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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential
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largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing applications. As AI models continue to increase in size and computational complexity
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and transparency for different stakeholders? How can privacy-preserving mechanisms and AI-assisted data engineering support secure and efficient data sharing while fostering trust and responsible data
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