Since 2013, Google has supported logo structured data, which recognizes two Organization
fields: logo and url. Today we're expanding our support for organizational information by
extracting additional administrative data such as name, address, contact information, and
various business identifiers. You can continue to provide the logo and url fields to specify
which image we use as your logo in Google search results.
Hi, everyone! We've just released Chrome 119 (119.0.6045.193) for Android: it'll become available on Google Play over the next few days.
This release includes stability and performance improvements. You can see a full list of the changes in the Git log. If you find a new issue, please let us know by filing a bug.
Android releases contain the same security fixes as their corresponding Desktop release (Windows: 119.0.6045.199/.200; Mac & Linux: 119.0.6045.199) unless otherwise noted.
Over the years, we’ve added features to Google Drive that help you more efficiently find files and folders. In October, we launched a new view in Google Drive that shows all pending access requests, recent comments, and approvals for files to help you quickly see recent activity and take action, all in one place.
Today, we’re excited to introduce the latest series of changes that accelerate user productivity across new views in Drive. A new streamlined homepage for Drive called Home makes it easier and faster for you to find files that matter most. Specifically, you’ll notice:
Personalized file and folder suggestions with machine learning algorithms that can help you get started quickly. These suggestions utilize a variety of signals, such as what files or folders you’ve recently opened, shared or edited, or what documents are attached to upcoming Calendar events.
Filter chips to narrow down your search and find relevant files faster across Drive, making it easy to find suggested files by type, people, modified date or the location.
A more modern design inline with Google Material Design 3 guidelines that helps you navigate across Drive much more efficiently.
Who’s impacted
End users
Why you’d use it
The new Google Drive Home page will make it easier and faster for you to find the files you need and collaborate with others.
Additional details
When you go to drive.google.com, instead of landing in ‘My Drive’ you will now be directed to ‘Home.’ If you would like to set your default to ‘My Drive,’ click on the “Change to My Drive” option in the banner on Home:
Getting started
Admins: There is no admin control for this feature.
End users: This feature will be ON by default and can be opted-out by the user. If a user chooses to opt-out, their default page will be My Drive. To opt-out, go to My Drive and click on the “Change to My Drive” option in the banner.
Rollout pace
Rapid Release domains: Extended rollout (potentially longer than 15 days for feature visibility) starting on November 28, 2023
Scheduled Release domains: Extended rollout (potentially longer than 15 days for feature visibility) starting on January 11, 2024
Availability
Available to all Google Workspace customers and users with personal Google Accounts
Note: The Drive Activity view is available to Google Workspace customers only
For years, users have had the ability to scan physical documents, such as a receipt or passport, using the Google Drive app on Android devices. And earlier this year, we added additional functionality to recommend relevant title suggestions for scanned documents by leveraging machine learning.
Today, we’re introducing additional enhancements to the Drive scanner on Android devices, which now powers the Google Pixel camera and includes improvements to the scanner experience when capturing content. Specifically, you’ll notice:
Automatic capture to help you get the best scan quickly
Camera viewfinder that helps you position your document for the highest quality scan
The option to import from your camera roll
A faster way to initialize a scan with a new scanner button
We’re also expanding the Google Drive scanner and title suggestion feature to iOS devices. Now, when using your iOS phone or tablet, you can easily scan and digitally organize physical documents, crop them if needed, and receive relevant title suggestions based on machine learning.
Getting started
Admins: There is no admin control for this feature.
End users:
Open the Drive app on your Android device > scan a document via the camera icon or scan a document via the Scan button under the “+” icon > assess/adjust the automatic cropping > scan multiple pages in a session (if needed) > apply filters > save to Drive.
Open the Drive app on your iOS device > scan a document via the camera icon or scan a document via the Scan button under the “+” icon > > scan multiple pages in a session (if needed) > click on scan to apply filters or crop as needed > save to Drive.
Note: Title suggestions are only available in the US.
