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Our January events featured data scientists, PhD candidates, research scientists, and AI strategists who spoke about their career paths and the AI applications they're working on. And we've got more in February! Check out our upcoming events: https://hubs.ly/H0mSxG40 pic.twitter.com/Aia0UZlSha
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train_test_split every day all day creds:
@amuellermlpic.twitter.com/MnM8gppZJ2
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Test your image classification model with your phone camera! Learn how to deploy models with TensorFlow Lite: http://bit.ly/2tUGOg9 pic.twitter.com/8bjAY6LmHU
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recaptcha is getting out of hand creds: debojeet chatterjeepic.twitter.com/YCwrkSomjm
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Backpropagation and labeled data are the bread and butter of deep learning. But recent research from the University of Amsterdam suggests neither is necessary to train effective neural networks to represent complex data: http://bit.ly/38wLUOj pic.twitter.com/Ok6IV7QLWZ
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This week in AI, algorithms design living machines, AI interviews job applicants, Youtube's recommender spreads misinformation, and researchers ditch backpropagation. Catch up on the news in The Batch: https://hubs.ly/H0mHLWh0 pic.twitter.com/40M2IPNa7p
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Course 3 of the TensorFlow: Data and Deployment Specialization is out on
@coursera! Machine learning is powered by data, but it's often frustrating to handle. This course will teach you to more effectively manage data in TensorFlow. Enroll here: https://hubs.ly/H0mGKNy0 pic.twitter.com/1ke9TanURz
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Get your model running on iOS and Android devices. Walk through the basic steps in Course 2 of the TensorFlow: Data and Deployment Specialization: http://bit.ly/36dOgQz pic.twitter.com/r2zildDe3W
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Want the tl;dr version of AI's overwhelming presence at
#CES2020? We highlighted the weirdest and coolest products, from half-baked concepts like abnormal cat litter recognition to futuristic prototypes like Samsung's virtual assistants: http://bit.ly/3ahjfOT pic.twitter.com/QQ9sJ8OKi6 -
In this week's The Batch, AI dominates CES, Hollywood predicts blockbusters, Washington regulates AI, and neural nets study math: https://hubs.ly/H0mB_F10 pic.twitter.com/BUJQZMSIme
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From Kathmandu to Tokyo: In December, we held 11 Pie & AI events in 11 cities, thanks to our amazing event ambassadors! Where will we be this month? Stay in the loop: http://bit.ly/2Ns5nrf pic.twitter.com/jDdOsKoXka
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"Automatic summarization is one of the most important, yet least solved, tasks in natural language processing." Learn why
@RichardSocher thinks so and what solutions the@SFResearch team is working on: https://hubs.ly/H0mzVD50 pic.twitter.com/WHS8vcEknF
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Sounds like a great decade to us but we might be a little biasedpic.twitter.com/lQgyeCJ2Cp
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Recent language models like BERT and ERNIE rely on trendy layers based on transformer networks and require lots of compute. Deep learning researcher
@Smerity shows these layers and enormous GPUs may not be necessary: http://bit.ly/2QZXxWV pic.twitter.com/d03D7A7CAD
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Dear deep learners: A quick update on Course 3 & 4 of the TensorFlow: Data and Deployment Specialization. We’re a bit behind schedule but are on track to release C3 by end of January and C4 by end of February so that you can continue learning. Thanks for your patience!pic.twitter.com/gadlaWx5Mh
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What's next for AI?
@ylecun says: "In 2020, I expect self-supervised methods to learn features of video and images. Could there be a similar revolution in high-dimensional continuous data like video?" Read more: https://hubs.ly/H0mt1_W0 pic.twitter.com/ILqeMlB5KC
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New year's resolution: read more papers!pic.twitter.com/gYxDjT8Dit
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"It's time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring to the real world." Read
@animaanandkumar's hopes for AI research in 2020: https://hubs.ly/H0mlJqT0 pic.twitter.com/Mjv8houf8M
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New year, new dreams.
@ylecun,@katecrawford,@kaifulee,@animaanandkumar, and other AI luminaries tell you their hopes for AI in 2020 in our special new year's issue of The Batch: https://hubs.ly/H0mlJKk0 pic.twitter.com/6SlL257JeT
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