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Google Marketing Live 2026: The New Era of Marketing with Artificial Intelligence

The biggest Google Marketing Live in history packed into a single day the most complete vision for the future of marketing: a platform where artificial intelligence stops being a feature and becomes the very infrastructure on which campaigns, creatives, measurement, and sales operate.

The Google Marketing Live 2026 was held at the Bay View campus in Mountain View, California, with a live stream on YouTube. It was the largest GML in the company's history — not just in audience, but in announcement density. In a single day, Google presented its most complete vision for the future of marketing: a platform where artificial intelligence stops being a feature and becomes the very infrastructure on which campaigns, creatives, measurement, and sales operate. What follows is a thematic synthesis of everything presented, discussed, and demonstrated throughout the event.

Watch the full event on YouTube

A Decade in One Year: The Context of Change

To understand what Google announced in 2026, you first need to grasp how fast the landscape has shifted. Just twelve months ago, generating images or videos with consistent quality was still an unpredictable task. Today, generative media models like Veo, Imagen, and Gemini Omni produce cinematic videos with realistic physics, coherent narrative, and visual consistency from scene to scene — something that would have been technically impossible just a few months earlier.

The opening keynote was itself a demonstration of this: the event's intro video was generated entirely with Gemini Omni Flash, the latest model in the Gemini family, launched the day before at Google I/O. The difference from the previous year's video was striking. The leap wasn't incremental — it was transformative.

This acceleration has a technical explanation. Gemini 3.5 Flash, the engine behind this year's innovations, is a frontier model with one defining characteristic: speed. Compared to other models at a similar level, it generates four times more tokens per second. When combined with Google Antigravity — the internal agent-oriented development platform — the result is a development velocity that compressed launch cycles from months to weeks. Products that previously took a quarter to implement now ship in days.

The economic concept chosen to frame this moment was the Jevons Paradox: when technology makes a resource more efficient, consumption of that resource doesn't fall — it grows exponentially. The same principle applies to digital marketing. As AI makes it easier to research, create, target, and measure, marketers don't do less — they do much more. Searches grow. Creatives multiply. Optimizations happen in real time. Markets expand.

The central premise of GML 2026 is that the Gemini advantage isn't just technological — it's a business advantage. For every dollar invested in Google Search at global scale, the average incremental return is six dollars. And the most recent MMM (Media Mix Modeling) study conducted with TransUnion showed that the combined ROAS of Google and YouTube rose 40% year over year, reaching 21% above any other media platform.

The Reinvention of Google Search

Google Search is undergoing its biggest transformation in its 27-year history. To understand the scale of this change, a few numbers tell the story: AI Overviews, launched two years ago, already has more than 2.5 billion monthly active users. AI Mode, introduced just one year ago as a conversational experience within Search, has already surpassed 1 billion monthly users — and searches in this mode have doubled every quarter since launch.

The change isn't just in volume. It's in nature. People have started bringing fundamentally different questions to Google. Searches with terms like "ideas for," "where should I," and "which should I buy" are growing 30% faster than overall AI Mode growth. Brainstorming searches — those where the user is at the beginning of a journey, exploring possibilities rather than looking for a single objective answer — are in full expansion.

A typical AI Mode search is on average three times the length of a traditional search. Users now describe context, constraints, preferences, and goals in completely natural language. A concrete example: instead of typing "treadmill," a user might search "I'm looking for a treadmill to use in my home office, I enjoy walking, I need it to be quiet and reliable — what are the best options for me?" The system doesn't just understand the question — it delivers a personalized recommendation with a comparison of options and links for deeper research, all in a single response. According to Google's own data, 75% of people who use AI Overviews and AI Mode report making faster decisions with more confidence.

The most visible interface evolution is the reformulation of the search box — the biggest update in 25 years. The text field now expands to accommodate long questions, with integrated access to all modalities: text, image, and video. AI Overviews and AI Mode have been merged into a unified experience, allowing users to move frictionlessly from an initial question to in-depth answers through follow-up questions in a natural conversational flow.

Personalization has also advanced. With the personal intelligence feature, users can voluntarily connect their Gmail, Google Photos, and — coming soon — Google Calendar accounts to AI Mode. The result is a search that knows the user's life context — like what's available during a layover, or the time they usually work out.

