The Kotwel Knowledge Base
Practical articles on data quality, human insight, AI systems, and the flywheels that turn learning into durable advantage.
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3 articles found
How models learn to operate when one sensor disappears, why absence must remain distinct from delay or corruption, and what evaluation exposes dependence on a dominant channel.
How rewards turn robot experience into a control policy, why offline data and simulation reduce costly hardware interaction, and where reinforcement learning still breaks on ambiguous success signals.
What has to hold before two modalities agree on which of their parts refer to the same thing, why a robot policy scores highly on instructions it is actively contradicting, and where that correspondence comes from the labeling rather than the architecture.
