英語 での Deep neural networks の使用例とその 日本語 への翻訳
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In the last few years, deep neural networks have been used to replace many existing ASR modules, resulting in significant gains in word recognition accuracy.
A year later, Schmidhuber's lab used GPUs to develop the first pure deep neural networks that won international contests in handwriting recognition and computer vision.
According to this very helpful post on the NVIDIA Blog, Tensor cores are designed to speed up the training and inference of large, deep neural networks.
Starting from a core logic developed during initial training, deep neural networks can continuously refine their performance as they are presented with new images, speech, and text.
Machine Learning Studio provides state-of-the-art algorithms, such as Scalable Boosted Decision trees, Bayesian Recommendation systems, Deep Neural Networks, and Decision Jungles developed at Microsoft Research.
We started employing this particular technology to make deep neural networks imagine new molecules, to make it perfect right from the start.
And researchers at the University of California, Berkeley, have used another key AlphaGo technology, deep neural networks, to teach machines how to screw one bottle caps.
Uber began using NVIDIA GPU computing technology in its first test fleet of Volvo XC90 SUVs, and currently uses high-performance NVIDIA processors to run deep neural networks in both its self-driving ride-hailing cars and self-driving freight trucks.
Upcoming posts in this series will introduce the general principles of machine learning and examine the internals of some of the most powerful and widely used machine learning algorithms- SVMs, Bayesian networks, decision trees, Bayesian neural networks and deep neural networks- and describe how they can be applied in practice to solve real world problems.
Here, the latest technology is used including imitation learning methods that utilize deep neural networks. The potential of AI is moving beyond the role of achieving greater efficiency that has been the mandate of machines heretofore, and onto improving quality and accuracy.
With deeper networks, more training data and powerful new hardware to make it all work, deep neural networks(or“deep learning” systems) suddenly began making rapid progress in areas such as speech recognition, image classification and language translation.
By collaborating with AI developers, we continued to improve our GPU designs, system architecture, compilers, and algorithms, and sped up training deep neural networks by 50x in just three years- a much faster pace than Moore's Law.
Applying SDL's machine learning, AI and deep neural networks expertise, SDL Content Assistant can quickly identify themes, patterns and extract topics from source documentation, automatically generating key information and content summaries, highlighting any important quotes, facts and figures and even suggesting social posts.
The company also announced Nvidia Drivenet, its own deep neural network.
How can a deep neural network learn anything?
And CUDA Deep Neural Network library is the cuDNN.
This data will be used for training a deep neural network.
Deep Neural Network.
Key Words Deep neural network: a multi-layer network for discovering statistical features hidden in the data, from simple ones to gradually complex ones.
G and deep neural network ASICs, in particular, are expected to reach the plateau in the next two to five years.