Tag Archives: Software

Our best Chromecast yet, now with Google TV


Chromecast changed the way we enjoy our favourite movies, TV shows and YouTube videos by making it easy and inexpensive to bring your online entertainment to your TV—a revolutionary idea in 2013. Today, we have more content choices than ever, sprinkled across an ever-expanding variety of apps, which can make it difficult to find what to watch. This inspired us to rethink what simple and easy content discovery on your TV should look like. So today, we're making our biggest leap yet to help you navigate your entertainment choices, bringing together the best of local and global content into one convenient location, with the all-new Chromecast with Google TV. 
Best Chromecast yet 
Chromecast with Google TV has your favourite Chromecast features and now comes with the all-new Google TV entertainment experience. Google TV experience brings together movies, shows and more from across your apps and subscriptions and organises them just for you. We're also bringing our most requested feature—a remote—to Chromecast. 

A new look, inside and out 
The new Chromecast with Google TV comes in a compact and thin design and is packed with the latest technology to give you the best viewing experience. It neatly plugs into your TV's HDMI port and tucks behind your screen. Power it on and you'll be streaming crystal clear video in up to 4K HDR at up to 60 frames per second in no time. With Dolby Vision, you’ll get extraordinary colour, contrast and brightness on your TV. We also support HDMI pass-through of Dolby audio content. 

More power in your hand 
The new Chromecast voice remote is comfortable to hold, easy to use and full of new features. It has a dedicated Google Assistant button that can help you find something to watch, answer everyday questions like “how's the weather?” or play your favourite artist on YouTube Music all with just your voice. And when it's time to cozy up on the couch for movie night, you can control your smart home lights to set the mood or check your front door with Nest Camera to keep tabs on your pizza delivery. We also have dedicated buttons for popular streaming services, YouTube and Netflix, to give you instant access to the content you love. Best of all, you won't have to juggle multiple remotes thanks to our programmable TV controls for power, volume and input. 

TV just for you 
In need of some good movie or TV recommendations? Google TV's For You tab gives you personalised watch suggestions from across your subscriptions organised based on what you like to watch—even your guilty pleasure reality dramas. Google TV’s Watchlist lets you bookmark movies and shows you want to save for later. You can add to your Watchlist from your phone or laptop, and it will be waiting on your TV when you get home. 
Best of all, you'll also have access to thousands of apps and the ability to browse 400,000+ movies and TV shows sorted and optimised for what you like—ask Google Assistant to see results from across your favourite apps, like YouTube, Netflix, Disney+, Stan, 9Now and ABC iview, among others. 

Starting today Chromecast with Google TV is available for pre-order in Australia for $99 in three fun colours to match your decor or personality: Snow, Sunrise and Sky, and will be available from the Google Store as well as other retailers like JB Hi-Fi, Harvey Norman, OfficeWorks, and The Good Guys starting from October 15. Sunrise and Sky will be exclusively available on Google Store. 


Made for music, the new Nest Audio is here

This year, we’ve all spent a lot of time exploring things to do at home. Some of us gardened, and others baked. We tried at-home workouts, or redecorated the house, took up art projects. But one thing that many—maybe all of us—did? Enjoy a lot of music at home. Personally, I have spent so much more time listening to music during quarantine—bossa nova is my go to soundtrack for doing the dishes and Lil Baby has become one of my favourite artists. 
So, in a time when we’re all listening to more music than ever, we’re especially excited to introduce Nest Audio, our latest smart speaker that is made for music lovers. 

