AI

Southeast Asia’s digital economy to hit $368 billion

2026-10-21T04:00:00+00:00

Generative AI is now an essential part of daily life for 243 million Southeast Asians. Read about how this will impact the region’s economy in our 11th e-Conomy SEA report.

Nitin Gajria

Managing Director, Southeast Asia and South Asia Frontier Markets

In Southeast Asia, generative AI has become an essential part of daily life, actively used by 243 million people (58% of the working population) and scaling four times faster than the rollout of the mobile internet. This has major implications for the region’s economy, according to the 11th edition of the annual e-Conomy SEA report 1 . Building the Intelligent Economy, by Google, Temasek, and Bain & Company, finds that widespread AI implementation is propelling the region’s digital economy to grow 17% year-on-year (YoY) to reach $368 billion 2 in Gross Merchandise Value (GMV) in 2026. This puts it firmly on track to exceed $1 trillion by 2035. Using tokens 3 as the new benchmark for the AI economy, the report projects that growing confidence in agentic commerce will drive a 60-fold surge in regional AI usage over the next five years.

Here are the three key takeaways from this year's e-Conomy SEA 2026 report:

1. AI is sustaining growth in every sector.

Across the digital economy, AI is reshaping how people live, shop, and move. E-commerce ($226B GMV, +18% YoY) anchors this shift, as shoppers use multimodal discovery and in-app assistants to confidently navigate complex purchases. These personalized experiences organically drive 10% higher conversions and order volume uplifts as large as 75%.

In online travel ($59B GMV, +10% YoY), traditional search engines remain the top platform people use to plan travel, while generative AI has overtaken social media to become the second-most used tool for organizing complex itineraries.

Online media ($44B revenue, +22% YoY) is personalizing content feeds and connecting audiences with more relevant ads, yielding a 10 to 20% quality engagement uplift as commerce media becomes a $4 billion market.

Mobility and food delivery ($40B GMV, +15% YoY) saves consumers time via predictive suggestions, smarter routing, and AI-powered offerings like pooled rides, fueling healthy transactional growth.

Finally, digital financial services ($1,650B GTV, +16% YoY) help consumers with real-time fraud detection, broader credit access, and personalized financial recommendations that complement human advice, alongside Singapore’s regional leadership in digital wealth platforms.

2. Consumer trust will help unlock the era of agentic commerce.

Digital automation is already well established across the region, where 72% of users rely on everyday features like price tracking. This familiarity is clearing the runway for agentic commerce, with 75% expressing willingness to let AI agents autonomously compare prices and complete transactions on their behalf.

This momentum is rooted in regional optimism: people in Southeast Asia view AI as a net benefit to society, with 62% reporting greater trust in AI tools today than a year ago. Driven by proven track records (56%), rising familiarity (55%), and output accuracy (53%), this trust signals a clear runway for deeper platform integration. To feel comfortable using new agentic capabilities, users expect clarity and guardrails, including robust privacy safeguards (44%), transparent information on what AI can and cannot do (36%), and the ability to reverse agentic transactions (30%).

3. Four major areas must adapt to enable AI adoption.

To support a projected 60-fold increase in regional AI usage by 2030, the region's broader digital ecosystem must systematically evolve across four critical conditions:

Accelerated agentic adoption and sustainable economics: Businesses need to move beyond using AI to answer single questions and start using it to help complete multi-step tasks from start to finish, backed by strong privacy safeguards and clear safety rules. At the same time, running AI models must keep getting more affordable and deliver clear, practical value, so businesses of all sizes can adopt the technology sustainably.
Scaled physical infrastructure: Physical expansion must rapidly keep pace with soaring compute demand. Meeting this trajectory requires a ~3x expansion in data center capacity over the next five years, with AI workloads capturing a dominant share of total infrastructure.
Strict model and energy efficiency: National frameworks, such as Singapore’s binding Power Usage Effectiveness (PUE) rules under the Digital Infrastructure Bill, must guide next-generation facilities, paired with expanded clean energy access like Malaysia’s Corporate Renewable Energy Supply Scheme (CRESS) model.
Unified regional governance: Anchoring this trajectory, the upcoming ASEAN Digital Economy Framework Agreement (DEFA) in November 2026 will establish the world's first region-wide digital trade pact, providing a framework that can unlock further growth in the Southeast Asia digital economy.

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Gemini 4 Argon: Built to solve your hardest problems

2026-10-13T16:00:00+00:00

We’re giving developers, enterprises, scientists, and consumers access to our latest frontier model.

Gemini 4 Argon is now globally available today for developers and enterprises via the API in AI Studio and Gemini platform, for Google AI Ultra subscribers in Google Antigravity, and Google AI Ultra and Pro subscribers in the Gemini app and AI Mode in Search.

Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science. Its depth and precision across multi-step tasks leads Argon to outperform other frontier models on benchmarks across domains, ranking #1 on the Vals Index, which measures model performance across critical economic sectors like finance, coding, legal, and tax work.

The model launches today at an introductory price 1 of $2 per million input tokens and $10 per million output tokens (with cached input tokens at 95% off).

Teams at Google, across enterprises, and in the research community have already been using Argon to land significant impact across fields:

To solve major engineering problems like large codebase refactoring and optimizations
To optimize business workflows across domains like legal, finance, and science
To find and patch critical cybersecurity vulnerabilities
To enable novel breakthroughs in quantum computing, nuclear fusion, and life sciences

Solving complex engineering tasks

At Google, we’ve been using Argon on our hardest engineering problems. Over the past few weeks, software engineers have been shipping high-quality code faster than ever. Argon in Antigravity has helped teams increase agentic code submissions by more than 35% while reducing code rollbacks by nearly a third.

Untangling browser feature code in Chrome: Argon helped the Chrome team separate core webpage handling from a ~6 million line legacy folder of browser features held within Chromium’s 40 million-line codebase. Piping multiple clean code changes at a time, Argon helped the team finish an architectural refactor across hundreds of files, completing months of work in weeks. For Chrome's billions of global users, this will unlock the ability for live webpages to move fluidly between tabs, side panels, and floating windows without reloading, eliminating an entire category of browser crashes.
Optimizing a production Python codebase in hours: Argon in Antigravity is helping the team behind Google's open-source Agent Development Kit (ADK), a framework powering enterprise agents, push their performance engineering further. The team gave Argon their .agents/skills rulebook and a one-paragraph goal to eliminate framework overhead without breaking existing apps. Working autonomously overnight, Argon surfaced optimizations, now live in google/adk-python, that cut in-memory session prep time by 40% in long sessions and sped up cold imports by 21%. Read the engineering deep dive to learn more.
Quantum chemistry open-source package optimization: xTB (Semiempirical Extended Tight-Binding) is one of the most-cited open-source quantum chemistry packages for molecules. Scientists use it to predict molecules' 3D shapes and to screen large numbers of drug and materials candidates. Using Argon in Antigravity, our researchers made xTB up to 2.3x faster at predicting molecular structures and 1.8x faster at conformer search. The changes have been contributed to the official xTB repository on GitHub.
Making our open Gemma models nearly three times as fast: Using Argon, we achieved a 2.85x end-to-end inference speedup on an A100 via vLLM (accelerating throughput from ~37,900 to over 108,000 tokens per second on Gemma 4 E2B) with 100% token parity and zero quality drop in just a few days, a process that would usually take months. Check out the upstream pull requests (optimizing everything from attention tuning to speculative decoding) to see the exact changes.
Delivering complex 3D visualizations: Argon brings major improvements in spatial reasoning, mathematical precision, and visual coding compared to previous Gemini models. Using slash commands like /goal and prompting for multi-agent loops with custom skills in Antigravity, Googlers are using Argon to prototype complex 3D visualizations, high-fidelity games, and interactive animations in vanilla code that can be rendered directly in the browser.

Transforming critical business and professional workflows

Argon combines frontier reasoning, deep visual perception, expanded domain knowledge, and stronger writing capabilities across legal, finance, science, and coding to help with high-stakes professional workflows. It communicates clearly, keeping you in the loop, and follows style instructions better than any of our previous Gemini models. Argon answers questions more directly with less hedging, doesn’t repeat itself more than necessary, and skips clichés throughout the responses.

Enterprise customers and startups in our early access program are already seeing strong wins with Argon.

Using its advanced reasoning and multimodal capabilities while maintaining strict grounding, Argon excels in deep multimodal document comprehension, longitudinal data analysis, and interactive analytical sandboxes.

Accelerating real-world impact with researchers and domain experts

Researchers, engineers, and security specialists are already using Argon to push the boundaries of cyber defense, science, math, and robotics. It’s helping cyber defenders and researchers test hypotheses, autonomously audit critical codebases and formal proofs, and catch subtle zero-day vulnerabilities and logic flaws.

Bringing state-of-the-art cyber capabilities to more trusted defenders

Starting today, we’re beginning expansion to hundreds of additional Fairwind Program partners.

Wiz is already using Argon for its "Scan for Good" initiative, which protects critical infrastructure for the public good and for free. With early access to the model, Wiz has demonstrated Argon's real-world impact across multiple high-stakes sectors:

Securing sensitive government data: As part of a long-standing cyber resilience program and in collaboration with a federal agency, Argon helped to proactively identify and remediate a gap that risked exposing sensitive data and government infrastructure. This effort helped prevent against the exposure of critical security sector development details and unauthorized access to specialized models.
Protecting critical healthcare infrastructure: Wiz also used Argon to protect vital healthcare infrastructure. By chaining complex vulnerabilities, the model helped the team discover and quickly fix a public file download bypass that exposed a master key and granted administrator access. Argon went beyond spotting a vulnerability to proactively safeguarding hundreds of thousands of private patient records.

Unlocking new scientific breakthroughs

Argon is already having real-world impact across the scientific community — enabling novel discovery for scientists and experts across multiple domains.

