most important fields in AI ...
The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...
Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.
Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry 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 ...
eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Exploring the utility of prostate-derived extracellular vesicles as a urine biomarker for clinically significant prostate cancer. This is an ASCO Meeting Abstract from the 2024 ASCO Genitourinary ...
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