The near-term horizon points to personalized information agents working continuously in the background: monitoring apartments for sale within the criteria the user specified, tracking product launches from favorite athletes across blogs, shopping sites, and the Shopping Graph, and notifying the user at the right moment to act.

For marketing professionals, this transformation has immediate practical implications. First: SEO isn't dead — it's become more demanding. Generative search systems continue using organic ranking principles, but especially value content with genuine expertise, first-person experiences, unique perspectives, and original data. Generic content doesn't compete. Second: the keyword model as the foundation of media strategy is structurally obsolete. Long, conversational searches simply cannot be captured manually. The only way to appear in this new landscape at scale is to trust AI to do the matching — and that requires tools like AI Max for Search and Performance Max.

New Ad Formats: The Best Ad Is an Answer

If search behavior has changed radically, ads needed to follow. Google's stated premise is that in an environment where users can ask anything, the best ad is no longer a graphic or a sponsored link — it's an answer. A relevant, contextualized, useful, and trustworthy answer.

Google introduced five new ad formats for the AI Mode era, all integrated into the natural flow of the user's conversation with the search system.

The first format is the contextual ad in AI Mode. When a user searches "I want my house to smell like a high-end spa or like a forest after rain," the system delivers tips on scenting environments, compares olfactory profiles, and within that response presents an ad for a smart diffuser from the brand Pura. The ad doesn't interrupt the experience — it completes it. Instead of an image with a generic CTA, the user receives a detailed explanation of why that product solves exactly the problem described: the diffuser works on an automatic schedule and has a wide fragrance library. The relevance is so high that the user considers buying from a brand they had no prior familiarity with.

The second format is Direct Offers. Brought inside AI Mode as an integrated part of the conversation, they allow advertisers to present exclusive offers — discounts, local coupons, bundles — at the exact moment the user demonstrates purchase intent. Gemini dynamically creates the ideal offer from the promotional rules defined by the advertiser. If a user is researching how to prepare a guest room for visiting family, the system can present a bed and sheet bundle from Wayfair with a discount applicable to the combined purchase. The format is available not just for retail — hotels will also be able to use it.

The third format is Shopping Ads with Gemini. Traditional product listings have gained a layer of intelligence: texts generated by Gemini that explain, in natural human language, why a given product meets the specific criteria of the user's search. Instead of just showing price and image, the ad articulates the characteristics relevant to that specific query — like different brewing settings, foam capacity, and size for a compact coffee machine.

The fourth format is the Business Agent for Leads, an agentic ad designed for qualified lead capture. When searching for business and technology universities on the West Coast, the user sees an ad with the option to ask a question directly within the ad. The response is generated based on the advertiser's website content — such as how AI is used in the classrooms of a specific business school — and presents the option to speak with the admissions department, with a form pre-filled with the user's data. The lead arrives far more qualified to the advertiser. The format is being tested in education, automotive, and real estate.

The fifth format connects recommended products within AI Mode directly to the retailers that have them in stock, closing the loop from discovery to immediate availability.

All these formats share one characteristic: they are exclusive to AI Max for Search and Performance Max campaigns. They cannot be accessed through standard search or traditional shopping campaigns, because they fundamentally depend on automated targeting capability and dynamic text generation — capabilities that only the AI models embedded in these campaign types can provide.

To address advertisers' legitimate concerns about brand control and voice, Google launched the AI Brief. It works like an agency briefing: the advertiser describes their brand in conversational language, the audiences they want to reach, the tone of communication, and the limits that cannot be crossed. The system interprets these guidelines and generates a set of rules that guides all adaptive formats. The advertiser receives a preview before launch and can refine until the result faithfully reflects their identity.

The return is already visible: advertisers adopting AI Max or PMax average 15% more conversions at equivalent ROAS. Lufthansa Group saw a 24% increase in ROAS with AI Max. IKEA recorded 65% more non-branded clicks and 28% incremental ROAS lift.

Agentic Commerce: The Infrastructure of the Future

While the new ad formats represent the evolution of advertising, Agentic Commerce represents something more structural: the reinvention of the infrastructure through which transactions happen on the internet.

