This article explains the computing resources essential for generative AI.
Key Points
1. Definition of Computing Resources
- Foundational technologies including computer processing power, storage, and networks necessary for digital processing such as AI
- Generative AI training requires parallel computing capabilities that can process massive data quickly and efficiently
- The core component is the GPU (Graphics Processing Unit)
- US company NVIDIA's GPUs maintain high global market share
2. Importance of Computing Resources in Generative AI
- Training phase: Requires enormous computing power to process large-scale datasets
- Usage phase: Continuous inference processing to respond immediately to user inputs
- Securing and optimizing computing resources directly impacts AI performance, response speed, and costs
- A critical factor determining corporate and national competitiveness
3. Ministry of Economy, Trade and Industry's Initiatives
- Managed by the Information Processing Infrastructure Industry Office, Information Industry Division
- Deploying related measures through the policy feature "AI ni Ai wo" (Love for AI)
- Recognizes securing computing resources as key to Japan's AI industry development
The article concludes that computing resources are not merely technical elements but strategic infrastructure supporting the foundation of generative AI development and operations.