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Mark Zuckerberg at Trump inauguration
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How Meta plans to recoup its billions in AI investment

2025 will be all about hitting a billion Meta AI users, then monetizing them.

The year ahead for Meta is all about AI. But the year after that will be all about monetizing it.

The company is currently training Llama 4, the next iteration of its large language model, which it expects to release this year. Even though Llama is a free, open-source product, it sits right at the center of Meta’s plans for growth.

Unlike its competitors in the AI horserace, like OpenAI and Anthropic, Meta can pour tens of billions of profits from its other businesses into this effort (and the infrastructure needed to run it), and has lots of ways that it can turn the free product into a revenue firehose.

On yesterday’s Q4 earnings call, Meta CEO Mark Zuckerberg said:

“We have a really exciting roadmap for this year with a unique vision focused on personalization. We believe that people dont all want to use the same AI — people want their AI to be personalized to their context, their interests, their personality, their culture, and how they think about the world.”

Anytime you hear the word “personalization” in a Big Tech product, that means it will be used for ads. None of the big AI players have integrated ads into their chatbot products, but if anyone is prepared for this, it’s Meta.

Meta is an advertising company, after all. For all of FY 2024, the company pulled in over $160 billion in ad revenue, growing 21% year over year.

Zuckerberg regularly says that Meta’s pattern is to grow a product to 1 billion users, then monetize:

“We try to scale them to reach usually a billion people or more. And it’s at that point once they’re at scale that we really start focusing on monetization. So sometimes we’ll experiment with monetization before — we’re running some experiments with Threads now for example.”

But Zuckerberg cautioned that the “actual business opportunity for Meta AI and AI Studio and business agents and people interacting with these AIs” won’t show up until after 2025.

And if Meta’s plans for monetizing AI look anything like its current ad business, you might not even have to use Meta’s chatbot to help fuel the new business.

The Meta tracking “pixel” has turned billions of internet users into targets for Meta advertising, even if they aren’t users of Meta platforms. The Meta pixel has become such a built-in default on billions of websites that it has caused sensitive data collection from suicide hotlines, hospitals, tax-filing companies, and federal student loan providers. Dozens of lawsuits have been filed due to the ad technology’s misuse.

Nobody really knows exactly how the “personalization” of AI services will be monetized, but after spending hundreds of billions to build all this fancy, city-sized AI infrastructure, you better believe they will want a return on their investment.

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FT: Meta considering “tens of billions” in new capital to fund AI

Just days after Google announced a monster $85 billion upsized equity raise, the extremely profitable Meta is seeking to sell “tens of billions of dollars” in stock, according to a new report from the Financial Times.

Meta is planning on spending between $125 billion and $145 billion on AI capital expenditure this year alone.

Shares dropped more than 5% on the news.

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FT: Anthropic staff helping the NSA use Mythos for offensive cyberattacks

Anthropic’s Mythos AI model was deemed too dangerous to release to the public, with the company citing its ability to orchestrate novel cyberattacks.

And that’s just what the National Security Agency is doing, with the help of Anthropic staff embedded at the agency, according to a report from the Financial Times.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

tech

Longtime Tesla bear JPMorgan upgraded Tesla and raised its price target to $475 from $145

For more than a decade, JPMorgan was Wall Streets most stubborn Tesla skeptic, anchored by auto analyst Ryan Brinkman’s strict focus on traditional car fundamentals and near-term delivery numbers.

But JPM recently handed coverage of the stock to a new analyst, Rajat Gupta, who is throwing that playbook out the window. In a note Friday, the firm upgraded Tesla to neutral from underweight and raised its price target 228% to $475 from $145. (The analyst consensus on FactSet is $403.) Instead of focusing on the company’s struggling vehicle business, the new analyst is orienting himself more toward Tesla’s idea of the future, now modeling Tesla’s physical AI and robotaxi fleets all the way out to the year 2040.

Here are the main reasons for the capitulation:

  • Looking past the car lot: Gupta argues that Tesla is at the forefront of physical AI, entering uncharted TAMs” and therefore deserves the benefit of the doubt to be valued on LT earnings potential rather than near-term speed bumps.

  • Unmatched vertical integration: Teslas control over everything from battery cells to custom silicon gives it a massive moat. JPM notes this starting point advantage is unmatched at an industrial level scale” and “still somewhat under-appreciated and misunderstood.

  • The AWS flywheel effect: Deploying Optimus robots inside its own factories should not only lower COGS for the base automotive business, but more importantly, help validate the product at an industrial scale.” Gupta called it “a classic flywheel effect, somewhat analogous to AWS and Kiva at AMZN.

For Tesla bulls who have argued for years that this is an AI company and not a carmaker, JPM’s sudden $3.9 trillion valuation model is the ultimate validation.

skynet terminator

Anthropic ponders self-improving AI

Anthropic says Claude already writes 80% of its code. A new post asks what happens when the models can improve themselves — and whether anyone could stop them.

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