Machine Learning Bias
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes.
Systematic errors in AI models that arise from the data or algorithms used, leading to poor outcomes.
Test-Driven Development (TDD) is a software development methodology where tests are written before the code that needs to pass them.
A phenomenon where the winner of an auction tends to overpay due to emotional competition, leading to a less favorable outcome than anticipated.
Trust, Risk, and Security Management (TRiSM) is a framework for managing the trust, risk, and security of AI systems to ensure they are safe, reliable, and ethical.
The process of distinguishing a product from its competitors through unique features, benefits, or branding to attract and retain customers.
A graphical representation showing the amount of work remaining versus time, used in agile project management to track progress.
The study of architectural concepts, including the principles and methodologies used in the design and construction of buildings and structures.
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes.
A small, cross-functional team of 6-12 people focused on delivering a specific product feature or component.