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Most AI companies are racing to build the biggest, smartest model. Google is doing something else entirely. While startups chase headlines with trillion-parameter releases and billion-dollar valuations, Google is investing $75 billion into AI infrastructure — owning the chips, the data centres, the networks, and the distribution. In this video, we break down: • Why much of today’s AI boom may be economically fragile • The cloud credit dependency problem • How GPU scarcity reshaped the industry • Why Google’s TPUs change the power dynamic • What Gemini really represents (hint: it’s not “just a model”) • Why distribution may be Google’s unfair advantage • And what happens if the AI bubble bursts Google isn’t trying to win the AI model race. They’re trying to own the conditions that make the race possible. If you're interested in AI strategy, infrastructure economics, Nvidia dependence, TPU supply chains, or the long-term future of AI platforms — this is for you. Like, comment, and subscribe! Check Out Our Other Videos: 📌 Other Tech Insights: • Is Apple LOSING the AI Race?! 📌 Watch next: • How AI Will Change Humanity Forever - AGI ... L E T ' S C O N N E C T ! LinkedIn: / rikin-patel-impact YouTube Subscribe: / @impact-it #GoogleAI #AIstrategy #ArtificialIntelligence #Gemini #TPUs #Nvidia #AIinfrastructure #TechAnalysis #AIeconomics #CloudComputing #BigTech