Announcing the First Group of Google Open Source Peer Bonus winners in 2021!

 

Google Open Source Peer Bonus logo


The Google Open Source Peer Bonus program is designed to reward external open source contributors nominated by Googlers for their exceptional contributions to open source. We are very excited to announce our first group of winners in 2021!

Our current winners have contributed to a wide range of projects including Apache Beam, Kubernetes, Tekton and many others. We reward open source enthusiasts not only for their code contributions, but also community work, documentation, mentorships and other types of engagement.

We have award recipients from 25 countries all over the world: Austria, Canada, China, Cyprus, Denmark, Finland, France, Germany, India, Isle of Man, Italy, Japan, Korea, Netherlands, Norway, Russia, Singapore, Spain, Sweden, Switzerland, Uganda, Taiwan, Ukraine, United Kingdom, and the United States.

Open source encourages innovation through collaboration and our modern world, and technology that we rely on, wouldn’t be the same without you—the contributors, who are in many cases volunteers. We would like to thank you for your hard work and congratulate you on receiving this award!

Below is the list of current winners who gave us permission to thank them publicly:

WinnerProject
Kashyap JoisAndroid FHIR SDK
David AllisonAnkiDroid
Chad DombrovaApache Beam
Jeff KlukasApache Beam
Steve NiemitzApache Beam
Yoshiki ObataApache Beam
Jaskirat SinghCHAOSS - Community Health Analytics Open Source Software
Eric AmordeCocoaPods
Subrata Banikcoreboot
Ned BatchelderCoverage.py & related CPython internals
Matthew BryantCursedChrome
Simon Legnerdevdocs.io
Dmitry GutovEmacs/company-mode
Brian JostFirebase
Joe HinkleFirebase iOS SDK
Lorenzo FiamigoFirebase iOS SDK
Mike GerasymenkoFirebase iOS SDK
Morten Bek DitlevsenFirebase iOS SDK
Angel PonsFlashrom
Ole André Vadla RavnåsFrida
Junegunn Choifzf
Alex SaveauGradle Play Publisher
Nate GrahamKDE
Amit SagtaniKDE Community
Niklas HanssonKubeflow Pipelines
William TeoKubeflow Pipelines
Antonio OjeaKubernetes
Dan MangumKubernetes
Jian ZengKubernetes
Darrell Commanderlibjpeg-turbo
James (purpleidea)mgmt
Kareem ErgawyMLIR
Lily BallardNix / Fish
Eelco DolstraNix, NixOS, Nixpkgs
Samuel Dionne-RielNixOS
Dmitry DemenskyOpen source TypeScript definitions for Google Maps Platform
Kay WilliamsOpenSSF
Hassan Kibirigeplotnine
Henry Schreinerpybind11
Paul MoorePython 'pip' project
Tzu-ping ChungPython 'pip' project
Alex GrönholmPython 'wheel' project
Ramon Santamariaraylib
Alexander Weissrestic
Michael Eischerrestic
Ben Leshrxjs
Takeshi Nakatanis3fs
Daniel Wee Soong LimSymbiFlow
Unai Martinez-CorralSymbiFlow, Surelog, Verible, more
Andrea FrittoliTekton
Priti DesaiTekton
Vincent DemeesterTekton
Chengyu Zhangtestsmt & testsmt/yinyang
Dominik Winterertestsmt & testsmt/yinyang
Tom RiniU-Boot

Thank you for your contributions to open source!

By Maria Tabak — Google Open Source Programs Office

Announcing the First Group of Google Open Source Peer Bonus winners in 2021!

 

Google Open Source Peer Bonus logo


The Google Open Source Peer Bonus program is designed to reward external open source contributors nominated by Googlers for their exceptional contributions to open source. We are very excited to announce our first group of winners in 2021!

Our current winners have contributed to a wide range of projects including Apache Beam, Kubernetes, Tekton and many others. We reward open source enthusiasts not only for their code contributions, but also community work, documentation, mentorships and other types of engagement.