A music machine 
Nest Audio is 75 percent louder and has 50 percent stronger bass than the original Google Home—measurements of both devices were taken in an anechoic chamber at maximum volume, on-axis. With a 19mm tweeter for consistent high frequency coverage and clear vocals and a 75mm mid-woofer that really brings the bass, this smart speaker is a music lover’s dream. 
Nest Audio’s sound is full, clear and natural. We completed more than 500 hours of tuning to ensure balanced lows, mids and highs so that nothing is lacking or overbearing. The bass is significant and the vocals have depth, which makes Nest Audio sound great across genres: classical, R&B, pop and more. The custom-designed tweeter allows each musical detail to come through, and we optimised the grill, fabric and materials so that you can enjoy the audio without distortion. 
Our goal was to ensure that Nest Audio stayed faithful to what the artist intended when they were in the recording studio. We minimised the use of compressors to preserve dynamic range, so that the auditory contrast in the original production is preserved—the quiet parts are delicate and subtle, and the loud parts are more dramatic and powerful. 
Nest Audio also adapts to your home. Our Media EQ feature enables Nest Audio to automatically tune itself to whatever you’re listening to: music, podcasts, audiobooks or hearing a response from Google Assistant. And Ambient IQ lets Nest Audio also adjust the volume of Assistant, news, podcasts, and audiobooks based on the background noise in the home, so you can hear the weather forecast over a noisy dishwasher. 

Whole home audio 
If you have a Google Home, Nest Mini or even a Nest Hub, you can easily make Nest Audio the centre of your whole home sound system. In my living room, I’ve connected two Nest Audio speakers as a stereo pair for left and right channel separation. I also have a Nest Hub Max in my kitchen, a Nest Mini in my bedroom and a Nest Hub in the entryway. These devices are grouped so that I can blast the same song on all of them when I have my daily dance party. 
With our stream transfer feature, I can move music from one device to the other with just my voice. Just last month, we launched multi-room control, which allows you to dynamically group multiple cast-enabled Nest devices in real-time. 

An even faster Assistant 
When we launched Nest Mini last year, we embedded a dedicated machine learning chip with up to one TeraOPS of processing power, which let us move some Google Assistant experiences from our data centres directly onto the device. We’ve leveraged the same ML chip in Nest Audio too.
Google Assistant helps you tackle your day, enjoy your entertainment and control compatible smart home brands like Philips Hue, TP-Link and more. In fact, our users have already set up more than 100 million devices to work with Google Assistant. Plus, if you’re a YouTube Music or Spotify Premium subscriber, you can say, “Hey Google, recommend some music” and Google Assistant will offer a variety of choices from artists and genres that you like, and others like them to choose from.

Differentiated by design 
Typically, a bigger speaker equals bigger sound, but Nest Audio has a really slim profile—so it fits anywhere in the home. In order to maximise audio output, we custom-designed quality drivers and housed them in an enclosure that helps it squeeze out every bit of sound possible. 
Nest Audio is available in two colours in Australia: Chalk and Charcoal. Its soft, rounded edges blend in with your home’s decor, and its minimal footprint doesn't take up too much space on your shelf or countertop. 
We’re continuing our commitment to sustainability with Nest Audio. It’s covered in the same sustainable fabric that we first introduced with Nest Mini last year, and the enclosure (meaning the fabric, housing, foot, and a few smaller parts) is made from 70 percent recycled plastic. 

Starting today Nest Audio is available for pre-order in Australia for $149 at the Google Store and other retailers, including JB Hi-Fi, Harvey Norman, and The Good Guys. It will be on-sale from October 15 through these same retailers, as well as Officeworks and Vodafone. 

Pixel 4a (5G) and Pixel 5 pack 5G speeds and so much more

Today, we hosted Launch Night In, a virtual event introducing new products from across Google that will offer a little joy, entertainment and connection for people. These products bring together the best of Google’s hardware, software and AI to deliver helpful experiences built around you. Not only are these products more helpful; they’re more affordable too. 
Our new smartphones, Pixel 4a with 5G and Pixel 5 offer more helpful Google features backed by the power and speeds of 5G.1 From Google’s latest AI and Assistant features, to the biggest ever batteries we’ve put in a Pixel, to industry-leading camera features, Pixel 4a with 5G and Pixel 5 join our much loved Pixel 4a in providing more help at a more helpful price. 

5G speeds at affordable prices 
5G is the latest in mobile technology, bringing fast download and streaming speeds to users around the world. Whether you’re downloading the latest movie2, listening to your favourite music on YouTube Music, catching up on podcasts with Google Podcast or downloading a game Pixel 4a with 5G and Pixel 5 can provide you with fast speeds at a helpful price.1 Starting at just $799 for Pixel 4a with 5G.

