The correct answer is B because edge AI performs computation near where the data is created instead of sending everything to a centralized cloud or data center. NVIDIA explains that edge AI is called “edge AI” because “the AI computation is done near the user at the edge of the network, close to where the data is located, rather than centrally in a cloud computing facility or private data center.” NVIDIA’s edge computing page also states that edge devices collect data and that bringing AI to those devices lets edge computing “process this data locally,” reducing the need to transmit it to the cloud or data center and enabling real-time decision-making.
Why the other options are incorrect: Edge AI does not eliminate network management. It also does not rely solely on CPUs; NVIDIA edge AI commonly uses GPUs and accelerated computing. Edge deployments do not necessarily require higher-capacity GPUs at every site; the defining characteristic is local or near-source processing.
[Reference: NVIDIA Blog — What Is Edge AI and How Does It Work?; NVIDIA Edge Computing Solutions., ]
