Inside Meta’s Billion-Dollar AI Power Play: LLaMA, Scale AI, and the Race to Own the Future of Artificial Intelligence

Meta, then known as Facebook, began its AI journey in 2013 by establishing the Facebook AI Research (FAIR) lab. This initiative was led by Yann LeCun, a pioneer in deep learning and one of the most respected minds in AI. The goal of FAIR was to advance the state-of-the-art in AI through open research and collaboration. 

Over the following years, FAIR expanded its presence globally, establishing labs in Paris, Montreal, Tel Aviv, and other cities. Early focus areas included image recognition, natural language processing, and recommendation systems. 

In 2015, Facebook acquired Wit.ai, a startup focused on natural language interfaces, to strengthen its voice technology capabilities. During this period, the company also launched several early AI products, such as M, a virtual assistant for Messenger, although it was later discontinued due to heavy human dependence.

In 2017, Meta released PyTorch, a flexible deep learning framework that quickly became a favorite among researchers and practitioners. PyTorch's simplicity and Pythonic nature helped it gain popularity over older frameworks like TensorFlow. 

In 2018, the company further formalized its AI strategy by renaming its AI division from FAIR to Meta AI, with Jérôme Pesenti leading the division and LeCun moving to a Chief AI Scientist role. The company also began releasing more open-source tools like Horizon (a reinforcement learning platform) and Glow (a machine learning compiler). 

Meta had become one of the leading global contributors to AI research. At the same time, the company began acquiring startups to support its AI ambitions, including CTRL-Labs (brain-computer interfaces) and GrokStyle (visual search), signaling a move toward integrating AI with augmented and virtual reality. 

It deepened its research into fundamental AI capabilities. A major highlight came in 2022, when Meta used its AI infrastructure to predict the 3D structure of over 600 million proteins, an accomplishment with far-reaching implications for biotechnology and medicine. 

The company also continued its acquisitions, investing in technologies that supported its long-term vision of the metaverse, AR/VR, and immersive computing. During this time, Meta’s AI tools were increasingly used in content moderation, advertisement optimization, and recommendation engines across Facebook and Instagram.

The generative AI boom reshaped Meta’s strategy starting in 2023. In February, Meta released the first version of its LLaMA (Large Language Model Meta AI) models, which were open-weight foundation models meant to rival OpenAI’s GPT and Google’s PaLM. By July, LLaMA 2 was released and became one of the most powerful open-access large language models. 

Meta also launched a dedicated Generative AI team to integrate LLMs into its products. In September 2023, Meta introduced Meta AI, a virtual assistant powered by LLaMA, integrated across its core apps: Facebook, Instagram, WhatsApp, and Messenger. The assistant could answer questions, generate text and images using Emu (Meta’s internal image generator), and even interact through Meta’s Ray-Ban smart glasses, giving it physical-world applications.

In 2024, Meta expanded access to its AI tools, deploying the Meta AI assistant across more than 40 countries and embedding it deeper into its messaging and content platforms. It also released LLaMA 3, offering both instruction-tuned and chat-optimized versions. The emphasis was on openness, as Meta continued to make its AI models freely available under community licenses, positioning itself as the open-source counterweight to companies like OpenAI and Anthropic. 

In 2025, Meta released LLaMA 4, a state-of-the-art model powering its generative tools and Meta AI assistant. Simultaneously, Meta ramped up its investments in AI infrastructure, including the construction of custom AI chips, a 16,000-GPU supercomputer, and data centers optimized for AI workloads. 

The company plans to increase its compute power to over 1.3 million GPUs, backed by a projected capital investment of up to $72 billion. To support this expansion sustainably, Meta signed a 20-year nuclear energy agreement to supply clean energy to its AI data centers. This scale of investment indicates a long-term commitment to achieving Artificial General Intelligence (AGI) and dominating AI innovation.

