云启资本

Interview with a Pioneer of Open-Source Commercialization: How Programmers Question Sales, Understand Sales, and Become Sales

Now is the best time to pay attention to "open-source commercialization."

Founding Partner Chenyu Mao Ranks No. 4 on "China's Top Angel Investors" List | Yunqi Capital Update

Focus on the long term, keep digging deep.

A Deep Dive into 70 Years of Optical Computing: What New Breakthroughs Await Beyond Moore's Law? | Yunqi Science --- In 1965, Gordon Moore, then director of the R&D laboratory at Fairchild Semiconductor, published an article in *Electronics* magazine titled "Cramming More Components onto Integrated Circuits." In it, he made a bold prediction: the number of transistors on an integrated circuit would double approximately every year, with computing power growing exponentially while costs declined. This observation, later refined to a doubling every 18–24 months, became the famous "Moore's Law" that has driven the semiconductor industry for nearly six decades. However, as transistor sizes approach the atomic scale, the physical limits of silicon-based electronic computing are becoming increasingly apparent. Heat dissipation, quantum tunneling effects, and manufacturing costs are all pushing traditional computing toward a wall. In this context, optical computing — using photons instead of electrons as information carriers — has emerged as one of the most promising paths beyond Moore's Law. This article traces 70 years of optical computing development, examining its technical principles, key breakthroughs, and the new frontiers it may open in the post-Moore era. ## The Physical Advantages of Photons Why light? The answer lies

"The Future Computer" will have a computing architecture composed as follows —

How Has "Digital-Intelligent Transformation" Delivered on Cost Reduction and Efficiency Gains for Traditional Textile Manufacturing? | YunXun

When "Demand-Driven Production" Becomes Reality

Eight Yunqi Capital Portfolio Companies Named to *Hurun China Under 35s / Under 40s Entrepreneurs to Watch 2023* | Yunqi Capital News

Deep industry expertise, real value creation.

Live from OpenAI's Developer Conference: GPT Dead Last? | Yunqi Capital Tech Talk

What's more important is...

Jina AI Launches World's First Open-Source 8K Vector Model | Cloud News · Open Source

Currently, only two AI technology companies — OpenAI and Jina AI — have released 8k embedding models.

What Are the 5 Critical Questions for Making Open Source Commercialization Work? | Yunqi Capital × China Open Source Conference

AGI and Globalization Are Changing Open Source — Here's How

First "Global Open Source Contribution Ranking" Released, Three PingCAP Co-Founders Make the List | Cloud News · Open Source

Ranked solely by contribution.

"Inside Google": During 10 Hours of Deep Conversation Across Silicon Valley and Shanghai, What New AGI Trends Did We Discuss? | FutureScope

Six Emerging Trends in AGI from a Global Perspective

Vol.18 The Non-Sci-Fi Story of Brain-Computer Interfaces: From Top-Tier Hospitals to Home Bedrooms, How Many Steps to Rebuild Prefrontal Order? | A Conversation with Ximing Wang of Kongshan Ci

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.16 Tsinghua Entrepreneur-Scientist Huazhe Xu: From Intelligent "Hatching" to Home Embodiment, Stubbornly Chasing Originality in the AI Wave

Vol.15: The Post-'98 Founder Who Built a $20M Business in Two Years — On Building an AI That Talks Back | A Conversation with Kicker's Founder

Vol.14 OpenClaw Is Just the Beginning: Are Agents Reinventing the Company? | A Conversation with Happycapy's Founder

Vol. 13 The Smarter AI Social Gets, the More Human We Become Like NPCs? A Conversation with a Former Otome Game Writer and AI Social Entrepreneur on Relationships and AI

Vol.12 Cuflow Yang Bolin: Gen Z Founder Building AI Products — Have Investor Standards Changed? | Y Transformers

Vol.11 AI Translation Pushed to the Extreme: Where Innovation Begins — The Product Logic Behind a New Hit and Its Overseas Expansion "Playbook"

Vol.10: Do Robot Woks Make Pre-Made Meals? A Conversation with Geng Kaiping of ZhiGu TianChu

Vol.09 How Should Search Engines Work in the Agent Era? A Conversation with Yu Chen and Zhiheng Du on AI "New Infrastructure"