Tag Archives: Open source

These 27 organizations will mentor students in Google Code-in 2018

We’re excited to welcome 27 open source organizations to mentor students as part of Google Code-in 2018. The contest, now in its ninth year, offers 13-17 year old pre-university students from around the world an opportunity to learn and practice their skills while contributing to open source projects–all online!

Google Code-in starts for students on October 23rd. Students are encouraged to learn about the participating organizations ahead of time and can get started by clicking on the links below:
  • AOSSIE: Australian umbrella organization for open source projects.
  • Apertium: rule-based machine translation platform.
  • Catrobat: visual programming for creating mobile games and animations.
  • CCExtractor: open source tools for subtitle generation.
  • CloudCV: building platforms for reproducible AI research.
  • coala: a unified interface for linting and fixing code, regardless of the programming languages used.
  • Copyleft Games Group: develops tools, libraries, and game engines.
  • Digital Impact Alliance: collaborative space for multiple open source projects serving the international development and humanitarian response sectors.
  • Drupal: content management platform.
  • Fedora Project: a free and friendly Linux-based operating system.
  • FOSSASIA: developing communities across all ages and borders to form a better future with Open Technologies and ICT.
  • Haiku: operating system specifically targeting personal computing.
  • JBoss Community: a community of projects around JBoss Middleware.
  • KDE Community: produces FOSS by artists, designers, programmers, translators, writers and other contributors.
  • Liquid Galaxy: an interactive, panoramic and immersive visualization tool.
  • MetaBrainz: builds community maintained databases.
  • MovingBlocks: a Minecraft-inspired open source game.
  • OpenMRS: open source medical records system for the world.
  • OpenWISP: build and manage low cost networks such as public wifi.
  • OSGeo: building open source geospatial tools.
  • PostgreSQL: relational database system.
  • Public Lab: open software to help communities measure and analyze pollution.
  • RTEMS Project: operating system used in satellites, particle accelerators, robots, racing motorcycles, building controls, medical devices.
  • Sugar Labs: learning platform and activities for elementary education.
  • SCoRe: research lab seeking sustainable solutions for problems faced by developing countries.
  • The ns-3 Network Simulator Project: packet-level network simulator for research and education.
  • Wikimedia: non-profit foundation dedicated to bringing free content to the world, operating Wikipedia.
These 27 organizations are hard at work creating thousands of tasks for students to work on, including code, documentation, design, quality assurance, outreach, research and training tasks. The contest starts for students on Tuesday, October 23rd at 9:00am Pacific Time.

You can learn more about Google Code-in on the contest site where you’ll find Frequently Asked Questions, Important Dates and flyers and other helpful information including the Getting Started Guide.

Want to talk with other students, mentors, and organization administrations about the contest? Check out our discussion mailing list. We can’t wait to get started!

By Stephanie Taylor, Google Open Source

Introducing the Unrestricted Adversarial Examples Challenge



Machine learning is being deployed in more and more real-world applications, including medicine, chemistry and agriculture. When it comes to deploying machine learning in safety-critical contexts, significant challenges remain. In particular, all known machine learning algorithms are vulnerable to adversarial examples — inputs that an attacker has intentionally designed to cause the model to make a mistake. While previous research on adversarial examples has mostly focused on investigating mistakes caused by small modifications in order to develop improved models, real-world adversarial agents are often not subject to the “small modification” constraint. Furthermore, machine learning algorithms can often make confident errors when faced with an adversary, which makes the development of classifiers that don’t make any confident mistakes, even in the presence of an adversary which can submit arbitrary inputs to try to fool the system, an important open problem.

