Proliferation

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  "title": "Proliferation",
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  "lastUpdated": "2026-03-13",
  "dateCreated": "2026-02-15",
  "llmSummary": "AI proliferation accelerated dramatically as the capability gap narrowed from 18 to 6 months (2022-2024), with open-source models like DeepSeek R1 now matching frontier performance. US export controls reduced China's compute share from 37% to 14% but failed to prevent capability parity through algorithmic innovation, leaving proliferation's net impact on safety deeply uncertain.",
  "description": "AI proliferation—the spread of capabilities from frontier labs to diverse actors—accelerated dramatically as the capability gap narrowed from 18 to 6 months (2022-2024). Open-source models like DeepSeek R1 now match frontier performance, while US export controls reduced China's compute share from 37% to 14% but failed to prevent capability parity through algorithmic innovation.",
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    {
      "text": "Qwen overtook Llama in downloads 2025",
      "url": "https://www.red-line.ai/p/state-of-open-source-ai-2025",
      "resourceId": "42b42eecf63e696b",
      "resourceTitle": "open-source models closed to within 1.70%"
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      "text": "State of AI Report",
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      "resourceTitle": "State of AI Report 2025"
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      "text": "Red Line AI",
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      "resourceTitle": "open-source models closed to within 1.70%"
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      "text": "International AI Safety Report",
      "url": "https://internationalaisafetyreport.org/publication/first-key-update-capabilities-and-risk-implications",
      "resourceId": "6acf3be7a03c2328",
      "resourceTitle": "International AI Safety Report (October 2025)"
    },
    {
      "text": "Overtook LLaMA in total downloads by mid-2025",
      "url": "https://www.red-line.ai/p/state-of-open-source-ai-2025",
      "resourceId": "42b42eecf63e696b",
      "resourceTitle": "open-source models closed to within 1.70%"
    },
    {
      "text": "the gap narrowing to just 1.7% on some benchmarks by 2025",
      "url": "https://hai.stanford.edu/ai-index/2025-ai-index-report",
      "resourceId": "da87f2b213eb9272",
      "resourceTitle": "Stanford AI Index 2025"
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    {
      "text": "30% of Python code written by US open-source contributors was AI-generated in 2024",
      "url": "https://internationalaisafetyreport.org/publication/first-key-update-capabilities-and-risk-implications",
      "resourceId": "6acf3be7a03c2328",
      "resourceTitle": "International AI Safety Report (October 2025)"
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    {
      "text": "Mean downloaded model size increased from 827M to 20.8B parameters (2023-2025)",
      "url": "https://www.red-line.ai/p/state-of-open-source-ai-2025",
      "resourceId": "42b42eecf63e696b",
      "resourceTitle": "open-source models closed to within 1.70%"
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    {
      "text": "Trump administration rescinds AI Diffusion Rule",
      "url": "https://www.bis.gov/press-release/department-commerce-announces-rescission-biden-era-artificial-intelligence-diffusion-rule-strengthens",
      "resourceId": "b6939175cd95cd38",
      "resourceTitle": "BIS - Department of Commerce Announces Rescission of Biden-Era AI Diffusion Rule"
    },
    {
      "text": "Huawei will produce only 200,000 AI chips in 2025, while Nvidia produces 4-5 million",
      "url": "https://www.cfr.org/article/chinas-ai-chip-deficit-why-huawei-cant-catch-nvidia-and-us-export-controls-should-remain",
      "resourceId": "fe41a8475bafc188",
      "resourceTitle": "China's AI Chip Deficit: Why Huawei Can't Catch Nvidia"
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    {
      "text": "DeepSeek R1 generated CBRN info \"that can't be found on Google\"",
      "url": "https://www.anthropic.com",
      "resourceId": "afe2508ac4caf5ee",
      "resourceTitle": "Anthropic"
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    {
      "text": "Open-weight models closed the performance gap from 8% to 1.7% on some benchmarks in a single year",
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      "resourceId": "da87f2b213eb9272",
      "resourceTitle": "Stanford AI Index 2025"
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    {
      "text": "China's AI Safety Governance Framework 2.0 (Sep 2024)",
      "url": "https://carnegieendowment.org/research/2025/10/how-china-views-ai-risks-and-what-to-do-about-them",
      "resourceId": "4f75d2d6d47e8531",
      "resourceTitle": "AI governance framework"
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    {
      "text": "China-based models diverge on safety",
      "url": "https://carnegieendowment.org/research/2025/10/how-china-views-ai-risks-and-what-to-do-about-them",
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    {
      "text": "China's AI Safety Framework diverges from Western approaches",
      "url": "https://carnegieendowment.org/research/2025/10/how-china-views-ai-risks-and-what-to-do-about-them",
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{
  "eaForum": "https://forum.effectivealtruism.org/topics/proliferation"
}