A major strategic divide is emerging over the future of agentic commerce. Shopify is opening its merchant ecosystem to Meta’s new AI shopping agent, Muse, while Amazon has taken the opposite approach and blocked the same agent from shopping on Amazon.com. The contrast reveals two very different visions of how AI should interact with online retail. Shopify appears willing to let third-party agents become a new commerce channel, while Amazon is defending tighter control over its marketplace, customer experience and commercial infrastructure.

On one side, Shopify is working with Meta so Muse can help users discover products and complete purchases across Shopify-powered stores using Shop Pay. On the other, Amazon says Meta did not obtain permission for Muse to access its marketplace and has blocked the agent from shopping on behalf of customers. The dispute raises a wider question for the entire e-commerce industry: should AI agents be welcomed as a new layer of distribution and checkout, or treated as external intermediaries that could weaken retailer control over customers, data and monetization?

Shopify embraces Meta’s Muse as an AI commerce channel

Shopify has chosen the more open approach. The company is partnering with Meta to integrate Shop Pay agentic checkout into Muse, allowing the AI assistant to facilitate purchases from merchants operating on Shopify. Shopify had already started preparing for this shift earlier in September by adding Meta as an AI channel inside Shopify Admin. Merchants can manage whether product catalogs are shared with Meta, control direct checkout access and monitor performance from within Shopify’s agentic-commerce settings.

This is significant because Shopify is not merely allowing Muse to browse merchant websites. It is connecting Meta to structured commerce infrastructure, giving the AI cleaner access to product data, availability and checkout functionality. That reduces the need for the agent to interpret conventional websites designed for humans. Instead, Shopify can act as the commerce layer beneath the AI interface, providing the product and transaction infrastructure while Meta controls the consumer-facing experience.

Shop Pay becomes the transaction layer

The partnership also highlights the strategic value of Shop Pay. Muse users will be able to complete purchases through Shopify’s accelerated checkout infrastructure across participating stores. That means the customer may begin and remain inside Meta’s AI environment while the transaction itself still flows through Shopify’s commerce stack. For Shopify, the loss of the traditional storefront as the primary interface does not necessarily mean losing the economic value of the transaction.

This is a critical distinction in the emerging agentic-commerce model. Shopify does not primarily depend on consumers visiting Shopify.com, because its business is built around providing infrastructure to merchants wherever commerce happens. If discovery increasingly moves into AI assistants, Shopify can still capture value through product feeds, checkout, payments and merchant operations. Its strategy therefore appears less focused on protecting the storefront and more focused on becoming indispensable infrastructure underneath AI-driven commerce.

Amazon takes the opposite approach

Amazon has chosen a far more restrictive position. The company blocked Muse from shopping on Amazon.com after Meta reportedly declined Amazon’s request to exclude its marketplace from the agent’s shopping capabilities. Users attempting to shop on Amazon through Muse began seeing a message stating that continued access by an unauthorized AI agent violated Amazon’s Conditions of Use. Amazon says the issue centers on authorization, transparency and how third-party agents interact with its platform.

According to Amazon, Meta did not provide advance notice that Muse would shop on Amazon.com, the agent does not adequately identify itself while browsing, and the company has concerns around customer credentials and account access. Amazon argues that third-party applications making purchases on behalf of users should operate transparently and respect whether a service provider wants to participate. The company’s position is that consumer permission alone is not enough; the merchant platform should also be able to decide whether an external agent can access and transact through its systems.

Meta disputes the credential-risk concern

Meta has said Muse does not directly see users’ passwords or payment credentials. According to the company, credentials are stored securely and can be used by the AI without being exposed to the model itself. Muse operates inside a virtual machine and can use a browser to interact with services when a public API is not available. Meta also says the agent seeks confirmation before taking sensitive actions such as sending messages or completing purchases.

This difference in interpretation is central to the dispute. Meta views the consumer as authorizing the agent to act on their behalf, while Amazon argues that the platform being accessed also needs to consent. That tension could become one of the most important legal and commercial questions in agentic commerce. It effectively asks whether an AI agent should be treated like a user-controlled browser, an automated bot, a commercial intermediary, or something entirely new.

Amazon wants AI agents to identify themselves

Amazon’s position is also closely linked to transparency and identity. The company argues that an external AI agent entering customer accounts, browsing product pages and initiating transactions should clearly identify itself to the retailer. This reflects a broader issue emerging across e-commerce and payments: merchants increasingly want to know which agent is acting, who authorized it, what permissions it has, whether it is operating within those limits and who is responsible if something goes wrong.

These are no longer theoretical questions. Payment networks including Mastercard and Visa are already developing identification and authorization layers specifically for AI agents. Amazon is effectively applying the same logic at the marketplace level. If agentic commerce is to scale, retailers may demand a standardized way to recognize trusted agents, verify user intent and establish accountability before allowing automated systems to interact deeply with their commerce infrastructure.