In September, we introduced message bubbles in Google Chat on web and Android, enabling users to more easily differentiate incoming versus outgoing messages in the Chat message stream. Today, we’re excited to announce the expansion of message bubbles to iOS devices.
On your phone or tablet:
Each incoming message will have an independent message bubble aligned to one side with a solid color background
Each outgoing message will have an independent message bubble aligned to the other side with a different color background
Getting started
Admins and end users: No action required. You’ll automatically see these updates in your web and mobile experience over the next several weeks.
The recently announced search themes beta feature for Performance Max campaigns lets you provide Google AI with valuable inputs about your customers and business to further optimize Performance Max campaign serving and placement. Beginning in Google Ads API v15, you can create search themes for Performance Max campaigns with the API.
How It Works
Search themes beta lets you indicate queries that you know your customers are looking for. They are optional and are additive to what queries Performance Max would match by using your URLs, assets, and more.
You can add up to 25 search themes per asset group.
Search themes will respect brand exclusions in Performance Max and account-level negative keywords. You can configure brand exclusions through campaign criteria using the BRAND criterion type. Similarly, account-level negative keywords are configured at a customer level usingCustomerNegativeCriterionService and the NegativeKeywordList criteria.
Results driven from search themes will bring your customers to the landing pages you’ve indicated with your Final URL expansion, page feeds, or URL settings. Final URL expansions can be enabled or disabled withurl_expansion_opt_out.
Search themes will have the same prioritization as your phrase match and broad match keywords in your Search campaigns.
You’ll be able to see the search categories that your ads matched to, and associated conversion performance, in your search terms insights at both the campaign and account levels with the campaign_search_term_insight andcustomer_search_term_insight reports. You can also view search term insights for custom date ranges, download your data, and access it using the API.
Implementation Details
In the Google Ads API, a search theme is a type ofAssetGroupSignal, which can be attached to Performance Max campaigns at the asset group level. You can add a search theme to an asset group by creating an AssetGroupSignal and populating the
AssetGroupSignal.search_theme with aSearchThemeInfo criterion containing a text string representing your search theme, for example, "activities for children". In addition, you must populate the AssetGroupSignal.asset_group with the resource name of an existing asset group you are targeting.
Here is a Java example for creating a search theme asset group signal:
// Creates a search theme asset group signal.
AssetGroupSignal assetGroupSignal =
AssetGroupSignal.newBuilder()
.setAssetGroup(assetGroupResourceName)
.setSearchTheme(
SearchThemeInfo.newBuilder().setText("activities for children").build())
.build();
You can add multiple asset group signals to a single asset group by creating multiple AssetGroupSignal objects targeting the same asset group. However, each AssetGroupSignal object can only represent a single search theme or audience signal.
Reporting
You can use theasset_group_signal resource to get the search themes present in a Google Ads account. While performance metrics are currently available at the asset group level, they are not available at the asset group signal level.
Here is a GAQL example to retrieve search theme texts for a specific asset group:
SELECT
asset_group_signal.search_theme.text
FROM asset_group_signal
WHERE
asset_group.id = <Asset Group ID>
Policy Exemptions
In v15 of the Google Ads API, we also introduced two new fields to provide additional information about search_theme approval:asset_group_signal.approval_status and asset_group_signal.disapproval_reasons. Search theme text must be approved by Google. The asset_group_signal.approval_status field provides information about the approval status, and if the search theme text is not approved, the asset_group_signal.disapproval_reasons field lists the reasons why.
Here is a GAQL example to retrieve search theme texts with policy review information for a specific asset group:
SELECT
asset_group_signal.search_theme.text,
asset_group_signal.approval_status,
asset_group_signal.disapproval_reasons
FROM asset_group_signal
WHERE
asset_group.id = <Asset Group ID>
If your search theme text is not approved, and you believe the usage adheres to Google’s policies, you can submit a policy exemption request for the search theme that triggered the policy violation.
