There is an interesting viewpoint - a certain tech giant is currently underestimated, and its true value may be close to $4 trillion. Why? Because it is currently the only player that has integrated the entire AI industry chain from underlying hardware to application.
Let’s first talk about the chips. This company manufactures its own training chips, avoiding the "intelligence tax" that other vendors pay to NVIDIA. Their TPU has already been commercialized—META and Anthropic are even discussing procurement contracts worth billions of dollars, which proves that the self-research route for hardware is not just a gimmick; it can indeed save costs and expand scale.
The data advantages are even more exaggerated. Just think about it, the world's largest search engine, video platform, map service, email system, along with browsers and mobile operating systems—these products generate user behavior data every minute, which directly feeds back into model training. While others spend money to buy data, it passively collects data. This real-time, massive, multi-scenario training corpus is something competitors simply cannot replicate.
The model capabilities are also online. Gemini 3 is fully trained based on its own chips and is now deeply embedded in all major products. Many people are concerned that AI will impact search advertising revenue, but the reality is quite the opposite—AI enhances the search experience, accelerates cloud business growth, and can also unlock monetization potential for YouTube. Each product line is becoming more competitive because of AI.
The most crucial aspect is the distribution capability. A single model update can instantly cover billions of users. Combined, entry points like Search, YouTube, Android, and Workspace essentially control the lifeblood of global mobile and desktop traffic. Other companies that create good models still have to figure out how to promote them, while it can be deployed with one click in system-level applications, allowing users to access the latest features the next day when they open their phones.
This closed loop from chips, data, models to distribution is the real moat. Currently, there is no second company in the market that has achieved this level of vertical integration.
View Original
This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.
There is an interesting viewpoint - a certain tech giant is currently underestimated, and its true value may be close to $4 trillion. Why? Because it is currently the only player that has integrated the entire AI industry chain from underlying hardware to application.
Let’s first talk about the chips. This company manufactures its own training chips, avoiding the "intelligence tax" that other vendors pay to NVIDIA. Their TPU has already been commercialized—META and Anthropic are even discussing procurement contracts worth billions of dollars, which proves that the self-research route for hardware is not just a gimmick; it can indeed save costs and expand scale.
The data advantages are even more exaggerated. Just think about it, the world's largest search engine, video platform, map service, email system, along with browsers and mobile operating systems—these products generate user behavior data every minute, which directly feeds back into model training. While others spend money to buy data, it passively collects data. This real-time, massive, multi-scenario training corpus is something competitors simply cannot replicate.
The model capabilities are also online. Gemini 3 is fully trained based on its own chips and is now deeply embedded in all major products. Many people are concerned that AI will impact search advertising revenue, but the reality is quite the opposite—AI enhances the search experience, accelerates cloud business growth, and can also unlock monetization potential for YouTube. Each product line is becoming more competitive because of AI.
The most crucial aspect is the distribution capability. A single model update can instantly cover billions of users. Combined, entry points like Search, YouTube, Android, and Workspace essentially control the lifeblood of global mobile and desktop traffic. Other companies that create good models still have to figure out how to promote them, while it can be deployed with one click in system-level applications, allowing users to access the latest features the next day when they open their phones.
This closed loop from chips, data, models to distribution is the real moat. Currently, there is no second company in the market that has achieved this level of vertical integration.