The foundation of this system has four layers. The first is the Shopping Graph — the world's largest commerce dataset, with more than 60 billion listings. It's the data foundation that allows Google to understand purchase intent with a depth no other platform can replicate. The second layer is the accumulated trust in YouTube and Search — platforms people use to discover, research, and decide. The third is the payment infrastructure of Google Pay and Wallet, enabling fast and secure transactions. And the fourth is the global scalability of Google Cloud.

On this foundation, Google launched the Universal Commerce Protocol (UCP) — an industry standard developed in collaboration with a founding group of partners, joined by Amazon, Meta, Microsoft, Salesforce, and Stripe. The UCP is a common language that allows agents and systems from different companies to communicate without the need for individual custom integrations. In practical terms: a retailer that implements UCP once gets their inventory data, stock status, loyalty programs, and checkout options flowing in real time to any agent or surface within the Google ecosystem — and potentially beyond.

UCP expansion is already underway: the protocol reaches beyond the United States to Canada, Australia, and the UK in the coming months. And it extends beyond retail, with partnerships in food and travel sectors promising to transform experiences like delivery orders via Ask Maps or hotel reservations within AI Mode.

The most concrete manifestation of UCP for consumers is the Universal Cart. Launched the day before GML at Google I/O, the Universal Cart is a smart shopping hub that works across all Google products and multiple retailers. Users can add products to the cart while browsing Search, chatting with Gemini, watching YouTube, or reading emails in Gmail. Once an item is added, the cart starts working: it monitors price variations, alerts on availability, and when the user is ready, enables the purchase directly on Google or forwards the complete cart to the retailer's site. The US launch for Search and the Gemini app happens in summer 2026, with YouTube and Gmail to follow.

The other concrete innovation is native checkout in ads for retailers connected to UCP. When a user receives a Direct Offer in AI Mode, they can complete the purchase without leaving the interface: click "buy," review the order — discount already applied — tap "pay with Google Pay" — and done. No redirects. No forms to fill out. The same flow has arrived on YouTube: video ads can now include product listings and a "Buy now" button that leads directly to a branded checkout screen within YouTube itself, with payment and shipping details pre-filled.

The result of this architecture is a dramatic compression of the path between discovery and decision. What previously required multiple visits, several open tabs, forms, and redirects can now happen in seconds, within a single conversation.

YouTube: Where Brand and Performance Meet

For a long time, YouTube was positioned as a branding platform — ideal for reach and brand recognition, but not necessarily where conversions happened. That perception is wrong, and the 2026 data makes it hard to dispute.

YouTube reaches more than 90% of American adults. It's the number one platform in streaming watch time for the third consecutive year, surpassing Netflix, Amazon Prime Video, and the entire Disney catalog. More than 2 billion Shorts are watched on TVs per month — on the biggest screen in the house, the shortest format of all. The platform is home to the creators people actually trust: when a creator makes a genuine product recommendation, 13 times more people search for the brand and five times more people buy.

But the performance numbers are what really changes the conversation with the CFO. YouTube's long-term ROAS is more than double the ROAS of linear TV, paid social media, and streaming platforms combined. Specifically compared to social platforms, YouTube's effectiveness is 86% higher. And when Google and YouTube work together in the media mix, they are present in 82% of all product or brand discovery journeys — and in 89% of purchase journeys, consumers use Google or YouTube before the largest social platform, or skip the social platform entirely.

The central mechanism that transforms YouTube into a performance engine is Demand Gen. Unlike purely awareness campaigns, Demand Gen uses the strongest real intent signals available — search behavior, Maps history, YouTube interactions — to identify consumers at the moment they're developing interest, before they've even articulated a search. The latest Gemini models have turbocharged this targeting capability, resulting in an average of 30% more conversions compared to previous configurations.

The comparison with social platforms is structural: a social feed captures passive behavior and superficial interests. Search, YouTube, and Maps history is an authentic representation of who the user really is — what they research, watch, buy, plan. This signal quality difference translates directly into ROAS.

Advertisers adding Demand Gen to the mix — rather than running Search-only or PMax-only — average 10% more ROAS and 12% more actual sales. Concrete cases reinforce this: GM achieved 3x ROI on YouTube using Demand Gen to follow consumers throughout the entire car-buying journey — from initial interest to vehicle pickup. Allianz used the format to reach travelers still in the planning phase, before travel insurance was even on their radar, and achieved 4% incremental revenue lift. Petco directed Demand Gen to find real pet lovers — not discount hunters — and outperformed social benchmarks, especially during Cyber Week.