For example, if your search theme contains medical terms, and you believe the usage of the terms adheres to Google Ads policies and warrants further review, you can use the AssetGroupSignalOperation.exempt_policy_violation_keys[] field to request a policy exemption.
Improving Performance Max integrations Blog Series
This article is part of a series that discusses new and upcoming features that you have been asking for. Keep an eye out for further updates and improvements on our developer blog, continue providing feedback on Performance Max integrations with the Google Ads API, and as always, contact our team if you need support.
Starting today, Enhanced Smart Fill in Google Sheets is available for customers with the Duet AI for Google Workspace Enterprise add-on. This builds upon Smart Fill in Google Sheets, a feature we introduced in 2020 that detects patterns between columns and suggests data for remaining cells using Google’s Knowledge Graph. More recently, we launched Help me organize in Sheets, a Duet AI feature that gives you a running start for creating highly-organized plans and trackers.
As previously announced, offering Enhanced Smart Fill will continue our efforts to help users spend less time on manual data organization and analysis in Sheets. This capability uses AI to detect if there are relationships between cell contents. If a relationship exists, Sheets can make contextual suggestions in the form of remaining values that you can accept. Once you click to accept the suggested values, Sheets will automatically fill them.
Enhanced Smart Fill can recognize and fill patterns like: sentiment classification, combining and generating text, extracting specific text, formatting addresses, structuring phone numbers and emails, condensing text and more. For example, a restaurant could organize their reviews and rating data more easily with Enhanced Smart Fill. Rather than manually typing in data, Sheets can detect a pattern in the existing ratings and reviews content and suggest values for the remaining cells. Simply review the suggestions and accept them in one click using Enhanced Smart Fill.
Enhanced Smart Fill filling in star ratings based on review sentiment
Sales teams could also use Enhanced Smart Fill to more easily organize next steps in a sales cycle. Instead of manually extracting next steps from a column of unformatted notes, you can accept suggested next steps that Sheets will provide you based on the account information listed in other columns.
Enhanced Smart Fill suggesting text to extract from a column of populated cells
Or, let’s say you hosted a fundraiser and want to customize thank you notes for donors based on their donation type. Rather than writing the notes one by one, you could quickly see a list of suggested thank you messages that Sheets generates based on the pattern of your first set of messages. Simply click to accept the suggested values so that you can quickly and efficiently thank your donors.
Enhanced Smart Fill suggesting fills to continue a thank you note pattern
This feature will only appear if relationships between data points exist within your spreadsheet.
Getting started
Admins: This feature will be ON by default and there is no admin control for this feature. Visit the Help Center to learn more about Duet AI for Google Workspace Enterprise.
End users: This feature will be ON by default and only appears when Sheets has a suggestion to make. Visit the Help Center to learn more about Enhanced Smart Fill.
The Extended Stable channel has been updated to 118.0.5993.159for Windows and Mac which will roll out over the coming days/weeks.
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.
The Stable channel has been updated to 119.0.6045.199 for Mac and Linux and 119.0.6045.199/.200 for Windows, which will roll out over the coming days/weeks. A full list of changes in this build is available in the log.
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.
This update includes 7 security fixes. Below, we highlight fixes that were contributed by external researchers. Please see the Chrome Security Page for more information.
[N/A][1491459] High CVE-2023-6348: Type Confusion in Spellcheck. Reported by Mark Brand of Google Project Zero on 2023-10-10
[$31000][1494461] High CVE-2023-6347: Use after free in Mojo. Reported by Leecraso and Guang Gong of 360 Vulnerability Research Institute on 2023-10-21
[$10000][1500856] High CVE-2023-6346: Use after free in WebAudio. Reported by Huang Xilin of Ant Group Light-Year Security Lab on 2023-11-09
[$7000][1501766] High CVE-2023-6350: Out of bounds memory access in libavif. Reported by Fudan University on 2023-11-13
[$7000][1501770] High CVE-2023-6351: Use after free in libavif. Reported by Fudan University on 2023-11-13
[N/A][1505053] High CVE-2023-6345: Integer overflow in Skia. Reported by Benoît Sevens and Clément Lecigne of Google's Threat Analysis Group on 2023-11-24
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.