Today we're announcing the Unrestricted Adversarial Examples Challenge, a community-based challenge to incentivize and measure progress towards the goal of zero confident classification errors in machine learning models. While previous research has focused on adversarial examples that are restricted to small changes to pre-labeled data points (allowing researchers to assume the image should have the same label after a small perturbation), this challenge allows unrestricted inputs, allowing participants to submit arbitrary images from the target classes to develop and test models on a wider variety of adversarial examples.
Adversarial examples can be generated through a variety of means, including by making small modifications to the input pixels, but also using spatial transformations, or simple guess-and-check to find misclassified inputs.
Structure of the Challenge
Participants can submit entries one of two roles: as a defender, by submitting a classifier which has been designed to be difficult to fool, or as an attacker, by submitting arbitrary inputs to try to fool the defenders' models. In a “warm-up” period before the challenge, we will present a set of fixed attacks for participants to design networks to defend against. After the community can conclusively beat those fixed attacks, we will launch the full two-sided challenge with prizes for both attacks and defenses.

For the purposes of this challenge, we have created a simple “bird-or-bicycle” classification task, where a classifier must answer the following: “Is this an unambiguous picture of a bird, a bicycle, or is it ambiguous / not obvious?” We selected this task because telling birds and bicycles apart is very easy for humans, but all known machine learning techniques struggle at the task when in the presence of an adversary.

The defender's goal is to correctly label a clean test set of birds and bicycles with high accuracy, while also making no confident errors on any attacker-provided bird or bicycle image. The attacker's goal is to find an image of a bird that the defending classifier confidently labels as a bicycle (or vice versa). We want to make the challenge as easy as possible for the defenders, so we discard all images that are ambiguous (such as a bird riding a bicycle) or not obvious (such as an aerial view of a park, or random noise).
Examples of ambiguous and unambiguous images. Defenders must make no confident mistakes on unambiguous bird or bicycle images. We discard all images that humans find ambiguous or not obvious. All images under CC licenses 1, 2, 3, 4.
Attackers may submit absolutely any image of a bird or a bicycle in an attempt to fool the defending classifier. For example, an attacker could take photographs of birds, use 3D rendering software, make image composites using image editing software, produce novel bird images with a generative model, or any other technique.

In order to validate new attacker-provided images, we ask an ensemble of humans to label the image. This procedure lets us allow attackers to submit arbitrary images, not just test set images modified in small ways. If the defending classifier confidently classifies as "bird" any attacker-provided image which the human labelers unanimously labeled as a bicycle, the defending model has been broken. You can learn more details about the structure of the challenge in our paper.

How to Participate
If you’re interested in participating, guidelines for getting started can be found on the project on github. We’ve already released our dataset, the evaluation pipeline, and baseline attacks for the warm-up, and we’ll be keeping an up-to-date leaderboard with the best defenses from the community. We look forward to your entries!

Acknowledgements
The team behind the Unrestricted Adversarial Examples Challenge includes Tom Brown, Catherine Olsson, Nicholas Carlini, Chiyuan Zhang, and Ian Goodfellow from Google, and Paul Christiano from OpenAI.

Source: Google AI Blog


Google Code-in 2018 is looking for great open source organizations to apply

We are accepting applications for open source organizations interested in participating in Google Code-in 2018. Google Code-in (GCI) invites pre-university students ages 13-17 to learn by contributing to open source software.

Working with young students is a special responsibility and each year we hear inspiring stories from mentors who participate. To ensure these new, young contributors have a solid support system, we only select organizations that have gained experience in mentoring students by previously taking part in Google Summer of Code.

Organization applications are now open and all interested open source organizations must apply before Monday, September 17 at 16:00 UTC.

In 2017, 25 organizations were accepted – 9 of which were participating in GCI for the first time! Over the last 8 years, 8,108 students from 107 countries have completed more than 40,000 tasks for participating open source projects. Tasks fall into 5 categories:
  • Code: writing or refactoring.
  • Documentation/Training: creating/editing documents and helping others learn more.
  • Outreach/Research: community management, outreach/marketing, or studying problems and recommending solutions.
  • Quality Assurance: testing and ensuring code is of high quality.
  • Design: graphic design or user interface design.
Once an organization is selected for Google Code-in 2018 they will define these tasks and recruit mentors from their communities who are interested in providing online support for students during the seven week contest.

