C. Alino

@cirhuzalain

Engineer | LifeLong Learner

Africa
Vrijeme pridruživanja: srpanj 2013.

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  1. proslijedio/la je Tweet
    16. sij

    Introducing Reformer, an efficiency optimized architecture, based on the Transformer model for language understanding, that can handle context windows of up to 1 million words, all on a single accelerator with only 16GB of memory. Read all about it ↓

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  2. proslijedio/la je Tweet
    16. tra 2019.

    We used architecture search to find a better architecture for object detection. Results: Better and faster architectures than Mask-RCNN, FPN and SSD architectures. Architecture also looks unexpected and pretty funky. Link:

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  3. proslijedio/la je Tweet
    13. lis 2018.

    Cross-Entropy Loss Leads To Poor Margins Show that cross-entropy loss is one of the hidden culprits of adversarial examples Introduce differential training – novel training paradigm that uses a loss function defined on pairs of from each class

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    31. svi 2018.

    If you like this work, check out our causal models for genomics. This is where I first discovered this with , and also scaled it to huge GWAS data sets.

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    Generating Mario levels through a Generative Adversarial Network. The search can be guided towards objectives such as number of jumps or level difficulty. Paper: Code: Data: Overview:

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    Eager execution & high-level APIs allow developers to train models easily and effectively. Learn about loading datasets, training a classifier, & making predictions with ! Watch the livestream here ↓

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    9. svi 2018.

    Google Duplex: An System for Accomplishing Real World Tasks Over the Phone

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    Incredible progress in human computer speech and understanding, just listen to the examples!

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  9. proslijedio/la je Tweet
    8. svi 2018.

    1/ We've reworked our research web site to be part of our overall Google AI website. So, you can now find what used to be at . There's been some confusion, so I thought I would clarify: we still do a wide range of research across

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    My answer: Yes. A Google program (Duplex) can pass as a human on the phone. Should it be required to tell people it’s a machine? A great article by

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    8. svi 2018.
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    8. svi 2018.
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    Google told CNET its phone call bot will "likely" (!) identify itself as a bot on calls. Also that when it breaks, it will fall back to a human in a Google call center—kinda like Facebook's now-shuttered M assistant.

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    8. svi 2018.

    Woohoo! TensorFlow Node.js bindings hit NPM

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    Very impressive application of deep learning from Chen Chen & for "Seeing in the Dark" with regular cameras. Code available, too!

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  16. proslijedio/la je Tweet
    8. svi 2018.

    Learn how Google Duplex uses advances in natural conversation technologies to autonomously complete specific user tasks via the phone and Google Assistant.

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  17. proslijedio/la je Tweet
    8. svi 2018.
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  18. proslijedio/la je Tweet
    8. svi 2018.

    DeepMind, meet Android. Introducing our first collaboration with the world's most popular mobile operating system:

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  19. proslijedio/la je Tweet
    8. svi 2018.

    Excited that some of my colleagues on the Ads team have released their "Field Guide to Machine Learning" to help people bridging the gap between ML theory and practice:

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