Shopify sees AI agents as another distribution channel

Shopify’s strategy appears fundamentally different. Rather than requiring consumers to begin every transaction within a Shopify-controlled environment, the company is treating AI assistants as another sales and distribution channel. This resembles the way Shopify already connects merchants with Google, social networks, marketplaces, mobile commerce and point-of-sale systems. Agentic platforms now become another route through which merchants can reach potential customers.

That approach fits Shopify’s architecture particularly well. Its value lies in powering merchants across multiple channels rather than owning a single consumer destination. If an AI platform becomes the place where shoppers discover and compare products, Shopify can still remain the system handling structured catalog data, merchant operations, payments and checkout. In that model, losing control of the interface does not necessarily mean losing control of the transaction infrastructure.

Amazon has more to lose from external agents

Amazon’s incentives are very different because its marketplace is not simply a transaction engine. The company controls product discovery, search, advertising, reviews, recommendations, checkout, fulfillment and customer service inside one highly integrated environment. External AI agents could bypass several of those layers by searching, comparing and selecting products on behalf of users without presenting Amazon’s traditional marketplace interface.

This matters because Amazon has built a huge advertising business around product discovery. Sponsored placements, search positioning and marketplace visibility are all tied to shoppers navigating Amazon directly. If an AI agent evaluates products based mainly on price, reviews, availability and delivery terms, some of the commercial value of those interfaces could be reduced. Amazon therefore has more strategic incentive than Shopify to preserve control over how shoppers discover and select products.

The fight is about who controls product discovery

This is why the Shopify-Amazon split matters beyond Muse itself. Agentic commerce is changing where product discovery happens. Today, shoppers typically search, browse, compare products, open listings, add items to a cart and complete checkout. An AI agent could compress that process into a single instruction such as: “Find me the best stroller under €500, with strong reviews and delivery before Friday.”

The agent could then search across multiple merchants, evaluate the available options and complete the transaction according to the user’s preferences. If that behavior becomes common, the center of gravity in e-commerce may move away from individual marketplace interfaces and toward AI platforms. The strategic question then becomes less about who owns the product listing and more about who owns the interface between shopper and merchant.

Shopify is betting on infrastructure, Amazon on ecosystem control

The two companies are effectively making different bets on the next phase of e-commerce. Shopify is betting that infrastructure remains valuable even if another company controls the consumer interface. Its role can still include catalog data, merchant operations, payments, checkout and order management. Amazon appears more determined to preserve control over both the infrastructure and the customer-facing environment, including search, advertising, recommendations and transaction flow.

Neither position is necessarily permanent. Amazon could eventually negotiate access agreements with selected AI platforms, while Shopify could impose stricter controls if agentic commerce creates problems for merchants. But the current split exposes two competing models. One is open and infrastructure-led, while the other is more closed and ecosystem-driven. Those models could shape how retailers interact with AI agents over the next several years.

Amazon is already challenging other AI shopping agents

Muse is not the first AI shopping agent Amazon has opposed. The company has also attempted to restrict access by agents from Perplexity, Google and OpenAI. Its dispute with Perplexity has already moved into the courts, where Amazon initially secured a preliminary injunction before a US appeals court later rejected part of its argument under federal anti-hacking law. Contractual claims based on terms of service remain a separate issue.

That legal background helps explain the language Amazon is now using with Muse. The company is framing the dispute around authorization and contractual access rather than purely around cybersecurity. This suggests Amazon is trying to establish a broader principle: AI agents should not assume unrestricted access to its commercial environment simply because an individual user authorizes them to act.

Amazon itself uses agentic shopping technology

Amazon is not opposed to AI shopping agents in principle. The company has developed its own agentic-commerce capabilities, including Buy for Me, which can help customers purchase products from external merchant sites, and Alexa for Shopping, which can research products and provide recommendations. Amazon argues that the difference lies in transparency and merchant consent.

According to Amazon, Buy for Me identifies itself when interacting with external merchants and allows businesses to opt out. That distinction reinforces the company’s central argument: the problem is not autonomous shopping itself, but how external agents enter and use another company’s commerce environment. In other words, Amazon supports agentic commerce when the rules of access are negotiated and visible to all participants.

Muse is gaining traction quickly

The dispute matters partly because Muse is already attracting significant attention. Meta launched the personal AI agent on September 8, positioning it as a system capable of handling multi-step tasks including shopping, appointment booking, email management and other everyday activities. Shortly after launch, Muse climbed rapidly through Apple’s US App Store rankings, indicating strong early consumer interest.