As usual, our ongoing internal security work was responsible for a wide range of fixes:
[1505618] Various fixes from internal audits, fuzzing and other initiatives
Google is aware that an exploit for CVE-2023-6345 exists in the wild.
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.
Join us virtually from 9:30 am to 1:00 pm PT for an immersive and insightful set of deep dives for every level of Machine Learning experience.
The Women in ML Symposium is an inclusive event for anyone passionate about the transformative fields of Machine Learning (ML) and Artificial Intelligence (AI). Meet this year’s women in ML as they uncover practical applications across multiple industries and discuss the latest advancements in frameworks, generative AI, and more.
Joana Carrasqueira, presenter for “Enabling Anyone to Build with Google AI”
Joana is a Developer Relations Lead for AI/ML at Google and her mission is to empower individuals and organizations to harness the power of AI to address real-world challenges.
She is a business leader with a track record of bringing strategic vision and global cross-functional programs to life. She’s also the creator of Google’s Women in ML program and flagship symposium, a pioneering initiative that has equipped thousands of developers with knowledge and skills in AI/ML.
Prior to Google, she worked at the Silicon Valley Innovation Center on innovation consulting for Forbes top500, startups and Venture Capital firms. Served as Education Manager at the International Pharmaceutical Federation, working closely with WHO, UNESCO, the United Nations and started her career at the Portuguese Pharmaceutical Society.
Joana holds an MBA from IE Business School, a Master in Pharmaceutical Sciences and a Leadership Certificate from U.C. Berkeley in California.
Sharbani Roy, presenter for “What’s New in Machine Learning?”
Sharbani is Sr. Director in Google’s Core Machine Learning group.
Before joining Google, Sharbani led engineering and product teams in Amazon Alexa, focused on media streaming, real-time communication, and applied ML (e.g., NLU, CV, and AR) for 1P/3P developers and end consumers.
Sharbani holds degrees in physics and mathematics from the University of Chicago and an MBA from Stanford University, and lives in Seattle with her husband and three children.
Eve Phillips, presenter for “Future of Frameworks: Navigate the OSS Landscape"
Eve is a Director of Product Management at Google.
Currently, Eve leads the ML Frameworks product team, which includes responsibility for TensorFlow, JAX and Keras. Previously, she led product teams within Google for Clinicians and ChromeOS. Prior to Google, she served as CEO of Empower Interactive, delivering tech-enabled behavioral health.
Earlier, she held roles in leading technology companies and investors including Trilogy, Microsoft, and Greylock.
Eve earned a BS and M.Eng in EECS from MIT and an MBA from Stanford.
Meenu Gaba, presenter for “Data-Centric AI: A New Paradigm"
Meenu leads the Machine Learning infrastructure team at Google, with a mission to power AI innovation with world-class ML infrastructure and services.
She is a technology leader with years of experience launching new products and growing small teams into mature scalable, multi-tiered organizations that are poised to deliver high quality products. Meenu enjoys fast-paced, dynamic, highly iterative/innovative environments and has lots of experience in balancing these disciplines while fostering a people-first culture and forming solid grounds for cross-functional relationships.
Meenu holds a Master's degree in Computer Science. In her free time, she enjoys hiking, solving crosswords, and watching movies.
Kelly Shaefer, presenter for “Maximize Your Data Exploration”
Kelly leads product teams at Google Labs, building both entirely new AI products and AI-enabled features into Google's largest existing products.
In the past, she led the Growth team for Google Workspace, including Gmail, Drive, Docs, and many more.