We have award recipients from 25 countries all over the world: Austria, Canada, China, Cyprus, Denmark, Finland, France, Germany, India, Isle of Man, Italy, Japan, Korea, Netherlands, Norway, Russia, Singapore, Spain, Sweden, Switzerland, Uganda, Taiwan, Ukraine, United Kingdom, and the United States.

Open source encourages innovation through collaboration and our modern world, and technology that we rely on, wouldn’t be the same without you—the contributors, who are in many cases volunteers. We would like to thank you for your hard work and congratulate you on receiving this award!

Below is the list of current winners who gave us permission to thank them publicly:

WinnerProject
Kashyap JoisAndroid FHIR SDK
David AllisonAnkiDroid
Chad DombrovaApache Beam
Jeff KlukasApache Beam
Steve NiemitzApache Beam
Yoshiki ObataApache Beam
Jaskirat SinghCHAOSS - Community Health Analytics Open Source Software
Eric AmordeCocoaPods
Subrata Banikcoreboot
Ned BatchelderCoverage.py & related CPython internals
Matthew BryantCursedChrome
Simon Legnerdevdocs.io
Dmitry GutovEmacs/company-mode
Brian JostFirebase
Joe HinkleFirebase iOS SDK
Lorenzo FiamigoFirebase iOS SDK
Mike GerasymenkoFirebase iOS SDK
Morten Bek DitlevsenFirebase iOS SDK
Angel PonsFlashrom
Ole André Vadla RavnåsFrida
Junegunn Choifzf
Alex SaveauGradle Play Publisher
Nate GrahamKDE
Amit SagtaniKDE Community
Niklas HanssonKubeflow Pipelines
William TeoKubeflow Pipelines
Antonio OjeaKubernetes
Dan MangumKubernetes
Jian ZengKubernetes
Darrell Commanderlibjpeg-turbo
James (purpleidea)mgmt
Kareem ErgawyMLIR
Lily BallardNix / Fish
Eelco DolstraNix, NixOS, Nixpkgs
Samuel Dionne-RielNixOS
Dmitry DemenskyOpen source TypeScript definitions for Google Maps Platform
Kay WilliamsOpenSSF
Hassan Kibirigeplotnine
Henry Schreinerpybind11
Paul MoorePython 'pip' project
Tzu-ping ChungPython 'pip' project
Alex GrönholmPython 'wheel' project
Ramon Santamariaraylib
Alexander Weissrestic
Michael Eischerrestic
Ben Leshrxjs
Takeshi Nakatanis3fs
Daniel Wee Soong LimSymbiFlow
Unai Martinez-CorralSymbiFlow, Surelog, Verible, more
Andrea FrittoliTekton
Priti DesaiTekton
Vincent DemeesterTekton
Chengyu Zhangtestsmt & testsmt/yinyang
Dominik Winterertestsmt & testsmt/yinyang
Tom RiniU-Boot

Thank you for your contributions to open source!

By Maria Tabak — Google Open Source Programs Office

What creators should know about Google’s product reviews update

Google Search is always working to show the most useful and helpful information possible, through testing, experimenting, and review processes. From this, we know people appreciate product reviews that share in-depth research, rather than thin content that simply summarizes a bunch of products. That’s why we’re sharing an improvement to our ranking systems, which we call the product reviews update, that’s designed to better reward such content.

What creators should know about Google’s product reviews update

Google Search is always working to show the most useful and helpful information possible, through testing, experimenting, and review processes. From this, we know people appreciate product reviews that share in-depth research, rather than thin content that simply summarizes a bunch of products. That’s why we’re sharing an improvement to our ranking systems, which we call the product reviews update, that’s designed to better reward such content.

Ikumi Kobayashi on taking inclusion seriously

Welcome to the latest edition of “My Path to Google,” where we talk to Googlers, interns and alumni about how they got to Google, what their roles are like and even some tips on how to prepare for interviews.


