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  "documentTitle": "2025 Air Street Capital The State of AI Report 2025",
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  "authorName": "Air Street Capital",
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  "notes": "Data source: Zeta Alpha. Chart shows delta vs corpus in percentage points.",
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      "kind": "callout",
      "text": "Clear patterns pop out: big LLM work clusters on datacenter parts, while robots and edge devices overwhelmingly use the Jetson.",
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      "text": "Largest positive and negative chip topic skews",
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      "text": "LLMs love datacenter GPUs: AMD MI300 is the standout for LLM papers (+43 pp vs average), with MI250, Huawei Ascend, and NVIDIA H100/H200 also common. LLMs are least tied to ASICs, Jetson, 4090, and Apple M1.\nThe Jetson dominates robotics and edge computing and also shows up in computer vision.\nModalities have their own favorites: Apple M4 skews to multimodal and speech work while the RTX 4090 is most used for 3D models.\nFPGAs are rarely used with diffusion models and RL.",
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      "text": "Delta vs corpus (pp): 43",
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      "kind": "paragraph",
      "text": "We tagged 6,356 papers (January to June 2025) by topic and looked at which accelerator each paper cited. Clear patterns pop out: big LLM work clusters on datacenter parts, while robots and edge devices overwhelmingly use the Jetson. A few consumer and mobile chips also anchor specific niches.",
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      "kind": "title",
      "text": "What chips power which research? Topic skews by accelerator (H1 2025)",
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      "evidence": "'Challengers no closer to catching NVIDIA' (p.162); $7.5B in challengers vs $85B in NVIDIA stock (p.167).",
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