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JBS Dev: On imperfect data and the AI last mile – from model capability to cost sustainability

Joe Rose, president of JBS Dev, argues that imperfect data is not a barrier to AI adoption. He shares a medical sector case where generative AI and agentic approaches handled messy records, emphasizing human oversight. Future trends: cost sustainability and running models on edge devices.

SourceArtificial Intelligence NewsAuthor: AI News
JBS Dev: On imperfect data and the AI last mile – from model capability to cost sustainability
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Under the source content permission, this page provides an editorial summary, key points, and a link to the original article.

Key points and analysis

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EngineersIntermediate

Key points

  • Data does not need to be perfect for generative AI workloads.
  • JBS Dev used AI to clean messy medical billing records, automating steps gradually.
  • Future AI innovation will focus on cost sustainability and portability, not just model capability.
  • Advises using existing cloud tools instead of purchasing new SaaS licenses.

Highlights and analysis are generated automatically and may contain errors. Check the original source.