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This article is the first part of the AI Engineering Panorama series. From a historical perspective, it reviews the evolution of GPUs from gaming graphics cards to AI accelerators, the bold bet of CUDA, the independent path of Google's TPU, and why NVIDIA ultimately prevailed. It also provides a detailed analysis of the underlying logic of AI infrastructure such as chips, supply chain, networking, and power.
An analysis of DeepSeek AI's unconventional strategy: prioritizing radical architecture innovations (MoE, MLA, engram, mHC) that drastically reduce compute and memory needs, enabling a long-term play to build a 10T Chinese AI hardware ecosystem and pursue a 1T valuation.