Android: celebrating a big milestone together with you
When I started working at Google in early 2007, it was before Android, before iOS. Mobile was still niche. And while many of us had a sense that mobile was going to be big, I’m not sure we really realized just how big it was going to get. Fast forward to today, and there are now 2 billion monthly active Android devices globally. This is an extraordinarily humbling milestone—and it’s the largest reach of any computing platform of its kind. Today at Google I/O, we celebrated that milestone and showcased a number of ways we’re working to make …Read More
Source:: Android: celebrating a big milestone together with you
Introducing the TensorFlow Research Cloud
Researchers require enormous computational resources to train the machine learning (ML) models that have delivered recent breakthroughs in
The TensorFlow Research Cloud offers researchers the following benefits:
- Access to Google’s all-new Cloud TPUs that accelerate both training and inference
- Up to 180 teraflops of floating-point performance per Cloud TPU
- 64 GB of ultra-high-bandwidth memory per Cloud TPU
- Familiar TensorFlow programming interfaces
You can sign up here to request to be notified when the TensorFlow Research Cloud application process opens, and you can optionally share more information about your computational needs. We plan …Read More
Source:: Introducing the TensorFlow Research Cloud
News Feed FYI: New Updates to Reduce Clickbait Headlines
By Arun Babu, Engineer, Annie Liu, Engineer, and Jordan Zhang, Engineer
People tell us they don’t like stories that are misleading, sensational or spammy. That includes clickbait headlines that are designed to get attention and lure visitors into clicking on a link. In an effort to support an informed community, we’re always working to determine what stories might have clickbait headlines so we can show them less often.
Last year we made an update to News Feed to reduce stories from sources that consistently post clickbait headlines that withhold and exaggerate information. Today, we are making three updates that build …Read More
Source:: News Feed FYI: New Updates to Reduce Clickbait Headlines
Using Machine Learning to Explore Neural Network Architecture
At Google, we have successfully applied deep learning models to many applications, from
To make this process of designing machine learning models much more accessible, we’ve been exploring ways to automate the design of machine learning models. Among many algorithms we’ve studied, evolutionary algorithms [1] and reinforcement learning algorithms [2] have shown great promise. But in this blog post, …Read More
Source:: Using Machine Learning to Explore Neural Network Architecture
Efficient Smart Reply, now for Gmail
Last year we launched Smart Reply, a feature for
Each module processes inputs and provides transformed representations of those inputs on its outputs (which are, in turn, available for the next level). In the Smart Reply system, and the figure above, the repeated structure has two layers of hierarchy. The first makes each feature useful as a predictor of the final result, and the second combines these features. By definition, the second works at a more abstract representation and considers a wider timescale.
By …Read More
Source:: Efficient Smart Reply, now for Gmail