Outside of Google, she led the Enterprise product team at Stripe and was the P&L owner for Stripe's multi-billion dollar Payments area.
Kelly has an undergraduate degree from Wharton at UPenn, and an MBA from Harvard Business School.
Divyashree Sreepathihalli, presenter for “Keras: Shortcut to AI Mastery”
Divya is a talented machine learning software engineer who is currently a part of the Keras team at Google.
In this role, she specializes in developing Keras core modeling APIs and KerasCV to improve the functionality of the software.
Prior to joining Google, Divya worked as a Deep Learning Scientist for Zazu Sensor, a startup group in Intel's Emerging Growth Incubation (EGI) group. Her work there focused on computer vision and deep learning algorithm development for object detection and tracking, resulting in significant advancements for the startup.
Divya completed her Masters in Computer Engineering from Texas A&M University where she focused on Artificial intelligence in 2017.
Na Li, presenter for “Prototype ML with Visual Blocks”
Na Li is a software engineer manager from Google CoreML.
She leads a team to build developer tools to support ML development journey, from prototyping to model visualization and benchmarking.
Prior to Google, she was a research scientist at Harvard, working in HCI domain.
Throughout her career, Na strives to make ML accessible for everyone.
Zoe Wang, presenter for “Deploying ML Models to Mobile Devices”
Zoe is a technical program manager at Google.
Her career has been focused on Machine Learning (ML) productionization.
Currently she works with her team bringing ML models to mobile devices that power some of AI features for Pixel and other edge devices.
Prior to Google, Zoe worked at Meta on ML Platforms for end-to-end ML lifecycles.
Yvonne Li, presenter for “New GenAI Products and Solutions on Google Cloud”
Yvonne Li is a software engineer on the Duet Platform team at Google, where she focuses on improving the quality of generative AI models.
As a machine learning engineer and developer advocate at IBM, she designed and developed language models and curated open source datasets.
She has over 3 years of experience in the big tech industry, and is passionate about using machine learning to solve real-world problems.
Yvonne is the author of two Coursera courses: Data Analysis with R, and, Data Visualization with R.
Nithya Natesan, presenter for “AI-powered Infrastructure: Cloud TPUs”
Nithya Natesan is a Group Product Manager in the Cloud ML Accelerators team focussing on GPU / TPU offerings for Google Cloud.
Prior to Google, she was head of product management at NVIDIA, launching several products like DGX Cloud, Base Command Platform.
She has ~14 years of experience in hyper convergence Data Center software products, with recent focus on ML / AI Infra and Platform products. She is passionate about building rock solid PM teams, and shipping high quality usable ML / AI products.
Andrada Vulpe, presenter for “Community Matters: 8 Reasons Why You Should Be Involved with Kaggle”
Andrada is a Data Scientist at Endava, a Notebooks Grandmaster on Kaggle, a Dev Expert at Weights and Biases and a proud Z by HP Data Science Global Ambassador.
She is highly passionate about Python, R, Machine and Deep Learning, powerful visualizations and everything in between.
Andrada finished her MSc in Data Science and Analytics in the UK and won 2 Kaggle Analytics competitions.
Jeehae Lee, presenter for “From Recovering Pro Golfer to AI Entrepreneur”
Jeehae Lee is a golf industry executive who has worked to create and build transformational sports technology businesses.
As the Co-Founder & CEO of Sportsbox AI, Jeehae is currently developing products using AI-enabled 3D motion analysis technology that will help participants of various sports and fitness activities learn and improve their skills.
Before founding Sportsbox, she spent five years between 2015 and 2020 at Topgolf Entertainment Group, leading strategy and new business development for various divisions including Toptracer. Between 2012 and 2013, she was at global sports and entertainment marketing agency, IMG, representing professional golfer icon Michelle Wie West. Prior to her career in sports business, she played professional golf at the highest level in the sport, competing on the LPGA tour for three years between 2009 and 2011.
