ML Olympiad 2023: Globally Distributed ML Competitions by Google ML Community

Posted by Hee Jung, DevRel Community Manager

What is the ML Olympiad?

The ML Olympiad is an associated Kaggle Community Competitions hosted by ML GDE, TFUG, 3rd-party ML communities, supported by Google Developers. The ML Developer Programs team and the communities successfully ran the first round of the campaign in 2022 and are now launching the second round. The goal of this campaign is to provide ML training opportunities for developers by leveraging Kaggle’s features.

ML Olympiad Community Competitions

17 ML Olympiad community competitions are currently open. Visit the ML Olympiad page to participate.

Into the Space

  • Predicting which spaceship passengers were transported by the anomaly using records recovered from the spaceship’s damaged computer system.
  • Host: MD Shahriyar Al Mustakim Mitul / TFUG Dhaka

    Water Quality Prediction

    • Estimating the quality of water.
    • Hosts: Usha Rengaraju, Vijayabharathi Karuppasamy (TFUG Chennai), Samuel T (TFUG Mysuru)

      Breast Cancer Diagnosis

      • Predicting medical diagnosis [breast cancer].
      • Host: Ankit Kumar Verma / TFUG Prayagraj

        Book Recommendations

        • To provide personalized recommendations to users based on their reading history and preferences using various machine learning algorithms.
        • Hosts: Anushka Raj, Yugandhar Surya / TFUG Hajipur

          Argania Tree Deforestation Detection

          • Use Sentinel-2 satellite imagery to detect and map areas of deforestation in the Argania region.
          • Hosts: Taha Bouhsine / TFUG Agadir

            Multilingual Spell Correction

            • Reconstruct noisy sentences in European languages: English, French, German, Bulgarian and Turkish.
            • Host: Radostin Cholakov (ML GDE)

              CO2 Emissions Forecasting

              • Forecasting CO2 emissions based on deforestation in Côte d'Ivoire.
              • Hosts: Armel Yara, Kimana Misago, Jordan Erifried / TFUG Abidjan

                Ensure Healthy Lives (in local language) 

                • Use ML techniques to help achieve common good health and well-being.
                • Hosts: Vinicius Fernandes Caridá (ML GDE), Pedro Gengo, Alex Fernandes Mansano / TFUG São Paulo

                  Predictive Maintenance

                  • Predict future engine’s failures.
                  • Host: Daniel Pereda / TFUG Santiago

                    Firetrucks Are Red And Cars Are Blue

                    • To create a model that can accurately predict the correct class for each image, without overfitting.
                    • Host: Prasoon Kottarathil / TFUG Thrissur

                      Dialect Recognition (in Arabic) 

                      • Dialect recognition in order to improve user experience in AI applications.
                      • Hosts: Ruqiya Bin Safi (ML GDE), Eyad Sibai, Hussain Alfayez / Saudi TFUG & Applied ML/AI group

                        Sentiment Analysis Of JUMIA Tunisia  (in local language) 

                        • Use JUMIA customer reviews to determine the sentiment of content from text data.
                        • Host: Boulbaba BEN AMMAR / TFUG Sfax

                          Kolkata Housing Prediction

                          • Kolkata housing prediction results can be used to address related social and economic issues.
                          • Host: Rishiraj Acharya / TFUG Kolkata

                            Can You Guess The Beer Style?

                            • This is a machine learning competition focused on classifying beer into 17 distinct styles based on key descriptors.
                            • Host: Marvik

                              Detect ChatGpt answers

                              • The goal of this competition is to classify ChatGpt answers vs real human answers for a variety of questions.
                              • Host: Elyes Manai (ML GDE) / IEEE ESSTHS + GDSC ISETSO + PyData Tunisia

                                MLAct Pose Detection

                                • Raising awareness about some basic yoga poses, and encouraging our community members to practice the basic parts of computer vision.
                                • Host: Imen Masmoudi / MLAct ML Community

                                  Hausa Sentiment Analysis 2.0 (in local language) 

                                  • Classify the sentiment of sentences of Hausa Language.
                                  • Hosts: Nuruddeen Sambo, Dattijo Murtala Makama / TFUG Bauchi

                                    Navigating ML Olympiad

                                    You can search “ML Olympiad” on Kaggle Community Competitions page to see them all. And for further info, look for #MLOlympiad on social media.

                                    Google Developers supports the hosts of each competition. Browse through the available competitions and participate in those that interest you!

                                    Supporting DDR4 and DDR5 RDIMMs in open source DRAM security testing framework

                                    In 2021, Google and Antmicro introduced a platform for testing DRAM memory chips against the unfortunate side effect of the physical shrinking of memory chips—the Rowhammer vulnerability. The platform was developed to propose a radical improvement over the “security through obscurity” approach that was predominant in the industry; as both Antmicro and Google believe that the open source approach to mitigating security threats is a way towards accelerating developments in the field.