You can find a timeline, FAQ and other information about Google Code-in on our website. If you’re an educator interested in sharing Google Code-in with your students, you can find resources here.

By Stephanie Taylor, Google Open Source

Introducing the Tink cryptographic software library

Cross-posted on the Google Security Blog

At Google, many product teams use cryptographic techniques to protect user data. In cryptography, subtle mistakes can have serious consequences, and understanding how to implement cryptography correctly requires digesting decades' worth of academic literature. Needless to say, many developers don’t have time for that.

To help our developers ship secure cryptographic code we’ve developed Tink—a multi-language, cross-platform cryptographic library. We believe in open source and want Tink to become a community project—thus Tink has been available on GitHub since the early days of the project, and it has already attracted several external contributors. At Google, Tink is already being used to secure data of many products such as AdMob, Google Pay, Google Assistant, Firebase, the Android Search App, etc. After nearly two years of development, today we’re excited to announce Tink 1.2.0, the first version that supports cloud, Android, iOS, and more!

Tink aims to provide cryptographic APIs that are secure, easy to use correctly, and hard(er) to misuse. Tink is built on top of existing libraries such as BoringSSL and Java Cryptography Architecture, but includes countermeasures to many weaknesses in these libraries, which were discovered by Project Wycheproof, another project from our team.

With Tink, many common cryptographic operations such as data encryption, digital signatures, etc. can be done with only a few lines of code. Here is an example of encrypting and decrypting with our AEAD interface in Java:
 import com.google.crypto.tink.Aead;
import com.google.crypto.tink.KeysetHandle;
import com.google.crypto.tink.aead.AeadFactory;
import com.google.crypto.tink.aead.AeadKeyTemplates;
// 1. Generate the key material.
KeysetHandle keysetHandle = KeysetHandle.generateNew(
AeadKeyTemplates.AES256_EAX);
// 2. Get the primitive.
Aead aead = AeadFactory.getPrimitive(keysetHandle);
// 3. Use the primitive.
byte[] plaintext = ...;
byte[] additionalData = ...;
byte[] ciphertext = aead.encrypt(plaintext, additionalData);
Tink aims to eliminate as many potential misuses as possible. For example, if the underlying encryption mode requires nonces and nonce reuse makes it insecure, then Tink does not allow the user to pass nonces. Interfaces have security guarantees that must be satisfied by each primitive implementing the interface. This may exclude some encryption modes. Rather than adding them to existing interfaces and weakening the guarantees of the interface, it is possible to add new interfaces and describe the security guarantees appropriately.

We’re cryptographers and security engineers working to improve Google’s product security, so we built Tink to make our job easier. Tink shows the claimed security properties (e.g., safe against chosen-ciphertext attacks) right in the interfaces, allowing security auditors and automated tools to quickly discover usages where the security guarantees don’t match the security requirements. Tink also isolates APIs for potentially dangerous operations (e.g., loading cleartext keys from disk), which allows discovering, restricting, monitoring and logging their usage.

Tink provides support for key management, including key rotation and phasing out deprecated ciphers. For example, if a cryptographic primitive is found to be broken, you can switch to a different primitive by rotating keys, without changing or recompiling code.

Tink is also extensible by design: it is easy to add a custom cryptographic scheme or an in-house key management system so that it works seamlessly with other parts of Tink. No part of Tink is hard to replace or remove. All components are composable, and can be selected and assembled in various combinations. For example, if you need only digital signatures, you can exclude symmetric key encryption components to minimize code size in your application.

To get started, please check out our HOW-TO for Java, C++ and Obj-C. If you'd like to talk to the developers or get notified about project updates, you may want to subscribe to our mailing list. To join, simply send an empty email to tink-users+subscribe@googlegroups.com. You can also post your questions to StackOverflow, just remember to tag them with tink.

We’re excited to share this with the community, and welcome your feedback!

By Thai Duong, Information Security Engineer, on behalf of Tink team

Announcing Google Code-in 2018: nine is just fine!

