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This is the most important chart to understand right now as an AI investor There are 3 waves of token consumption. Each wave is bigger than the last, and we're only just starting wave 2 Wave 1: Chat Wave 2: Agents Wave 3: Physical AI (humanoids, robotaxis) Token usage is expected to multiply 24 TIMES by 2030, with enterprise agents alone burning ~120 quadrillion tokens/month The growth in chat is limited from here, but that's ok because wave 2 has already kicked off and its accelerating extremely fast right now Wave 2 is Agents that work continuously instead of answering one prompt at a time, enterprises deploy them by the thousand, and consumer agents (the new Siri, Gemini on Android) haven't even shipped at scale yet. That's the 24x, and it's why compute, memory and power demand keeps accelerating through 2030 But wave 3 is the real kicker and it crushes everything else. This is the part that isn't in many of the models today. Physical AI: Humanoids, robotaxis, autonomous machines. Expected to be the biggest consumer by 2030 and reach 400 quadrillion tokens a month by 2040, the biggest of every category on the chart And here's why wave 3 is different for infra investors: it pays the infra stack TWICE. Every robot runs inference around the clock (tokens), and every robot IS hardware itself too. A humanoid carries roughly 10x the memory of an advanced car, plus the sensors, chips and power systems. Wave 3 demand shows up in tokens AND in physical components As I've said many times before, the demand for compute and AI infra is infinite becuase the demand for intelligence is infinite. As the form factors we use intelligence continue to grow, the demand does too The sooner you understand this, the sooner it becomes easier to learn how to invest in it. or to make it even easier, you can track my real-time portfolio and 4 other analysts' with live trade notifications and research inside Milk Road PRO. It's just $1 to try it out right now, learn more here: If you enjoyed this, give me a follow @kylereidhead for more insights on AI and markets

North-Micro-Vision-Instruct：多模态小模型 Cohere开源，仅2.4B参数，适合OCR、图片描述、视觉定位等任务，不适合复杂推理任务。评分比不上Qwen3.5-2B，Qwen在小模型领域几乎垄断领先。 模型：

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