Today’s post is all about Ikumi Kobayashi, a Search Optimization Specialist based out of Tokyo whose search for an inclusive and accessible workplace ultimately led her to her role at Google and a newfound confidence.


Can you tell us about your decision to apply to Google? 

I have profound hearing loss in both ears and use hearing aids. I rely on lip-reading during conversations. As a person with a disability (PwD), I struggled during my job hunt in Japan because most of the companies I applied to had limited job postings for PwD, and the benefits for PwD were often unequal compared to people without a disability. 


I decided to apply to Google because I wanted to work in a company that takes diversity and inclusion seriously. I was nervous before applying to Google because teamwork can be difficult for a hard-of-hearing person like me, but I decided to give it a try because I had nothing to lose.


How would you describe your path to your current role at Google? 

I studied communications in undergrad and joined Google right out of grad school, so Google is the first company I’ve worked at. I was an intern my first year at Google, and during that time my team supported me to overcome anxiety and build confidence as a Googler with a hearing disability. 


I started as a Google Ads Account Manager, but I found face-to-face conversations with many clients everyday difficult and I preferred working more with the product and with my teammates. After three months, I moved to my current team. My job title is now Search Optimization Specialist and my responsibility is to support Japanese companies in the entertainment industry as they run and optimize their Google Search Ads. It is very rewarding to see the companies I support grow and I am really thankful for the previous and current team who accommodated flexibly for me.

Ten people gathered around a table inside of a restaurant.

Ikumi and teammates out at dinner in 2019.

What does your typical day look like right now? 

After our Google Tokyo office completely shut down in March 2020, I have been working remotely in my apartment in Tokyo. I really miss meeting my teammates and friends in the office, but I keep myself energized by proactively setting up meetings as much as possible. Conversations with Googlers always help me to maximize my productivity. Outside of work, I'm a fashion enthusiast and go to a fashion design school three times a week after work. I love to watch fashion shows on YouTube during my free time.


What inspires you to come in (or log on) every day?

I am passionate about advocating for diversity, inclusion and accessibility so I joined the Disability Alliance — an employee resource group for Googlers. Right now, I am the only Japanese hard-of-hearing Googler on the Google Ads team and we can do more to diversify the Asia-Pacific Google community. I strive to do my best to make our community even more accessible for Googlers with disabilities.

Ikumi speaking into a microphone in front of a large group. A slide is projected behind her introducing herself.

What's one thing you wish you could go back and tell yourself before applying? 

I would love to tell my past self (and anyone else with a disability who is considering applying to Google) that Google will not let you down because of your disability. I was once a very unconfident person because I was always left behind during conversations and felt helpless. Google’s mission statement is to make the world's information universally accessible and useful, and that applies to the workplace as well. 


Can you tell us about the resources you used to prepare for your interview or role? 

Before applying to Google as a grad student, I had little work experience so I spent lots of time revisiting my past challenges and thinking through how I tried to overcome them. Leadership doesn't only mean leading a group. If you have an experience challenging yourself to achieve a goal, that is also a leadership skill. My advice is to go to the interview fully prepared to share your strengths.


Do you have any other tips you’d like to share with aspiring Googlers?

Be confident and embrace your uniqueness. Also, don't be afraid to share any accommodation needs during the application process. Bring all of yourself to the interview and tell us how amazing you are! 

Ikumi Kobayashi on taking inclusion seriously

Welcome to the latest edition of “My Path to Google,” where we talk to Googlers, interns and alumni about how they got to Google, what their roles are like and even some tips on how to prepare for interviews.


Today’s post is all about Ikumi Kobayashi, a Search Optimization Specialist based out of Tokyo whose search for an inclusive and accessible workplace ultimately led her to her role at Google and a newfound confidence.


Can you tell us about your decision to apply to Google? 

