Glossary

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Machine Learning (ML)

Machine Learning (ML) is a branch of artificial intelligence (AI) that enables computers and machines.

Managed Kubernetes Service

A Managed Kubernetes Service is a cloud-based offering where a third-party provider manages the deployment.

Masked Language Modeling

Masked Language Modeling (MLM) is a technique where parts of text data, typically individual words or tokens, are intentionally hidden or replaced with special symbols (such as [MASK]).

Memory Compression refers to the systematic process by which an agentic AI system condenses, abstracts, and restructures large volumes of historical data, interactions, and experiences into compact, high-value representations that can be efficiently stored, retrieved, and reasoned over.

Memory Retrieval Strategy

A Memory Retrieval Strategy in agentic AI refers to the systematic approach an autonomous agent uses to identify, select, and retrieve relevant information from its memory systems—such as short-term, long-term, episodic, semantic, or procedural memory—at the right time and in the right form to support reasoning, planning, and decision-making.

MLOps (Machine Learning Operations)

MLOps, short for Machine Learning Operations, refers to streamlining the deployment, monitoring, management, and governance of machine learning (ML) models in production.

Model Deployment

Model deployment refers to the process of integrating a trained machine learning (ML).

Model Distillation

Model distillation is a machine learning technique in which a smaller, simpler model (referred to as the student model) learns to mimic the behavior of a larger, more complex model (referred to as the teacher model).

Model Hallucination

Model hallucination happens when a machine learning model generates information that is not based on the actual input data. Instead, the model creates or imagines details that are not present in the real dataset.