@berryxia: Moonshot AI founder Yang Zhilin recently released a 40-minute video. Born in 1992, valedictorian of Tsinghua CS undergrad, PhD from CMU, co-author of Transformer-XL and XLNet, former researcher at Google Brain and Meta, he calmly deconstructs Kimi K2 in front of the camera...

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Summary

Moonshot AI founder Yang Zhilin released a 40-minute video detailing the training process of the Kimi K2 model, which cost only $4.6 million. In an 8-model real-time programming competition, Kimi K2 took first place, defeating GPT-5.5 and others, demonstrating how a small team can overturn the traditional compute-stacking paradigm through architecture optimization.

Moonshot AI founder Yang Zhilin recently released a 40-minute video. Born in 1992, valedictorian of Tsinghua CS undergrad, PhD from CMU, co-author of Transformer-XL and XLNet, former researcher at Google Brain and Meta, he calmly deconstructs the entire training process of Kimi K2 in front of the camera. They spent only $4.6 million. Last week, in an 8-model real-time programming battle, Kimi K2 directly took first place, GPT-5.5 came third, and Claude Opus 4.7 fifth. After watching it, my biggest takeaway is that the rules of the AI race have quietly changed. Everyone is still competing over who can burn more money and stack more compute, but he used hardcore architectures like extreme optimization, linear attention, and sub-agents to directly level the resource gap or even overtake. 40 minutes of pure substance, zero fluff, explaining the key tactics clearly. If you are working on AI agents or planning to enter the large model track in 2026, I strongly recommend saving this video to watch slowly over the weekend. Small teams, with smart architecture, are gradually overturning the traditional playbook of big companies. Do you still think that only by throwing money can you win?
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