I have profound hearing loss in both ears and use hearing aids. I rely on lip-reading during conversations. As a person with a disability (PwD), I struggled during my job hunt in Japan because most of the companies I applied to had limited job postings for PwD, and the benefits for PwD were often unequal compared to people without a disability. 


I decided to apply to Google because I wanted to work in a company that takes diversity and inclusion seriously. I was nervous before applying to Google because teamwork can be difficult for a hard-of-hearing person like me, but I decided to give it a try because I had nothing to lose.


How would you describe your path to your current role at Google? 

I studied communications in undergrad and joined Google right out of grad school, so Google is the first company I’ve worked at. I was an intern my first year at Google, and during that time my team supported me to overcome anxiety and build confidence as a Googler with a hearing disability. 


I started as a Google Ads Account Manager, but I found face-to-face conversations with many clients everyday difficult and I preferred working more with the product and with my teammates. After three months, I moved to my current team. My job title is now Search Optimization Specialist and my responsibility is to support Japanese companies in the entertainment industry as they run and optimize their Google Search Ads. It is very rewarding to see the companies I support grow and I am really thankful for the previous and current team who accommodated flexibly for me.

Ten people gathered around a table inside of a restaurant.

Ikumi and teammates out at dinner in 2019.

What does your typical day look like right now? 

After our Google Tokyo office completely shut down in March 2020, I have been working remotely in my apartment in Tokyo. I really miss meeting my teammates and friends in the office, but I keep myself energized by proactively setting up meetings as much as possible. Conversations with Googlers always help me to maximize my productivity. Outside of work, I'm a fashion enthusiast and go to a fashion design school three times a week after work. I love to watch fashion shows on YouTube during my free time.


What inspires you to come in (or log on) every day?

I am passionate about advocating for diversity, inclusion and accessibility so I joined the Disability Alliance — an employee resource group for Googlers. Right now, I am the only Japanese hard-of-hearing Googler on the Google Ads team and we can do more to diversify the Asia-Pacific Google community. I strive to do my best to make our community even more accessible for Googlers with disabilities.

Ikumi speaking into a microphone in front of a large group. A slide is projected behind her introducing herself.

What's one thing you wish you could go back and tell yourself before applying? 

I would love to tell my past self (and anyone else with a disability who is considering applying to Google) that Google will not let you down because of your disability. I was once a very unconfident person because I was always left behind during conversations and felt helpless. Google’s mission statement is to make the world's information universally accessible and useful, and that applies to the workplace as well. 


Can you tell us about the resources you used to prepare for your interview or role? 

Before applying to Google as a grad student, I had little work experience so I spent lots of time revisiting my past challenges and thinking through how I tried to overcome them. Leadership doesn't only mean leading a group. If you have an experience challenging yourself to achieve a goal, that is also a leadership skill. My advice is to go to the interview fully prepared to share your strengths.


Do you have any other tips you’d like to share with aspiring Googlers?

Be confident and embrace your uniqueness. Also, don't be afraid to share any accommodation needs during the application process. Bring all of yourself to the interview and tell us how amazing you are! 

Announcing the 2021 Research Scholar Program Recipients

In March 2020 we introduced the Research Scholar Program, an effort focused on developing collaborations with new professors and encouraging the formation of long-term relationships with the academic community. In November we opened the inaugural call for proposals for this program, which was received with enthusiastic interest from faculty who are working on cutting edge research across many research areas in computer science, including machine learning, human-computer interaction, health research, systems and more.

Today we are pleased to announce that in this first year of the program we have granted 77 awards, which included 86 principal investigators representing 15+ countries and over 50 universities. Of the 86 award recipients, 43% identify as an historically marginalized group within technology. Please see the full list of 2021 recipients on our web page, as well as in the list below.

We offer our congratulations to this year’s recipients, and look forward to seeing what they achieve!