We are excited to announce the 9th consecutive year of the Google Code-in (GCI) contest! Students ages 13 through 17 from around the world can learn about open source development by working on real open source projects, with mentorship from active developers. GCI begins on Tuesday, October 23, 2018 and runs for seven weeks, ending Wednesday, December 12, 2018.

Google Code-in is unique because, not only do the students choose what they want to work on from the 2,500+ tasks created by open source organizations, but they have mentors available to help answer their questions as they work on each of their tasks.

Getting started in open source software can be a daunting task for a developer of any age. What organization should I work with? How do I get started? Does the organization want my help? Am I too inexperienced?

The beauty of GCI is that participating open source organizations realize teens are often first time contributors, so the volunteer mentors come prepared with the patience and the experience to help these newcomers become part of the open source community.

Open source communities thrive when there is a steady flow of new contributors who bring new perspectives, ideas and enthusiasm. Over the last 8 years, GCI open source organizations have helped 8,108 students from 107 countries make meaningful contributions. Many of these students are still participating in open source communities years later. Dozens have gone on to become Google Summer of Code (GSoC) students and even mentor other students.

The tasks that contest participants will complete vary in skill set and level, including beginner tasks any student can take on, such as “setup your development environment.” With tasks in five different categories, there’s something to fit almost any student’s skills:
  • Code: writing or refactoring
  • Documentation/Training: creating/editing documents and helping others learn more
  • Outreach/Research: community management, marketing, or studying problems and recommending solutions
  • Quality Assurance: testing and ensuring code is of high quality
  • Design: graphic design or user interface design
Open source organizations can apply to participate as mentoring organizations for in Google Code-in starting on Thursday, September 6, 2018. Google Code-in starts for students October 23rd!

Visit the contest site g.co/gci to learn more about the contest and find flyers, slide decks, timelines, and more.

By Stephanie Taylor, Google Open Source

That’s a wrap for Google Summer of Code 2018

We are pleased to announce that 1,072 students from 59 countries have successfully completed the 2018 Google Summer of Code (GSoC). Congratulations to all of our students and mentors who made this our biggest and best Google Summer of Code yet.

Over the past 12 weeks, GSoC students have worked diligently with 212 open source organizations and over 2,100 mentors from all around the world, learning to work with distributed teams and developing complex pieces of code. Student projects are now public – take a closer look at their work.

Open source communities need new ideas to keep projects thriving and evolving; GSoC students bring fresh perspectives while helping organizations enhance, extend, and refine their codebases. This is not the end of the road for GSoC students! Many will go on to become mentors in future years and many more will become long-term committers.

And finally, a big thank you to the mentors and organization administrators who make GSoC possible. Their dedication to welcoming new student contributors into their communities is awesome and inspiring. Thank you all!

By Mary Radomile, Google Open Source

ZuriHac 2018: Haskell hackathon in Rapperswil

Google Open Source recently co-sponsored a three-day hackathon for Haskell, an open source functional programming language. Ivan Krišto from Google’s Zürich office talks more about the event below.

Over the weekend of June 9th, Rapperswil, Switzerland became a home for 300 Haskellers. Hochschule für Technik Rapperswil hosted the seventh annual ZuriHac, the biggest Haskell Hackathon in Europe. ZuriHac is a free, international coding festival with the goal to expand our community and to build and improve Haskell libraries, tools and infrastructure.

Participants could choose to hack all day long, attend the Haskell beginners course led by Julie Moronuki, join the Glasgow Haskell Compiler (GHC) DevOps track organized by GHC contributors with the goal to bring in new contributors, listen to the Haskell flavoured talks, or socialize and swim in the lake. The event was colocated with C++ standardization committee meetings which offered a unique opportunity for sharing ideas between the two communities.

Here is a short summary of featured talks at ZuriHac.
The event concluded with a presentation of the results of the three day hackathon: project presentations.

Video by Hochschule für Technik Rapperswil.

Once again, we broke the attendance record! We’re already preparing for ZuriHac 2019 and hope to keep up this amazing growth. See you next year!

