4min snip

AI Research at Capital One with Bayan Bruss

Software Engineering Daily

NOTE

Iterate to Innovate: Aligning AI with Business Needs

Integrating machine learning into application stacks requires a profound understanding of both the business context and the capabilities of technology. The process is iterative, resembling a spaceship docking as teams refine their approach through testing hypotheses against real-world problems. When initial solutions fail, valuable insights about constraints and assumptions emerge, leading to revised strategies. This continual feedback loop fosters broader investigations into systemic challenges such as model explainability and the application of AI to diverse data types. By addressing these foundational issues, organizations can better harness AI's potential, ensuring that models function reliably and meet specific business requirements.

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