云启资本

云启资本

@yunqipartners

科技常新，寻找未来开创者

534 articles18 episodes

Articles

Quick Take on OpenAI's New Models: o3, o4-mini — What Can Image Reasoning + Autonomous Tools Bring? | Yunqi Tech π

Quick Take on OpenAI's New Models: o3, o4-mini — What Can Image Reasoning + Autonomous Tools Bring? | Yunqi Tech π

In the early hours of April 17 Beijing time, OpenAI released two new AI reasoning models, o3 and o4-mini. These are likely the last standalone AI reasoning models before GPT-5, with further improvements in both performance and cost efficiency. In this episode of **"Yunqi Tech π"**, we break down the details for you.

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Dissecting LLMs in Cars: How to Turn Automobiles Into "Thinking" Robots? | Yunqi Capital Attent!on Podcast

Dissecting LLMs in Cars: How to Turn Automobiles Into "Thinking" Robots? | Yunqi Capital Attent!on Podcast

AI technology continues to leap forward, and our daily lives — what we wear, eat, live in, and how we get around — are being profoundly reshaped by this technological storm. In the mobility sector in particular, a new wave of intelligent vehicle evolution, driven by "large models hitting the road," is now in full swing.

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Still in Between Startups? Maybe It's Time to Talk to Someone | Yunqi Capital × Shanghai Jiao Tong University Engineering Research Institute "Finding Next-Gen AI Founders" — Now Open for Registration

Still in Between Startups? Maybe It's Time to Talk to Someone | Yunqi Capital × Shanghai Jiao Tong University Engineering Research Institute "Finding Next-Gen AI Founders" — Now Open for Registration

Whether in technological innovation or commercial exploration, AI is the most striking blue ocean of the moment.

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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·