Recent content by erinondriver

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    Learning AI explained: a practical look at data quality

    For Learning AI, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is data quality. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome...
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    Understanding AI Servers: testing and automation

    When working with AI Servers, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is testing. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can...