Growing adoption increases the urgency for retailers and commerce platforms to decide how they want to interact with these agents. For Shopify merchants, Meta represents a potential new source of product discovery and checkout. For Amazon, Muse currently represents an unauthorized intermediary operating inside a commercial environment Amazon has spent decades building and monetizing.

Agentic commerce could disrupt e-commerce advertising

Advertising may become one of the areas most affected by this shift. Traditional marketplaces monetize shopper attention by selling visibility within search results and product pages. Retailers pay to move products higher in rankings or increase exposure across marketplace interfaces. AI agents may operate differently, especially if they prioritize objective criteria such as price, delivery speed, return policies and product specifications.

If consumers increasingly delegate purchasing decisions to agents, traditional sponsored placement could become less influential. An AI may not respond to the same visual hierarchy and advertising formats as a human shopper. That creates a potential challenge not only for Amazon but also for Google and other platforms whose commercial models depend heavily on monetizing search and product discovery.

Merchants face their own strategic decision

Retailers will also need to decide how open they want to be to AI agents. Participation could bring significant benefits by creating new channels for product discovery, customer acquisition, conversion and cross-border sales. At the same time, merchants may lose some control over brand presentation, customer relationships, upselling and the overall shopping journey.

A consumer who shops entirely through Muse may never see the merchant’s homepage, marketing funnel or carefully designed product pages. Competition could therefore shift toward machine-readable factors such as price, stock availability, delivery speed, product attributes and returns. That would change how retailers think about optimization and could make structured product data increasingly important.

Structured commerce data becomes more valuable

Shopify’s role demonstrates this shift clearly. When Shopify shares catalog data directly with Meta, Muse does not need to scrape and interpret every merchant website independently. Instead, the agent can access standardized commerce information such as product descriptions, variants, prices, stock levels and checkout capabilities.

That gives Shopify an important strategic position in the agentic ecosystem. The company already sits between merchants and numerous external sales channels, and AI assistants can become another distribution layer connected to that infrastructure. As more shopping moves through agents, the platforms controlling high-quality structured commerce data may become increasingly valuable.

The future could split into open and closed commerce ecosystems

The Shopify-Amazon divide may point toward a broader fragmentation of agentic commerce. Some platforms may operate as open commerce infrastructure, allowing multiple AI agents to access catalogs and transactions through standardized integrations. Others may remain more closed, allowing only approved agents or proprietary AI experiences to participate.

The result could resemble earlier battles over mobile operating systems, app stores and platform APIs. Retailers and marketplaces may have to choose between reach and control, while AI companies may need to negotiate access to the largest commerce ecosystems rather than assuming they can browse and transact freely.

A defining battle over the next e-commerce interface

The dispute between Shopify, Amazon and Meta ultimately comes down to control. Meta wants Muse to become an interface through which consumers can complete everyday tasks, including shopping. Shopify sees an opportunity to make its merchant ecosystem accessible through that interface. Amazon sees an external agent entering a shopping environment it has spent decades building, optimizing and monetizing.

All three positions are commercially rational, but they point toward very different futures for e-commerce. Shopify’s model says the consumer can shop anywhere while Shopify provides the infrastructure underneath. Amazon’s model says the shopping environment itself remains strategically important and should not be accessed by third-party agents without permission. As AI shopping agents become more capable, the next major battle in e-commerce may not be over assortment or delivery speed, but over which AI is allowed to stand between the shopper and the store.

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Meta is moving forward with its revenue diversification strategy and is preparing to introduce new premium subscriptions across its core platforms: WhatsApp, Instagram, and Facebook. The goal is to offer advanced features focused on control, creativity, productivity, and artificial intelligence, while keeping basic use of each platform free.

This initiative represents a significant evolution in Meta’s business model, which has traditionally relied heavily on advertising, and reflects a broader industry shift toward recurring subscription-based revenue.

A multi-subscription approach instead of a single bundled offer

Rather than launching a single, all-in-one subscription, Meta plans to experiment with different subscription models and feature bundles tailored to each individual application. Each platform will have its own premium options, aligned with how users actually interact with it.

This approach allows Meta to test which features users, businesses, and creators are willing to pay for, while fine-tuning pricing, packaging, and value propositions based on real usage data.

More control, productivity, and creative power for users

The new premium subscriptions are designed to give users greater control over how they interact with content and audiences, while also providing tools that enhance productivity and content creation. Each app will feature its own set of premium capabilities, optimized for its specific use case.

Instagram's premium features are under testing

On Instagram, Meta is testing features that respond to long-standing user demands, particularly from power users and content creators. Among the functions currently being evaluated are unlimited audience list creation, the ability to identify followers who do not follow back, and the ability to view stories anonymously without notifying the content creator.

These tools aim to enable a more strategic use of the platform, especially for those managing communities, personal brands, or professional profiles.