Algorithms and Optimization
Alexandros Psomas, Purdue University
   Auction Theory Beyond Independent, Quasi-Linear Bidders
Julian Shun, Massachusetts Institute of Technology
   Scalable Parallel Subgraph Finding and Peeling Algorithms
Mary Wootters, Stanford University
   The Role of Redundancy in Algorithm Design
Pravesh K. Kothari, Carnegie Mellon University
   Efficient Algorithms for Robust Machine Learning
Sepehr Assadi, Rutgers University
   Graph Clustering at Scale via Improved Massively Parallel Algorithms

Augmented Reality and Virtual Reality
Srinath Sridhar, Brown University
   Perception and Generation of Interactive Objects

Geo
Miriam E. Marlier, University of California, Los Angeles
   Mapping California’s Compound Climate Hazards in Google Earth Engine
Suining He, University of Connecticut
   Fairness-Aware and Cross-Modality Traffic Learning and Predictive Modeling for Urban Smart Mobility Systems

Human Computer Interaction
Arvind Satyanarayan, Massachusetts Institute of Technology
   Generating Semantically Rich Natural Language Captions for Data Visualizations to Promote Accessibility
Dina El-Zanfaly, Carnegie Mellon University
   In-the-making: An intelligence mediated collaboration system for creative practices
Katharina Reinecke, University of Washington
   Providing Science-Backed Answers to Health-related Questions in Google Search
Misha Sra, University of California, Santa Barbara
   Hands-free Game Controller for Quadriplegic Individuals
Mohsen Mosleh, University of Exeter Business School
   Effective Strategies to Debunk False Claims on Social Media: A large-scale digital field experiments approach
Tanushree Mitra, University of Washington
   Supporting Scalable Value-Sensitive Fact-Checking through Human-AI Intelligence

Health Research
Catarina Barata, Instituto Superior Técnico, Universidade de Lisboa
   DeepMutation – A CNN Model To Predict Genetic Mutations In Melanoma Patients
Emma Pierson, Cornell Tech, the Jacobs Institute, Technion-Israel Institute of Technology, and Cornell University
   Using cell phone mobility data to reduce inequality and improve public health
Jasmine Jones, Berea College
   Reachout: Co-Designing Social Connection Technologies for Isolated Young Adults
Mojtaba Golzan, University of Technology Sydney, Jack Phu, University of New South Wales
   Autonomous Grading of Dynamic Blood Vessel Markers in the Eye using Deep Learning
Serena Yeung, Stanford University
   Artificial Intelligence Analysis of Surgical Technique in the Operating Room

Machine Learning and Data Mining
Aravindan Vijayaraghavan, Northwestern University, Sivaraman Balakrishnan, Carnegie Mellon University
   Principled Approaches for Learning with Test-time Robustness
Cho-Jui Hsieh, University of California, Los Angeles
   Scalability and Tunability for Neural Network Optimizers
Golnoosh Farnadi, University of Montreal, HEC Montreal/MILA
   Addressing Algorithmic Fairness in Decision-focused Deep Learning
Harrie Oosterhuis, Radboud University
   Search and Recommendation Systems that Learn from Diverse User Preferences
Jimmy Ba, University of Toronto
   Model-based Reinforcement Learning with Causal World Models
Nadav Cohen, Tel-Aviv University
   A Dynamical Theory of Deep Learning
Nihar Shah, Carnegie Mellon University
   Addressing Unfairness in Distributed Human Decisions
Nima Fazeli, University of Michigan
   Semi-Implicit Methods for Deformable Object Manipulation
Qingyao Ai, University of Utah
   Metric-agnostic Ranking Optimization
Stefanie Jegelka, Massachusetts Institute of Technology
   Generalization of Graph Neural Networks under Distribution Shifts
Virginia Smith, Carnegie Mellon University
   A Multi-Task Approach for Trustworthy Federated Learning

Mobile
Aruna Balasubramanian, State University of New York – Stony Brook
   AccessWear: Ubiquitous Accessibility using Wearables
Tingjun Chen, Duke University
   Machine Learning- and Optical-enabled Mobile Millimeter-Wave Networks

