DeepSeek 🤯
TL;DR DeepSeek’s January 2025 release of R1 shook markets - a frontier-grade reasoning model trained for a reported $6M, a fraction of US lab budgets The app shot to #1 on Apple’s App Store inside days, and the open weights forced an industry-wide rethink of what training really costs Subsequent releases (V3 and beyond) cemented DeepSeek as a serious competitor in the open-source and cost-efficient AI category The story is less “China caught up” and more “the cost floor moved” - implications for closed-model pricing, GPU demand, and open-weight strategy Worth understanding as the moment that made cheap, capable, open models a credible default rather than a curiosity Overview In January 2025, a Chinese AI lab most people had never heard of dropped a frontier-grade reasoning model for a reported $6 million and watched it hit the top of the Apple App Store inside days. DeepSeek R1 did not just impress researchers - it shook equity markets, forced a hard look at what US labs were actually spending their billions on, and made cheap, capable, open-weight models a credible default rather than an interesting curiosity. ...