New camera, new lenses—same great photos 
Ask any Pixel owner and they’ll tell you: Pixels take great photos. Pixel 4a with 5G and Pixel 5 are no exception. These phones bring Pixel’s industry-leading photography features to the next level. 
  • Better videos with Cinematic Pan: Pixel 4a with 5G and Pixel 5 come with Cinematic Pan, which gives your videos a professional look with ultrasmooth panning that’s inspired by the equipment Hollywood directors use. 
  • Night Sight in Portrait Mode: Night Sight currently gives you the ability to capture amazing low-light photos—and even the Milky Way with astrophotography. Now, these phones bring the power of Night Sight into Portrait Mode to capture beautifully blurred backgrounds in Portraits even in extremely low light. 
Night Sight in Portrait Mode, captured on Pixel 
  • Portrait Light: Portrait Mode on the Pixel 4a with 5G and Pixel 5 lets you capture beautiful portraits that focus on your subject as the background fades into an artful blur. If the lighting isn’t right, your Pixel can drop in extra light to illuminate your subjects
  • Ultrawide lens for ultra awesome shots: With an ultrawide lens alongside the standard rear camera, you’ll be able to capture the whole scene. And thanks to Google’s software magic, the latest Pixels still get our Super Res Zoom. So whether you’re zooming in or zooming out, you get sharp details and breathtaking images. 
Ultrawide, captured on Pixel 
  • New editor in Google Photos: Even after you’ve captured your portrait, Google Photos can help you add studio-quality light to your portraits of people with Portrait Light, in the new, more helpful Google Photos editor
Stay connected and entertained with Duo 
To make it easier and more enjoyable to stay connected to the most important people in your life, the new HD screen sharing in Duo video calls lets you and a friend watch the same video, cheer on sports with a friend and even plan activities – no matter how far apart you are.3 And with features like Duo Family mode, you will be able to keep kids entertained and engaged with new interactive tools, like colouring over backgrounds, while you video chat. 

A smarter way to record and share audio 
Last year, Recorder made audio recording smarter, with real-time transcriptions and the power of search.4 Now, Recorder makes it even easier to share your favourite audio moments. Since Recorder automatically transcribes every recording, now you can use those transcripts to edit the audio too. Just highlight a sentence to crop or remove its corresponding audio. Once you have something you want others to hear—say a quote from an interview or a new song idea—you can generate a video clip to make sharing your audio easier and more visual than ever. 
Editing in Recorder is easy

To improve searching through your transcripts, smart scrolling will automatically mark important words in longer transcripts so you can quickly jump to the sections you’re looking for as you scroll. But most helpful of all? Recorder still works without an internet connection, so you can transcribe, search and edit from anywhere, anytime. 

The biggest Pixel batteries ever 
Pixel 4a with 5G and Pixel 5 also have all-day batteries that can last up to 48 hours with Extreme Battery Saver.5 This mode automatically limits active apps to just the essentials and lets you choose additional apps you want to keep on. 

And now, the specs 
Like all Pixel devices, security and safety are paramount in Pixel 4a with 5G and Pixel 5. Both devices come with our TitanTM M security chip to help keep your on-device data safe and secure, and both phones will get three years of software and security updates. Your Pixel also has built-in safety features like car crash detection6 and Safety Check.7
Plus, Pixel 5 is designed with the environment in mind; we used 100% recycled aluminium in the back housing enclosure to reduce its carbon footprint. You can charge your Pixel 5 wirelessly8 and even use it to wirelessly charge other Qi-certified devices using Battery Share.9 Pixel 5 also doesn’t mind a little water or dust. The metal unibody can handle being submerged in 1.5 metres of fresh water for 30 minutes.10
When you buy the Google phone, you get more from Google. Pixel 5 and Pixel 4a with 5G come with trial subscriptions to Google’s entertainment, security and storage services for new users.11 If you’re a new user you’ll get a YouTube Premium trial for 3 months, 100 GB of storage with Google One for 3 months and 3 months of Google Play Pass and Gold/Silver Status on Play Points. See g.co/pixel/4a5Goffers or g.co/pixel/5offers, as applicable, for more details.11 
In Australia, Pixel 5 will range in two colours, Just Black and Sorta Sage (selected retailers). It will retail for $999 and can be pre-ordered today from Google Store, Telstra, Optus, Vodafone, JB Hi-Fi, Officeworks and Harvey Norman, and will be available starting October 15. Pixel 4a with 5G will retail for $799 and can be pre-ordered today from JB Hi-Fi, Officeworks and Harvey Norman, and will be available from these retailers in addition to Google Store and Telstra in November ranging in Just Black. 


