Google has quietly turned the tables once again. While seemingly calm, it was actually a moment that shifted the balance of power in the AI industry. The newly unveiled Gemini 3 Pro has topped major leaderboards. And it's not just a first place; it's a significant lead over current-generation competing models. But what's even more shocking is this: the model was trained entirely on Google's TPUs, not a single NVIDIA GPU was used.
For a long time, the AI industry took its dependence on NVIDIA for granted. GPUs were considered the steel of the AI era, and every company was locked in a war over them. However, Google quietly forged a completely different path. By integrating its own chips, operating system, data centers, and software stack, it achieved a system for AI development free from external dependencies. And the results of this effort have only now been revealed publicly.
The reason this is so frightening is simple: Google has proven that NVIDIA GPUs are no longer the sole arbiter of competition at the forefront of AI. This doesn't mean NVIDIA's position is being shaken, but rather signals a fundamental shift in the rules of AI competition. It means we're entering an era where only companies that build everything from chips to cloud computing will have true strategic autonomy, and that autonomy will determine AI performance and cost.
Google has been pursuing this strategy slowly but persistently for a long time. While other companies struggled to secure GPUs, Google has quietly improved the performance of its chips and cultivated an ecosystem. Now that the fruits of its labor are tangible, the phrase "the next Google is Google" is no longer out of place. It's a classic strategy of a powerhouse, changing the game and then regaining the top spot.
The message Korean industry must take from this scene is clear. While a dependence on imported GPUs might be convenient in the short term, it will solidify technological dependence in the long term. We cannot resist the trend of infrastructure independence becoming a greater strategic asset than AI model competitiveness. Unless we integrate chips, cloud, data centers, and models into a single value chain, we will not be able to compete at the forefront.
The structure of AI hegemony is shifting. The countries and companies that embrace it first will seize the opportunities of the next decade.
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