App-specific approaches for WhatsApp and Facebook

While Meta has not yet disclosed a full list of premium features for WhatsApp and Facebook, the underlying logic remains consistent. The focus is on improving contact management, communication organization, and control over content visibility. In WhatsApp’s case, these enhancements could be particularly valuable for small businesses and professionals already using the app as a customer communication or sales channel.

Artificial intelligence is at the core of the value proposition

Artificial intelligence plays a central role in this new phase of monetization. Meta plans to expand the use of Manus, the AI agent it recently acquired for approximately 1.85 billion euros, integrating it more deeply across its platforms and offering it through standalone subscriptions for business use cases.

In parallel, Meta is testing separate subscriptions for specific AI-powered tools. One example is Vibes, an AI-driven video generation tool integrated into Meta AI. While basic video creation will remain free, Vibes is expected to transition to a freemium model, allowing users to pay a monthly fee for access to more advanced creative options and expanded capabilities.

Coexistence with Meta Verified

These new premium subscriptions will not replace Meta Verified, the existing offering aimed at creators and businesses that includes account verification, priority support, and protection against impersonation. Instead, Meta positions the new subscriptions as complementary services, targeting a broader audience interested in practical, creative, and productivity-focused features rather than identity verification.

Monetization in an era of subscription fatigue

With this move, Meta aims to increase recurring revenue, even as advertising remains its primary income source and faces growing pressure to diversify. At the same time, the company must navigate subscription fatigue, as users are increasingly selective about how many monthly digital services they are willing to pay for.

A relevant benchmark is Snapchat+, Snap's paid subscription service, which has surpassed 16 million subscribers at a monthly price of around 3.7 euros. This success suggests there is real demand for premium social media features when the value proposition is clearly defined.

What this shift could mean for users and creators

If Meta succeeds in balancing premium value with a strong free experience, these subscriptions could reshape how users engage with social platforms. For creators and professionals, they offer access to more advanced tools without relying solely on third-party solutions. For general users, they open the door to a more personalized, controlled, and feature-rich social media experience.

Although final pricing and global launch dates have not yet been confirmed, Meta is expected to roll out these subscriptions gradually through controlled testing. The results of these experiments will determine whether premium subscriptions become a long-term pillar of Meta’s business strategy in the years ahead.

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Meta has officially launched its new AI-powered video feed, Vibes, across European markets. Announced on November 6, 2025, this rollout marks a significant step in bringing generative AI content to mainstream users within the EU. After its initial success in the United States, Vibes is now integrated into the Meta AI app, allowing users to create, remix, and share AI-generated short videos directly to Facebook and Instagram.

The launch underscores Meta’s strategy to position artificial intelligence at the core of its next-generation social ecosystem. With Vibes, the company introduces a dynamic space where AI-generated media becomes not just a tool, but a social format in its own right.

What are Meta Vibes and how it work

Vibes offers users a dedicated feed filled with AI-generated short-form videos created through text prompts or remixing tools. Anyone can type a short description—such as “a medieval knight walking through neon-lit streets”—and within seconds, Vibes produces a shareable, animated clip.

Key Features of Vibes

• Text-to-video generation: Users can transform words into concise, creative AI-generated clips.
  
• Remix options: Existing videos can be modified by changing their style, tone, lighting, or background music.
  
• Feed integration: The generated clips appear in a scrollable video feed similar to Reels or TikTok.
  
• Cross-sharing: All creations can be posted directly to Instagram and Facebook.
  

Meta reported that since Vibes’ debut in the U.S., AI video generation within the app has grown more than tenfold, reflecting the rapid adoption of generative creativity by users.

Why Meta Is Expanding Vibes to Europe

The European rollout follows months of technical and regulatory preparation. Bringing a generative AI tool into Europe requires strict compliance with EU data and content regulations, including privacy protection and copyright oversight.

Meta’s European expansion aligns with a wider global strategy to stay ahead of AI-driven competitors such as TikTok’s experimental AI video filters and YouTube’s Dream Screen. By embedding Vibes within its Meta AI app, the company ensures that its user base of more than 400 million EU residents has access to the latest in AI-enabled creativity, all within a framework that meets local compliance standards.

Impact on Content Creation and Social Media Marketing

Vibes represents more than just a new entertainment feature—it is a transformational tool for digital creators, brands, and marketers. The ability to instantly generate, remix, and distribute videos will redefine the speed and cost of content production.

Benefits for Creators

• Rapid idea-to-video turnaround enables daily content updates without the need for expensive equipment or editing.
  
• New creative formats are emerging, including AI-generated worlds, virtual influencers, and stylized storytelling.
  

Benefits for Businesses and Marketers

• Generative media becomes a scalable asset. Brands can produce localized video ads for multiple countries using the same creative base.
  
