{"id":40550,"date":"2025-06-10T11:35:45","date_gmt":"2025-06-10T11:35:45","guid":{"rendered":"https:\/\/quickassetsmarket.com\/index.php\/2025\/06\/10\/metas-72b-ai-gamble-visionary-empire-or-another-money-pit\/"},"modified":"2025-06-10T11:35:45","modified_gmt":"2025-06-10T11:35:45","slug":"metas-72b-ai-gamble-visionary-empire-or-another-money-pit","status":"publish","type":"post","link":"https:\/\/quickassetsmarket.com\/index.php\/2025\/06\/10\/metas-72b-ai-gamble-visionary-empire-or-another-money-pit\/","title":{"rendered":"Meta\u2019s $72B AI gamble: visionary empire or another money pit?"},"content":{"rendered":"
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Meta Platforms Inc. (NASDAQ:META) has always been a company of adaptation and innovation. <\/p>\n

But its new defining moment doesn’t have to do with social media, the metaverse, or advertising dominance. <\/p>\n

It’s about a singular obsession with AI.<\/p>\n

Its CEO, Mark Zuckerberg, appears restless and more involved than ever. <\/p>\n

After a year of missed model deadlines, public credibility gaps, and internal talent losses, he is now going all in.<\/p>\n

The company is spending up to $72 billion on AI and infrastructure this year alone.<\/p>\n

But critics and investors are now wondering if Meta is actually ahead, or if it is moving too fast without a solid foundation.<\/p>\n

What\u2019s going on with Llama 4?<\/h2>\n

Meta\u2019s largest AI project to date is the Llama 4 family of models. <\/p>\n

The flagship version, known as Behemoth, is built with two trillion parameters and is supposed to represent a leap in capabilities.\u00a0<\/p>\n

But it\u2019s still not ready. The model missed its initial April launch<\/a>, then missed an internal June deadline, and is now delayed again without a firm timeline.<\/p>\n

What Meta has released are two smaller models, Maverick and Scout. <\/p>\n

Both are natively multimodal, meaning they can process text, images, and other types of data.\u00a0<\/p>\n

They are available to developers and are powering some of Meta\u2019s chatbot services across Facebook, WhatsApp, and Instagram. <\/p>\n

Meta also adopted a Mixture of Experts architecture, which improves performance efficiency by activating only parts of the model as needed.<\/p>\n

Internally, though, things are not looking good. Engineers say Behemoth doesn\u2019t meaningfully outperform Llama 3. <\/p>\n

Meta submitted a version of the model to a public leaderboard that wasn\u2019t the same one released to users. <\/p>\n

Critics said the company should have been clearer, and developers questioned the value of Meta\u2019s benchmarks.<\/p>\n

The credibility hit was significant. Eleven of the fourteen researchers who developed the original Llama model have left the company<\/a>. <\/p>\n

According to sources inside Meta<\/a>, management is now considering changes to the AI division\u2019s leadership.<\/p>\n

Meta\u2019s plan to automate everything<\/h2>\n

As technical development continues, Meta is also changing how it governs risk. <\/p>\n

According to NPR<\/a>, the company is now using AI to automate up to 90% of all internal reviews. <\/p>\n

This includes reviews for privacy, misinformation, hate speech, and youth safety. <\/p>\n

What used to require sign-off from human analysts is now decided by internal tools and questionnaires that engineers complete themselves.<\/p>\n

Product teams can now get instant decisions from AI systems before launching updates. In most cases, they decide whether something qualifies for further human review.<\/p>\n

Inside Meta, some see this as a way to move faster in a competitive environment. But former employees warn it creates blind spots. <\/p>\n

One former director said that engineers are evaluated on shipping speed, not safety. <\/p>\n

Another called the new process \u201cself-defeating,\u201d arguing that past scandals were often caused by overlooked risks that human teams could have caught.<\/p>\n

The European Union may offer some buffer. Thanks to the Digital Services Act<\/a>, Meta\u2019s EU headquarters in Ireland will still oversee regional compliance. <\/p>\n

But for the rest of the world, change is already underway.<\/p>\n

Meta has also ended its US fact-checking program<\/a> and loosened its policies on hate speech.<\/p>\n

The company says this is about efficiency, while critics argue it\u2019s a step back in platform accountability.<\/p>\n

Why advertising may never look the same<\/h2>\n

Meta is also reshaping its advertising business. By the end of 2026, the company plans<\/a> to fully automate the creation of ads using AI. <\/p>\n

Advertisers will upload a product image, enter a budget, and Meta\u2019s system will generate the entire campaign, from video and text to targeting and delivery.<\/p>\n

This approach could open the door for millions of small businesses that don\u2019t use ad agencies. But it also threatens large players in the industry. <\/p>\n

Zuckerberg described the move as a redefinition of advertising. Meta\u2019s ad business already brings in around $160 billion per year<\/a>. <\/p>\n

These new tools could make that number much bigger by lowering costs and simplifying access.<\/p>\n

