AI Hallucination

AI Hallucination

Term explanation

Definition and meaning

AI hallucination describes the phenomenon where an LLM confidently produces content that is factually incorrect, fabricated, or entirely made up — presented as though it were true. Hallucinations occur because language models generate statistically probable text based on training patterns, without access to verified facts. In enterprise contexts, hallucinations in presentations are a serious risk. AI grounding — anchoring outputs to verified company data — is the primary strategy for preventing hallucinations in production AI systems.

LIZ AI is built to eliminate hallucinations in presentations. By grounding every slide in verified data from your connected enterprise systems, LIZ ensures that what appears in your deck is always accurate and traceable.

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Other glossary terms

B2C Events

B2C events (business-to-consumer events) are organized experiences designed to engage end consumers directly — such as product launches, brand activations, pop-up experiences, festivals, or public demonstrations. Unlike B2B events, B2C events prioritize emotional connection, entertainment, and brand perception over formal knowledge exchange. They are used to build brand awareness, drive purchase consideration, and create memorable experiences that consumers associate with a product or brand.

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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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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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Effect Options

Effect Options in PowerPoint allow presenters to customize how animations and transitions behave — including direction, timing, sequence, and the degree of motion applied. For example, a Fly In animation can be set to arrive from the left, right, top, or bottom. Effect Options give presenters precise control over the appearance and feel of animations without requiring advanced design skills, making it easy to fine-tune motion effects to match the tone and pacing of a presentation.

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