Quantum computing: Argon is helping our researchers accelerate progress across both quantum error correction and algorithm design. To help error decoders keep pace with quantum hardware in real-time, Argon translated an internal version of AlphaQubit, our ML quantum error correction decoder, into a single, highly optimized hardware kernel — nearly doubling its inference throughput so we can deploy larger, more capable models and scale to larger quantum devices, while continuing to meet strict real-time thresholds. Argon is also reducing spacetime costs for quantum subroutines. For arcsin, a building block in recent quantum simulation algorithms, an implementation written by Argon and formally verified in Lean cuts spacetime cost by more than 100x compared to a published quantum CORDIC baseline, a step toward a standard library of optimized quantum circuits.
Nuclear fusion: Stellarators are incredibly complex machines that represent a leading candidate for limitless clean fusion energy, but optimizing their 3D magnetic fields is famously difficult. Since 1967, a long-standing hypothesis known as “Grad’s conjecture” assumed that finding exact mathematical solutions for these fields was impossible, until recent counterexamples were found, including by Professor Matt Landreman (University of Maryland). Now, a team at Google alongside Professor Landreman has discovered a broader class of counterexamples to Grad's conjecture. These new solutions give the fusion community reliable benchmarks to test their stellarator simulations codes, which are valuable tools for future designs.
Rare disease research: Researchers at Gamow Labs used Argon to analyze de-identified genomes from newborns with rare developmental lung disorders. In one case, Argon pinpointed a chromosomal rearrangement that routine software missed for years, and explained why it went undetected. On private Gamow Labs evals derived from real clinical and lab data, Argon topped on RareBench (57% on assistance with rare-disease diagnosis) and LabBench (52.2% on wet-lab reasoning). These advances point to faster diagnosis for families facing rare conditions. See blog 2 for more details.
Enzyme design: Engineering enzymes with precise reactivity is notoriously slow, often demanding months of bespoke model tuning and candidate screening. Serine esterases are a class of enzymes that cut ester bonds on targeted molecules, widely used in recycling, and the manufacture of pharmaceuticals, biofuels and detergents. Our scientists worked with Argon to design serine esterases, targeting the benchmark molecule 4MU-acetate that glows under UV light once its ester bonds are broken. In a matter of hours, Argon assembled relevant data, performed model tuning and identified multiple biochemistry-inspired filters to get to a final set of five novel designs. Subsequent laboratory testing confirmed robust catalytic activity across these designs. The speed and ease of successful enzyme generation demonstrates the potential for rapid acceleration in enzyme engineering in fields such as biomanufacturing, green chemistry, and drug development.

To further advance the pace of research, we’re offering 10,000 scientists the highest usage tier in Google Antigravity free of charge for 6 months (onboarded on a rolling basis), subject to eligibility, capacity, and selection. Applications are now open.

Speeding up robotics development

By bringing together advanced visual-semantic reasoning, deep physical understanding, and autonomous code generation, Argon unlocks new workflows across the robotics stack and accelerates progress toward physical AGI. This leap in capability is reflected in Argon’s performance on the Embodied Reasoning (ERQA) benchmark, which tests a model's ability to understand and solve physical, spatial problems in 3D environments. Relying on pure reasoning, Argon outperforms all other frontier models, with an 87% score.

To demonstrate these capabilities in action, we tested Argon’s ability to learn an out-of-distribution physical skill simply by watching. In an internal test, Argon watched a raw video of a human playing cornhole, mapped the spatial coordinates of the environment, and calculated the required whole-body joint movements. It then autonomously built the simulation code. When transferred onto Apptronik’s Apollo humanoid, the robot quickly sank seven consecutive shots in a real-world trial.

This "Video-to-Sim-to-Real" pipeline compresses weeks of manual simulation modeling into a few hours, transforming ordinary videos into a scalable, infinite training ground for robotics. Learn more about how this accelerates the pace of development in robotics in our developers blog.

Developing Argon responsibly and safely

Safety and security are foundational to model development at Google. Because Argon is a highly capable model, we collaborated with a variety of third-party partners on measurement of certain model capabilities and safeguards. Gemini 4 Argon represents our most comprehensive safety and security stack yet:

Misuse & jailbreak defenses: The same coding and scientific capabilities that help defenders patch hospital software or accelerate bioengineering also require strong safeguards against malicious actors. Under our Frontier Safety Framework, we evaluated Argon’s enhanced capabilities across several domains, and deployed a multi-layer defense stack combining jailbreak resistance, monitoring, and enforcement. This greatly improved our robustness — for instance, external bio red teaming could only unlock less than 1% of bio sub-tasks we test for. Further, when it comes to dangerous requests — from writing exploit code to helping with dangerous biological materials — Argon is significantly better at not fulfilling harmful requests than our previous models. On an adversarial set meant to stress test the model, violations reduced nearly 2-fold — also significantly better than previous Gemini models.
Agent alignment & real-time monitoring: As agents become more capable problem solvers, we have to ensure they don’t get overly eager to finish a task by taking unauthorized shortcuts when they hit a roadblock, like a permission error or a failing test.
- First, we trained Argon to respect system boundaries, report negative findings honestly, and pause for human confirmation before taking irreversible steps. On coding benchmarks where models have no incentive to hold back, shortcut attempts dropped to just 2% on Gemini 4 Argon, our best performance compared to previous Gemini models.
- Second, as a defense-in-depth layer, we built an automated misalignment monitor that reads the agent’s step-by-step reasoning and actions to catch and block unintended workarounds in real time. We used this monitor across internal deployments, capability evaluations, and reinforcement learning training runs — while strictly avoiding penalizing the model’s thoughts during training so its reasoning remains transparent and monitorable.
Prompt injection resistance: When agents browse webpages, read emails, or inspect code, they can encounter hidden malicious instructions designed to hijack their task. Through adversarial training and automated red teaming, Argon leads the Gray Swan Indirect Prompt Injection (IPI) benchmark, cutting attack success across 15 adaptive attempts to 0.7%.

For more information, see the Gemini 4 Argon Model Card.

Get started today

Argon works longer and harder to solve highly complex scientific, coding, and agentic problems. This is enabled by an industry-leading 1M unified input-output token limit via the Gemini API. Read through our documentation for developers and enterprises to learn about the new continuation protocol and ensure the appropriate setup for your needs. Argon is rolling out today globally:

For developers: Build with the Gemini API paid tier in AI Studio and Android Studio, and if you’re a Google AI Ultra subscriber, you can try it in Google Antigravity and AI Studio.
For enterprises: Try it in Gemini for business, the API, and in Google Antigravity.
For everyday users: Try it starting today in the Gemini app and AI Mode in Search if you’re a Google AI Ultra or Pro subscriber.
For scientists & researchers: Apply for a chance to get access to Google Antigravity’s highest usage tier free of charge for 6 months (onboarded on a rolling basis), subject to eligibility, capacity, and selection. Applications are now open.
For cybersecurity defenders: Apply to join the Fairwind Program to get access to Argon without cyber guardrails on a rolling basis.

Gemini 4 Argon is just the beginning. We’re looking forward to bringing you the rest of the Gemini 4 family.

Introducing Playground: Create and play custom games

2026-10-07T12:00:00+00:00

If you can think it, you can play it. Create, play, and share custom games — no coding required.

Maryam Karimzadehgan

Software Engineer, AI Innovation + Research

Games are one of the most creative forms of expression, and the gaming community keeps growing. But game creation has historically been limited to a select group of people who have technical experience and knowledge of complex game engines.

Today, we’re introducing Playground, an experimental gaming platform that lets you create, play, and share custom games. Playground lowers the barriers to creation, so bringing game ideas to life can now be as easy as describing it through a few prompts — no coding experience required.

Create your custom game

With Playground’s conversational interface, you can direct the game just by typing what you want to build. Start from a blank canvas, remix starter prompts, or use guided support to shape your concept — and then test it right away. Want to tweak the physics, rewrite the rules, customize the characters, or overhaul the environment? Just ask. You stay in complete control of the creative direction from rough concept to final product.

Create games in Playground using text prompts

Play, compete, and share across devices

The fun doesn’t stop at creation. Playground is home to an ever-growing catalog of community games. And because it’s browser-based, you can play these games on your phone or laptop.

Once your game is ready, you can keep your game private, drop a shareable link to challenge friends and family, or publish it to the Playground Explore gallery for the broader Playground community. To have fun with your friends, Playground games support in-game leaderboards and multiplayer gameplay in select genres. With a Play Games profile, you can claim a custom handle, like your favorite games, battle for the top spot, and follow creators to catch their latest releases.

Our gallery uses player ratings and play activity to spotlight games that are fresh, creative, and fun. To keep the experience safe and welcoming, every published game undergoes safety screenings aligned with our Community Guidelines, along with user reporting.

Explore the Playground gallery

Stay tuned for Unity Spark

For dedicated creators ready to expand their concepts, Playground will soon offer an integration with Unity Spark. Unity Spark unlocks robust, professional-level mechanics, high-fidelity 3D capabilities, and the flexibility of the Unity runtime. The accessibility of Playground and the world-class, game-building expertise of Unity provides the building blocks for an ecosystem where you can start with a simple text prompt and eventually grow into building immersive experiences with Unity. And these games will be available for everyone using Playground to enjoy.

Unity Spark is currently in testing, with closed beta coming soon. Check out the demo games on playground.google, and learn more at unity.com/spark.

Get started today

Playground is an early experiment designed to make game creation more approachable and ignite everyday creativity. Playground will continue to evolve alongside our community, and we invite you to share your games and your feedback. Playground launches today for users in the U.S. (18+) at playground.google, with tiered creation access rolling out based on your Google AI subscription.

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The latest AI news we announced in September 2026

2026-10-02T15:00:00+00:00

Here’s a recap of some of our biggest AI updates from September, including Gemini 4 Argon, new Connected Apps in the Gemini App, and WeatherNext 3.

Blog Team

For more than 20 years, we’ve invested in machine learning and AI research, tools, and infrastructure to build products that make everyday life better for more people. Teams across Google are working on ways to unlock AI’s benefits in fields as wide-ranging as healthcare, crisis response, and education. To keep you posted on our progress, we're doing a regular roundup of Google's most recent AI news.

Here’s a look back at some of our AI announcements from September.

September's headline belongs to Gemini 4 Argon, our newest frontier model. Built with advanced reasoning and a 1-million-token context window, it’s designed to tackle complex challenges — especially in cybersecurity defense. The release capped an active month for Google AI launches that included Gemini 3.8 Flash and 3.8 Flash Cyber. We also introduced expressive voice models with Gemini 3.8 Live, made Googlebook available for pre-order, and brought the Gemini app to Windows. Beyond daily tools, we marked major scientific milestones by mapping human DNA in AlphaGenome Atlas, tracking global methane from space, and launching Project Suncatcher to test machine learning hardware in orbit. And as a nice bonus, we were grateful to see our teams’ work on designing better AI interfaces recognized by Fast Company as the 2026 Design Company of the Year.

Learn about Gemini 4 Argon: our next era of frontier intelligence. Gemini 4 Argon is engineered to bring advanced reasoning to the most difficult of problems. Built with an industry-leading 1-million-token context window, Argon excels at heavy-duty workloads like coding, cybersecurity defense, and knowledge work like financial research and legal drafting, and autonomous cybersecurity patching. Safely releasing frontier capabilities at this level requires a phased approach, and Argon is currently rolling out to trusted cyber defenders through the Fairwind Program. We’re actively gathering feedback from early testers to iterate on guardrails before expanding availability to developers, enterprises, and consumers.

Get next-gen intelligence for agents and cybersecurity with Gemini 3.8 Flash and 3.8 Flash Cyber. Gemini 3.8 delivers our best reasoning and coding performance yet at the same speed and low cost as 3.7 Flash. Gemini 3.8 Flash provides substantial gains in long-horizon software engineering, multi-step problem solving, and agentic workflows. Alongside it, Gemini 3.8 Flash Cyber equips defenders with frontier-grade autonomous vulnerability discovery and automated code patching — available to trusted organizations through our new Fairwind Program.