Looking for the Pixel’s that’s right for you? Head to the Google Store now. 

1 Requires a 5G data plan (sold separately). 5G service and roaming not available on all carrier networks or in all areas. Contact carrier for details about current 5G network performance, compatibility, and availability. Phone connects to 5G networks but, 5G service, speed and performance depend on many factors including, but not limited to, carrier network capabilities, device configuration and capabilities, network traffic, location, signal strength and signal obstruction. Actual results may vary. Some features not available in all areas. Data rates may apply. See g.co/pixel/networkinfo for info. 
2 Download speed claims based on testing videos from three streaming platforms. Average download time was less than sixty seconds. File sizes varied between 449MB and 1.3GB. Download speed depends upon many factors, such as file size, content provider and network connection. Testing conducted in an internal 5G network lab and on pre-production hardware in California in July/August 2020. Actual download speeds may be slower. Australian results may vary. 
3 Screen sharing not available on group calls. Requires Wi-Fi or 5G internet connection. Not available on all apps and content. Data rates may apply. 5G service, speed and performance depend on many factors including, but not limited to, carrier network capabilities, device configuration and capabilities, network traffic, location, signal strength, and signal obstruction. 
4 Transcription and search are available in English only. 
5 For “all day”: Maximum battery life based on testing using a mix of talk, data, standby, and use of other features. Testing conducted on two major US carrier networks using Sub-6 GHz non-standalone 5G (ENDC) connectivity. For “Up to 48 hours”: Maximum battery life based on testing using a mix of talk, data, standby, and use of limited other features that are default in Extreme Battery Saver mode (which disables various features including 5G connectivity). Testing conducted on two major US carrier networks. For both claims: Pixel 4a (5G) and Pixel 5 battery testing conducted by a third party in California in mid 2020 on pre-production hardware and software using default settings, except that, for the “up to 48 hour claim” only, Extreme Battery Saver mode was enabled. Battery life depends upon many factors and usage of certain features will decrease battery life. Actual battery life may be lower.
6 Not available in all languages or countries. Car crash detection may not detect all accidents. High-impact activities may trigger calls to emergency services. This feature is dependent upon network connectivity and other factors and may not be reliable for emergency communications or available in all areas. For country and language availability and more information see g.co/pixel/carcrashdetection. 
7 Personal Safety app features are dependent upon network connectivity and other factors and may not be reliable for emergency communications or available in all areas. For more information, see g.co/pixel/personalsafety. 
8 Qi-compatible. Wireless charger sold separately. 
9 Designed to charge Qi-certified devices. Use of Battery Share significantly reduces Pixel battery life. Cases may interfere with charging and will reduce charging speed. Charge speeds may vary. See g.co/pixel/wirelesscharging for more information. 
10 Pixel 5 has a dust and water protection rating of IP68 under IEC standard 60529. Charger and accessories are not water-resistant or dust-resistant. Water and dust resistance are not permanent conditions and may be compromised due to normal wear and tear, repair, disassembly or damage. 
11 The Google One, Google Play Pass, Google Play Points, and YouTube Premium offers are available to eligible new users with the purchase of Pixel 4a (5G) or Pixel 5. Offer expires April 30, 2021 at 11:59pm PT. See g.co/pixel/4a5Goffers or g.co/pixel/5offers, as applicable, for more details.