Beyond consolidated results, GML 2026 brought new Demand Gen launches:

  • Demand Gen ads are coming to Google Maps, reaching people already in purchase mode on an active decision mission.
  • Product Feeds — which already increase conversions by 33% — expand to tablets for the first time and arrive in mobile pause ads: when the user pauses the video, products remain available for exploration.
  • Creator integration got simpler: when setting up Demand Gen campaigns, the system now automatically suggests partnerships with creators who have already mentioned the brand, making it easier to add that content directly to the campaign.
  • YouTube Affiliate Program creators can have their affiliate videos boosted directly within Demand Gen.

The Coach case illustrates the synthesis of brand and performance: the brand needed to win Gen Z without compromising its luxury identity. It didn't just optimize for clicks — it invested in authenticity via YouTube, working with creator Haley Pham (4 million subscribers), scaled the assets with Demand Gen, and achieved: 60% increase in global top-of-mind, a sixfold increase in purchase consideration, and sustained growth in Gen Z consumer acquisition — all in a single quarter.

Also announced was Ask YouTube, a new conversational search experience within the platform. Just as AI Mode transformed Search, Ask YouTube lets users ask complex questions and receive curated responses with the most relevant videos, with follow-up questions supported. The same deep-search logic that expanded Search will now come to YouTube, increasing the time people spend discovering content on the platform.

Creativity at Scale: Asset Studio

Creative is the single biggest driver of ad effectiveness — responsible for nearly half of all incremental sales generated by advertising. And at the same time, it's historically the main operational bottleneck for most marketing teams.

Asset Studio was built to resolve that contradiction. It's the central creative hub of Google Ads — a single place to organize, create, test, and optimize all assets. And in 2026 it received integration with the most advanced models available: Gemini for text and strategy, Veo for video generation, Imagen for image creation, and — starting summer 2026 — Gemini Omni, the model that combines reasoning with the company's best generative media models.

The workflow has been dramatically simplified. A marketing professional can point to their website URL and automatically receive a set of image and video assets aligned with the brand's visual identity — generated from existing content. Integration with external tools like YouTube Studio, Product Studio, Adobe, Canva, and digital asset management systems means that creative already existing on other platforms simply shows up in the Asset Studio library, available for adaptation in a few clicks.

For those who need video — the format most frequently absent from small and medium business portfolios — the process now starts with a natural language description of the idea. The system generates a visual storyboard that can be adjusted scene by scene before rendering. The result is a finished video, optimized for YouTube's formats and surfaces, available in multiple versions for testing.

The most significant differentiator is the integrated testing functionality. Instead of accumulating historical performance data and trying to infer what worked, the advertiser can now create a direct test with a single click: select the asset to test, the system automatically runs it against current top performers and delivers the net incremental result. No need to duplicate campaigns, manually manage variations, or wait for long cycles. The logic is that of a controlled experiment — the gold standard for understanding causality in creative.

The platform also supports sharing previews with internal stakeholders — legal, marketing team, agency clients — before assets go live, with an integrated approval flow.

For lean teams, the impact is unlocking: the level of creative production that previously required a dedicated production team is now within reach of a single person with brand vision and clear objectives.

The Foundation of Modern Measurement

None of the innovations presented at GML 2026 produce sustainable results without a solid measurement foundation. And the reality at most companies is that this foundation doesn't exist — or exists in a fragmented and outdated form.

The problem starts with data. Most companies have their information spread across five or six tools that don't communicate. Additionally, ad blockers and browser restrictions silently eliminate some signals before they reach analytics systems. The result: decisions based on incomplete data, without the marketing team knowing what's missing.

The solution starts with consolidation. Google's Data Manager offers a central connection point for data sources — CRM, offline data, e-commerce systems — that works with a single connector for the entire Google product network. Data is shared once and works automatically across all products on the platform. Complementing this, the Google Tag Gateway protects signals that would be eliminated by blockers, ensuring data flows intact to optimization systems. The impact is direct: advertisers building their "data strength" with first-party data average 11% incremental ROAS increase. Doc Martens, upon integrating first-party data with Performance Max, saw an immediate 16% revenue jump.