Converse naturally with Gemini 3.8 Live and 3.8 Live Extended Thinking. We've launched two fast, natural language audio models: Gemini 3.8 Live for everyday conversation, and Gemini 3.8 Live Extended Thinking, the top-rated speech-to-speech model for multi-step reasoning without all the lag. Both have rolled for developers in Google AI Studio and Gemini API, and for everyone across Search Live, Gemini Live, and Google Workspace, where you can get things done using your voice in Gmail, Docs, and Keep.

Say hello to Gemini 3.8 Flash-Lite TTS and Gemini 3.8 Flash TTS. Our most expressive text-to-speech models yet let you generate custom voices, direct scene dialogue, and more from simple text prompts. Instead of choosing from a fixed list of static presets, you now get a dynamic creative studio to build voice-first applications and elevate audio experiences, rolling out across products including Gemini Notebook and Google Vids.

Tackle tasks with new Connected Apps in Gemini. We brought more of your favorite apps directly into Gemini, including productivity tools like Airtable, Linear, monday.com, and PandaDoc; creative platforms including Adobe, Picsart, Squarespace, and Webflow; and lifestyle services such as Peloton, SeatGeek, and Experian. Instead of switching between tabs, you can now tackle your tasks all in one place. To get started, head to your Gemini settings and select the apps you want to link.

Create your best tracks yet with Lyria 3.5 in Gemini. From simple text prompts or images, you can now use our most expressive music generation model yet to produce richer arrangements, coherent songs, and personalized audio right in the Gemini app. Lyria 3.5 is available globally in Gemini and across Google AI Studio, Google Flow Music, and Google Vids.

Sharpen your study routine with new Gemini Notebook tools. Now you can transform your study routine in Gemini Notebook with interactive coursework tools and animated video summaries. Master complex topics using custom flashcards, versatile quiz formats, and 60-second Short Video Overviews in over 80 languages. For back-to-school season, eligible college students can also claim a free 12-month Google AI student plan with higher usage limits.

Coordinate family life effortlessly with CC in Google Labs. Google Labs is expanding CC from a personal agent into a collaborative group agent designed to handle household logistics and shared schedules. CC even gets its own email address to coordinate family calendars, track group to-dos, and streamline daily logistics in one spot with built-in privacy controls. CC for groups is now rolling out as an experimental preview in Google Labs.

Learn how AI breakthroughs accelerate science and improve lives. AI is transforming theoretical science into practical, everyday impact. By accelerating life-saving therapies, forecasting natural disasters, and personalizing education, our technology delivers tangible benefits worldwide. Today, Google tools support more than 300 languages spoken by 7 billion people — reaching 86% of the global population. By open-sourcing models like MedGemma and partnering with leading research institutions, we're helping scientists make discoveries faster to improve lives everywhere. Plus, new visualizations of our AI & Economy ATLAS data make it easier to see how AI is reshaping global work, including scientific research.

See how the future of AI computing could be in space. Project Suncatcher will launch its first test satellite with Planet to evaluate how Google TPUs perform under real space conditions. Satellites in low-Earth orbit can access up to eight times more solar power than on Earth, opening up new possibilities for long-term AI infrastructure. Learn questions we’re still exploring in our new four-part video series.

Pre-order Googlebook, the laptop of choice for Android users. Built on Android and paired with desktop foundations from ChromeOS, Googlebook is designed for Gemini Intelligence and engineered to work with your Android phone right out of the box. New on-device AI features like Magic Pointer let you point and ask Gemini about anything on your screen with a quick cursor wiggle, while Rambler smart voice dictation instantly structures verbal brain dumps into organized, shareable notes. With no-code custom widgets and background task processing, Googlebook simplifies your daily workflow so you can get more done effortlessly.

Check out WeatherNext 3, our most advanced and accurate global weather AI model. Our flagship AI weather forecasting model now includes real-time satellite data, hourly refreshes, higher resolution, precise precipitation forecasting, and clean energy variables. Plus, it’s now integrated across Search, Gemini, Maps, Google Maps Platform, and Cloud.

Explore AlphaGenome Atlas: a high-resolution map of human DNA. There are billions of possible mutations in the human genome — far too many to ever test in a lab. So we introduced AlphaGenome Atlas, a database that predicts the effects of every possible single nucleotide variant in the human genome, all 9 billion of them. Designed to require zero coding skills, it’s already accelerating real-world breakthroughs in rare disease research and complex genetics.

Track methane emissions globally from space. We partnered with NASA's Jet Propulsion Laboratory to develop MAPL-EMIT, a deep learning AI model that tracks global methane leaks from space. The model detects 50% more emissions than human experts and has already uncovered over 23,000 previously unmapped plumes, including 24 of the world's 25 largest-emitting landfills. All data is openly available on Google Earth Engine to help climate researchers and operators take faster action

See five amazing visuals of the male fruit fly’s brain map. Scientists at Google, HHMI Janelia, and Cambridge University have built the first complete brain map of an adult male fruit fly, charting over 166,000 neurons and nearly 12,000 distinct cell types with the help of Google AI. By stitching together millions of microscopic images into a navigable 3D model, this research uncovers how sensory cues transform into movement. It’s a breakthrough for neuroscience that brings us closer to understanding how complex brains function.

Learn about the new DeepMind Institute. The DeepMind Institute is a platform for researchers and thinkers from across Google DeepMind, Google, and the wider global research community to work on and publish creative, deeply informed ideas about a world with AGI. With AGI on the horizon, it’s incumbent on the creators of AI technology to sincerely and thoughtfully address its risks — but its transformative impact cannot be steered by technologists alone. DMI serves as a dedicated forum to spur debate, bring together diverse global voices, and build a consensus that ensures AGI benefits everyone.

Access fast help on your PC with the Gemini app for Windows. Now, using the Alt + Space shortcut, you can open Gemini any time over your work to fact-check docs or brainstorm ideas without breaking your stride. In the dedicated workspace, you can delegate multi-step tasks to Gemini Spark, synthesize files across Gmail and Drive, and generate Nano Banana images or Gemini Omni videos — all in one place.

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Watch the winning trailer from the Future Vision XPRIZE, The Gifted.

2026-09-28T19:00:00+00:00

Watch the winning trailer from the Future Vision XPRIZE, The Gifted.

Google Beam expands with new regions, partners, and customers

2026-09-23T18:00:00+00:00

We’re expanding Google Beam to five new countries, partnering with Industrious for an extended network, and proving our impact at Google and beyond.

Aaron Luber

Director, Business Development, Google Beam

Since its early days, Google Beam has been driven by a singular vision: bringing people together so they can experience genuine, face-to-face connection, no matter the distance. We’ve tested Beam with early users, including in our own offices, and shown how it can help transform everyday meetings into authentic moments of connection.

Today, we’re announcing a major expansion of our global footprint, new data on our proven impact, and the launch of our first-ever extended network.

Expanding our global footprint

We are officially expanding our global reach, with Google Beam units shipping to customers across six countries, including the U.S., Canada, U.K., France, Germany, and Japan. Backing this rollout is a robust, global ecosystem of 18 channel partners who are fully equipped to deploy and support Beam.

Delivered by our flagship hardware partner as HP Dimension with Google Beam, this experience is built for modern enterprise collaboration. By integrating seamlessly with both Google Meet and Zoom, Beam can provide the flexibility organizations need while helping to elevate everyday conversations.

Proving our real-world impact

Through extensive internal testing at Google, we’ve learned how transformative Beam can be for areas like recruiting, talent development, and cross-functional collaboration. In a recent eight-week internal study, Google teams using Beam felt 50% more connected to one another, found it 33% easier to ensure their feedback was clearly understood, and saw a 21% drop in the need for follow-up meetings. All of this has reinforced our own belief in expanding our own deployment of Beam for Googlers, alongside our customers.

We are also working closely with leaned-in partners to prove out these exact use cases in the field. Earlier this year, we partnered with Bain and Company to test how HP Dimension with Google Beam could help transform their campus recruiting and candidate interviews. By using this technology, Bain was able to create authentic, face-to-face connections with candidates from anywhere—without the need for extensive travel. Watch how Bain is transforming their interview process here.

We are thrilled to see this excitement mirrored by other first customers like Netflix, Capital Group, and many more who are eager to transform how they connect their global workforces.

Creating the first-ever Beam extended network

To help make Beam accessible to organizations of all sizes, we are partnering with Industrious, a global operator of premium flexible workspaces worldwide. Together, we are creating the first-ever Beam extended network.

We conducted a pilot earlier this year, in which we heard firsthand how distributed teams are connecting for manager check-ins, interviews, and client consultations. Now, this network will increase access to Google Beam, opening the doors for more startups and businesses of all sizes to better connect and make their meetings feel much more natural.

Starting in October, you can book and experience HP Dimension with Google Beam directly at select Industrious locations across the U.S., including Atlanta, Chicago, New York City and Palo Alto. Learn more here.

The way we work is evolving, but the need for genuine human connection remains constant. Discover how organizations worldwide are transforming their meetings and explore more real-world use cases at beam.google.

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New experts join Google’s AI & Economy team

2026-09-18T14:00:00+00:00

Nobel Laureate Philippe Aghion, Professor Ajay Agrawal, and leading researchers join Google’s AI & Economy program to expand our scientific understanding of AI’s impact on economic activity worldwide.

Scott Strand

Head of StratOps and Special Projects, Technology & Society

Zanna Iscenko

AI & Economy Lead, Chief Economist's Office

We recently launched the AI & Economy ATLAS v1.0 and its interactive open-access site to understand how people are using Google’s AI tools at work and in their daily lives. But tracking adoption patterns is only the beginning. As artificial intelligence reshapes jobs, businesses, and everyday lives, navigating this shift requires a multidisciplinary approach that unites fine-grained data with rigorous economic inquiry.

To further help organizations, workers, researchers, and policymakers make sense of this complex transition, we are expanding our AI & Economy Research Program, and welcoming world-class economists to help build and lead this work.

Technological shifts are rarely instantaneous. Our program measures and analyzes this evolution in real time, focusing on core areas including the future of work, productivity and growth, global technology diffusion, and AI’s impact on scientific discovery.