Announcing Cirq: An Open Source Framework for NISQ Algorithms



Over the past few years, quantum computing has experienced a growth not only in the construction of quantum hardware, but also in the development of quantum algorithms. With the availability of Noisy Intermediate Scale Quantum (NISQ) computers (devices with ~50 - 100 qubits and high fidelity quantum gates), the development of algorithms to understand the power of these machines is of increasing importance. However, a common problem when designing a quantum algorithm on a NISQ processor is how to take full advantage of these limited quantum devices—using resources to solve the hardest part of the problem rather than on overheads from poor mappings between the algorithm and hardware. Furthermore some quantum processors have complex geometric constraints and other nuances, and ignoring these will either result in faulty quantum computation, or a computation that is modified and sub-optimal.*

Today at the First International Workshop on Quantum Software and Quantum Machine Learning (QSML), the Google AI Quantum team announced the public alpha of Cirq, an open source framework for NISQ computers. Cirq is focused on near-term questions and helping researchers understand whether NISQ quantum computers are capable of solving computational problems of practical importance. Cirq is licensed under Apache 2, and is free to be modified or embedded in any commercial or open source package.
Once installed, Cirq enables researchers to write quantum algorithms for specific quantum processors. Cirq gives users fine tuned control over quantum circuits, specifying gate behavior using native gates, placing these gates appropriately on the device, and scheduling the timing of these gates within the constraints of the quantum hardware. Data structures are optimized for writing and compiling these quantum circuits to allow users to get the most out of NISQ architectures. Cirq supports running these algorithms locally on a simulator, and is designed to easily integrate with future quantum hardware or larger simulators via the cloud.
We are also announcing the release of OpenFermion-Cirq, an example of a Cirq based application enabling near-term algorithms. OpenFermion is a platform for developing quantum algorithms for chemistry problems, and OpenFermion-Cirq is an open source library which compiles quantum simulation algorithms to Cirq. The new library uses the latest advances in building low depth quantum algorithms for quantum chemistry problems to enable users to go from the details of a chemical problem to highly optimized quantum circuits customized to run on particular hardware. For example, this library can be used to easily build quantum variational algorithms for simulating properties of molecules and complex materials.

Quantum computing will require strong cross-industry and academic collaborations if it is going to realize its full potential. In building Cirq, we worked with early testers to gain feedback and insight into algorithm design for NISQ computers. Below are some examples of Cirq work resulting from these early adopters:
To learn more about how Cirq is helping enable NISQ algorithms, please visit the links above where many of the adopters have provided example source code for their implementations.

Today, the Google AI Quantum team is using Cirq to create circuits that run on Google’s Bristlecone processor. In the future, we plan to make this processor available in the cloud, and Cirq will be the interface in which users write programs for this processor. In the meantime, we hope Cirq will improve the productivity of NISQ algorithm developers and researchers everywhere. Please check out the GitHub repositories for Cirq and OpenFermion-Cirq — pull requests welcome!

Acknowledgements
We would like to thank Craig Gidney for leading the development of Cirq, Ryan Babbush and Kevin Sung for building OpenFermion-Cirq and a whole host of code contributors to both frameworks.


* An analogous situation is how early classical programmers needed to run complex programs in very small memory spaces by paying careful attention to the lowest level details of the hardware.

Source: Google AI Blog


TFGAN: A Lightweight Library for Generative Adversarial Networks



(Crossposted on the Google Open Source Blog)

