🔹What a little more #computing_power can do
From: Kim Martineau
To recognize a cat in a picture, a deep learning model may need to see millions of photos before its artificial #neurons “learn” to identify a cat. But there may be a more efficient way. New MIT research shows that models only a fraction of the size are needed. “When you train a big network there’s a small one that could have done everything,”. neural network could get by with on-tenth the number of connections if the right subnetwork is found at the outset.
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📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2019/what-extra-computing-power-can-do-0916
#neuralnetworks
#GAN
#deeplearning
#machinelearning
From: Kim Martineau
To recognize a cat in a picture, a deep learning model may need to see millions of photos before its artificial #neurons “learn” to identify a cat. But there may be a more efficient way. New MIT research shows that models only a fraction of the size are needed. “When you train a big network there’s a small one that could have done everything,”. neural network could get by with on-tenth the number of connections if the right subnetwork is found at the outset.
———————————
📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2019/what-extra-computing-power-can-do-0916
#neuralnetworks
#GAN
#deeplearning
#machinelearning