Expanding our scientific expertise and engagement

Executing a research agenda of this scope requires deep collaboration among academia, industry leaders, and policymakers. To expand our scientific capacity and engage more deeply with these diverse stakeholders, we are bringing together leading external advisors, visiting scholars, and dedicated research program leadership. Joining us as Academic Advisors and Visiting Fellows:

Philippe Aghion, Academic Advisor: Professor Aghion, 2025 Nobel Laureate in Economics and the Kurt Björklund Chaired Professor at INSEAD and the Collège de France, joins our advisory group alongside Nobel Laureate Michael Spence and Cambridge’s Dame Diane Coyle, applying his pioneering work on innovation-led growth and creative destruction to model AI's long-term macroeconomic trajectory.
Ajay Agrawal, Visiting Fellow: Professor Agrawal joins our Visiting Fellows program, where he will collaborate closely with David Autor, a current Fellow and head of MIT’s Department of Economics. Professor Agrawal, who holds the Geoffrey Taber Chair in Entrepreneurship and Innovation and is a Professor of Strategic Management at the University of Toronto’s Rotman School of Management, will advance our core research on the economics of AI and scientific discovery, AI and robotics, and how AI can expand the frontier of human welfare.

To steer empirical projects and integrate insights across our agenda, we are also introducing two renowned researchers as Directors of Google’s AI & Economy Research Program:

Anu Madgavkar: Formerly a Partner at the McKinsey Global Institute (MGI), Madgavkar joins Google following a two-decade career leading global research on labor markets, technology adoption, and structural economic transitions. She has frequently advised governments, multilateral institutions, and business leaders worldwide, contributing regularly to the World Economic Forum and the United Nations. At Google, she will lead empirical research on global AI diffusion, small business ecosystems, and the workforce impacts of generative AI.
Daniel Rock: Joining from the Wharton School of the University of Pennsylvania, Professor Rock is a leading economist on AI and labor, having co-authored foundational papers on technological transitions. An AI2050 Early Career Fellow and MIT Digital Fellow, he will lead Google's empirical research, bridging frontier model telemetry with rigorous econometrics to analyze enterprise productivity, labor restructuring, and scientific discovery.

Anu Madgavkar and Daniel Rock will lead Google's AI & Economy Research Program alongside Alex Imas, Director of AGI Economics at Google DeepMind, and Zanna Iscenko, AI & Economy Lead, in Google's Chief Economist's Office.

Shaping future research and collective impact

Maximizing AI’s economic opportunity while mitigating disruption requires sustained partnership. This expanded team of experts will serve as a scientific bridge, directly informing future ATLAS updates and empirical research.

Together, we will focus on identifying the organizational practices, public policy frameworks, and training programs needed to ensure AI upskills workers, democratizes expertise, and drives broadly shared prosperity.

To learn more, read our latest research publications, and interact with our latest global data, visit ai.google/economy.

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Co-creating the future of fashion with Google

2026-09-18T13:00:00+00:00

Two fashion designers created custom tools in Google Flow to help with set design and styling for New York Fashion Week.

Yeawon Choi

UX Designer, Envisioning Studio

Ask an independent fashion designer how they actually spend their time, and "designing clothes" is rarely the answer. Administrative tasks, factory logistics, and vendor coordination take up the bulk of their days, leaving very little time for design.

Ahead of New York Fashion Week, Google’s Envisioning Studio, with support from Google Labs, set out to streamline the creative workflow process—helping designers bring ambitious runway visions to life with less friction.

Google engineers worked side by side with designers Jane Wade and Sergio Hudson, using Google Flow, our AI creative studio, to build two specialized tools to address their specific challenges. Jane’s Google Flow tool helped her create balanced head-to-toe looks before producing physical samples. Sergio used his tool to stage his runway on a tight studio budget.

Virtually styling a collection

The Google Flow tool we co-created with Jane, Styling Suite, mapped every facet of her runway model looks. In-person casting and fittings typically consume up to three full days for a design team. The tool allowed her to curate hair, makeup, accessories, shoes, and garments on digital models, then play with the styling virtually. She was able to balance each look and identify missing elements before cutting and sewing additional pieces.

Grounding runway design in a real budget

Sergio’s main challenge was staging his show without breaking his budget. In the past, asking his production crew to change lighting and props added to the overall costs, since a new 3D rendering was needed for every design revision. Our co-developed Google Flow tool, Runway Visualization, eliminated the back-and-forth by simulating his runway. It let him adjust the set-up of his venue and swap the lighting and props with options that worked within his budget. He was also able to refine which paths the models would walk, allowing him to harmonize the show and viewer experience.

Moving fashion AI out of pilot mode

The results of these collaborations were visible on the runways at New York Fashion Week — and there’s room for more innovation.

While there’s plenty of excitement around AI in the fashion industry, many projects remain stuck in theoretical testing. AI can make the production process smoother for designers by co-developing tools that work within their existing processes and ensure they’re firmly in the driver’s seat.

Build your own bespoke tools in Google Flow using natural language to describe the tool or workflow you’re looking to create, no coding experience required.

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Making global data easier to explore

2026-09-17T20:00:00+00:00

UN System Data Commons is an open, AI-ready platform integrating critical global statistics into a single searchable resource.

Prem Ramaswami

Head of Data Commons

Every year, entities across the United Nations system compile data to track challenges that affect how we work, learn, stay healthy, and care for our loved ones.

These agencies work with some of the highest-integrity data in the world. But the statistics needed to solve big global challenges have lived in separate silos, organized in conflicting formats across, and within, different UN system organizations. Connecting the dots often meant months of painstaking manual work for data analysts before any real analysis could begin.

To solve this challenge, the UN system is launching the UN System Data Commons—an open-source platform built on Data Commons by Google that unites global statistics into one interconnected resource known as an AI-ready knowledge graph. With support from Google.org to the UN Foundation, the project makes critical data universally accessible, helping everyone from researchers to leaders track global progress in real time.

Connected data for complex global efforts

Many of society’s greatest challenges — from public health to poverty eradication — cannot be solved with a single data source. Effectively tackling these crises requires understanding how different datasets intersect.

The UN System Data Commons helps uncover these intersections by unifying siloed datasets, so that they can speak the same language. The platform automatically integrates metrics, timelines, and geographic boundaries into a single interconnected environment. This gives analysts more time to focus on uncovering key trends and designing evidence-based solutions, instead of formatting spreadsheets.

Natural language features for easier exploring

The UN System Data Commons uses AI to democratize access to these insights, letting people explore through intuitive, natural-language search. This means anyone, from a nonprofit program manager to a journalist to an international policy analyst, can ask questions in plain language and instantly receive relevant data and interactive visualizations.

Users can query the platform directly with questions such as:

How does access to clean water in rural areas affect school attendance?
How many people gained access to electricity in the last decade?
How has life expectancy changed across different regions of the world?

If you prefer to browse, the Explore tab makes it easy to filter data by location or themes like health or education. The Blog section also breaks down complex trends into ready-to-read reports, like using UNICEF data to explore what works to reduce child poverty. Most importantly, every dataset is validated with UN system statisticians and technical experts, so every answer stays grounded in trusted, official facts.

Putting AI to work as agentic research assistants

Today’s launch also brings AI assistant capabilities directly to the research workflow. Instead of spending hours manually searching for numbers and assembling spreadsheets, you can prompt an AI assistant to do the heavy lifting. Built on open standards like the Model Context Protocol (MCP), Data Commons makes data AI ready enabling AI agents to autonomously fetch authoritative figures directly from the UN System Data Commons, connect the dots across different domains, and package everything together into ready-to-use charts, graphs, infographics, or written draft reports. Even with grounded, verified data, review the underlying sources before citing critical figures.

More data and new features to come

Over the coming year, the UN system will continue adding datasets from more UN entities, with a goal of including 80% of UN system statistical datasets by 2027.

Explore the data yourself at data.un.org.

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Building AI to accelerate science and improve lives

2026-09-15T16:00:00+00:00

We’re asking what’s possible for health, natural disaster and weather resilience, learning, and economic opportunity.

Today, we reached a significant milestone that stands as a testament to decades of AI research and advancement: Google technologies now support more than 300 languages, spoken by 7 billion people — representing 86% of the global population. To help us understand how these tools are driving real-world opportunity, we also released new interactive insights today with our AI & Economy ATLAS, the most comprehensive look at how real people are using AI globally. This comes on top of a raft of key AI advances in science to benefit people over just the past few weeks:

We mapped the predicted impact of all 9 billion possible single letter genetic changes across the human genome with AlphaGenome Atlas and made it openly available to researchers.
We introduced WeatherNext 3, our most advanced and accurate global weather model, delivering 50% more accurate precipitation forecasts a day or more ahead — and it’s already in use in our products.
We brought together data on global health, food security, and socioeconomics into a single Planetary Prediction Engine to forecast planetary crises — this has already been used in the ongoing Ebola outbreak in the Democratic Republic of the Congo and in the U.S. in identifying vulnerable communities across 21 CDC health indicators.
We scaled AI research to help cut the climate impact of aviation — this is already being applied in the U.K. (in collaboration with the government) and in Asia.

What ties all of this work together? It is the belief that advances in AI can accelerate scientific progress in ways that will directly improve people’s lives today and in the future. This is a key element of what motivates our work in AI. We’re focusing our work in key areas that matter most: making disease detectable, treatable, and preventable, predicting natural disasters, expanding learning, and unlocking economic opportunities for more people.

While the possibilities are exciting, the benefits of AI are not guaranteed. Making them real — and mitigating their challenges and risks — demands that society works together. Though there is more still to do, AI’s progress is already making it possible for us to aspire to do bold and ambitious things that can benefit people, and to ask and address questions that were once considered impossible to solve.

We’re making progress in using AI to improve disease detection and diagnosis, and to better understand health conditions:

Deepening scientific discovery: In 2024, Demis Hassabis and John Jumper were co-awarded a Nobel Prize for their work on AlphaFold, which has predicted all 200 million protein structures known to science, providing a new basis for understanding and researching diseases. It is now used by 4 million researchers in 190 countries in areas from drug discovery to understanding neglected diseases like Chagas disease and leishmaniasis. AlphaMissense is helping researchers identify disease-causing genetic mutations. And now, we’re building on AlphaFold and AlphaMissense with AlphaGenome Atlas, offering scientists predictive insights into how genetic variations alter cellular behavior.
Earlier detection: Our recent breast cancer study with Imperial College London and the U.K.’s NHS showed AI can detect 25% of interval cancers previously missed in mammograms of 175,000 women. At the same time, we’re making meaningful progress in tools to help detect lung cancer, colorectal cancer, and genetic mutations in tumor cells.
Global screenings: For tuberculosis — where ~40% of infected people worldwide go undiagnosed — our chest X-ray (used by Nexus Intelligence) has screened over 25,000 x-rays across 40 locations in six nations. We are also using bioacoustic models to detect TB via coughs using Health Acoustic Representations. Meanwhile, our diabetic retinopathy model, developed with partners, has supported more than 1.15 million screenings globally, with plans to expand to 6 million over the next decade to help detect a treatable but growing cause of preventable blindness.
Expanding access: We’re pioneering the use of everyday smart phones and wearables for early detection of cardiovascular disease, insulin resistance, hypertension, loss of pulse, and passive heart rate monitoring. We’re working with leaders in Arkansas to help develop a blueprint for improving health outcomes in rural areas.
Tools for scientists and health practitioners: Collaborative AI tools like Co-Scientist are helping researchers accelerate and expand core steps of the scientific method, like generating and validating novel hypotheses (such as identifying new therapeutic applications for existing drugs for acute myeloid leukemia). We have also open-sourced AI tools like DeepConsensus, DeepVariant, and DeepPolisher. Over the last decade, these tools have assisted in understanding the human genome, drafting the first pangenome, and enabling ongoing work as part of the Human Pangenome Reference Consortium, better representing human genetic diversity and allowing experts to more accurately diagnose and treat diseases. Through AMIE (Articulate Medical Intelligence Explorer), we are advancing toward longitudinal disease management, building prospective evidence in real-world settings, collaborating with academic and medical institutions (e.g., Beth Israel Deaconess Center), and conducting a first-of-its-kind nationwide trial in real-world care settings. AMIE assists those providing care on the frontlines — freeing up doctors to spend more time with their patients.