Training a neural network usually involves defining a loss function, which tells the network how close or far it is from its objective. For example, image classification networks are often given a loss function that penalizes them for giving wrong classifications; a network that mislabels a dog picture as a cat will get a high loss. However, not all problems have easily-defined loss functions, especially if they involve human perception, such as image compression or text-to-speech systems. Generative Adversarial Networks (GANs), a machine learning technique that has led to improvements in a wide range of applications including generating images from text, superresolution, and helping robots learn to grasp, offer a solution. However, GANs introduce new theoretical and software engineering challenges, and it can be difficult to keep up with the rapid pace of GAN research.
A video of a generator improving over time. It begins by producing random noise, and eventually learns to generate MNIST digits.
In order to make GANs easier to experiment with, we’ve open sourced TFGAN, a lightweight library designed to make it easy to train and evaluate GANs. It provides the infrastructure to easily train a GAN, provides well-tested loss and evaluation metrics, and gives easy-to-use examples that highlight the expressiveness and flexibility of TFGAN. We’ve also released a tutorial that includes a high-level API to quickly get a model trained on your data.
This demonstrates the effect of an adversarial loss on image compression. The top row shows image patches from the ImageNet dataset. The middle row shows the results of compressing and uncompressing an image through an image compression neural network trained on a traditional loss. The bottom row shows the results from a network trained with a traditional loss and an adversarial loss. The GAN-loss images are sharper and more detailed, even if they are less like the original.
TFGAN supports experiments in a few important ways. It provides simple function calls that cover the majority of GAN use-cases so you can get a model running on your data in just a few lines of code, but is built in a modular way to cover more exotic GAN designs as well. You can just use the modules you want — loss, evaluation, features, training, etc. are all independent. TFGAN’s lightweight design also means you can use it alongside other frameworks, or with native TensorFlow code. GAN models written using TFGAN will easily benefit from future infrastructure improvements, and you can select from a large number of already-implemented losses and features without having to rewrite your own. Lastly, the code is well-tested, so you don’t have to worry about numerical or statistical mistakes that are easily made with GAN libraries.
Most neural text-to-speech (TTS) systems produce over-smoothed spectrograms. When applied to the Tacotron TTS system, a GAN can recreate some of the realistic-texture, which reduces artifacts in the resulting audio.
When you use TFGAN, you’ll be using the same infrastructure that many Google researchers use, and you’ll have access to the cutting-edge improvements that we develop with the library. Anyone can contribute to the github repositories, which we hope will facilitate code-sharing among ML researchers and users.

Tangent: Source-to-Source Debuggable Derivatives



Tangent is a new, free, and open-source Python library for automatic differentiation. In contrast to existing machine learning libraries, Tangent is a source-to-source system, consuming a Python function f and emitting a new Python function that computes the gradient of f. This allows much better user visibility into gradient computations, as well as easy user-level editing and debugging of gradients. Tangent comes with many more features for debugging and designing machine learning models:
This post gives an overview of the Tangent API. It covers how to use Tangent to generate gradient code in Python that is easy to interpret, debug and modify.

Neural networks (NNs) have led to great advances in machine learning models for images, video, audio, and text. The fundamental abstraction that lets us train NNs to perform well at these tasks is a 30-year-old idea called reverse-mode automatic differentiation (also known as backpropagation), which comprises two passes through the NN. First, we run a “forward pass” to calculate the output value of each node. Then we run a “backward pass” to calculate a series of derivatives to determine how to update the weights to increase the model’s accuracy.

Training NNs, and doing research on novel architectures, requires us to compute these derivatives correctly, efficiently, and easily. We also need to be able to debug these derivatives when our model isn’t training well, or when we’re trying to build something new that we do not yet understand. Automatic differentiation, or just “autodiff,” is a technique to calculate the derivatives of computer programs that denote some mathematical function, and nearly every machine learning library implements it.

Existing libraries implement automatic differentiation by tracing a program’s execution (at runtime, like TF Eager, PyTorch and Autograd) or by building a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output.

As a result, you can finally read your automatic derivative code just like the rest of your program. Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility.

You can easily inspect and debug your models written in Tangent, without special tools or indirection. Tangent works on a large and growing subset of Python, provides extra autodiff features other Python ML libraries don’t have, is high-performance, and is compatible with TensorFlow and NumPy.

Automatic differentiation of Python code
How do we automatically generate derivatives of plain Python code? Math functions like tf.exp or  tf.log have derivatives, which we can compose to build the backward pass. Similarly, pieces of syntax, such as subroutines, conditionals, and loops, also have backward-pass versions. Tangent contains recipes for generating derivative code for each piece of Python syntax, along with many NumPy and TensorFlow function calls.

