Concept

concept
Generative Artificial Intelligence (GenAI), such as foundation models, represents a powerful and transformative class of AI capable of learning patterns from data and generating new content. However, GenAI has notable shortcomings including hallucinations or bias which can lead to misuse or hinder its widespread adoption and positive societal and economic impact. These shortcomings stem from three key areas: technical, operational, and user robustness.

Technical robustness

The ability of GenAI systems to consistently perform their intended functions across a range of technical conditions, which include adversarial inputs, noisy and incomplete input data and the inherent stochasticity in the generative process.

Technical robustness

Operational robustness

The resilience of GenAI systems in varied deployment environments and operational settings, including the capability of the systems of being efficiently and effectively fine-tuned or adapted to different tasks and domains without significant loss in performance and security.

Operational robustness

User robustness

The capability of GenAI systems to engage in meaningful and contextually relevant interactions with a diverse range of users, each with unique behaviours, cultural backgrounds, and prone to human errors. It also encompasses resilience to ethical, fairness, and misuse risks of GenAI.

User robustness

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