16th International Conference on Advances in Computing and Information Technology (ACITY 2026)

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Glossary

1

Artificial intelligence (AI)

The broad field of building systems that perform tasks associated with human intelligence, such as language understanding, image recognition and decision support.

2

Machine learning (ML)

A branch of AI in which models learn patterns from data rather than following only hand-coded rules; at a conference such as ACITY 2026 it usually refers to supervised, unsupervised or reinforcement learning methods.

3

Large language model (LLM)

A neural network trained on large text corpora to predict and generate language, used for tasks such as summarization, code assistance and conversational interfaces.

4

Retrieval-augmented generation (RAG)

An architecture that combines a language model with an external search or document retrieval step so answers can cite or use up-to-date source material.

5

MLOps

The practices and tooling for moving machine learning models from experimentation into reliable production, including versioning, testing, deployment, monitoring and retraining.

6

Federated learning

A training approach where models are updated across distributed devices or organizations without pooling all raw data in one central location.

7

AI governance

The policies, controls and accountability structures used to manage AI risk, including model documentation, human oversight, auditability and regulatory compliance.

8

Data sovereignty

The principle that data is subject to the laws and governance rules of the country or jurisdiction where it is collected or stored, a key issue for cloud and cross-border AI services.

9

Digital twin

A virtual model of a physical asset, process or system that is updated with real-world data and used for simulation, monitoring or optimization.

10

Edge AI

Running AI inference close to the source of data, such as on a device, sensor or local gateway, rather than sending all data to a central cloud.

11

Benchmark

A standardized test or dataset used to compare model performance; conference sessions often discuss whether benchmarks reflect real-world robustness and fairness.

12

High-performance computing (HPC)

Large-scale computing infrastructure used for simulation, data processing and AI training, typically involving clusters, accelerators and specialized networking.