The second measurement problem is causality. A campaign result is not evidence that the campaign caused that result. The real purchase journey is non-linear: the consumer sees a video, searches for the brand days later, receives retargeting, clicks and buys. Every platform along the way can claim credit for the conversion. The challenge is distinguishing what actually drove the decision from what was merely present in the process.

For this, Google launched two new causality signals:

Attributed Branded Searches (ABS) track whether, after exposure to an ad, the user performed a brand or product search. This subsequent search is a powerful indicator of generated intent — a short-term signal that the ad planted genuine interest.

Qualified Future Conversions (QFC) go further: they use signals like subsequent branded searches, video views, and site visits to mathematically project the value a campaign will generate over the next six months — before those conversions happen. The Crew Clothing case illustrates the concrete value of this metric: the British retailer ran a prospecting campaign on YouTube that looked flat in the first 30 days. Looking through QFCs, the real value was revealed — a 70% lift in long-term conversions. Instead of cutting the campaign, they scaled it.

Both metrics are permanently available in the interface, without needing to run experiments. They're reliable proxies for continuous decisions.

The third element is the unified view. The central tool for this is Meridian — Google's next-generation open-source MMM (Media Mix Model). Meridian integrates data from multiple sources and channels to generate a holistic understanding of where the marketing budget is producing the most results. In 2026, Meridian's intelligence was incorporated directly into Google Analytics 360, creating a unified measurement command center.

The most significant news on this front is that Google Analytics 360 now allows cross-channel analysis including TikTok, Pinterest, Snap, and other social platforms — all in one place. In addition, the scenario planning feature allows simulating different budget allocations across channels and projecting the impact before moving spend. And the interface now supports natural language: the professional can simply ask "how should I allocate my budget next quarter?" and receive a response based on the account's real data.

Marketing Agents: The End of Manual Execution

The technical execution of campaigns — configuring targeting, adjusting bids, structuring ad groups, generating reports — has always been a core competency of the digital marketing professional. But this competency is becoming a commodity. When AI can execute these tasks with more speed, consistency, and precision than any human, execution stops being a competitive differentiator.

The differentiator becomes strategy: knowing what you want, for whom, why, and with what success metric. The ability to ask the right questions. And that's exactly what Ask Advisor was designed to enable.

Ask Advisor is the evolution of the AI agents Google began launching in 2025. Instead of multiple separate agents across each product, there is now a single intelligent interlocutor that operates continuously and connectedly across Google Ads, Merchant Center, Google Analytics, and Google Marketing Platform. It has context memory: it remembers the objectives the user defined in a previous conversation and loads them automatically into the next interaction, without needing to be re-prompted.

In practice, Ask Advisor can answer questions like "how can I optimize my campaign for new customer acquisition?" or "show me abandoned carts segmented by new and existing customers, by region" — and delivers responses based on real account data, not generic information. It can proactively identify improvement opportunities, suggest strategy adjustments, generate creative asset drafts, write ad copy, and when the user approves, launch campaigns.

The impact differs for each professional profile:

For large companies, Ask Advisor removes the bottleneck on strategic idea execution. Expansion into new markets, reaching new segments, deepening the customer experience — projects previously bottlenecked by lack of operational capacity now have a 24-hour execution partner.

For small businesses, it's the equalizer. The professional without a team and without budget for external consulting now has access to a level of specialized guidance previously reserved for large advertisers. The speed and agility AI provides compensates for the scale disadvantage.

For agencies, Ask Advisor changes the profitability equation. Teams that previously managed 10 clients satisfactorily can now serve 50, because the volume of technical execution has been absorbed by the agents. The freed-up space can be used for higher-value services: strategic consulting, creativity, business analysis.

Success Stories: Results the CFO Wants to See

GML 2026 was rich in concrete results from advertisers who implemented the strategies and tools discussed. Organized by theme, they form a useful panorama of what's possible:

Search and AI Max:

  • Lufthansa Group: +24% in ROAS with AI Max for Search.
  • IKEA: +65% in non-branded clicks, +28% in incremental ROAS with AI Max.
  • Advertisers adopting AI Max or PMax average 15% more conversions at equivalent ROAS.