• Small and mid-sized companies gain access to professional-grade visuals at minimal cost.
  
• The AI feed structure introduces new ad-placement and engagement opportunities, similar to those found on Reels and TikTok.
  

However, critics have warned of the rise of low-quality, mass-produced video content that could flood feeds. Maintaining creative quality and brand consistency will therefore be essential for professional marketers using the platform.

Implications for European Businesses and B2B E-Commerce

For B2B and e-commerce sectors, Meta Vibes opens a new creative frontier. Businesses can use AI-generated videos for:

• Product visualisation: Generate 3D-style videos or demo reels for product listings.
  
• Localized campaigns: Tailor content for specific European markets in multiple languages.
  
• Faster market entry: Automate creative production for seasonal or cross-border campaigns.
  

In a B2B context, AI-generated videos can simplify complex product explanations, highlight case studies, or visualize technical processes—offering cost-effective storytelling tools for digital commerce.

The rise of such tools also aligns with the growing adoption of AI agents in business operations. As companies integrate AI to handle product data, logistics, and marketing, Vibes complements this ecosystem by automating visual communication and branding.

Risks and Regulatory Considerations

Meta’s entry into Europe with Vibes does not come without scrutiny. EU regulators continue to closely monitor generative AI, particularly in areas such as data sourcing, copyright, and misinformation.

Key Risks for Businesses

• Authenticity issues: Deepfake-style videos or synthetic content could blur the line between real and generated media.
  
• Brand safety: Businesses must monitor how their content appears in AI-generated feeds to avoid reputational damage.
  
• Compliance: Companies using AI-generated assets for advertising must ensure they meet EU transparency and consumer-protection standards.
  

Meta has pledged to label all AI-generated videos within Vibes, thereby improving transparency and helping users distinguish between synthetic content and authentic footage.

The Future of AI-Generated Video in Europe

Vibes marks a pivotal moment in Europe’s digital evolution. It signifies a shift where AI becomes both the creator and the medium, allowing users to express, share, and engage through automated visual storytelling.

For creators, it means freedom and speed. For businesses, it means cost-efficient scalability. For consumers, it signals a future where every scroll might unveil a new AI-generated world.

As Meta continues expanding its AI ecosystem, expect Vibes to integrate with shopping, advertising, and creator monetization tools, ultimately shaping the future of social commerce and content production in the AI era.

The European launch of Meta Vibes marks a milestone in the convergence of artificial intelligence, creativity, and commerce. With its generative video feed now available across the region, Meta is redefining how digital content is made, shared, and monetized.

For marketers, creators, and e-commerce brands, understanding and mastering this new AI tool will be crucial to staying visible and competitive in the rapidly evolving digital economy.

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Meta has announced that it will begin training its AI models using public content from European Facebook, Instagram, and Threads users. This includes posts, comments, and captions, as well as the history of conversations with its chatbot. However, it will not affect private messages or the content of minors' accounts.

This decision comes after confirmation from a panel of EU privacy regulators, highlighting Meta's approach to meeting legal responsibilities. The move has sparked controversy, but it is also a crucial step forward in Meta's plans to consolidate its position in the competitive world of AI.

The company maintains that its goal is to make its AI more representative of the different cultural, linguistic, and social nuances of the areas where it operates. In a statement, Meta said: “We believe we have a responsibility to develop AI that is not only available to Europeans, but built for them.”

Training models with public data is not exclusive to Meta. Companies like Google and Open AI have also used user-generated content to enrich their AI models. However, Meta has emphasized that its method is more transparent and that users cannot be involved in this process.

Organizations like the European Center for Digital Rights (NOYB) have filed complaints in 11 EU countries. The company claims that Meta deliberately hinders the opt-out process through “dark patterns,” design strategies that weaken privacy protection, such as difficult-to-find forms or the requirement to provide a reason for opting out, even if any justification is accepted.

How can you prevent Meta from using your data?

Meta will start to inform those EU users via emails and notifications on their platforms. These will include a link to a form to opt out of using your content in AI training. In addition, this form will be available through their privacy policy, where modifications have already begun to be reflected. Meta has indicated that it will honor all opt-out requests.

The procedure for objecting is:

• Access the form via the link in Meta's notice or from their privacy policy.
• State that you do not want your public information to be used to train their AI models.
• Provide a reason (any reason will be accepted)
• Send the form

It is important to act before Meta's deadline, as after that time, the company states that it will not be able to guarantee the deletion of the data previously used in training its AI models.

What does this mean for users?

Although Meta claims that this training will facilitate AI that is more in tune with European diversity, many users are concerned about the consequences in terms of privacy. The ruling opens up a new front in the discussion about how big tech uses personal data and to what extent users can have absolute control over it.