To protect people’s safety and livelihoods, we need accurate predictions of natural disasters and weather. To make accurate predictions, we must understand the physical earth. Here’s how our technical and scientific progress is already making a difference in crisis prediction and detection:

Extreme weather and earthquakes: Last year, authorities in Jamaica used WeatherNext to accurately predict Hurricane Melissa’s path, securing early disaster funding and enabling life-saving emergency preparations long before the storm made landfall. Just a few months ago, our Earthquake Alert system alerted millions of people in Venezuela ahead of an earthquake. And we’re making progress in other areas, including cyclones and extreme heat.
Monsoons and floods: The scale of this work is encouraging. In 2025, our monsoon predictions provided information for 38 million farmers in India. And in just a few years, our forecasts on Flood Hub — now including both riverine floods and flash floods — have grown to cover 2 billion people across more than 150 countries in areas at risk for significant flood events.
Wildfires: Our AI tools have helped predict wildfire boundaries in the U.S. and 33 other countries. We’re also working with partners toward a FireSat constellation of satellites to detect wildfires previously too small to detect anywhere on earth. In 2025, we generated more than 520 crisis alerts on Google Search that provided timely wildfire information to over 75 million users around the world.
Next-gen prediction: With WeatherNext 3, we’re combining real-time satellite observations with AI, delivering high-resolution, hourly forecasts without immense supercomputing power — a major step forward for data-sparse regions that have been long underserved by high-resolution forecasting.
Planetary crisis mapping: We recently introduced the Earth AI Planetary Prediction Engine (PPE), an autonomous AI system that uses simple language instructions to almost instantly predict global crises like disease outbreaks, food shortages, and climate risks, helping humanitarian responders act faster during emergencies. In the ongoing Ebola outbreak in the Democratic Republic of the Congo, PPE successfully pinpointed 83% of emerging hotspots ahead of time, beating current forecasting systems. In Nigeria, PPE doubled food security forecasting accuracy at the local district level. And in the U.S., PPE outperformed traditional models in identifying vulnerable communities across 21 CDC health indicators. We’re continuing to expand prediction horizons to make these tools even more useful.

Learning is the bedrock of economic and societal progress. The world has made huge strides in education: 90% of primary school-aged children globally are enrolled in school, and approximately 87% complete their primary education. But 2022 research showed uneven access to education, differences in education quality, and limited content availability across languages, among other issues. Global learning outcomes have declined over the last two decades across 81 countries.

AI offers a profound opportunity to expand access to knowledge and support learners and educators alike:

For learners: AI can enable personalized learning, remove language barriers, and make complex subjects more accessible through tools like Guided Learning. It can also expand access and support for learners and teachers, for example with free access to student tools in multiple countries.
For educators: AI can help with research, preparation, and administrative tasks, freeing up time to spend with students.

Tackling challenges and focusing on responsible design: AI presents real challenges for learning, including questions on accuracy, safety, critical thinking, cheating, and learning loss. That’s why we have partnered with ISTE+ASCD to provide AI literacy training to all 6 million educators in the U.S., while conducting ongoing and rigorous research to ensure we design our educational tools with teachers in the lead, and AI as the assistant. We still have much to work through together.

Across the economy, AI can drive innovation and productivity for workers, businesses, and organizations across sectors. Its true value isn’t in what it does on its own, but in how people choose to use it and what they build with it:

For small businesses: AI can help deliver new products, services, and economic growth. Small businesses are scaling custom marketing campaigns with Pomelli and bringing together complex regional sales data from different product lines with the Gemini Enterprise App.
The future of work: The economic benefits of AI are neither automatic nor guaranteed. Like other new technologies, we expect AI to reshape work in three major ways: Some jobs are likely to decline, some jobs will grow, and many more jobs will change as AI increasingly assists workers. To understand these shifts, we’ve launched the AI & Economy ATLAS, which provides empirical insights on how people are using AI tools at work and in their daily lives, and translated the data into an interactive, open-access experience.
Skilling: Training and skill building must be accessible to all regardless of a person's geography, language, or access to capital. To date, Google has provided more than $1 billion globally in training and skilling initiatives, helping over 100 million people gain essential digital and AI skills, from electricians and other skilled tradespeople, to rural healthcare workers, to manufacturing workers. More tailored worker assistance and transition support will likely be needed.

Grounded in our company’s founding mission, we are making important strides in breaking down languages and accessibility barriers with products, research, and models that understand the world’s languages exactly as they are expressed:

Language tools: AI and machine learning have been part of Google Translate since its launch in 2006. Since then, advances in AI have helped us expand our technologies and products to support nearly 300 languages, spoken by 7 billion people — representing 86% of the world’s population, and helping more than 1 billion people translate around 1 trillion words each month. Our goal is to support the world’s 1,000 most-spoken languages.
Inclusive speech technology: Access is broader than translation alone. For example, automatic speech recognition uses AI to understand spoken words and convert them into text. To help build inclusive speech technology, we partnered with Makerere University, University of Ghana, and Digital Umuganda to create an open dataset for 27 African languages spoken by over 100 million people. One language alone may have 100 dialects, each with its own nuance, which is why we’ve also partnered with IISC-Banglore and ARTPARK on Project Vaani to open-source speech and image datasets for 109 Indic languages.
Accessibility: Beyond spoken languages, we've been making our tools more accessible for people with disabilities, including with our recent sign-language-to-text (SL2T) model for sign-to-text dictation.

Bold and responsible, together

We believe that such bold ambitions for the societal benefits of AI must always be accompanied by an equal commitment to responsibility. This is the basis of our bold and responsible approach to AI. Beyond our ongoing work to address the immediate and future risks of AI (detailed in our annual updates), the application of AI and science presents distinct challenges: On the one hand, we need the right detection, reporting, and mitigation tools in place to address risks around chemical, biological, radiological, and nuclear (CBRN) mis-use. At the same time, it is important to avoid the risk of missed use — that is, not applying AI in places and communities where it would provide benefit and, in some cases, worsening existing societal challenges and gaps.

We believe advancing scientific discovery and bringing those benefits to communities requires that we collaborate deeply with many other researchers and scientists working to tackle similar issues, including academia, national laboratories, philanthropic foundations, non-governmental organizations, governments, other companies, and local partners. The examples of advances cited above have benefited from such research collaborations and our own Google.org grant-making to accelerate scientific discovery and to address society’s greatest challenges. That’s why as part of our longstanding commitment to supporting science and discovery in academia, Google has given more than $1 billion across 1,700+ research institutions worldwide since 2006.

As Nobel laureate Joel Mokyr noted, new technology drives scientific advances, which in turn drive new technologies, creating "a positive feedback loop that can keep growing with no end in sight.” And it does so in ways that have improved people’s wellbeing and propelled societal progress. AI is the most powerful engine for that loop we have ever built — and we’re just getting started.

Read more about how we’re using AI to help people, improve lives, and benefit society at our website.

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AI for Societal Impact

2026-09-15T16:00:00+00:00

For over a decade, we’ve seen artificial intelligence steadily advance scientific discovery, shifting from theoretical research to real-world impact. Today, the potential of these tools is no longer hypothetical — it is measurable and fundamentally reshaping how we solve humanity's most complex challenges.

Across the globe, we’re partnering with communities and researchers who are putting AI to work in key areas that matter most: making disease detectable, treatable, and preventable, predicting natural disasters, expanding learning, and unlocking economic opportunities for more people.

Explore this collection to see how experts and local leaders are using AI breakthroughs to ensure everyone can share the opportunity of AI.

AI for everyone in every language

2026-09-15T16:00:00+00:00

Today, our technologies and products power everyday interactions in more than 300 languages, spoken by more than 7 billion people — representing 86% of the global population. Reaching this milestone is meaningful, but it also underscores work that is critical to our mission. For decades, technology has worked best for a handful of dominant languages, leaving thousands of living languages and dialects poorly represented or absent altogether from the digital world.

When we launched Google Translate in 2006, our goal was simple: to break down the barriers between languages. Advances in AI have helped us bring that vision to more people, expanding Translate from a handful of languages to more than 250 today. But translating text isn’t enough. Technology needs to understand how people actually communicate in the real world. So we focus our research and development on building systems that honor cultural nuance and the richness of human language, enabling everyone to participate and be understood on their own terms.

Here’s what that work looks like in practice.

Going from text to true understanding

Historically, speech recognition systems followed a rigid, multi-step process: transcribing audio into text, processing that text, and then synthesizing it back into audio. While functional, this pipeline strips away the richest parts of human communication: tone, pacing, emotion, and context.

People don't speak in perfectly neat, grammatical sentences. We laugh, overlap, hesitate, and weave multiple languages together mid-sentence, like when we speak Spanglish or Hinglish.

To capture this, we moved beyond text transcripts to native audio intelligence — training models like Gemini to process audio directly as is, while also grasping both sound and intent. These efforts include:

Fluid real-time dialogue tools:
- Today, Gemini 3.5 Live Translate powers real-time spoken translation across 70 languages and 2,000+ language pairs, naturally capturing code-switching and emotional cues along the way.
- Gemini 3.5 Transcribe is our most precise speech-to-text model yet, turning raw audio into polished, formatted text, even in noisy environments or with complex jargon. It also powers features like Rambler on Android Gboard, which removes filler words, fixes grammar and punctuation, and lets you edit or rewrite with voice commands and switch seamlessly between languages.
The 1,000 Languages Initiative: AI is helping us break down language barriers at a scale that was previously unimaginable. But reaching more people in their preferred language means going beyond the languages where AI performs best today: Our goal is to support the world’s 1,000 most-spoken languages. To help make that possible, our Universal Speech Model — trained on 12 million hours of audio — used cross-lingual transfer learning, techniques that enable models to transfer what they learn from data-rich languages, to improve speech understanding in languages with far less training data. This allows models to apply patterns learned from data-rich languages to under-resourced ones.
Rigorous foundational research: This work builds on 25 years of open research and more than 400 peer-reviewed speech papers, which have helped push the frontier and advance speech models.