YouTube and Demand Gen:

  • GM: 3x ROI on YouTube using Demand Gen across the entire vehicle purchase journey.
  • Allianz: +4% incremental revenue lift reaching travelers in the planning phase.
  • Petco: Outperformed social benchmarks during Cyber Week with Demand Gen — more ROAS, more clicks, and lift in spend per purchase.
  • Coach: +60% in global top-of-mind, sixfold increase in consideration, sustained Gen Z consumer acquisition growth — all in one quarter, using YouTube and creators with Demand Gen.
  • Gap (Cat's Eye): Double-digit ROAS increase year over year; branded searches for Gap surpassed even searches for the Cat's Eye campaign; consumers exposed to the YouTube video had a higher average cart value.

Data and Measurement:

  • Doc Martens: +16% in revenue upon integrating first-party data with Performance Max.
  • Advertisers with "data strength" via first-party data: +11% in incremental ROAS on average.
  • Crew Clothing: 70% uplift in long-term conversions visible via Qualified Future Conversions — a campaign that would have been cut was scaled instead.

Holistic AI:

  • Royal Bank of Canada (AI Excellence Award 2026 winner): Integration of AI Max for Search, Bid Exploration, Performance Max, and Demand Gen resulted in +341% in reach and +76% in credit card approvals.
  • Wpromote (agency, AI Excellence Award 2026 winner): Using PMax with CRM signals for Learning Care Group, achieved +331% in enrollments with 49% more cost-per-marketing efficiency.

The Modern Marketer's Roadmap: What to Do Now

The breadth of innovations presented can generate paralysis. To avoid it, Google structured a set of concrete actions — the "ROI Essentials" — that any professional can implement in the next two weeks to start capturing the value of available tools.

Search: Adopting AI Max for Search or Performance Max is the prerequisite for appearing in the new ad formats in AI Mode. It's not possible to do this manually. The transition to automated targeting doesn't mean losing control — it means delegating matching and text adaptation to AI while maintaining control via AI Brief over brand voice, audiences, and creative guidelines.

Commerce: Investing in the quality of Product Feeds in Merchant Center is the most important step to being discovered in any agentic commerce experience. Rich, accurate feeds are the fuel that powers the Shopping Graph, the Universal Cart, AI Mode recommendations, and shoppable ads on YouTube.

YouTube: Adding Demand Gen to the campaign mix is the most direct path to increasing ROAS. Using creators relevant to the brand within Demand Gen campaigns amplifies results. And adopting Engaged View Conversions metrics — rather than measuring YouTube by the same click model used on other platforms — is essential for seeing the real value being generated.

Creative: Experiment with Asset Studio. Create variations. Run A/B tests on assets. Creative is the biggest performance driver in advertising, and the tools now make it possible to systematically test what works, even without a dedicated production team.

Measurement: Update the Google Tag Gateway to protect signals against ad blockers. Connect CRM and offline data via Data Manager. Implement Attributed Branded Searches and Qualified Future Conversions metrics for a forward-looking view of campaign value. And consider Google Analytics 360 as the unified command center for cross-channel analysis.

Agents: Start using Ask Advisor. Formulate business objectives in natural language. Let the system suggest strategies based on the account's real data. The biggest barrier to adoption is usually hesitation — the feeling that you must fully understand the tool before using it. Google's recommendation is the opposite: ask first, learn in the process.

The Compounding Advantage

The central thesis of Google Marketing Live 2026 can be summarized in one sentence: the Gemini advantage is, in practice, your business advantage.

This isn't a marketing claim. It's a structural description of how the ecosystem works: more advanced models improve Demand Gen targeting, which improves intent signals, which feed better creatives generated by Asset Studio, which perform in more relevant formats in AI Mode, which convert with less friction via UCP and Universal Cart, and whose real effectiveness is captured by Meridian's holistic measurement — which in turn feeds back into the entire strategy.

Each component amplifies the others. And each improvement in AI models — which happens continuously and automatically, without the advertiser needing to do anything — improves the results of all components simultaneously.

The Jevons Paradox applies here in its most powerful form: as high-performance marketing becomes easier, the best professionals do more. They reach more markets. Create more assets. Test more hypotheses. Expand into more segments. Efficiency doesn't compress ambition — it liberates it.

What GML 2026 leaves as its legacy isn't a list of features. It's a paradigm shift: the marketing professional who previously needed to master technical execution to stay relevant now needs to master strategy — because execution is progressively in the hands of the artificial intelligence they direct.

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