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Build intelligent security for healthcare APIs with Amazon Bedrock

Learn how to add context-aware security monitoring to FHIR APIs using Amazon Bedrock. This post shows how to detect anomalous access patterns, classify data sensitivity automatically, and generate compliance reports in natural language, all without adding latency to clinical workflows.

We haven't written up this one. AWS Machine Learning has the full story — the link below goes straight to it.

Read the original at aws.amazon.com →

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acc vs acc_norm: Why Length Bias Skews LLM Eval Scores

Your fine-tune gains three points of acc_norm on HellaSwag and loses two points of acc . Same checkpoint, same harness, same seed.

  • "acc" measures highest summed log-likelihood of candidate continuation
  • "accnorm" divides sum by byte length of continuation string
  • Length bias can skew LLM evaluation scores significantly

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