🔹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

🔹Computing and artificial intelligence: Humanistic perspectives from MIT

"The advent of artificial intelligence presents our species with an historic opportunity — disguised as an existential challenge: Can we stay human in the age of AI? In fact, can we grow in humanity, can we shape a more humane, more just, and sustainable world?"

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📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning

link: https://shass.mit.edu/news/news-2019-computing-and-ai-humanistic-perspectives-mit-foreword-dean-melissa-nobles

#MIT
#AI
#machinelearning
#computing