In an industry defined by massive capital outlays and proprietary technology, Meta has chosen a strikingly different path for its artificial intelligence ambitions. The social media giant is spending between $30 billion and $37 billion on AI in 2024, placing it in a high-stakes arms race with the largest technology companies in the world. But instead of keeping its most advanced models behind closed doors, Meta has publicly released its LLaMA family of large language models—a sharp departure from the strategies of Google and OpenAI, which guard their most advanced systems as trade secrets.
Meta’s bet on openness aims to attract independent developers and researchers who might otherwise build on proprietary platforms. By making its models freely available, the company hopes to benefit from external improvements without bearing the full cost of development.
Whether that bet pays off remains an open question as the industry moves fast and the spending commitments are enormous.
Open Source as a Differentiator
Meta’s decision to open-source LLaMA contrasts with the walled-garden approaches of its major rivals. Google launched its Gemini model in December 2023, and its DeepMind division—founded in 2010 and acquired by Google in 2014—continues its own research. Microsoft has invested $13 billion in OpenAI since 2019 and is weaving AI into its Azure cloud platform and Office products.
OpenAI itself, founded in December 2015, released GPT-4 in March 2023 and carried an $80 billion valuation as of February 2024. The choice of open source matters beyond corporate strategy.
Meta’s platforms shape what billions of users see, read, and buy. The company reported in November 2024 that its AI assistant, Meta AI, had reached 500 million monthly active users. That gives the company a foundation to build on, but Google, Microsoft, and OpenAI are not standing still.
The competition extends beyond chatbots: Meta’s AI-powered advertising tools now go up against Google’s Performance Max and Amazon’s AI advertising systems.
The Scale of Investment
The spending figures lay out the magnitude of the race. Meta’s AI investment of $30-37 billion in 2024 compares with Google’s $45 billion in capital expenditures, most of it on AI.
Microsoft is spending $50 billion. These commitments reflect a conviction that AI will drive the next generation of products and services, but they also carry risk. For Meta, the decision to release its models openly means it foregoes the direct revenue that rivals generate from licensing or controlling proprietary AI systems.
Long before its current AI push, Meta invested heavily in machine learning to power content recommendations and advertising. Early acquisitions of AI startups and the development of facial recognition tools laid groundwork for today’s systems.
The company began as a college social network and over two decades grew into a global communications conglomerate. It rebranded from Facebook to Meta in 2021, signaling ambitions beyond social media, particularly into virtual reality and augmented reality. That pivot came as regulators intensified scrutiny of its market power in advertising and data collection. Meta Platforms is an American multinational technology conglomerate that owns social media services including Facebook, Instagram, and WhatsApp, and develops virtual reality hardware and software.
The company’s name derives from the Greek word for “beyond,” a reference to its goal of building the metaverse—a network of shared three-dimensional virtual spaces.
What the Race Means for Users
The next phase will likely hinge on which company can translate massive capital expenditure into products that users and advertisers actually adopt. Meta’s open-source approach could shift how the technology develops, potentially spreading power away from a handful of dominant firms. It also creates new risks around misuse and safety.
For readers, the outcome of this strategy will influence everything from online advertising costs to the way digital assistants handle personal information. With Meta AI already reaching hundreds of millions of monthly active users, the company has a foundation to build on.
But the timeline suggests this race is only accelerating, and the spending commitments are enormous. Whether openness, scale, and the reach of existing platforms will be enough remains to be seen.
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