{"id":44577,"date":"2025-12-13T16:01:29","date_gmt":"2025-12-13T10:31:29","guid":{"rendered":"https:\/\/dailynewsindia.co.in\/index.php\/2025\/12\/13\/the-polite-war-nobody-advertised-how-ais-power-brokers-are-learning-the-language-of-antitrust\/"},"modified":"2025-12-13T16:01:29","modified_gmt":"2025-12-13T10:31:29","slug":"the-polite-war-nobody-advertised-how-ais-power-brokers-are-learning-the-language-of-antitrust","status":"publish","type":"post","link":"https:\/\/dailynewsindia.co.in\/index.php\/2025\/12\/13\/the-polite-war-nobody-advertised-how-ais-power-brokers-are-learning-the-language-of-antitrust\/","title":{"rendered":"The Polite War Nobody Advertised: How AI\u2019s Power Brokers Are Learning the Language of Antitrust"},"content":{"rendered":"
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Mumbai (Maharashtra) [India], December 13:<\/strong> <\/span>Once upon a time, monopolies wore top hats and owned railroads. Today, they wear hoodies, speak in APIs, and call themselves \u201cecosystems.\u201d<\/p>\n

Artificial intelligence didn\u2019t invent corporate dominance \u2014 it merely upgraded it. And now regulators across continents are finally asking the question Big Tech hoped would stay theoretical: At what point does innovation stop being competitive and start being exclusive?<\/em><\/p>\n

This isn\u2019t a sudden moral awakening. It\u2019s a reaction to numbers.<\/p>\n

A handful of companies now control the three pillars of AI power<\/a><\/strong>:
compute, data, and cloud distribution. Together, those pillars decide who gets to build, who gets to scale, and who quietly disappears after a promising seed round.<\/p>\n

Nobody is calling it a cartel out loud \u2014 but the room has gone quiet enough that the comparison is unavoidable.<\/p>\n

Artificial Intelligence wasn\u2019t born centralised. It just grew up that way.<\/p>\n

Early machine-learning breakthroughs thrived in academic labs and scrappy startups. Training costs were manageable. Models were small. Access was imperfect but democratic. Then models grew \u2014 not linearly, but explosively.<\/p>\n

Today, training a frontier-grade AI system costs hundreds of millions to billions of dollars<\/strong> in compute, energy, specialized chips, and engineering labor. Only a few players can afford to run that race without collapsing halfway through.<\/p>\n

So the market adapted \u2014 predictably.<\/p>\n

Cloud providers bundled compute with proprietary Artificial Intelligence services. Hardware access became contractual. Data pipelines grew vertically integrated. And \u201cpartnerships\u201d started looking suspiciously like toll booths.<\/p>\n

From a PR lens, it\u2019s brilliant.
From a regulatory lens, it\u2019s\u2026 familiar.<\/p>\n

The Case Big Tech makes (and it isn\u2019t entirely wrong)<\/h3>\n

Let\u2019s be fair \u2014 because regulators increasingly are.<\/p>\n