Machine Perception
Amir Patel, University of Cape Town
   WildPose: 3D Animal Biomechanics in the Field using Multi-Sensor Data Fusion
Angjoo Kanazawa, University of California, Berkeley
   Practical Volumetric Capture of People and Scenes
Emanuele Rodolà, Sapienza University of Rome
   Fair Geometry: Toward Algorithmic Debiasing in Geometric Deep Learning
Minchen Wei, Hong Kong Polytechnic University
   Accurate Capture of Perceived Object Colors for Smart Phone Cameras
Mohsen Ali and Izza Aftab, Information Technology University of the Punjab, Pakistan
   Is Economics From Afar Domain Generalizable?
Vineeth N Balasubramanian, Indian Institute of Technology Hyderabad
   Bridging Perspectives of Explainability and Adversarial Robustness
Xin Yu and Linchao Zhu, University of Technology Sydney
   Sign Language Translation in the Wild

Networking
Aurojit Panda, New York University
   Bertha: Network APIs for the Programmable Network Era
Cristina Klippel Dominicini, Instituto Federal do Espirito Santo
   Polynomial Key-based Architecture for Source Routing in Network Fabrics
Noa Zilberman, University of Oxford
   Exposing Vulnerabilities in Programmable Network Devices
Rachit Agarwal, Cornell University
   Designing Datacenter Transport for Terabit Ethernet

Natural Language Processing
Danqi Chen, Princeton University
   Improving Training and Inference Efficiency of NLP Models
Derry Tanti Wijaya, Boston University, Anietie Andy, University of Pennsylvania
   Exploring the evolution of racial biases over time through framing analysis
Eunsol Choi, University of Texas at Austin
   Answering Information Seeking Questions In The Wild
Kai-Wei Chang, University of California, Los Angeles
   Certified Robustness to against language differences in Cross-Lingual Transfer
Mohohlo Samuel Tsoeu, University of Cape Town
   Corpora collection and complete natural language processing of isiXhosa, Sesotho and South African Sign languages
Natalia Diaz Rodriguez, University of Granada (Spain) + ENSTA, Institut Polytechnique Paris, Inria. Lorenzo Baraldi, University of Modena and Reggio Emilia
   SignNet: Towards democratizing content accessibility for the deaf by aligning multi-modal sign representations

Other Research Areas
John Dickerson, University of Maryland – College Park, Nicholas Mattei, Tulane University
   Fairness and Diversity in Graduate Admissions
Mor Nitzan, Hebrew University
   Learning representations of tissue design principles from single-cell data
Nikolai Matni, University of Pennsylvania
   Robust Learning for Safe Control

Privacy
Foteini Baldimtsi, George Mason University
   Improved Single-Use Anonymous Credentials with Private Metabit
Yu-Xiang Wang, University of California, Santa Barbara
   Stronger, Better and More Accessible Differential Privacy with autodp

Quantum Computing
Ashok Ajoy, University of California, Berkeley
   Accelerating NMR spectroscopy with a Quantum Computer
John Nichol, University of Rochester
   Coherent spin-photon coupling
Jordi Tura i Brugués, Leiden University
   RAGECLIQ - Randomness Generation with Certification via Limited Quantum Devices
Nathan Wiebe, University of Toronto
   New Frameworks for Quantum Simulation and Machine Learning
Philipp Hauke, University of Trento
   ProGauge: Protecting Gauge Symmetry in Quantum Hardware
Shruti Puri, Yale University
   Surface Code Co-Design for Practical Fault-Tolerant Quantum Computing

Structured Data, Extraction, Semantic Graph, and Database Management
Abolfazl Asudeh, University Of Illinois, Chicago
   An end-to-end system for detecting cherry-picked trendlines
Eugene Wu, Columbia University
   Interactive training data debugging for ML analytics
Jingbo Shang, University of California, San Diego
   Structuring Massive Text Corpora via Extremely Weak Supervision

