{"version":"v1","site":{"name":"expectedwrong","url":"https://expectedwrong.com"},"links":{"collection":"https://expectedwrong.com/api/public/posts","rss":"https://expectedwrong.com/rss.xml","llms":"https://expectedwrong.com/llms.txt"},"post":{"slug":"deepseek-r1-nuked-the-moat","title":"A Chinese Lab Just Nuked the Moat","subtitle":"DeepSeek R1 dropped four weeks ago and the vibes have not recovered.","url":"https://expectedwrong.com/deepseek-r1-nuked-the-moat","api_url":"https://expectedwrong.com/api/public/posts/deepseek-r1-nuked-the-moat","published_at":1739880000,"published_at_iso":"2025-02-18T12:00:00.000Z","updated_at":1771552879,"updated_at_iso":"2026-02-20T02:01:19.000Z","tags":["ai","deepseek","llm","compute","open-source"],"excerpt":"DeepSeek R1 dropped four weeks ago and the vibes have not recovered.","meta_description":"DeepSeek R1 dropped four weeks ago and the vibes have not recovered.","reading_time_minutes":2,"word_count":221,"engagement":{"signals":0,"counterpoints":0},"body_markdown":"Four weeks ago a Chinese lab released a reasoning model that matches o1, costs almost nothing to run, and is fully open. Nvidia lost six hundred billion dollars in market cap in a single day. The stock recovered. The implications did not.\n\nThe thing that's hard to sit with — and this is the \"oh dang\" part — is that the entire Western AI investment thesis was predicated on compute being the moat. You need the clusters. You need the chips. You need the billions. Turns out you need a team of researchers willing to think carefully about efficiency, which is a different resource entirely and one that doesn't show up on a balance sheet.\n\nThe \"haha\" part is watching the people who spent three years explaining why scale was destiny now explaining why this, actually, proves their point about scale — just in a different direction — if you think about it correctly — from a certain angle —\n\nThey trained it on synthetic data generated by a bigger model. The bigger model is American. So in some sense we're here.\n\nWe are genuinely at a moment where nobody knows what the next four weeks look like, let alone four years. That's not a complaint. It's just the thing that's true right now, in February 2025, before whatever happens next.","body_text":"Four weeks ago a Chinese lab released a reasoning model that matches o1, costs almost nothing to run, and is fully open. Nvidia lost six hundred billion dollars in market cap in a single day. The stock recovered. The implications did not. The thing that's hard to sit with — and this is the \"oh dang\" part — is that the entire Western AI investment thesis was predicated on compute being the moat. You need the clusters. You need the chips. You need the billions. Turns out you need a team of researchers willing to think carefully about efficiency, which is a different resource entirely and one that doesn't show up on a balance sheet. The \"haha\" part is watching the people who spent three years explaining why scale was destiny now explaining why this, actually, proves their point about scale — just in a different direction — if you think about it correctly — from a certain angle — They trained it on synthetic data generated by a bigger model. The bigger model is American. So in some sense we're here. We are genuinely at a moment where nobody knows what the next four weeks look like, let alone four years. That's not a complaint. It's just the thing that's true right now, in February 2025, before whatever happens next.","hindsight":{"verdict":"persists","note":"The moat was nuked. The \"haha\" of watching scale-is-destiny people explain why efficiency proves their point is still playing out. Compute was not the moat. Careful thinking was.","links":[],"at":1739980800,"at_iso":"2025-02-19T16:00:00.000Z"}}}