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Tag: neural networks

Intel Acquires Model Optimizer SigOpt

Intel Corp. is acquiring AI optimization software vendor SigOpt, a move the chip maker said would complement its existing AI software portfolio while integrating SigOpt’s tools with its AI hardware to accelerate and sc Read more…

Models Trained to Keep the Trains Running

Steady advances in machine vision techniques such as convolutional neural networks powered by graphics processors and emerging technologies like neuromorphic silicon retina “event cameras” are creating a range of new Read more…

Speech Analytics Makes Unexpected Discovery

The folks at CallMiner had theories about what their speech analytics software would turn up when they launched an informal coronavirus customer research program back in March. The COVID-19 pandemic has upended life as w Read more…

Three Tricks to Amplify Small Data for Deep Learning

It’s no secret that deep learning lets data science practitioners reach new levels of accuracy with predictive models. However, one of the drawbacks of deep learning is it typically requires huge data sets (not to ment Read more…

Micron Bridges Memory Bandwidth Gap for ML

Deep learning accelerators based on chip architectures coupled with high-bandwidth memory are emerging to enable near real-time processing of machine learning algorithms. Memory chip specialist Micron Technology argues t Read more…

Real Progress Being Made in Explaining AI

One of the biggest roadblocks that could prevent the widespread adoption of AI is explaining how it works. Deep neural networks, in particular, are extremely complex and resist clear description, which is a problem when Read more…

AI Can See. Can We Teach It To Feel?

We've made great strides in the field of computer vision, to the point where self-driving cars equipped with artificial intelligence (AI) can effectively "see" their surroundings. But can we teach AI to "feel" something Read more…

Common Sense Makes Progress with Deep Learning

We've witnessed incredible progress in the capability of deep learning models to not only understand text, but to generate it too. While the generated text is grammatically sound, the actual meaning of the words leaves s Read more…

Will Neural Nets Replace Science Writers?

“Researchers have developed a new representation process on the rotational unit of RUM, a recurrent memory that can be used to solve a broad spectrum of the neural revolution in natural language processing.” The s Read more…

Accelerating Neural Network Design

The design of a neural network architecture remains a daunting problem, requiring human expertise and lots of computing resources. The soaring computational requirements of neural architecture search (NAS) algorithms use Read more…

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