Jeehae is a proud graduate of Phillips Academy in Andover, MA, and has a BA in Economics from Yale and an MBA from The Wharton School at University of Pennsylvania.
Jingwan (Cynthia) Lu, panelist for “The Impact of Generative AI in Different Industries”
Cynthia is a senior director from Adobe leading an applied research organization focusing on developing the Adobe Firefly family of GenAI models built from the ground up.
Her team started training Adobe’s first large-scale foundational model and helped rally together the rest of the company to roll out a new web-based product called Firefly featuring the image generation model as the first step in early 2023.
The same technology and its extension power Adobe Photoshop’s Generative Fill and Generative Expand features giving users intelligent image inpainting and outpainting experience. Time recognizes Adobe Photoshop Generative Fill and Generative Expand as best inventions of 2023 in the AI category.
Before Firefly, Jingwan was a computer vision research scientist and team lead who pioneered and led a large group effort to explore early generative models such as GANs within Adobe.
Wei Xiao, panelist for “The Impact of Generative AI in Different Industries”
Wei is the Director of Developer Relations at NVIDIA for the Middle East, Africa, and emerging regions. Her primary focus is to drive AI and accelerated computing integration within the ecosystem.
Before assuming her current role, Wei Xiao headed Ecosystem Engineering and Evangelism teams at both ARM and Samsung Semiconductor.
In addition to her professional endeavors, Wei dedicates her free time to teaching AI courses at the Graduate School of Computer Science at Santa Clara University.
Priya Mathur, panelist for “The Impact of Generative AI in Different Industries”
Priya is a Staff Data Science Manager at Google and she is the founder of Sparkle – GenAI Data Analyst.
At Google, she leads Data Science for Home Platform Monetization and GenAI efforts for DSPA.
Previously at Groupon, she led Data Science for App Push Notifications and TV Ads.
Katherine Chou, panelist for “The Impact of Generative AI in Different Industries”
Katherine is the Senior Director of Research and Innovations at Google with a specific focus on nurturing scientific and technical breakthroughs that can lead to global impact for science, health, climate, and advancement of platform technologies for our developers and researchers.
Katherine is focused on improving the availability and accuracy of healthcare using machine learning. She is a serial intrapreneur, particularly interested in removing health inequities and improving health and well-being outcomes across all populations.
She previously developed products within Google[x] Labs for Life Sciences (now Verily) and co-founded Medical Brain (now “Health AI'') at Google. She also headed up global teams to develop partner solutions and establish developer ecosystems for Mobile Payments, Mobile Search, GeoCommerce, YouTube, and Android.
Outside of Google, she is a Board member and Program Chair of Lewa Wildlife Conservancy, a Scientific Advisor to the ARCS Foundation, a fellow of the Zoological Society of London, and collaborates with other wildlife NGOs and the Cambridge Business Sustainability Programme in applying the Silicon Valley innovation mindset to new areas.
Katherine holds a double major in Computer Science and Economics at Stanford University and an M.S. in CS specialized in graphics.
Jaimie Hwang, presenter for “Take Action, Learn More, Start Building with Google AI”
Jaimie Hwang is a global product marketing leader with over a decade of experience, specifically in AI/ML.
She has built and led global product marketing teams at a number of AI companies, including an award-winning computer vision startup and tech giant Amazon.
She specializes in executive thought leadership, product storytelling, and integrated GTM strategy. She is passionate about promoting AI technology that is built responsibly and solves real-world problems in a human-centric way.
Jaimie holds a BS in Journalism and Integrated Marketing and Communications from Northwestern University. She lives in Seattle, Washington.
Save your spot at WiML Symposium 2023
The Women in ML Symposium offers sessions for all expertise levels, from beginners to advanced practitioners. RSVP today to secure your spot and explore our comprehensive agenda. We can’t wait to see you there!
- Da Yang, Google Ads API Team
Posted by Sharbani Roy – Senior Director, Product Management, Google
