A neural networkA model made of connected computational units with adjustabl architecture that uses information from previous steps when processing a sequence. Its usefulness depends on the sequence, task and evaluated performance relative to other approaches.
Techniques that constrain a model or its training to reduce overfittingWhen a model learns the training data too closely and perfor. The strength of the constraint should be evaluated; too much can prevent the model from learning relevant patterns.
Machine learning in which an agent learns behaviour through interaction and feedback expressed as rewards. Define the objective and action boundaries carefully because optimising a reward can produce unintended behaviour.
A measure comparing an investment’s return with its cost, using a stated calculation and time period. Include implementation, review, training and ongoing operating effort when assessing an AI initiative.
The ongoing process of identifying, assessing and addressing uncertainty and potential harm. In AI adoption, define ownership, controls, monitoring and escalation in proportion to the use case’s potential impact.
The ability of a system or operating approach to handle greater demand while maintaining acceptable performance and control. Assess costs, support, user capability and risk before extending a successful pilot.
Examining how different assumptions or possible conditions could affect an outcome. It supports informed decisions under uncertainty; scenarios are tools for analysis, not predictions of what will happen.
Developing plausible future situations to test strategy and readiness. Use the exercise to identify robust choices and warning signals rather than to claim certainty about the future.
Methods for examining meaning and relationships in language or other information. Results depend on context and the representation used, so interpretations should be checked against the intended business question.
Methods for estimating attitudes or emotional tone in text. They can support pattern detection, but sarcasm, context and language variation make individual classifications uncertain and unsuitable as unquestioned judgments.
