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Research at Google
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In order to enable greater access to the richness of all the audio content in videos, we announce the first ever automatic sound effect captioning system for YouTube, made possible with #machinelearning.

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Can evolutionary algorithms provide a technique to discover effective neural network architectures automatically? Check out a nice writeup by +Quartz on some new experiments by the Google Brain team (g.co/brain) and OpenAI.

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We’re excited to announce the launch of Distill, a new open science journal and ecosystem supporting human understanding of #machinelearning. Distill is an independent organization, dedicated to fostering a new segment of the research community.

Led by a diverse steering committee of leaders from the machine learning and user interface communities, we are very excited to see where Distill will go. To learn more about Distill, visit the Google Research blog, below.

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Today we’re releasing the Skip-Thoughts model in #TensorFlow, a #machinelearning algorithm developed at UToronto that learns to encode the semantic properties of sentences! Learn more at goo.gl/zqJb2R 
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At Google, we care about giving users the best possible online experience, both through our own services and products and by contributing new tools and industry standards for use by the online community. That’s why we’re excited to announce Guetzli, a new open source algorithm that creates high quality JPEG images with file sizes 35% smaller than currently available methods, enabling webmasters to create webpages that can load faster and use even less data.

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New #MotionStills for iOS, now with Live Photo export and smoother, deeper color GIFs. Get it at goo.gl/zkp0xz #REALLYBLUE #ILIKETURTLES
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At Google, we continuously improve the language understanding capabilities of our #machinelearning systems. While we are excited to share our research and to provide resources to the broader community, building systems that work well for languages other than English remains an ongoing challenge.

Today, we are excited to announce a few new research resources, available now, that address this problem. Learn more on the Google Research blog, linked below.

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Save time with Quick Access

Last year we launched Quick Access, a feature in +Google Drive that uses #machinelearning to surface the most relevant documents as soon as you visit the Google Drive home screen. Originally available only for G Suite customers on Android, Quick Access is now available for everyone who uses Google Drive, taking you to the documents you need in half the time compared to manually navigating or searching.

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AudioSet: A sound vocabulary and dataset

We are excited to announce the release of AudioSet, a comprehensive ontology of over 600 sound classes and a dataset of over 2 million 10-second YouTube clips annotated with sound labels. The ontology is specified as a hierarchical graph of event categories, covering a wide range of human and animal sounds, musical instruments and genres, and common everyday environmental sounds.

By releasing AudioSet, we hope to provide a common, realistic-scale evaluation task for audio event detection, as well as a starting point for a comprehensive vocabulary of sound events. Explore more at g.co/audioset

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Speed is everything for effective ML. That's why we developed XLA, a compiler for @TensorFlow! Read more https://goo.gl/QcjgxY
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