What is the difference between an AI workstation and a regular workstation?

An AI workstation is designed to support AI workloads, with high-performance GPUs and ample memory to facilitate the training of AI models. A regular workstation is more suitable for general work such as video editing and programming, but does not have the necessary GPU power and architecture to handle intensive AI processing.

Can an AI workstation replace cloud computing?

No, an AI workstation is not a substitute for cloud computing, as both are dedicated to different tasks. AI workstations are suitable for rapid local processing, enhanced data privacy, and routine AI development tasks, while cloud platforms remain essential for large-scale training, scalability, and global deployment of AI applications.

What is an NPU, and why does it matter for AI workstations?

An NPU is a specialized processor chip designed to accelerate AI tasks and applications, incorporated into modern workstation processors. Unlike CPUs or GPUs, NPUs are optimized for neural network operations, especially inference. They enable faster on-device AI inference, local LLM execution, and energy-efficient AI feature processing compared to traditional CPU or GPU workloads.

What is the difference between an AI workstation and an AI server?

An AI workstation is optimized for a single user or small group and is designed for desktop interactive development. An AI server is shared infrastructure used by multiple users, typically rack-mounted, managed by IT teams, and designed for horizontal scalability. Workstations are best for daily development tasks, while servers are ideal for multi-user labs and large-scale training workloads.