Security
Chitchanok Chuengsatiansup and Markus Wagner, University of Adelaide
   Automatic Post-Quantum Cryptographic Code Generation and Optimization
Elette Boyle, IDC Herzliya, Israel
   Cheaper Private Set Intersection via Advances in "Silent OT"
Joseph Bonneau, New York University
   Zeroizing keys in secure messaging implementations
Yu Feng , University of California, Santa Barbara, Yuan Tian, University of Virginia
   Exploit Generation Using Reinforcement Learning

Software engineering and Programming Languages
Kelly Blincoe, University of Auckland
   Towards more inclusive software engineering practices to retain women in software engineering
Fredrik Kjolstad, Stanford University
   Sparse Tensor Algebra Compilation to Domain-Specific Architectures
Milos Gligoric, University of Texas at Austin
   Adaptive Regression Test Selection
Sarah E. Chasins, University of California, Berkeley
   If you break it, you fix it: Synthesizing program transformations so that library maintainers can make breaking changes

Systems
Adwait Jog, College of William & Mary
   Enabling Efficient Sharing of Emerging GPUs
Heiner Litz, University of California, Santa Cruz
   Software Prefetching Irregular Memory Access Patterns
Malte Schwarzkopf, Brown University
   Privacy-Compliant Web Services by Construction
Mehdi Saligane, University of Michigan
   Autonomous generation of Open Source Analog & Mixed Signal IC
Nathan Beckmann, Carnegie Mellon University
   Making Data Access Faster and Cheaper with Smarter Flash Caches
Yanjing Li, University of Chicago
   Resilient Accelerators for Deep Learning Training Tasks

Source: Google AI Blog


Tools to help developers provide a positive user experience

Posted by Lisa Martinez, Head of Security & Privacy Business Development, Google Play and Andrew Ahn, Product Manager, Play and Android App Safety

Google helps protect billions of users every day through the use of a robust set of tools designed to keep users safe online. We’re proud to provide a wide range of these same resources to help developers build safe and successful apps. User participation increases when people have a safe and positive app engagement. We’d like to highlight a few of these free tools that developers can consider to help make user experiences safer for everyone.

Reducing toxic conversation with Perspective API

Perspective API, a free product offered by Jigsaw, uses machine learning to identify toxic language, like insults, profanity, or identity based attacks, making it easier to host healthier conversations in your apps. Perspective can be used to give feedback to commenters, help moderators more easily review comments, and keep conversations open online. Many online publishers and developers, such as the New York Times, El País, FACEIT, and Coral by VoxMedia have started to adopt this tool to promote constructive online dialogues. Learn how to get started here.

Increase child safety with Content Safety API

Google’s Content Safety API uses artificial intelligence to help developers better prioritize abuse material for review. We offer this service to NGOs and private companies to support their work protecting children. The API steps up the fight for child safety by prioritizing potentially illegal content for human review and helping reviewers find and report content faster. Quicker identification of new abuse images increases the likelihood that children being abused could be identified and protected from further abuse. Making review queues more efficient and less noisy also reduces the toll on human reviewers, who review images to confirm instances of abuse. Learn more about this on our Protecting Children site.

Prevent links to unsafe files and sites with the Safe Browsing API

Google Safe Browsing helps protect billions of devices every day by showing warnings to users when they attempt to navigate to dangerous sites or download dangerous files. Safe Browsing also notifies webmasters when their websites are compromised by malicious actors. Safe Browsing protections work across Google products and power safer browsing experiences across the Internet. Technical information on how to get started can be found here.

Thank you for continuing to partner with us to provide a positive experience for our shared users on Google Play.

Beta Channel Update for Desktop

 The Beta channel has been updated to 90.0.4430.61 for Windows Mac and Linux.



A full list of changes in this build is available in the log. Interested in switching release channels?  Find out how here. If you find a new issue, please let us know by filing a bug. The community help forum is also a great place to reach out for help or learn about common issues.


Srinivas Sista