Source: Statista<\/a><\/figcaption><\/figure>\n

The company insists agencies still have a role, especially in managing complex campaigns. <\/p>\n

But it\u2019s clear the tools are built to cut them out for a large share of the market.<\/p>\n

Why Meta wants to own the data too<\/h2>\n

As AI models grow in size and complexity, they require better data. <\/p>\n

Meta is trying to secure that pipeline by investing more than $10 billion in Scale AI<\/a>, a startup that labels and prepares data for model training. <\/p>\n

It\u2019s Meta\u2019s biggest external AI investment so far.<\/p>\n

Scale AI works with Microsoft, OpenAI, and the US Department of Defense. <\/p>\n

It also partners with Meta on a project called Defense Llama, a version of Meta\u2019s model designed for military use.<\/p>\n

Scale\u2019s founder, Alexandr Wang, is expected to join Meta\u2019s new AI unit once the deal is complete.<\/p>\n

The investment gives Meta a stake in the training infrastructure used by its competitors. <\/p>\n

It also positions the company to expand further into government and defense contracts.\u00a0<\/p>\n

Last month, Meta signed a deal with defense contractor Anduril<\/a> to build AI-enabled hardware for military applications, including augmented reality helmets.<\/p>\n

Scale\u2019s revenue is projected to double this year from $870 million to $2 billion. <\/p>\n

The company was last valued<\/a> at $14 billion in 2024, although that figure is expected to have doubled already<\/a>.<\/p>\n

Meta is using this partnership to secure long-term access to high-quality training data, a resource as important as compute power in the AI race.<\/p>\n

Zuckerberg is going founder mode again<\/h2>\n

In response to missed goals and internal frustration, Zuckerberg is personally building<\/a> a new elite group called the \u201csuperintelligence\u201d team. <\/p>\n

Its mission is to pursue artificial general intelligence, that is, AI that can perform as well as a human across a wide range of tasks.<\/p>\n

The team will include around 50 people. Zuckerberg is directly recruiting them, meeting with candidates at his homes and even managing a WhatsApp group called “Recruiting Party.” <\/p>\n

Some members of Meta\u2019s existing AI staff are expected to join. Others are being hired from outside.<\/p>\n

Zuckerberg says Meta doesn\u2019t need outside funding to compete. He\u2019s told recruits the company can finance a multi-gigawatt data center on ad revenue alone. <\/p>\n

He\u2019s also promising the freedom to build without the kind of investor pressure facing startups like OpenAI.<\/p>\n

The project is separate from Meta\u2019s existing AI divisions, which have faced criticism for delays and underperformance. <\/p>\n

The superintelligence group is an attempt to reboot Meta\u2019s AI efforts with speed, focus, and control.<\/p>\n

Can Meta win the AI race?<\/h2>\n

Meta\u2019s estimated $72 billion in AI spending places it behind Amazon, Microsoft, and Google in terms of raw capital.<\/p>\n

Source: Bloomberg<\/a><\/figcaption><\/figure>\n

But unlike its rivals, Meta doesn\u2019t operate a cloud business. It can\u2019t recycle infrastructure costs by selling compute to others. <\/p>\n

Every dollar it spends must earn a return inside its own ecosystem.<\/p>\n

To make that math work, Meta is betting on three things.<\/p>\n

It\u2019s betting that Llama, its open-source model family, can become the standard for developers.<\/p>\n

It\u2019s betting that AI-generated ads can grow its core business at a lower cost. <\/p>\n

And it\u2019s betting that its vast user base can absorb and normalize AI-driven products at a scale that few other companies can match.<\/p>\n

But those bets require precision. And right now, Meta is doing everything at once. <\/p>\n

It\u2019s training massive new models, investing in training data providers, replacing human review systems with algorithms, building defense tech, and chasing AGI, all in a single push.<\/p>\n

The ambition is undeniable. But the risk is that speed is outpacing maturity, and if Meta fumbles execution or loses public trust again, its $72 billion may be remembered as another \u201cmoney pit.\u201d<\/a><\/p>\n

The post Meta\u2019s $72B AI gamble: visionary empire or another money pit?<\/a> appeared first on Invezz<\/a><\/p>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Meta Platforms Inc. (NASDAQ:META) has always been a company of adaptation and innovation. But its new defining moment doesn’t have to do with social media, the metaverse, or advertising dominance. It’s about a singular obsession with AI. Its CEO, Mark Zuckerberg, appears restless and more involved than ever. After a year of missed model deadlines, <\/p>\n","protected":false},"author":1,"featured_media":40551,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":{"0":"post-40550","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-investing"},"_links":{"self":[{"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/posts\/40550","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/comments?post=40550"}],"version-history":[{"count":0,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/posts\/40550\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/media\/40551"}],"wp:attachment":[{"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/media?parent=40550"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/categories?post=40550"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/quickassetsmarket.com\/index.php\/wp-json\/wp\/v2\/tags?post=40550"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}