Computer Sciences
Deep learning techniques have recently proved to be highly promising for detecting cybersecurity attacks and determining their nature. Concurrently, many cybercriminals have been devising new attacks aimed at interfering ...
Computer Sciences
BERT, a transformer-based model characterized by a unique self-attention mechanism, has so far proved to be a valid alternative to recurrent neural networks (RNNs) in tackling natural language processing (NLP) tasks. Despite ...
Robotics
Researchers at UC Berkeley have developed a reproducible, low-cost and compact benchmark platform to evaluate robotic learning approaches, which they called REPLAB. Their recent study, presented in a paper pre-published on ...
Consumer & Gadgets
Our smart devices take voice commands from us, check our heartbeats, track our sleep, translate text, send us reminders, capture photos and movies, and let us talk to family and friends continents away.
Machine learning & AI
Artificial neural networks, ubiquitous machine-learning models that can be trained to complete many tasks, are so called because their architecture is inspired by the way biological neurons process information in the human ...
Aug 15, 2023
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590
Computer Sciences
MIT researchers have developed a novel "unsupervised" language translation model—meaning it runs without the need for human annotations and guidance—that could lead to faster, more efficient computer-based translations ...
Oct 31, 2018
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384
Computer Sciences
Researchers at the University of Pompeu Fabra, Cardiff University and the Technical University of Madrid used machine-learning algorithms to discover new things about the history of music.
Computer Sciences
Evidence suggests that the interface between humans and technology will only become more central to modern life.
Feb 20, 2018
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48
Computer Sciences
Computer graphic simulations can represent natural phenomena such as tornados, underwater, vortices, and liquid foams more accurately thanks to an advancement in creating artificial intelligence (AI) neural networks.
Mar 6, 2024
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176
Hardware
Johns Hopkins electrical and computer engineers are pioneering a new approach to creating neural network chips—neuromorphic accelerators that could power energy-efficient, real-time machine intelligence for next-generation ...
Mar 5, 2024
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