The regulatory context, stricter than in other areas, has forced Meta to delay these plans. Now, after obtaining the approval of the European Data Protection Committee, the company is ready to move forward. However, the focus will remain on how it implements this change and whether it truly ensures users' right to decide.

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Meta continues to rely on AI to assist retail and e-commerce companies, optimizing their performance and reaching consumers at the right time and place. 

Through its platform, it continues to improve AI-driven tools such as Andromeda, which evaluates a large amount of advertising and discovers the most effective method to reach the perfect customer.

In this context, Meta has introduced new features and ad placements for Advantage+ campaigns to improve online and in-store sales results by providing more alternatives to advertising systems.

Omnichannel ads to increase sales

One of Meta's most notable innovations is the expansion of omnichannel ads, which allows advertisers to target customers at both physical locations and their online platforms. Since last year, Meta has been trying to show advertising that highlights locations close to people who usually purchase in physical stores. Now, advertisers can use these omnichannel ads more extensively, including the ability to direct customers to the nearest stores with products in stock and present sales that motivate consumers to visit physical stores.

According to the first evaluations' results, omnichannel advertising saw a 15% reduction in CPA (cost per acquisition) and a 12% increase in ROAS (return on advertising spend) compared to their conventional campaigns. This feature will be accessible worldwide this summer, making it easier for advertisers to prepare for peak season shopping.

Craig Brommers, American Eagle's chief marketing officer, shared his impressions of the results of omnichannel advertising: “We were able to achieve a 48% higher return on our omnichannel ads with our target audience of 18—to 24-year-old shoppers. We are excited about these results and will incorporate this strategy into our campaigns.”

New tools to optimize online sales

In addition to omnichannel ads, Meta continues to innovate in optimization tools to increase online sales. Shops ads, powered by AI, work with Advantage+ campaigns to detect users most likely to purchase in a Facebook or Instagram store. This tool makes it easier for advertisers to reach potential customers more accurately, ensuring that ads are shown to individuals most likely to purchase.

In the coming months, Meta will provide a simplified payment experience that redirects customers to the ad's website to finalize the purchase after adding products to the cart in a store. In addition, Meta intends to test new markets in Australia and Taiwan to evaluate the effectiveness of this optimization.

Optimizations for text generation and additional products

Meta is also increasing the ability of its system to display extra products from a catalog while promoting a set of preferences. For example, a fashion company could highlight jackets and offer the system the possibility of displaying dresses that might appeal to consumers. During the first tests, advertisers have seen an increase of 14% in ROAS, with brands such as Boden in Europe and Dexter in LATAM achieving favorable results by implementing this optimization.

Meta has also expanded the availability of Incremental Attribution, a new attribution configuration that improves incremental conversions through machine learning to enrich these improvements.

New AI applications for retail

Meta continues investigating new generative AI applications for the retail and e-commerce industry. Among the innovations is using virtual models to insert clothing on AI-created models. This enhances the consumer experience, making it easier to visualize a product's appearance before making a purchase.

In addition, Meta continues to explore the generation of backgrounds in advertising catalogues and optimizing the personalization of ad copy. This allows advertisers to optimize how they showcase their products and generate more captivating advertising messages.

In addition to seasonal campaigns, Meta is implementing new tools to assist advertisers in creating key moments throughout the year and transforming customer interest into purchases. 

Starting in the spring, Meta will begin experimenting with advertising in Facebook notifications, making it easier for advertisers to reach those who have previously interacted with their ads or shown interest in their content. This feature allows consumers to be reminded of promotions in a different place.

Another important innovation is the ability to request emails before distributing promotion codes in ads, allowing advertisers to establish a stronger link with consumers. In addition, page links will be accessible globally on Instagram, allowing advertisers to highlight multiple landing pages in a single image or video ad, simplifying users' search for the content most appealing to them.

The post Meta bets on AI to improve retail appeared first on Cross-Border Magazine.

Meta, the parent company of Facebook and Instagram, is working on a plan to ‘evolve’ how users interact on its social networks via AI profiles. According to the Financial Times, the company led by Mark Zuckerberg is developing thousands of fictitious user profiles created through generative AI.

Specifically, the goal is to enhance interaction and entertainment among its platforms' 3 billion active users. These artificial profiles, which began appearing in mid-2024, will feature bios, profile pictures, and AI-generated content, explained Connor Hayes, vice president of product for generative AI at Meta.

“We want interactions between real users and AI users to be more realistic and emerge more naturally and socially,” Hayes said. While most of these accounts are private, Meta is already exploring integrating them more openly with human profiles.

AI profiles vs human profiles 

However, Meta's plan has sparked fierce debate among users and analysts. One of the main fears is that these artificial accounts will contribute to the dehumanization of social networking relationships, a problem already seen with anonymous profiles and fake accounts.

