PART 4 looks at the industry and infrastructure required for AI to actually be developed and operated.
AI development requires not only data, but also various resources such as GPUs and AI semiconductors, electricity, data centers, and specialized personnel. In addition, the way companies make AI technology publicly available or keep it closed also affects the AI ecosystem and industry competition.
In this PART, we will look step by step at the resources and infrastructure that make AI possible, as well as the structure of the AI industry.
#20. What Resources and Investment Does It Take to Build AI?
(The Reality of AI Development: Data, GPUs, Electricity, Talent, and More)
#21. Why Did GPUs Become Essential in the AI Era?
(A Core Resource for AI Computing)
#22. How Is an AI Data Center Different from a General Data Center?
(GPU, Networks, Power, Cooling, and AI Infrastructure)
23. Why Do Companies Make Their AI Open?
(AI Model Disclosure Scope and Corporate Choices)
#24. Do Companies Build Their Own AI Infrastructure or Use External Infrastructure?
(In-House Data Centers, Cloud, and External Infrastructure)