Putting communities at the heart of language data

Because the web disproportionately represents a few dominant languages, teaching AI to understand underrepresented languages required us to rethink how we gather data. The solution is local grassroots partnerships. This localized approach has driven three of our most ambitious open-data partnerships:

WAXAL (Wolof for “speaking,” pronounced "Wah-hal"): Built with partners including Makerere University and Digital Umuganda, WAXAL is a large-scale, open speech dataset covering 27 Sub-Saharan African languages spoken by more than 100 million people across more than 26 countries, capturing tonal variation and conversational rhythms often missing from traditional datasets.
Project Vaani: In partnership with the Indian Institute of Science (IISc) and Bhashini, Project Vaani is mapping India’s linguistic diversity through a region-anchored rather than language-anchored approach, enabling it to collect to date more than 30,000 hours of speech across 109 languages from more than 155,000 speakers.
Amplify Initiative: We teamed up with more than 1,600 local experts and 20 universities across four continents, including Brazil’s UFMG, India’s IIT Kharagpur, and Uganda’s Makerere University, to contribute 15,000 multimodal data points capturing local nuance.

We’re also building on our work prioritizing open-source language innovation through our new tool Language Explorer. It’s an interactive tool that visualizes LinguaMeta, the world’s largest open-source language data repository. Recognized by Fast Company for design innovation, it continuously maps more than 7,000 spoken, written, and signed languages.

The impact of these innovations and partnerships is greatest when they reach the people who can turn new data and insights into meaningful change in their communities. Google.org-supported efforts, including the Centre for Digital Language Inclusion and AI Singapore’s Project Aquarium, are helping bring multilingual tools to farmers, healthcare workers, teachers, and other essential community members around the world.

Overcoming real-world constraints

For more than 3 billion people 1 , reliable internet access is still out of reach. Technology is only truly accessible if it works where people live, including areas with limited or intermittent connectivity.

To help address this, we developed TranslateGemma, a family of lightweight open translation models built from Gemini and trained across 55 languages. Because TranslateGemma runs efficiently on-device, high quality translation no longer requires a connection to the cloud or the internet.

Still, running powerful AI models requires capable hardware, which excludes the hundreds of millions of people still using feature phones in low-resource regions. To bridge this divide, we’re supporting organizations like Viamo to power “Ask Viamo Anything” (AVA), a voice AI assistant that brings the power of Gemini to standard feature phones. Viamo has successfully piloted AVA in Rwanda with its existing interactive voice response users, and the service has already used Gemini to answer more than 2 million questions.

Designing for accessibility

Language isn’t just about regional dialects or vocabulary. It’s also about the many other ways people communicate. Conventional speech tools frequently fail people with non-standard speech, making them adapt to the technology rather than the other way around.

We’re working to change that by designing for accessibility from the ground up, for example, with Sign Language-to-Text (SL2T). Trained across 50+ sign languages, SL2T powers sign-to-text dictation in Gboard and Live Transcribe on Pixel 11, starting with American Sign Language (ASL) to English. This is an important first step toward making our products more accessible to the 70 million people worldwide who rely on sign language to communicate.

Getting local pronunciation right

Details matter, certainly in everyday tools like navigation. When a navigation app mispronounces a town or street name, it doesn’t just cause confusion, it can overlook the cultural heritage of the place.

We believe cultural context should be part of how language technology is built, and that means working directly with local communities. For example, in New Zealand, we worked with Māori language experts to improve the place name pronunciation in Google Maps, helping make the experience more accurate and genuinely local. Incorporating culturally authentic pronunciations directly into our text-to-speech models ensures technology reflects the language and heritage of the communities it serves.

Building language tools for everyone

One essential lesson we’ve learned over 20 years of AI language research and development is that technology should never narrow the spectrum of human expression — it should expand it.

Today, our language technologies are already embedded across our core ecosystem, connecting more than five billion people across nine platforms, including Search, Android, Chrome, YouTube, and Google Play. But scale is only part of the story. The bigger goal is depth and richness — building systems that grasp context, respect culture, and celebrate the many ways people communicate.

As we expand our use of AI to address some of society’s biggest opportunities, we’ll continue to work closely with local communities to build technology that helps more people communicate, participate, and be understood on their own terms.

New insights from Google’s AI & Economy ATLAS

2026-09-15T13:00:00+00:00

New data visualizations make ATLAS data easier to explore and use, while new research provides insights on how scientists are using AI.

Zanna Iscenko

AI & Economy Lead, Chief Economist's Office

Scott Strand

Head of StratOps and Special Projects, Technology & Society

How is AI being used by people every day, including in offices, labs, and creative studios around the world? Insights from Google’s AI & Economy ATLAS show how AI is actively reshaping global work. For example:

India’s creative industry is using AI at a higher rate than the rest of the world, with arts, design, and media occupations making up 19% of work-related AI usage, 1.6 times the global average.
The U.S. is leading in technical AI adoption, with computer and mathematical occupations accounting for 30% of work-related AI usage, double the share in the rest of the world.

To make these insights and ATLAS's millions of other global data points easier to explore, we're launching a new interactive, open-access experience. You can look more closely at the rates different occupations are using AI, from electricians to purchasing managers, dive into the ways people are using AI at home, and explore the rate of AI adoption in countries around the world.

And new ATLAS-based research from Google, Google DeepMind, in collaboration with MIT FutureTech provides new insights how scientists are using AI in their work, including:

Scientists are using AI at a higher rate than many other occupations; nearly half of surveyed scientists use some form of AI every day.
Both LLMs and specialized models are used widely for science, in mutually reinforcing ways.
Scientists report saving almost 7 hours a week with AI, freeing up time for more research. However, there are now bottlenecks further down the research production pipeline, creating a backlog of hypotheses.

Which professions are using AI most, and where?

ATLAS data reveals how different professions around the globe are adopting AI, highlighting key regional trends and usage patterns:

AI by occupation: In OECD countries, computer and mathematical and business and financial operations lead in AI usage. In non-OECD countries, office and administrative support, arts, design, entertainment, sports, and media, and educational instruction and library occupations take the top spots.
Income level vs. adoption: While AI adoption generally correlates with a country’s income level, countries like Brazil and the UAE stand out with higher adoption rates than their GDP per capita would predict.
AI for manual tasks: Usage for real-time equipment diagnostics and troubleshooting varies significantly by region. In Brazil and Germany, 7% of work AI usage goes toward manual tasks (1.4 times the global average), compared to 4% in Japan.

How are scientists using AI?

New research also highlights how scientists are using AI in their work. A new study from Google, Google DeepMind, and MIT FutureTech draws on ATLAS data. It’s an analysis of 2600 specialized AI models, and a survey of over 600 U.S. and U.K. scientists, all organized using a new taxonomy from MIT FutureTech that maps out what scientists do.

According to the research, scientists are using AI at a higher rate than many other occupations, and nearly half use some form of AI every day. While scientists are using both specialized models and LLMs, they're using them for different tasks. Usage of LLMs like Gemini is spread widely across scientific fields and task categories, while specialized AI models tend to be relatively more common in health and life sciences and in domain-specific data prediction, generation, and simulation tasks.

Scientists are reporting significant time gains based on AI, with savings of just below seven hours a week, freeing up more time for research. But this may not immediately translate to new discoveries. The research also finds evidence of significant time spent validating AI outputs, an increased backlog of hypotheses yet to be tested, and bottlenecks emerging in areas like physical experimentation and clinical validation. In this way, science is similar to most other occupations: although AI offers significant potential to increase productivity, the large-scale impact on outputs and discoveries may require redesigning scientific processes and workflows to realize the potential of fast-evolving AI capabilities.

What’s ahead?

Many questions about the future of AI and the economy remain. ATLAS is a long-term research project, and we’ll work with partners in academia and elsewhere to identify new areas of research and deliver new insights that contribute to a better understanding of how AI is transforming the economy.

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Watch astronaut Christina Koch and Google’s James Manyika discuss space, technology, and discovery.

2026-09-14T19:00:00+00:00

In the latest episode of our Dialogues on Technology and Society series, NASA astronaut, engineer, and scientist Christina Koch sits down with James Manyika, Google’s Senior Vice President of Research, Labs, Technology & Society.

Christina reflects on her trailblazing career — from spending 328 days aboard the International Space Station and conducting the historic first all-female spacewalk, to journeying around the Moon on NASA’s Artemis II mission.

She and James discuss viewing Earth as an electric blue “lifeboat” from 250,000 miles away, and the vital partnership between astronauts, robotics, and AI. Christina also explores the big question—“Are we alone?”—and shares her advice for future explorers: do what scares you, and support the people around you.

Watch the full dialogue to hear more.

DevFest is back

2026-09-14T16:00:00+00:00

DevFest season is officially back. From October 1 through December 31, 2026, nearly a million developers and builders will gather for the world’s largest community-led technology conference.

Hosted around the world by Google Developer Groups (GDGs), DevFest helps everyone — from seasoned software engineers to emerging solution builders — gain practical, hands-on experience with Google’s AI technologies.

What to expect at DevFest 2026

Under this year’s theme: "Build, Secure, Scale: Developers and Builders in the Agentic Era," the 2026 season prioritizes hands-on experimentation at every event. Attendees will engage directly with tools across Google’s stack — including Gemini, Google AI Studio, Google Antigravity, Google Cloud, Firebase, Android, Flutter, Angular, and Web MCP — through live codelabs, workshops, and agent-athons.

The tracks this year reflect three core realities for modern software development:

It’s never been easier to build. New tools allow more people and teams to prototype and deploy faster than ever.
What you build should be safe and secure. Speed cannot come at the expense of stability. Building in the agentic era requires rigorous focus on secure deployment, data privacy, and responsible AI guardrails.
You can work with production-ready infrastructure. Google provides top-of-class models to help builders and developers scale reliably from day one.

How to connect with local communities, globally

DevFest is built by the community, for the community. While backed by Google, each GDG curates its agenda and tailors each event to serve the specific needs and challenges of its local tech ecosystem. GDGs design their DevFests to foster an inclusive, welcoming environment where participants collaborate and uplevel their skills together.

Get involved

With more than 800 events planned across 115 countries, DevFest offers a space to sharpen your skills, test new architectures, and connect with the community.

You can find Your Local Event by visiting the DevFest Event Directory and keep up with the conversation by using #DevFest across social channels.

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3 ways to prep for your next big race with Search

2026-09-10T16:00:00+00:00

Search can help you get race-day ready with tailored training plans, custom playlists, and more.