In addition, communication experts have warned that this strategy could aggravate the proliferation of disinformation, 'fake news' and hoaxes on the platforms. Although Meta has assured that “content generated by these accounts will be clearly labeled as AI-produced,” the risk of manipulation and confusion among real users remains a major concern.

Meta has insisted that this initiative seeks to enrich the user experience and experiment with new forms of interaction. According to the company, AI-generated profiles will be designed to be compatible with humans, opening up a new dimension in the use of social networks.

Despite these intentions, the debate about the impact of this technology remains open. While some see an opportunity to explore creativity and innovation, others fear that this is a further step towards the depersonalization of platforms and an increase in the risks associated with artificial intelligence in the digital sphere.

For now, Meta is proceeding cautiously, but the first signs of its strategy are already generating controversy and questions about the future of social networks.

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Meta will launch Meta Movie Gen, an AI-generation multimedia tool, offering creators tools to generate, customize, and edit videos and produce audio, all in high quality and with text descriptions. Specifically, Meta Movie Gen is the third generation of Meta's foundational models, which the company targets content creators and filmmakers as a tool to help drive their creativity rather than replace it.

As the company explains on its official blog, the models it includes have been trained with licensed and other publicly available datasets to offer four capabilities: video generation, custom video generation, precise video editing, and audio generation.

Regarding video generation, the model uses a 30 billion parameter transformer to produce high-quality videos of up to 16 seconds at a rate of 16 frames per second from a text description.

As Meta notes, “the model can reason about object motion, subject-object interactions, and camera motion, and can learn plausible motions for a wide variety of concepts.” Meta Movie Gen models also generate personalized videos based on an image of a person and a description. This is coupled with the ability to edit with localized or more general actions and accurate results.

Meta Movie wants to be a multimedia ‘total solution’ 

Meta Movie Gen also generates audio; it is Meta’s vision to turn this into a full multimedia ‘total solution’. Specifically, it uses a 13 billion parameter model that produces high-quality video from either a base video or a text description. The output is up to 45 seconds long and includes ambient sound, sound effects, and instrumental background music. This model can also generate coherent audio for videos of arbitrary lengths.

In addition, the company stresses that as they continue to improve their models and move closer to a possible future release, “we will work closely with filmmakers and creators to integrate their feedback.” “By taking a collaborative approach, we want to make sure we create tools that help people enhance their inherent creativity in new ways they never dreamed possible. Imagine animating a 'day in the life' video to share on Reels and editing it using text messaging, or creating a personalized animated birthday greeting for a friend and sending it to them via WhatsApp,” adds Meta.

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Meta and Spotify have issued a joint statement addressing their views on Artificial Intelligence (AI) regulation in the European Union. Meta CEO Mark Zuckerberg and Spotify CEO Daniel Ek each complain in the statement published on their respective websites that EU privacy regulations around AI are holding back innovation.

The communiqués point out that Europe should embrace open-source AI, i.e., in a way that the source code is available to everyone in the public domain for use, modification, and distribution. Thus highlighting that failure to do so would slow down the continent's evolution since “artificial intelligence (AI) has the potential to transform the world: increase human productivity, accelerate scientific progress and contribute trillions of dollars to the global economy”. 

Moreover, this liberalization of codes allows “power not to be concentrated in a few big players and, as happened with the Internet before, creates a level playing field.”

Also highlighted throughout the letter is the “uneven” implementation of the EU's General Data Protection Regulation (GDPR). The two tycoons highlight that EU privacy regulators are creating delays and uncertainty and are unable to agree among themselves on how the law should be applied. They cite the example of Meta, which has been prevented from using European user data to train its AI systems. 

“In the short term, delaying the use of data that is routinely used in other regions means that the most powerful AI models will not reflect the collective knowledge, culture, and languages of Europe, and Europeans will not be able to use the latest AI products,” Meta's blog post warns. Therefore, they believe that Europeans will not be able to access the latest open source technology and will instead be left with AI “built for someone else.”

Regulations that are contrasting with those of other countries such as the United States or China, who have decided to let their companies innovate as much as possible in this new technology.

EU laws regarding AI 

In recent years, the EU authorities have become increasingly invested in regulating AI uses and research. In fact, the recent AI Act (EU) passed in 2024 is meant to lay down harmonized rules on artificial intelligence and tries to provide AI developers and deployers with clear requirements and obligations regarding specific uses of AI.

The EU's concern regarding AI uses so much so that there is already a plethora of major laws regulating or affecting it: The EU General Data Protection Regulation (EU) 2016/679, The Product Liability Directive, which, if adopted, will allow people harmed by software (including AI software) to receive compensation from the software manufacturer (replacing Directive 85/374/EEC) The General Product Safety Regulation 2023/988/EU, replacing Directive 2001/95/EC Various intellectual property laws under the national laws of EU 

But, besides the regulations, another key element to understand Facebook and Spotify's concern is the definition of AI used in the EU. For the EU, AI is defined in the EU AI Act using the following terms:

• "AI system" means "a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments."

