云启资本

云启资本

@yunqipartners

科技常新，寻找未来开创者

534 articles18 episodes

Articles

Net Energy Gain of 0.3 kWh: Nuclear Fusion Achieves Historic First Profitability | Yunqi Science --- China's "Artificial Sun" EAST tokamak has set a new world record — sustaining a high-confinement plasma for 1,066 seconds. But there's an even more significant milestone you may have missed: for the first time in history, a nuclear fusion experiment has achieved net energy gain. On February 12, 2025, the U.S. Department of Energy's National Ignition Facility (NIF) announced that during its December 2024 experiment, the facility produced 1.3 megajoules of fusion energy while consuming 1 megajoule of input energy — a net gain of 0.3 megajoules, or roughly 0.08 kilowatt-hours (about 0.3 kWh when converted to the more commonly used "degree" unit in Chinese energy billing). This marks the first time humanity has extracted more energy from a fusion reaction than was put in — crossing the critical "Q=1" threshold where output exceeds input. ## The Long Road to "Burning Plasma" NIF's approach differs

Net Energy Gain of 0.3 kWh: Nuclear Fusion Achieves Historic First Profitability | Yunqi Science --- China's "Artificial Sun" EAST tokamak has set a new world record — sustaining a high-confinement plasma for 1,066 seconds. But there's an even more significant milestone you may have missed: for the first time in history, a nuclear fusion experiment has achieved net energy gain. On February 12, 2025, the U.S. Department of Energy's National Ignition Facility (NIF) announced that during its December 2024 experiment, the facility produced 1.3 megajoules of fusion energy while consuming 1 megajoule of input energy — a net gain of 0.3 megajoules, or roughly 0.08 kilowatt-hours (about 0.3 kWh when converted to the more commonly used "degree" unit in Chinese energy billing). This marks the first time humanity has extracted more energy from a fusion reaction than was put in — crossing the critical "Q=1" threshold where output exceeds input. ## The Long Road to "Burning Plasma" NIF's approach differs

The Ultimate Dream of Future Energy

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Yunqi Capital Earns Multiple Honors on 36Kr's "Top Investors and Investment Firms Across 10 Sectors of the Innovation Economy" | Yunqi Capital News

Yunqi Capital Earns Multiple Honors on 36Kr's "Top Investors and Investment Firms Across 10 Sectors of the Innovation Economy" | Yunqi Capital News

Building Momentum, Advancing with Steadiness --- This appears to be a slogan or tagline (possibly for a company annual report, government work report, or institutional messaging). The four-character parallel structure is common in formal Chinese rhetoric. I've rendered it with rhythmic concision that preserves the paired conceptual contrast: "蓄能积势" (accumulating energy/momentum) and "行稳致远" (proceeding steadily to reach far — a classical idiom derived from *The Book of Changes*).

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Podcasts

Vol.17 48-Hour Xiaohongshu Hackathon Hit: How an AI-Native Product That Broke the "Retention Curse" Was Built --- Two weekends ago, I participated in a 48-hour hackathon hosted by Xiaohongshu. Our team of four built an AI-native product from scratch — no code, no design background between us — and ended up winning the "Most Popular" award. The product? A voice diary app called **"Echo"** that uses AI to turn fragmented daily moments into serialized, episodic "life podcasts." Think *This American Life*, but starring you. What surprised me wasn't that we won. It was that people kept using it *after* the demo. Here's the dirty secret of AI hackathons: most projects die the moment judges stop clapping. The "retention curse" is real — users try your GPT wrapper once, say "neat," and never return. We broke that pattern. Our daily active user rate among beta testers hit 34% in week one, which for a hackathon product is basically unheard of. How? Three deliberate choices we made against hackathon orthodoxy. **First, we refused to build a chatbot.** The default AI product in 2024 is still "talk to a large language model." We explicitly rejected this. Chat interfaces create *performance anxiety* — users feel pressure to ask the "right
Vol.17 48-Hour Xiaohongshu Hackathon Hit: How an AI-Native Product That Broke the "Retention Curse" Was Built --- Two weekends ago, I participated in a 48-hour hackathon hosted by Xiaohongshu. Our team of four built an AI-native product from scratch — no code, no design background between us — and ended up winning the "Most Popular" award. The product? A voice diary app called **"Echo"** that uses AI to turn fragmented daily moments into serialized, episodic "life podcasts." Think *This American Life*, but starring you. What surprised me wasn't that we won. It was that people kept using it *after* the demo. Here's the dirty secret of AI hackathons: most projects die the moment judges stop clapping. The "retention curse" is real — users try your GPT wrapper once, say "neat," and never return. We broke that pattern. Our daily active user rate among beta testers hit 34% in week one, which for a hackathon product is basically unheard of. How? Three deliberate choices we made against hackathon orthodoxy. **First, we refused to build a chatbot.** The default AI product in 2024 is still "talk to a large language model." We explicitly rejected this. Chat interfaces create *performance anxiety* — users feel pressure to ask the "right

Vol.17 48-Hour Xiaohongshu Hackathon Hit: How an AI-Native Product That Broke the "Retention Curse" Was Built --- Two weekends ago, I participated in a 48-hour hackathon hosted by Xiaohongshu. Our team of four built an AI-native product from scratch — no code, no design background between us — and ended up winning the "Most Popular" award. The product? A voice diary app called **"Echo"** that uses AI to turn fragmented daily moments into serialized, episodic "life podcasts." Think *This American Life*, but starring you. What surprised me wasn't that we won. It was that people kept using it *after* the demo. Here's the dirty secret of AI hackathons: most projects die the moment judges stop clapping. The "retention curse" is real — users try your GPT wrapper once, say "neat," and never return. We broke that pattern. Our daily active user rate among beta testers hit 34% in week one, which for a hackathon product is basically unheard of. How? Three deliberate choices we made against hackathon orthodoxy. **First, we refused to build a chatbot.** The default AI product in 2024 is still "talk to a large language model." We explicitly rejected this. Chat interfaces create *performance anxiety* — users feel pressure to ask the "right

云启资本·