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🔍 Research & Science
  • Research processes are supported by automated analyses, literature reviews, and experiment planning.
  • Large data sets can be searched efficiently and AI can propose new scientific hypotheses. This accelerates scientific progress; research teams work more effectively and previously unknown connections become visible.
  • Examples:
    • AI-supported literature search (e.g. Semantic Scholar): Thousands of essays and papers are found within seconds – instead of days of manual research.
    • Automatic analysis of lab data: Saves time in complex measurement series by automatic evaluation (often several hours per day).
    • Simulation of experiments and hypothesis generation: AI suggests promising experiments before they are performed in the lab – massively reduces preparation time.
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