By Ivan Krišto, Software Engineer

Congratulations to the latest Google Open Source Peer Bonus winners

We are pleased to announce the latest round of Google Open Source Peer Bonus winners and the projects they support.

Open source software is a cornerstone of software development inside and outside of Google, and the Google Open Source Peer Bonus program is one way we thank the people who make our work possible. Twice a year we invite Googlers to nominate external contributors to be rewarded for their contribution to open source projects.

This time we have a truly international team of recipients from Australia, Brazil, Canada, Germany, India, Italy, Ireland, France, Japan, Netherlands, Russia, Singapore, Switzerland, Sweden, UK and USA. You can learn about previous recipients in these blog posts.

Projects range from Linux distributions and version control systems to monitoring and testing software. Some are part of the backbone of our industry, others are critical dependencies of specific products and services we offer. All of them are important to us!

Listed below are the individuals who gave us permission to thank them publicly:

Name Project Name Project
Sultan AlsawafAndroid KernelRavi Santosh GudimetlaKubernetes
Allan McRaeArch LinuxSteve KuznetsovKubernetes
Seth Pollackaws-encryption-providerHisham MuhammadLuaRocks
George GensureBazel BuildfarmYutaka Matsubarameinheld
Omar CornutDear ImGuiPulkit GoyalMercurial
Alessandro ArzilliDelveYuya NishiharaMercurial
Matt KleinEnvoyAdam Mummery-SmithMixin
Ivan GrokhotkovESP8266 core for ArduinoArnout EngelenNotion
Esther OnfroyExodus PrivacyBrian BrazilPrometheus
Yao LiForkliftBruno Oliveirapytest
Warner LoshFreeBSDJames FriedmanRMWC
Elijah NewrenGitSteve KlabnikRust Book
Gábor SzederGitJack LukicSemantic UI
Alvaro Viebrantzgoogle-cloud-iot-arduinoVidar HolenShellCheck
Richard MusiolGopherJS, go-wasmIvan PopelyshevSkia graphics in Chrome
Tobias FuruholmGrafeasSpencer GibbSpring Cloud
David PursehouseJGitDaniel AlmSwift gRPC
Brian GrangerJupyterYong TangTensorFlow
Rodrigo MenezeskopsJason ZamanTensorFlow, Gentoo, SELinux
Rohith JayawardenekopsKai SasakiTensorFlow.js
Kam KasraviKubeflowManraj GroverTensorFlow.js
Pete MacKinnonKubeflowStefan WeilTesseract
Christoph BleckerKubernetesSumana HarihareswaraWarehouse (PyPI)
Davanum SrinivasKubernetesJia Lizone.js

Once again we would like to express our gratitude and appreciation to current and former recipients for their hard work, time and devotion to open source. Without you these projects wouldn’t thrive!

We look forward to your ongoing contributions and can’t wait to recognize even more contributors for their work in 2019.

By Maria Tabak, Google Open Source

Congratulations to the latest Google Open Source Peer Bonus winners

We are pleased to announce the latest round of Google Open Source Peer Bonus winners and the projects they support.

Open source software is a cornerstone of software development inside and outside of Google, and the Google Open Source Peer Bonus program is one way we thank the people who make our work possible. Twice a year we invite Googlers to nominate external contributors to be rewarded for their contribution to open source projects.

This time we have a truly international team of recipients from Australia, Brazil, Canada, Germany, India, Italy, Ireland, France, Japan, Netherlands, Russia, Singapore, Switzerland, Sweden, UK and USA. You can learn about previous recipients in these blog posts.

Projects range from Linux distributions and version control systems to monitoring and testing software. Some are part of the backbone of our industry, others are critical dependencies of specific products and services we offer. All of them are important to us!

