Agent Memory
Agent memory refers to an AI agent's ability to retain and recall information across tasks and sessions. Two types are commonly distinguished: short-term memory, which holds context within a single agent loop interaction, and long-term memory, which persists across sessions and stores facts, preferences, and historical decisions. Memory is what transforms a stateless AI tool into a context-aware agent that produces increasingly relevant results over time — a core requirement for production Agentic AI deployments.
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Large Language Model (LLM)
A large language model (LLM) is an AI system trained on vast amounts of text data that can understand, generate, and transform language at a human-like level. LLMs power a wide range of applications — from chatbots and writing assistants to automated document creation and data summarization. In enterprise software, LLMs are increasingly embedded into workflows to interpret unstructured data, draft content, and translate information between systems automatically. In contrast, the Large Presentation Model (LPM) is a specialised AI system that orchestrates the entire presentation cycle in an enterprise context.
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TOK Presentation
The Theory of knowledge (TOK) presentation is an essential part of the International Baccalaureate Diploma Program (IB). The TOK presentation assesses a student's ability to apply theoretical thinking to real-life situations.
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Diagonal Communication
Diagonal communication means that the employees of a company communicate with each other regardless of their function and their level in the organisational hierarchy and regardless of their department within the company.
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