Tangent has a one-function API:
Here’s an animated graphic of what happens when we call tangent.grad on a Python function:
If you want to print out your derivatives, you can run:
Under the hood, tangent.grad first grabs the source code of the Python function you pass it. Tangent has a large library of recipes for the derivatives of Python syntax, as well as TensorFlow Eager functions. The function  tangent.grad then walks your code in reverse order, looks up the matching backward-pass recipe, and adds it to the end of the derivative function. This reverse-order processing gives the technique its name: reverse-mode automatic differentiation.

The function df above only works for scalar (non-array) inputs. Tangent also supports
Although we started with TensorFlow Eager support, Tangent isn’t tied to one numeric library or another—we would gladly welcome pull requests adding PyTorch or MXNet derivative recipes.

Next Steps
Tangent is open source now at github.com/google/tangent. Go check it out for download and installation instructions. Tangent is still an experiment, so expect some bugs. If you report them to us on GitHub, we will do our best to fix them quickly.

We are working to add support in Tangent for more aspects of the Python language (e.g., closures, inline function definitions, classes, more NumPy and TensorFlow functions). We also hope to add more advanced automatic differentiation and compiler functionality in the future, such as automatic trade-off between memory and compute (Griewank and Walther 2000; Gruslys et al., 2016), more aggressive optimizations, and lambda lifting.

We intend to develop Tangent together as a community. We welcome pull requests with fixes and features. Happy differentiating!

Acknowledgments
Bart van Merriënboer contributed immensely to all aspects of Tangent during his internship, and Dan Moldovan led TF Eager integration, infrastructure and benchmarking. Also, thanks to the Google Brain team for their support of this post and special thanks to Sanders Kleinfeld, Matt Johnson and Aleks Haecky for their valuable contribution for the technical aspects of the post.

ICSE 2015 and Software Engineering Research at Google



The large scale of our software engineering efforts at Google often pushes us to develop cutting-edge infrastructure. In May 2015, at the International Conference on Software Engineering (ICSE 2015), we shared some of our software engineering tools and practices and collaborated with the research community through a combination of publications, committee memberships, and workshops. Learn more about some of our research below (Googlers highlighted in blue).

Google was a Gold supporter of ICSE 2015.

Technical Research Papers:
A Flexible and Non-intrusive Approach for Computing Complex Structural Coverage Metrics
Michael W. Whalen, Suzette Person, Neha Rungta, Matt Staats, Daniela Grijincu

Automated Decomposition of Build Targets
Mohsen Vakilian, Raluca Sauciuc, David Morgenthaler, Vahab Mirrokni

Tricorder: Building a Program Analysis Ecosystem
Caitlin Sadowski, Jeffrey van Gogh, Ciera Jaspan, Emma Soederberg, Collin Winter

Software Engineering in Practice (SEIP) Papers:
Comparing Software Architecture Recovery Techniques Using Accurate Dependencies
Thibaud Lutellier, Devin Chollak, Joshua Garcia, Lin Tan, Derek Rayside, Nenad Medvidovic, Robert Kroeger

Technical Briefings:
Software Engineering for Privacy in-the-Large
Pauline Anthonysamy, Awais Rashid

Workshop Organizers:
2nd International Workshop on Requirements Engineering and Testing (RET 2015)
Elizabeth Bjarnason, Mirko Morandini, Markus Borg, Michael Unterkalmsteiner, Michael Felderer, Matthew Staats

Committee Members:
Caitlin Sadowski - Program Committee Member and Distinguished Reviewer Award Winner
James Andrews - Review Committee Member
Ray Buse - Software Engineering in Practice (SEIP) Committee Member and Demonstrations Committee Member
John Penix - Software Engineering in Practice (SEIP) Committee Member
Marija Mikic - Poster Co-chair
Daniel Popescu and Ivo Krka - Poster Committee Members