Glossary

Reinforcement Learning from AI Feedback (RLAIF) is an advanced technique in artificial intelligence. It merges traditional Reinforcement Learning practices with feedback from another AI, thus enhancing adaptability and performance of AI and LLM systems.

Approximation error refers to the disparity between an estimated value and the exact value – a crucial concept when dealing with numerical computations.

The Rete Algorithm is a vital pattern-matching module applied in devising rule-based systems. Expertly designed for maximizing efficiency, it rapidly applies numerous rules to large sets of data within a knowledge base, using a network-like nodal structure.

Responsible AI is all about creating and executing artificial intelligence systems that balance ethical values, safety measures, and business objectives, thereby fostering mutual trust and fairness among business entities, individuals, and customers.

Explore the world of Robotics, a tech-field that focuses on designing, building, operating, structuring, producing, and utilizing robots in diverse applications.

The Receiver Operating Characteristic Area Under Curve (ROC-AUC) is a crucial measure in machine learning, evaluating the binary classifier model’s performance by comparing true positive and false positive rates.