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  "documentTitle": "2025 Bond Cap Artificial Intelligence AI 2025",
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  "notes": "The chart uses a timeline axis at the bottom to map specific models (ProGen, ProtBert, ProGen 2, Prot5, ESM2, ESM3) to their release years.",
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      "text": "The past year has witnessed remarkable progress in AI models applied to protein sequences.",
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      "text": "Number of Parameters: 98B",
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      "text": "Per Stanford HAI (4/25): The past year has witnessed remarkable progress in AI models applied to protein sequences. Large-scale machine learning models have improved our ability to predict protein properties, accelerating research in structural biology and molecular engineering... These AI-driven approaches have transformed protein science by minimizing reliance on costly, time-intensive experimental methods, enabling rapid exploration of protein function and design.",
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      "text": "Note: List of models may not be comprehensive. Source: Stanford RAISE Health via Nestor Maslej et al., 'The AI Index 2025 Annual Report,' AI Index Steering Committee, Stanford HAI (4/25)",
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      "text": "Next AI Use Case Frontier – Protein Sequencing = Model Size +290% Annually to 98 Billion Parameters Over Four Years",
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      "text": "Size of Major Protein Sequencing Models (B Parameters) – 2020-2024, per Stanford RAISE Health",
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