• "General-purpose AI model" means "an AI model, including where such an AI model is trained with a large amount of data using self-supervision at scale, that displays significant generality and is capable of competently performing a wide range of distinct tasks regardless of the way the model is placed on the market and that can be integrated into a variety of downstream systems or applications, except AI models that are used for research, development or prototyping activities before they are placed on the market"

• "General-purpose AI system" means "an AI system which is based on a general-purpose AI model and which has the capability to serve a variety of purposes, both for direct use as well as for integration in other AI systems"3

The post Meta and Spotify complain about the EU regulations for AI appeared first on Cross-Border Magazine.

The European regulation for artificial intelligence, the AI Act, approved in March 2024, could prevent Meta from implementing the Llama 3.1 AI models, as by the law definition they could be considered "a systemic risk" .

The AI Act was designed to protect the EU consumers and citizens, but it seems that it is instead blocking EU from accessing to the full power of the AI revolution.

A technical issue

In the technical documentation for the Llama 3 family of models - with the 3.1 models included - Meta states what the "scale" of these models is:

"We trained a model at a much larger scale than previous Llama models: our flagship language model was pre-trained using 3.8 × 10^25 FLOPs, almost 50 times more than the largest version of Llama 2. Specifically, we pre-trained a flagship model with 405B trainable parameters on 15.6T text tokens."

And precisely that computational power used to train these models is higher than what the AI Act specifies to not consider them a systemic risk.

With these technical limitations it is impossible to train a complex AI model. Now the EU authorities will have to make a choice: to enforce the law and thus have a considerable competitive disadvantage against the rest of the world, or to change the law to allow the use of more computational power in AI training.

The post The EU AI Act migth prevent Meta from implementing their AI models in Europe appeared first on Cross-Border Magazine.

Meta – parent of Facebook, Instagram, and WhatsApp –  will not launch its upcoming multimodal artificial intelligence (AI) models in the European Union (EU) due to the “unpredictable nature” of its regulatory environment.

“We will launch a multimodal Llama model in the coming months, but not in the EU due to the unpredictable nature of the European regulatory environment,” the company has advanced to Axios media.

This decision may have several consequences for both companies and users in the EU. One of them is that European companies will not have access to this multimodal AI technology to carry out their work processes, despite the fact that these are models that Meta always publishes under an open license.

In this line, users and companies will also not be able to develop their own products if they make use of the new models that Meta plans to launch. Similarly, the technology company has pointed out that it could also affect other companies that operate outside the EU and that, therefore, do use the multimodal models, as it could prevent these companies from offering their products and services in Europe.

Despite the fact that the Artificial Intelligence Regulation will come into force on August 1 this 2024, Meta is currently facing problems with the European regulation due to the need to use data from users participating in its platforms to continue training its AI models.

Specifically, the EU opposes the use of user data by companies such as Meta under the requirements of the current General Data Protection Regulation (GDPR), which seeks to ensure that users have greater control over the personal information handled by its online services, as well as deciding the type of advertising they receive.

Meta wants to use public info to train their AI 

In this context, Meta announced last May its intention to use information shared in Facebook and Instagram posts by public users to train its upcoming AI models. However, Meta later added an option so that, through an objection form, users could prevent using their data posted on both platforms.

Finally, in June, Ireland's data protection authority, the Data Protection Commission (DPC), announced that Meta had halted plans to train its AI models on public content shared by adults on Facebook and Instagram in the EU.

For its part, Meta shared its “disappointment” at having to delay training its large language models (LLMs) using public content from its platforms. “This is a step backward for European innovation, competition in AI development, and further delays in bringing the benefits of AI to people in Europe,” it sentenced in a statement on its blog, noting that “AI training is not a technology unique to Meta's services and that they are also more transparent than many of their industry peers.”

It is worth noting that other tech companies have also made this decision, as is the case of Apple, which recently detailed that it will delay the arrival of its AI features, Apple Intelligence, in the EU, as well as iPhone Mirroring for Mac and SharePlay Screen Sharing features due to “regulatory uncertainties” related, in this case, to the Digital Markets Act (DMA).

However, despite all this, Meta has also indicated to the media above outlet that they plan to release a larger version of their text-only Llama 3 model. This new version will be available to customers and companies in the EU. 

Likewise, the technology company has also confirmed that it will launch its following multimodal AI models in the United Kingdom because, although they also have a law similar to the GDPR, they do not have the same uncertainty scenario as in the European Union; it has clarified.

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