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Machine Learning and Artificial Intelligence to Advance Earth System Science Opportunities and Challenges: Proceedings of a Workshop (2022) / Chapter Skim
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Appendix A: Statement of Task
Pages 49-50

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From page 49...
... and ethical implications; o The interface of ML/AI with existing and emerging hardware, software, tools, and approaches; o Workforce capacity and skill sets; and o Data requirements and limitations. • Identify future opportunities to accelerate progress, such as: o Novel funding mechanisms and partnerships; and o Potential disruptions that could lead to rapid scientific, societal, and/or institutional progress.
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Key Terms

  • review current
  • potential disruptions
  • funding mechanisms
  • novel funding
  • interpreting results

  • integrating physics
  • workforce capacity
  • identify future
  • bridging research
  • current applications

  • results produced
  • skill sets
  • support decisionmaking
  • expert knowledge
  • enrich models

  • future opportunities
  • rapid scientific
  • emerging hardware
  • institutional progress
  • ethical implications

  • survey emerging
  • improving understanding
  • consider challenges
  • data requirements
  • ml models

  • specific topics


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