Over the past few years, Meta has invested billions of dollars into research and hired leading scientists to build powerful AI systems. It has also built a large computing infrastructure and released a group of large language models called LLaMA, its latest, LLaMA 3, to compete with OpenAI’s ChatGPT and Google’s Gemini. Meta has made its models open-source to allow anyone to access, use, and build on them freely, and says it wants to “open up” AI to benefit everyone. Most people think this is a bold step toward making superintelligence more fair, shared, and useful for the world. They say the company’s move will speed up innovation, help smaller players compete, and prevent a monopoly on AI. On the other hand, critics say Meta wants to shape how AI is built, used, and regulated without appearing too dominant by offering the tools but keeping control of the ecosystem. The company still decides when and how to release its models, limits what people can do with them, and builds the platforms where these tools will live and grow. This raises a tough but important question: Is Meta creating a smarter future for everyone, or is it quietly building a new kind of control? Not through force or censorship, but through subtle influence, design, and growing dependence. Meta invests big in AI for everyone Meta is pouring enormous resources into Artificial General Intelligence (AGI), AI models designed to think, reason, and learn like humans. These models will one day write code, answer questions, make ethical decisions, solve business problems, and adapt to new situations without reprogramming. Whoever builds AGI first will shape how billions of people interact with technology for decades, and Meta wants to be 10 steps ahead of its competition. The company collects vast amounts of data from billions of users to help teach its AI models how humans express thoughts, emotions, and intentions. Every meme, text, image, voice recording, video, “like,” and emoji reaction is raw data. Meta is building AGI directly from the messy, emotional, highly detailed reality of human life as it plays out online every day. This way, the systems learn what people say, how they say it, when they say it, who they say it to, and how others respond. Meta recently merged its FAIR (Fundamental AI Research) and GenAI (Generative AI) teams into a single, centralized unit focused solely on developing general-purpose AI systems. This shows the company is looking beyond smarter assistants or better content filters, focusing on new interfaces for communication, ways of organizing knowledge, and forms of social and economic influence. Meta Says Openness Helps Progress Mark Zuckerberg says Meta will “freely share” its AI models with the world for faster innovation, greater safety, and a more inclusive future where AI benefits everyone. Most supporters say this openness invites more innovation because people from different backgrounds can use, test, and improve the tools together. They don’t have to wait for a few big companies to decide what happens next. On top of that, they claim mistakes and risks become easier to catch because the model isn’t hidden behind company walls. However, critics argue that Meta has quietly kept the most advanced and powerful versions locked away despite releasing parts of Llama 3 to the public. The company still controls the versions with the highest intelligence and greatest influence, while the world gets a taste of what Llama can do. What’s more, critics say this strategy helps Meta improve its models without paying for outside research or user testing because millions of people use and test the tools. It also earns them praise for being open and generous. Meta says it supports openness, but its actions tell a different story. It gives some tools away, but holds the most powerful ones back. So the real question is: Is this true open-source progress, or just a smart way to stay ahead without seeming like a monopoly? Meta builds AI that learns from people’s data Meta doesn’t need to look far when training its powerful language model, Llama 3. It has a data goldmine with access to one of the world’s largest content ecosystems through Facebook, Instagram, WhatsApp, and Threads. The company says it used public web data, computer code, synthetic data (artificially generated content), and possibly material created by users on its platforms. That means anything from blog posts to Reddit threads to images you uploaded on your timeline might become part of the material used to train the AI. The model may be built on a foundation that many people never knowingly agreed to contribute to. Artists, writers, musicians, and developers argue that Meta and other tech giants are building billion-dollar AI systems using creative content they never paid for, credited, or asked permission to use. It feels like digital trespassing where companies walk into their space, take what they want, and profit from it under the guise of innovation. Governments and officials in regions like the European Union are starting to pay attention. They are now asking where this training data comes from, whether users gave meaningful consent, and how this aligns with privacy laws like the GDPR. They also want companies to explain how they handle sensitive data, copyrighted content, and personal information. Meta’s massive data advantage highlights the troubling power imbalance between those who build the future of AI and those whose lives, voices, and creations make that future possible. Cryptopolitan Academy: Coming Soon - A New Way to Earn Passive Income with DeFi in 2025. Learn More
