Neo Cloud

Neo cloud is the AI-native GPU-cloud model discussed in E230｜1万亿收入预期背后：英伟达的巅峰与软肋. [[AlexGMICloud|Alex]] contrasts neoclouds with hyperscalers: hyperscalers grew from CPU and storage cloud and often expose VM-oriented abstractions, while neoclouds are more likely to use k8s clusters and bare-metal access to preserve GPU efficiency.

The concept belongs under MaaS Infrastructure because customers are not only renting machines. In the source, a stronger neocloud offers earlier Nvidia GPU access, cluster management, model services, and kernel optimization so AI teams can convert accelerators into useful training and inference capacity.

Key Claims

• Neoclouds compete on AI workload fit rather than generic cloud breadth.
• Bare-metal efficiency can matter when virtualization overhead reduces expensive GPU utilization.
• K8s cluster management, model services, and kernel optimization can turn raw hardware into a more defensible product.
• Neoclouds still face [[DataCenterPowerBottleneck|land and power]], supply-chain, and SLA constraints.

Connections

• GMI Cloud, [[AlexGMICloud|Alex]], and GPU Cloud Operations - source case and operating requirements.
• Nvidia, GPU, and AI Infrastructure Full-Stack Moat - hardware and ecosystem context.
• MaaS Infrastructure, AI Compute Continuity, and Strategic AI Infrastructure Dependence - platform and dependence frame.