The Noise Floor Problem: How Flawed Data Pipelines Are Quietly Undermining AI Model Performance
Across research labs and enterprise AI teams, a persistent and underappreciated problem is degrading model quality from the inside out: the inability to distinguish meaningful training signals from computational noise. At COSP10 Research Hub, we examine the technical root causes, real-world consequences, and evidence-backed remedies that data engineers need to implement now.