                                    The framework was originally developed in the context of securing consumer-facing devices, using off-the-shelf Digilent Arty (DDR3, Xilinx Series7 FPGA) and Xilinx ZCU104 (DDR4, Xilinx UltraScale+ FPGA) boards, then followed by a dedicated open hardware board from Antmicro that allowed work on custom LPDDR4 modules. The framework has since helped discover a new attack method named Blacksmith and continues to provide valuable insights into how the security of both edge device and data center memory can be improved.

                                    In constant development since then, the project has welcomed two more major elements to the ecosystem in order to enable testing of DDR4 Registered Dual In-Line Memory Modules (RDIMM)—commonly used in data centers as well as the newer DDR5 standard and continues to provide useful data.

                                    Memory testing for data center use cases

                                    To extend the Rowhammer tester support from consumer-facing devices to shared-compute data center infrastructure, Antmicro developed the data center DRAM tester board. We adapted this open source hardware-test platform from the original LPDDR4 board to enable Rowhammer and other memory security experiments with DDR4 RDIMMs using a fully configurable, open source FPGA-based DDR controller.

                                    The data center DRAM Xilinx Kintex-7 FPGA based test board features:

                                    • DDR4 RDIMM connector
                                    • 676 pins FPGA (compared to the 484 for the LPDDR version)
                                    • RJ45 Gigabit Ethernet
                                    • Micro-USB console
                                    • HDMI output connector
                                    • JTAG programming connector
                                    • MicroSD card slot
                                    • 12 MBytes QSPI Flash memory
                                    • HyperRAM—external DRAM memory that can be used as an FPGA cache
                                    Photo of the Antmicro data center DRAM Xilinx Kintex-7 FPGA based tester board

                                    It’s worth mentioning that the RDIMM DDR4 memory (as opposed to the custom LPDDR4 modules designed for the original project) are generic and available off-the-shelf. This makes it easier for security researchers to get started with data center memory security research compared to edge devices using LPDDR.

                                    The Data Center DRAM Tester board design has now been upgraded into revision 1.2, which brings new features for implementing even more complex DRAM testing scenarios. The 1.2 boards support a Power over Ethernet (PoE) supply option so the board can act as a standalone network device with data exchange and power-cycling done over a single Ethernet cable. This simplifies integration of the board in DRAM testing clusters and custom runners capable of doing hardware-in-the-loop testing.

                                    The new revision of the board will support hot-swapping of the DRAM module under test, which should speed up testing of multiple DRAM modules without the need to power-cycle the tester. Finally, the new revision of the board will include power-measurement circuitry so it will be possible to compare the peak and average power consumption of DRAM while working with different DRAM refresh scenarios.

                                    We are also working on a custom enclosure design suitable for desktop and networked installations.

                                    Extending open source testing to DDR5

                                    With DDR5 quickly becoming the new standard for data center memory, Antmicro and Google’s Platforms teams also set out to develop a platform capable of interfacing with DDR5 memories, again directly from a low-cost FPGA without a dedicated hard block. The resulting DDR5 tester platform follows the structure of the data center DDR4 tester, while expanding on functionality of the Serial Presence Detection, which monitors the power supply states and system health, or adjusting the circuitry for a nominal IO voltage of 1.1V.

                                    Photo of the Antmicro DDR5 testbed

                                    Data center DRAM testing is part of Google’s and Antmicro’s belief in security through transparency. Both hyperscalers and a growing number of organizations who operate their own data centers increasingly embrace this perspective, and there is great value in providing them with a scalable, customizable, commercially supported open source platform that will help in collaborative research and mitigation of emerging security issues.

                                    Rowhammer attacks, security threats, and countermeasures remain an active research area. With Google, Antmicro continues to adjust the Rowhammer test platform to most recent developments, opening the way for researchers and memory vendors to more sophisticated testing methods to enable testing of state-of-the-art memories used in data centers. This work stems from and complements other open source activities the companies jointly lead as members of RISC-V International and CHIPS Alliance, aimed at making the hardware ecosystem more open, secure and collaborative. If you’re interested in open source solutions for DRAM security testing and memory controller development, or more broadly, FPGA and ASIC design and verification, don’t hesitate to reach out to Antmicro at [email protected].

                                    By Michael Gielda – Antmicro

                                    Meet our newest Accelerator: Climate Change cohort

                                    Posted by Matt Ridenour, Head of Startup Developer Ecosystem - USA

                                    Scaling high potential startups aimed at tackling climate change can have an immensely positive impact for our planet.