Peter Schottenfels

Contributor

As people look for ways to unplug and touch grass, running-related searches are spiking: Searches like “run club,” “how to choose running shoes,” and “how to train for a marathon” have reached all-time highs this year.

Running a race requires grit, strength, and (a surprising amount of) organization. Fortunately, Search’s AI features make it easier than ever to get your race plan together. Here are three ways Search can help you make it across the finish line.

1. Create a training plan that’s specific to you and your neighborhood.

Whether you’re a beginner or a seasoned runner with over a dozen races under your belt, having the right training plan is key to finishing the race. AI Mode in Search can help you map out your strategy and develop a detailed plan. Select the Canvas tool from the plus (+) menu and ask it to build a schedule for you, recommending cross-training and strength-building strategies. You can also discover fresh perspectives from sites and creators across the web. Try asking, “Help me make a sub 4.5hr training plan for the Texas Marathon with different routes I can run around Montrose. I'm currently running 4x a week with my longest run typically being 7-9 miles.”

2. Fuel your run with custom playlists.

Now that you’ve selected your race and have a plan in place, it’s time to hit the road. As many runners are well aware, when it comes to race training — especially for longer distances — mental endurance is as important as physical endurance. Finding ways to cope with the boredom and stay energized during a long run is crucial. If you choose to connect your YouTube Music account with Search, you can ask AI Mode to help create a custom playlist for your run so you can stay motivated and listen to your favorite artists on the go.

3. Discover the right gear to keep moving.

Sometimes going the distance comes down to having the right shoes and running gear, but it can be difficult to narrow down your choices. Search can make race-prep shopping a lot easier, allowing you to search for products that address your constraints — like road shoes for wide feet, lightweight hydration vests under $80, or anti-chafing apparel. Using Google’s Shopping Graph of over 60 billion product listings, Search can show you tailored recommendations, side-by-side comparisons of in-stock options, and even local availability, helping you find the exact gear you need to race with confidence.

Recreating a 70-year love story frame by frame

2026-09-09T16:00:00+00:00

Discover how filmmakers and Google DeepMind used AI to recreate a couple's unrecorded past in the short film "Love, Rendered."

Michael Chang

Google DeepMind engineer

“Love, Rendered,” a new documentary short, explores memory loss and the power of storytelling — and it showcases how technology can help rekindle memories that have begun to fade. The film follows Burt and Ethelle Shatz, a couple married for over 70 years, as they navigate Burt’s cognitive decline. Among his fading memories is one of their most precious: the day they met at a student co-op in Cleveland. Because it wasn’t photographed or filmed, the day existed only in their minds.

When I stepped in as the film’s technical lead, I knew the project would be as emotionally demanding as it was technically complex. Memory loss is personal to me. My grandfather suffered a stroke and memory loss before he passed. The last time I visited him, I was in my thirties. He was convinced I was still in college and was so happy I was graduating. That bittersweet memory never left me.

The experience made me want to see if this technology could help me connect more deeply with my family through the same medium. When this project began, I asked my father for old family photos. I tested our image restoration on photographs from when my parents met and used our video models to animate them. Watching my parents move as twenty-somethings really drove home how these tools could help keep what matters most from slipping away.

“Love, Rendered” was directed by Academy Award–nominated filmmaker Liz Garbus, who produced it alongside Dan Cogan and Darren Aronofsky. It was created in collaboration between Google DeepMind and Primordial Soup, Aronofsky’s creative venture.

Exploring the mystery of memories

Liz and Darren both came to the film curious about the resilience of memory. While directing the documentary “Coma,” Liz saw fMRI scans light up when patients in minimally conscious states heard familiar voices or were shown images of loved ones. Years later, Darren encountered footage of a former ballerina with Alzheimer’s who, upon hearing “Swan Lake,” instinctively danced the choreography from her wheelchair.

These touchstones led the creative team to reminiscence therapy, the clinical practice of using sensory cues like songs, family stories, and old photographs to stimulate memories, spark conversations, and rekindle emotional connections. But what happens when a memory isn’t attached to such cues?

To recreate Burt and Ethelle's unrecorded past, the filmmakers partnered with my team. Sitting alongside us, Ethelle became an active co-creator, correcting the curve of a staircase or the shape of a shoe heel.

Capturing human essence with AI

We worked alongside the team at Primordial Soup, leveraging emerging AI models as an art medium and toolkit, guiding the technology with human direction every step of the way.

Bridging the gaps between the missing details required a two-part technical approach designed to preserve emotional truth.

Image restoration: The team used generative models to restore black-and-white photos of Burt and Ethelle from their youth. The restored photographs helped to ensure that subsequent recreations remained faithful to their subjects.

Pose and performance control: Engineers used our performance capture models to map Burt and Ethelle’s present-day micro-mannerisms — the specific tilt of Burt’s head, a brief hesitation in his speech pattern, the subtle crinkle around his eyes. Mapping those traits onto their younger likenesses brought the recreation to life.

Combining these two mediums allowed us to intertwine Burt and Ethelle’s past and their present. In doing so, we generated a “memory” that they told us felt authentic.

See my colleague Jess Gallegos explain the workflow in more detail.

As Darren noted during production, a tool — like a paintbrush or a hammer — does nothing until it’s guided by human hands. In “Love, Rendered,” machine learning was the tool we used to guide Burt and Ethelle back through time, helping them hold onto a vanishing moment.

You can watch the full film here to experience their love story, frame by frame.

Preserving your family’s story

Whether you’re looking to connect with a grandparent or preserve your family’s core memories, you can restore old photos in the Gemini app. Upload an image of the photo and ask Gemini: “Can you restore and colorize this photo? Preserve the appearance, expression, and pose of the people.”

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Get ready for the game with new football features in Search

2026-09-09T16:00:00+00:00

Never miss a play this season. Our latest upgrades in Search bring a Live Game Feed and deeper stats straight to your screen. Plus, you can now connect your fantasy football account to get tailored insights for your roster.

Denise Ho

Senior Director, Product Management, Search

Football season is officially here in the U.S., and with our latest upgrades, Search is ready to be your ultimate game-day guide. Today, we’re introducing new features designed to help you dive deeper into every moment — including a Live Game Feed, more detailed player and league stats, and the ability to link your fantasy football account for tailored recommendations.

🏈 Never miss a play with the Live Game Feed.

No one wants to miss a game-changing play. Now, with the new Live Game Feed in Search, you can catch up on all the action and follow each game in real-time as it unfolds. To try it out, simply search for an ongoing game and look for the red “Live” icon. You’ll see an overall recap of the game so far, alongside a dynamic timeline featuring play-by-play updates, top social commentary, key video highlights, and AI-powered insights. The Live Game Feed for professional football is now available on mobile in the U.S. in English. Later this month, we’ll also introduce support for collegiate teams and bring the feed to even more people around the world.

🏆 Keep tabs on matchups, standings, and stats.

Whether you’re glued to your TV screen or checking in on the go, new upgrades in Search make it easier to see how the season is shaping up. Now, when you search for a matchup, you’ll see a new carousel that lets you check the scores for other games happening across the league, without needing to search for them individually.

Want to see how your favorite players are stacking up? We’re rolling out new stats this season that will show you the league leaders across categories like passing touchdowns or rushing yards, as well as more detailed player metrics like sacks, fumbles, and yards after catch. And coming soon, Search will also show you who’s favored to win the championship, plus brackets for the playoffs. All of these updates, including the new matchup carousel, will be available globally on mobile.

🎯 Manage your fantasy matchups with confidence.

When you’re setting your fantasy lineup before kickoff, getting tailored recommendations can help you make the right call. Now, you can link your Yahoo Fantasy or Sleeper account with Search and ask for customized insights through AI Mode.

To get started, simply ask AI Mode for help with your fantasy lineup, and you’ll see an option to securely link your fantasy account. Once connected, Search can bring in the context from your live roster and all of your leagues to help with anything from start/sit recommendations to waiver wire targets — no manual data entry or screenshots needed. You can even ask AI Mode for an assessment of your draft picks or a weekly recap on happenings across the league.

We built this feature for fantasy fans of all levels, and we’ll continue improving it throughout the season. Be sure to send us ideas or feedback through AI Mode using the thumbs up or thumbs down button on each response and let us know how we can make it even better. The ability to connect fantasy football apps with Search is now available in the U.S. in English.

Ready for kickoff? Try out the new football features on Search and dive deeper into every game this season.

Proactive cyber defense for governments and enterprises

2026-09-02T15:40:00+00:00

Today, we’re launching our Fairwind Program, a limited access program for governments and trusted partners to use our most advanced cyber defense capabilities.

Four Flynn

Vice President - Security and Privacy

Defenders wanting to use advanced AI have faced a difficult dilemma: adopt enormous frontier models that could be expensive to deploy and difficult to control across enterprise codebases, or turn to smaller open-weight models that might struggle with complex vulnerability remediation and require teams to build their own tooling and infrastructure from scratch. Until now.

Today, we’re launching our Fairwind Program to bring the best of Google’s AI and cyber defense capabilities to a trusted group of Google Cloud customers, government agencies, and cybersecurity partners, to help them proactively solve cyber risks at scale. As a first step, the Fairwind Program will give defenders access to powerful and advanced Gemini models to help them autonomously find and fix vulnerabilities, protecting critical infrastructure, public services, and national security.

Finding and autonomously fixing vulnerabilities

The Fairwind Program offerings bring together our most advanced cyber model, Gemini 3.8 Flash Cyber, with our CodeMender harness, to help defenders find, verify, and fix vulnerabilities at agentic scale. Spotting weaknesses creates awareness and fear; autonomously finding and fixing vulnerabilities delivers security.

CodeMender with Gemini 3.8 Flash Cyber delivers the specialized reasoning to write and validate code fixes, at a fraction of the operating cost of traditional frontier models. Instead of taking weeks to manually fix vulnerabilities, defenders can now generate verified, deployment-ready patches in minutes — within an organization’s secure cloud environment.

Scaling frontline defense

Providing early access to these powerful cyber capabilities gives trusted defenders a vital adaptation window to harden their systems before bad actors have a chance to exploit new capabilities. We’re staging initial access to government and enterprise partners most critical to society’s resilience:

Governments and national cyber authorities: Hardening public-sector networks and citizen services against targeted intrusions.
Critical infrastructure operators: Protecting essential services across healthcare, telecommunications, energy, and financial networks from operational disruption.
Core technology platforms: Securing widespread software foundations to uplift digital security for millions of downstream users at once.

To ensure these powerful AI capabilities are used responsibly, participating organizations agree to strict operational standards, including limiting access to employees within their internal cybersecurity, incident response, or penetration testing teams and deploying protections like multi-factor authentication.

We have more than 650 participating partners globally, including:

What our Fairwind Program partners are saying

Trusted defenders and industry leaders are already putting Gemini 3.8 Flash Cyber into practice:

The Fairwind Program will evolve alongside our partners and users' needs. We will adapt our product offerings and expand partner access, collaborating closely with industry, governments, and open-weight community leaders to strike the right balance between open access and robust security.

