Search Results
5 results for “privacy”
AI Ethics
AI ethics is the branch of applied ethics addressing the moral dimensions of designing, deploying, and governing artificial intelligence systems — covering fairness, accountability, transparency, privacy, and safety.
Edge AI
Edge AI is the deployment of artificial intelligence algorithms and inference workloads directly on local devices or edge computing nodes rather than in centralised cloud data centres, enabling low-latency, privacy-preserving, and bandwidth-efficient AI applications.
Federated Learning
Federated learning is a machine learning paradigm in which a model is trained across multiple decentralised devices or servers holding local data, without exchanging the raw data itself, preserving privacy while enabling collaborative model improvement.
PDPA AI Compliance
PDPA AI compliance refers to the application of Malaysia's Personal Data Protection Act 2010 to artificial intelligence systems, governing how personal data may be collected, processed, and used in AI training, inference, and deployment.
Synthetic Data
Synthetic data is artificially generated data that mimics the statistical properties of real datasets, created using generative AI or simulations to train machine learning models without exposing sensitive personal information.