We currently have 10 entries in this glossary.
Adversarial Attacks – Techniques used to fool AI models by subtly altering input data.
AI Ethics – The study of moral issues in AI, including bias, privacy, and accountability.
AI Governance – Policies and regulations guiding the development and deployment of AI.
Algorithmic Transparency – Making AI decision-making processes interpretable and understandable.
Data Privacy – Protecting personal and sensitive data used in AI systems.
Explainable AI (XAI) – AI systems designed to provide transparency in their decision-making processes.
Fairness in AI – Ensuring AI systems do not discriminate against individuals or groups.
Federated Learning – A technique that trains models across multiple devices without sharing raw data.
Singularity – A hypothetical point where AI surpasses human intelligence.
Turing Test – A measure of AI’s ability to exhibit human-like intelligence in conversation.