While we are prioritizing Gemini 3.8 Flash Cyber access for customers in the Fairwind Program, any Google Cloud customer can proactively secure their code by using CodeMender with publicly available models hosted on Gemini Enterprise Agent Platform, in combination with industry-leading solutions offered through AI Threat Defense.

Making an ecosystem-scale impact on cyber defense

Years of Google’s pioneering zero-trust architecture, advanced AI defenses, and built-in security allow us to protect billions of accounts daily – keeping more people and organizations safe online than anyone else. The Fairwind Program builds on this experience and is part of our broader commitment to global cyber resilience across the entire digital ecosystem, including helping to fortify grassroots cyber defense.

Through Google.org, our latest commitment brings our total cybersecurity funding to more than $100 million globally. We’re pleased to release our 2026 Google.org US Cybersecurity Impact Report, which details $36 million in funding for 35 cyber clinics to date, providing free, hands-on security support to over 1,250 hospitals, public school districts, and municipal utilities in the U.S.

Providing a security advantage

The defender’s edge comes from shrinking the time between detecting a flaw and patching it. Through Google’s Fairwind Program, government and enterprise partners gain autonomous tools to repair systems faster and at scale, keeping them one step ahead of agentic-speed threats.

The latest AI news we announced in August 2026

2026-09-01T20:45:00+00:00

Here’s a recap of some of our biggest AI updates from August, including the launch of Gemini 3.7 Flash, Gemini 3.5 Transcribe, and the all-new Pixel 11 series of devices.

News from Google Team

Here’s a look back at some of our AI announcements from August.

In August, we continued advancing AI responsibly — making it faster, more accessible, and truly practical for everyone, from software developers and students to creatives and scientists. We’re bringing intelligence directly to where people work and live, with powerful new hardware designed for Gemini in the Pixel 11 series, cost-efficient developer models like Gemini 3.7 Flash, the rollout of Gemini in Chrome on Android, and hands-free voice tools across Google Workspace and Gemini Live. As the Gemini app officially crossed 1 billion monthly users, we also expanded our creative and scientific footprint, introducing studio-quality video and music generation alongside open-source AI models that predict weather patterns and tackle climate challenges. Overall, August marked a shift toward AI that isn't just powerful in theory, but useful in everyday reality.

Build better agents at a lower cost with Gemini 3.7 Flash. We released Gemini 3.7 Flash as our most intelligent workhorse model yet for coding and agents. It arrived just three weeks after our launch of 3.6 Flash, delivering substantial improvements across software engineering, knowledge work, and web development workflows — with an introductory price of half the original 3.6 Flash cost per million tokens.

Try the new Pixel 11 series, designed for Gemini Intelligence. At Made by Google 2026, we unveiled Pixel 11, Pixel 11 Pro, Pixel 11 Pro XL, and Pixel 11 Pro Fold. These devices come with major camera upgrades, enhanced durability, and our fastest, most powerful chip, Google Tensor G6, that runs the latest Gemini Nano model. 1 They’re also designed for Gemini Intelligence to deliver time-saving, personal help. 2 See all the announcements from Made by Google 2026.

Start the semester with one year of Gemini, on us. We’re offering one year of a Google AI plan free of charge for eligible college students around the world — plus new and enhanced study tools — so students can make the most of this school year. We’ve also got tools to help teachers and students as they head back to school, including a dedicated student hub, new teacher-led tools, and SAT prep in Gemini.

Level up your learning with Search. To help you start the semester with confidence, we've added new AI-powered learning features in Search — all built to be safe by design. With these updates, Search can help you grasp complex concepts through interactive visuals, generate practice quizzes for exams like the SAT, ACT, GRE, and LSAT, learn step-by-step with Lens, and stay organized with notebooks.

Get more intelligent transcription with Gemini 3.5 Transcribe. Our latest speech-to-text model delivers precise, intelligent real-time transcription for developer workflows like voice agents, live captioning, and post-call analytics. Unlike conventional models that struggle with noise and jargon, Gemini 3.5 Transcribe converts raw audio directly into accurate, polished, context-aware understanding.

Get more done with new productivity features in Gemini Live. Gemini Live is moving beyond conversation to handle complex tasks on your behalf. With new features like Personal Intelligence, Daily Brief, Spark, and hands-free inbox management, you can easily talk through your day and delegate your to-dos without missing a beat.

See how more than 1 billion people are using the Gemini app every month. The Gemini app officially surpassed 1 billion monthly users, making it the fastest-growing product in Google’s history. To mark the milestone, we shared some usage insights, such as: 63% percent of users now talk directly to Gemini, including more “voice only” users — with busy parents 43% more likely to use it for everyday tasks. Gemini now generates 150 million+ images every day, and small businesses are power users, relying on Gemini's all-in-one image, video, and audio creation to craft marketing materials.

Generate videos with more control using Gemini Omni 1.1 Flash. We introduced Gemini Omni 1.1 Flash to bring people even more precision and control for generating videos. The new capabilities deliver studio-quality video production — including scene extension, first-and-last-frame interpolation, crisp 4K upscaling, and faster prototyping. Omni 1.1 Flash is now available in Google Flow, Google AI Studio, the Gemini Enterprise Agent Platform, and the Gemini app.

Explore how Gemma is offline everywhere from outer space to underwater. We released Gemma to help developers build responsible, innovative AI applications anywhere. Over one billion downloads later, Gemma supports environments from phones and edge infrastructure to space. You can explore some of the ways people are using it — from researching interspecies communication to driving medical breakthroughs — and share, discover, and collaborate in our new community repository.

Learn about Operation Blue Skies, a project to reduce aviation climate impact with AI. Our AI-powered forecasts already help flight crews and air traffic controllers adjust routes to avoid forming contrails — all within normal flight operations. Now, we’re partnering with the UK Government and aviation leaders to expand this technology across the North Atlantic, helping airlines reduce aviation’s climate impact on a global scale.

See how WeatherNext 2 demonstrated a massive leap forward in predicting cyclones. In a Nature paper, our researchers showed that WeatherNext 2 predicts cyclone track, intensity, and wind structure with state-of-the-art accuracy — delivering a decade of meteorological progress in one model. Now, we’re open-sourcing WeatherNext 2 to the research community to help build global climate resilience.

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Try Google Pics: Easy image creation and editing in Google Workspace

2026-09-01T16:00:00+00:00

Generate, refine, and co-create images with unparalleled precision. Plus, upcoming Workspace integrations will let you create and edit directly within Google Slides, Docs, and Drive.

Meg Whittenberger

Google Pics Product Manager

Google Pics — our image creation and editing tool from Google Workspace — is rolling out over the coming weeks to all Google AI Pro and Ultra subscribers and most Workspace business customers.

Built on our Nano Banana image generation and editing model, Pics gives you the control you need to create whatever you're imagining, whether you're designing a poster, producing social media posts, or editing digital illustrations. Google Pics will be both a standalone product and integrated into Workspace apps, starting with Slides, Docs, and Drive, so you’ll be able to edit images where you’re already working.

Precise control meets ease of use

Google Pics includes a suite of fine-tuned editing capabilities that let you generate images and make precise edits rather than starting from scratch. Here are some of the features you can look forward to:

Object segmentation: Pics lets you easily isolate an object and transform it without altering the rest of your image. You can input text comments on specific areas to request targeted changes and execute multiple edits at once.
In-image text editing and translation: Modify or translate text directly inside an image without disrupting the design or changing the font.
Collaborate with others: Share Pics creations with your friends and teammates, then collaborate to edit the same image.
Multiple generations: Pics generates several options from a single prompt, so you can choose your favorite from a variety of iterations.

Seamless integrations with Google Workspace

Millions of users interact with billions of images across Workspace products every month. To make this experience even more seamless, we’re bringing Google Pics directly into the tools you already use. You shouldn’t have to jump between applications to create and share visuals. Now, you can harness powerful AI image generation and editing right where you are — no copying, pasting, or switching tabs required.

This integration starts today with Docs and Slides, and will roll out to Drive in the coming weeks.

We can’t wait to see what you create. Try it at pics.new.

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AI

Southeast Asia’s digital economy to hit $368 billion

1. AI is sustaining growth in every sector.

2. Consumer trust will help unlock the era of agentic commerce.

3. Four major areas must adapt to enable AI adoption.

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Gemini 4 Argon: Built to solve your hardest problems

Solving complex engineering tasks

Transforming critical business and professional workflows

Accelerating real-world impact with researchers and domain experts

Bringing state-of-the-art cyber capabilities to more trusted defenders

Unlocking new scientific breakthroughs

Speeding up robotics development

Developing Argon responsibly and safely

Get started today

Introducing Playground: Create and play custom games

Create your custom game

Play, compete, and share across devices

Stay tuned for Unity Spark

Get started today

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The latest AI news we announced in September 2026

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Watch the winning trailer from the Future Vision XPRIZE, The Gifted.

Google Beam expands with new regions, partners, and customers

Expanding our global footprint

Proving our real-world impact

Creating the first-ever Beam extended network

Get the latest news from Google in your inbox

New experts join Google’s AI & Economy team

Expanding our scientific expertise and engagement

Shaping future research and collective impact

Get the latest news from Google in your inbox

Co-creating the future of fashion with Google

Virtually styling a collection

Grounding runway design in a real budget

Moving fashion AI out of pilot mode

Get the latest news from Google in your inbox

Making global data easier to explore

Connected data for complex global efforts

Natural language features for easier exploring

Putting AI to work as agentic research assistants

More data and new features to come

Get the latest news from Google in your inbox

Building AI to accelerate science and improve lives

Bold and responsible, together

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AI for Societal Impact

AI for everyone in every language

Going from text to true understanding

Putting communities at the heart of language data

Overcoming real-world constraints

Designing for accessibility

Getting local pronunciation right

Building language tools for everyone

New insights from Google’s AI & Economy ATLAS

Which professions are using AI most, and where?

How are scientists using AI?

What’s ahead?

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Watch astronaut Christina Koch and Google’s James Manyika discuss space, technology, and discovery.

DevFest is back

What to expect at DevFest 2026

How to connect with local communities, globally

Get involved

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3 ways to prep for your next big race with Search

1. Create a training plan that’s specific to you and your neighborhood.

2. Fuel your run with custom playlists.

3. Discover the right gear to keep moving.

Related stories

Recreating a 70-year love story frame by frame

Exploring the mystery of memories

Capturing human essence with AI

Preserving your family’s story

Get the latest news from Google in your inbox

Get ready for the game with new football features in Search

🏈 Never miss a play with the Live Game Feed.

🏆 Keep tabs on matchups, standings, and stats.

🎯 Manage your fantasy matchups with confidence.