Konstantine Buhler, a partner at Sequoia USA, recently gave a speech titled "The 10 Trillion AI Revolution," which is worth watching for the trillion dollar artificial intelligence revolution. Key points of speech: 1. Industry stage judgment The Industrial Revolution took 211 years to complete the refinement of the "steam engine → factory → assembly line"; The AI revolution has now only reached the stage of "GPU steam engine → deep learning factory", and the next scene is "dedicated assembly line" - AI dedicated systems for vertical scenarios will replace today's general large models and become the birthplace of new monopolists. 2. Market size reassessment The AI service market is not 20 billion, but 10 trillion US dollars (Sequoia directly adds up the "number of replaced professions multiplied by annual salary"). SaaS in the cloud era has boosted the software market from 350 billion to 650 billion; The AI era will recalculate all "human services" today, and the boundaries will be extrapolated as a whole. 3. The five major trends determine the playing style 1) Productivity leverage: 100 times efficiency for reduced controllability → Products must make "human-machine verification" the default workflow. 2) The evaluation criteria for the laboratory are: real business indicators>academic benchmarks, and the scenario "arena competition" should be conducted first. 3) Practical application of reinforcement learning: RL is no longer just a paper, but a core formula, whoever retrieves "RL+vertical data" first wins. 4) AI enters the physical world: After the software dividend is exhausted, hardware manufacturing, quality inspection, logistics, and robotics are the next 10 x depressions. 5) The new production function of computing power: FLOPs/person x 10-10000 times growth, inference efficiency and safety are invisible billions of market. 4. The 5 tracks currently being held by Sequoia 1) Persistent memory (long-term memory+identity consistency) 2) Seamless Communication Protocol (TCP/IP for AI to AI) 3) AI voice (landing faster than video, the most lucrative B2B scheduling/trading scenario) 4) AI security (three-layer protection of research and development, distribution, and terminal, can be used as a standardized product for "security agents") 5) Open source competitiveness (preventing giants from locking in the ecosystem, continuously investing in open source models and toolchains) 5. One sentence action list for entrepreneurs Step 1: Choose a vertical human resources track with an annual salary multiplied by the number of employees exceeding $50 billion; Step 2: Train a "small model" using RL+proprietary data, and first achieve world first on a real KPI; Step 3: Incorporate "persistent memory+multi-agent collaboration" into the product, allowing users to directly hire an AI team; Step 4: Replace the 50% cost savings with a new business model that charges based on results; Step 5: Feed business data back into the model within 18 months to form a data flywheel, achieving 10 times the efficiency difference of competitors - that is your "dedicated pipeline". 15 keywords Specialization, 10 trillion yuan substitution cost, RL engineering, AI physicalization, FLOPs production function, persistent memory, AI voice entrance, security agent, open source moat, real KPI competition, data flywheel, vertical small model, human-machine verification workflow, billing by results, efficiency difference x 10. Speech link: https://www. (youtube.com)/watch? v=yoycgOMq1tI