Listed below are the individuals who gave us permission to thank them publicly:

Name Project Name Project
Sultan AlsawafAndroid KernelRavi Santosh GudimetlaKubernetes
Allan McRaeArch LinuxSteve KuznetsovKubernetes
Seth Pollackaws-encryption-providerHisham MuhammadLuaRocks
George GensureBazel BuildfarmYutaka Matsubarameinheld
Omar CornutDear ImGuiPulkit GoyalMercurial
Alessandro ArzilliDelveYuya NishiharaMercurial
Matt KleinEnvoyAdam Mummery-SmithMixin
Ivan GrokhotkovESP8266 core for ArduinoArnout EngelenNotion
Esther OnfroyExodus PrivacyBrian BrazilPrometheus
Yao LiForkliftBruno Oliveirapytest
Warner LoshFreeBSDJames FriedmanRMWC
Elijah NewrenGitSteve KlabnikRust Book
Gábor SzederGitJack LukicSemantic UI
Alvaro Viebrantzgoogle-cloud-iot-arduinoVidar HolenShellCheck
Richard MusiolGopherJS, go-wasmIvan PopelyshevSkia graphics in Chrome
Tobias FuruholmGrafeasSpencer GibbSpring Cloud
David PursehouseJGitDaniel AlmSwift gRPC
Brian GrangerJupyterYong TangTensorFlow
Rodrigo MenezeskopsJason ZamanTensorFlow, Gentoo, SELinux
Rohith JayawardenekopsKai SasakiTensorFlow.js
Kam KasraviKubeflowManraj GroverTensorFlow.js
Pete MacKinnonKubeflowStefan WeilTesseract
Christoph BleckerKubernetesSumana HarihareswaraWarehouse (PyPI)
Davanum SrinivasKubernetesJia Lizone.js

Once again we would like to express our gratitude and appreciation to current and former recipients for their hard work, time and devotion to open source. Without you these projects wouldn’t thrive!

We look forward to your ongoing contributions and can’t wait to recognize even more contributors for their work in 2019.

By Maria Tabak, Google Open Source

How we brought the latest version of Python to App Engine and Cloud Functions

At Cloud Next 2018, we added Python 3.7 support to Cloud Functions and now we’ve announced Python 3.7 support for the App Engine standard environment. These new runtimes allow you to write Python functions and apps using the latest version of Python and the rich ecosystem of packages available on Python Packaging Index (PyPI).

This new runtime marks a significant update to App Engine and was enabled by new open source software that we recently released: gVisor and FTL.

Python, straight from the source

Running Python 3.7 on App Engine and Cloud Functions required us to fundamentally rethink our infrastructure. Traditionally, meeting Google Cloud’s security requirements meant that we had to run a modified version of the Python interpreter. However, using a modified interpreter constrained some language features and only allowed us to support a limited set of whitelisted Python libraries.

Thanks to gVisor, a container sandbox that provides improved security and process isolation, we can now run the unmodified Python 3.7.0 interpreter. We’ve done extensive testing to make sure Python 3.7 is compatible with gVisor. As part of our compatibility testing, we run Python’s full suite of language tests, and tests for Python packages that are popular on PyPI. We’re committed to ensuring that everything you’ve come to know and love about Python is supported on our platform.

Seamless deployments

Most importantly, this change in our infrastructure makes it easier to take advantage of Python’s vast ecosystem. As a developer, you just add project dependencies to a requirements.txt file and deploy.

During deployment, FTL, a tool for building containers, fetches dependencies listed in your requirements.txt file and installs them alongside your app or function. FTL also includes a short-lived dependency cache, which speeds up repeated deployments if no changes are detected in your requirements.txt file. This is particularly useful if you find just need to re-deploy because you found a typo.

Keeping up with the Pythonistas

In making these changes, we also decided to expand the list of system packages that are included with each runtime’s Ubuntu 18.04 distribution. We think that will make life just a little bit easier for developers working with the latest release of Python.

Looking forward, we’re excited about how these changes will allow us to keep up with the Python community’s progress as they release new versions and libraries. Please let us know what you think and if you run into any challenges.

You can learn more about how to get started with it on App Engine and Cloud Functions in our documentation. We can’t wait to see what you build with Python 3.7.

By Stewart Reichling, Product Manager