(Google CEO)

The underlying logic is that high-end computing will become a scarce future resource, and only those who build their own supply chains will survive. However, the market has reacted strongly—every company announcing huge spending has seen its stock price drop immediately, with higher investments correlating to steeper declines.

This is not just a problem for companies without a clear AI strategy (like Meta). Even firms with mature cloud businesses and clear monetization paths, such as Microsoft and Amazon, are facing pressure. Expenditures reaching hundreds of billions of dollars are testing investor patience.

While Wall Street’s nervousness may not alter the tech giants’ strategic direction, they will increasingly need to downplay the true cost of their AI ambitions. Behind this computing power contest lies the ultimate between technological innovation and capital’s patience.

Roger Luo said:The current AI computing power race has transcended mere technology, evolving into a capital-intensive strategic game. While giants are betting that computing power equals dominance, they must guard against the potential pitfalls of heavy-asset models—capital efficiency traps and innovation stagnation.

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(Google Cloud Announces General Availability of Confidential Computing)

MOUNTAIN VIEW, Calif. — Google Cloud announced Confidential Computing is now generally available. This technology offers businesses stronger data protection. It protects sensitive information while it is being processed. Data usually needs decryption for processing. Confidential Computing changes this. It keeps data encrypted even during use. This happens inside secure hardware areas. These secure areas are called Trusted Execution Environments (TEEs).

This extra layer of security matters greatly. Many industries handle extremely sensitive data. Healthcare, finance, and government sectors are examples. They need stronger safeguards against threats. Threats include unauthorized access or compromised infrastructure. Confidential Computing helps mitigate these risks. Customers control access to their data. Even cloud operators cannot see it during processing.

Google Cloud offers Confidential Computing across its services. Confidential Virtual Machines (VMs) are a key part. Confidential VMs work with leading CPUs. AMD EPYC and Intel® Xeon® Scalable processors support them. Confidential GKE Nodes also use this technology. They protect Kubernetes workloads. Google Cloud’s managed services benefit too. BigQuery and Cloud SQL can leverage Confidential Computing.

“Data security remains a top priority for every organization,” said June Yang, VP, Cloud Infrastructure, Google Cloud. “Confidential Computing provides a fundamental shift. It protects data during a critical phase. This phase is computation. We are empowering customers. They can operate more securely in the cloud. This applies especially to sensitive workloads.”

Customers are already using Confidential Computing. It helps with tasks like processing financial records. Analyzing healthcare data securely is another use case. Running confidential AI models is possible too. Early adopters report significant benefits. They gain enhanced security assurances. Compliance requirements become easier to meet. They can move sensitive projects to the cloud confidently.

(Google Cloud Announces General Availability of Confidential Computing)

Google Cloud collaborated with key partners. AMD and Intel provided essential hardware capabilities. The Confidential Computing Consortium also played a role. They helped drive open standards development. This ensures broader ecosystem compatibility. The general availability marks a major step. It makes advanced data-in-use protection accessible. Businesses of all sizes can now use it on Google Cloud.