As of mid-2025, Meta’s AI assistant is widely available and supports multilingual input, content generation, recommendations, and real-time interaction across platforms. Meta continues to lead in open-source AI, with PyTorch remaining the foundation of most of its models. The company’s AI portfolio spans image generation, voice interaction, advanced search, creative tools for advertisers, and multimodal experiences. Meta’s AI is not just a research tool anymore—it’s embedded in daily user experiences, from social media feeds to glasses, virtual meetings, and smart assistants.

Why Scale AI? Why Now?

Meta’s rumored $10 billion+ investment in Scale AI isn’t out of the blue. Scale AI, founded in 2016 by former MIT wunderkind Alexandr Wang, has become the backbone of modern AI development. Its core offering—data labeling—is the behind-the-scenes grunt work that teaches AI models what’s what. Is that image a cat or a dog? Is this email spam or not? Does this sentence sound toxic or safe?

Without well-labeled datasets, no AI model learns anything.

Scale AI’s clients read like a who's who of tech: It powers LLMs for OpenAI, Microsoft, Amazon, and yes, Meta. It recently developed Defense LLaMA — a secure, military-grade AI model built on Meta’s own LLaMA 3. It's a model trained for defense operations, showing just how deep the collaboration already runs between the two companies.

In 2023 alone, Scale AI reportedly made $870 million in revenue, and projections for 2025 top $2 billion. With a presence in over 9,000 cities and towns and a massive contractor workforce, it’s the silent circulatory system of the AI industry.

Meta had already invested in Scale’s Series F funding round ($1 billion), which valued the startup at $13.8 billion. But now, with talks suggesting a deal exceeding $10 billion, Meta may be looking to lock in a strategic AI partner—and perhaps even own a vital piece of the global AI supply chain.

For Meta, this investment is a bet on infrastructure dominance. The more high-quality data Meta can access and control, the better its models become. By tightening its relationship with Scale AI, Meta would be able to:

• Supercharge the development of future LLaMA models

• Improve accuracy, diversity, and safety in its AI assistant

• Build military and enterprise-grade AI offerings

• Compete toe-to-toe with OpenAI, Google DeepMind, and Anthropic

On the other hand, Scale AI could gain the financial muscle and technical access it needs to expand globally, increase automation, and potentially reduce its reliance on human labelers—a key controversy it has faced in recent years.

As AI becomes the engine of economies, education, military strategy, and even creativity, the stakes are monumental. Meta’s upcoming investment in Scale AI could reshape how global data flows are managed, how intelligent systems are trained, and who controls the next generation of digital infrastructure.

The world is watching. And with Meta's open-source push, LLaMA's rising popularity, and the scale of its ambition, it’s clear: Zuckerberg is playing for keeps.

This is no longer just about social media. This is about owning the operating system of the future.

If Meta finalizes this investment, expect:

• A new version of LLaMA (possibly LLaMA 5) with best-in-class data backing

• Expansion of Meta AI into physical-world devices like AR glasses, cars, and homes

• Meta potentially offering enterprise AI APIs like OpenAI’s GPT services

• An intensifying arms race for global AI leadership

As Meta charges ahead in the AI frontier, what’s becoming increasingly clear is that the company is building a strategic empire around it. Beyond model releases and open-source headlines, Meta is silently laying down the pillars of a new AI-driven world order: 

One where control over training data, infrastructure, and real-time deployment defines global tech supremacy.

The next phase won’t be measured by who builds the largest language model, but by who integrates AI most effectively into daily human experience. By investing in foundational players like Scale AI, Meta is also investing in a future where data sovereignty, AI ethics, and machine-human collaboration become global battlegrounds. 

Ultimately, Meta’s ambition signals something deeper: 

A belief that AI will replace the internet.

In the years ahead, human interaction with technology will be conversational, predictive, and immersive by default. Whoever builds that reality doesn’t just win market share—they write the blueprint for digital life itself. Meta wants that pen.