AI Economics for Operators
Pricing, capital, unit economics, vendor strategy, and the market structures behind AI operating decisions.
Artificial intelligence is both a technical system and an unusually capital-intensive market. This topic tracks the money underneath the models: token prices, inference costs, funding rounds, valuations, acquisitions, monetization, procurement, and the margins hidden behind headline benchmarks.
The operator’s question is always explicit: who captures the value, what does adoption actually cost, and which assumptions make a build, buy, partner, or investment decision rational? Company news appears here when it reveals a durable economic mechanism—not simply because a large AI company made another announcement.
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Gemma 4 Beat Models 20x Its Size. Google Gave It Away.
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The $13 Billion Divorce Starts with Three Models
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$150 Billion in AI IPOs. Not a Dollar of Profit.
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Apple Paid Google $1 Billion for Siri. It Still Can't Ship.
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Arm Built a Chip. The x86 Monopoly Just Blinked.
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OpenAI Kills Sora. Disney Takes Its Billion Home.
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Apple Can't Fix Siri but Still Owns AI's Toll Road
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China's AI Cloud Just Got 34% More Expensive
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Silicon Valley Is Spending $185M to Buy an AI Congress
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Meta's $135 Billion AI Gamble Is Already Unraveling