                                    In line with Google’s broader commitment to address climate change, we are proud to announce the third cohort for our Google for Startups Accelerator: Climate Change program. This 10-week digital accelerator brings the best of Google’s people, products and programming to help take early-stage North American climate tech startups to the next level.

                                    Meet the 12 exceptional startups using cloud technology, artificial intelligence, machine learning and more for a healthier planet.

                                    Agrology, Alexandria, VA

                                    Agrology's predictive agriculture platform helps farmers grow with confidence and beat climate change through data, insights and soil monitoring at scale.

                                    BattGenie, Seattle, WA

                                    BattGenie provides Li-ion battery management software and solutions, enabling safe, fast charging while improving battery life cycle.

                                    Bodhi, Austin, TX

                                    Bodhi empowers solar companies to deliver amazing customer experiences, automating communications so installers can focus on increasing renewable energy access.

                                    Cambio, San Francisco, CA

                                    Cambio is software that helps commercial real estate companies and their corporate tenants decarbonize their buildings.

                                    Cleartrace, Austin, TX

                                    Cleartrace is disrupting legacy reporting with a new standard for how energy and decarbonization information is collected, stored, accessed and transacted.

                                    ElectricFish, Fremont, CA

                                    ElectricFish builds and deploys resilient, flexible EV infrastructure to accelerate decarbonization and support community climate adaptation.

                                    Enersion, Toronto, ON

                                    Enersion offers zero-emission solar trigeneration energy that converts solar radiation into refrigerant-free cooling, heating and electricity.

                                    Eugenie AI, Cupertino, CA

                                    Eugenie is an AI intelligence platform for asset-heavy manufacturers to track, trace, and reduce emissions while improving operations.

                                    Finch, Denver, CO

                                    Finch is a platform that decodes products' environmental footprints to help consumers and shares insights with businesses.

                                    Refiberd, Cupertino, CA

                                    Refiberd is tackling the 186 billion pound global textile waste problem with the first AI-empowered circular textile sorting and reclamation system.

                                    Sesame Solar, Jackson, MI

                                    Sesame Solar is decarbonizing disaster response with rapidly deployable mobile Nanogrids with essential services, providing continuous power from 100% renewable energy.

                                    Voltpost, New York City, NY

                                    Voltpost decarbonizes mobility and democratizes charging access by retrofitting lamp posts into modular electric vehicle charging stations.

                                    These companies will join the other 22 startups from across North America who have participated in the accelerator (see program alumni).

                                    In addition to mentorship and technical project support, the 10-week program will focus on product design, customer acquisition, and leadership development, granting startups access to an expansive network of mentors, senior executives, and industry leaders. All Google for Startups Accelerators are equity-free, so selected companies don’t have to offer anything to participate.

                                    We are honored to partner with this cohort of companies through this accelerator and beyond, to advance their technologies and protect our planet.

                                    The program kicks off on Tuesday, March 7 and concludes with a virtual Demo Day on May 11. Stay tuned and join us in celebrating these exceptional startups.

                                    Stable Channel Update for ChromeOS/ChromeOS Flex

                                    The Stable channel is being updated to 110.0.5481.112 (Platform version: 15278.64.0) for most ChromeOS devices and will be rolled out over the next few days. This build contains a number of bug fixes and security updates.

                                    If you find new issues, please let us know one of the following ways:

                                    Interested in switching channels? Find out how.

                                    Cole Brown,

                                    Google ChromeOS




                                    Security Fixes and Rewards:


                                    Note: Access to bug details and links may be kept restricted until a majority of users are updated with a fix. We will also retain restrictions if the bug exists in a third party library that other projects similarly depend on, but haven’t yet fixed.



                                    [$3000] [1401666] High CVE-TBD Security: Sideload APKs on ChromeOS Reported by Samuel Culeron for Approach Belgium


                                    We would also like to thank all security researchers that worked with us during the development cycle to prevent security bugs from ever reaching the stable channel.

                                    Bid Manager API v1.1 will sunset on April 27, 2023

                                    The Bid Manager API v1.1 will sunset on April 27, 2023. The Bid Manager API v1.1 was deprecated in August 2022 and originally scheduled to sunset on February 28, 2023.

                                    Please migrate to v2 before the sunset date to avoid an interruption of service.

                                    You can read our release notes for more information about v2. Follow the steps in our v2 migration guide to help you migrate from v1.1 to v2.

                                    If you run into issues or need help with your migration, please contact us using our support contact form.

                                    Announcing v13 of the Google Ads API

                                    Today, we’re announcing the v13 release of the Google Ads API. To use some of the v13 features, you will need to upgrade your client libraries and client code. The updated client libraries and code examples will be published next week.


                                    Here are the highlights: Where can I learn more?
                                    The following resources can help you get started: If you have any questions or need additional help, contact us via the forum.