AI is a five layer cake, which layer would you like to eat? The official article from Nvidia is worth reading carefully, and the division of the five layer industrial stack is also very clear. Sort out the key points: 1. The essential positioning of AI 1) AI is not simply a "smart app" or a single model, but a core infrastructure like electricity and the Internet. 2) AI relies on real hardware, real energy, and real economy: it transforms raw materials into large-scale intelligence that every company will use and every country will build. 2. Fundamental shift in computing paradigm 1) In the past, computing was a "pre recorded software": humans wrote algorithms, structured data, and used SQL queries. 2) AI has completely broken through: it can understand unstructured information (images, text, sound, meaning), generate new intelligence in real-time based on context, no longer retrieve old instructions, but reason in real-time. 3. Five layer industrial stack of AI (core framework) Nvidia compares AI to a 'five layer cake', where each layer pulls on each other: 1) Energy is the bottom layer: real-time generation of intelligence requires real-time power generation, and energy is the first principle and ultimate bottleneck. 2) Chips: Efficiently converting energy into large-scale parallel computing determines how quickly and inexpensively AI can scale. 3) Infrastructure: AI factories (land, power supply, heat dissipation, network), not storing data, but manufacturing intelligent factories. 4) Models: Understanding various fields such as language, biology, chemistry, physics, finance, robotics, etc. (not just language models). 5) Applications: Creating economic value: drug discovery, industrial robots, autonomous driving, humanoid robots, etc. Key formula: Successful application → Pull all levels below until reaching the power plant. 4. Current stage and future scale 1) We have just started (with billions of dollars invested), and in the future, we will need trillions of dollars for infrastructure construction - the largest scale infrastructure project in human history. 2) Create a large number of non coding agricultural jobs: electricians, plumbers, steel workers, network technicians, etc., with high salaries and high demand (no need for computer PhDs). 3) AI enhances productivity (such as radiologists), but instead creates more jobs as production capacity expands and demand grows. 5. Key turning points in the past year 1) The model has reached the threshold of "scale availability": improved reasoning ability, reduced hallucinations, and significant improvement in grounding. 2) Open source models such as DeepSeeker R1 greatly accelerate full stack demand (application layer explosion → chip/energy pull). 3) The actual economic value has been demonstrated in fields such as drug discovery, logistics, customer service, software development, and manufacturing. 6. Final revelation 1) AI is an industrial revolution level transformation that reshapes energy production, factory construction, work methods, and economic growth. 2) Every country and every company must participate; Who controls the entire stack (especially the underlying energy chips), who defines this century. 3) We are still in the early stages: infrastructure, labor, and opportunities are far from fully unleashed, but the direction has been set. Nvidia has redefined AI from a "technology toy" to a "national level industrial infrastructure", emphasizing that "full stack construction" is the core of future competition, and calling for accelerated global layout (of course, also paving the way for its own chip and AI factories).