Agent Loop
The agent loop is the core operating cycle of an autonomous AI agent. It runs continuously through four phases: Perception (gathering information), Reasoning (planning the next step), Action (executing — such as calling a tool or generating content), and Observation (evaluating the result). The loop repeats until the task is complete or the agent requires human input. This is the mechanism behind Agentic AI systems — it is what allows agents to handle complex, multi-step tasks that a single prompt-and-response model could not.
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AI Hallucination
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.
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Hybrid Audience
A mix between in-person and virtual participants for an event or a lecture is called a hybrid audience. Working with a hybrid audience may be challenging, as it requires the presenter to find ways to engage both the live and the virtual audience.
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Personal Response System (PRS)
A personal response system (PRS) — also called an audience response system or clicker system — allows individual participants to respond to questions or vote in polls during a presentation or class. Each participant uses a handheld device or smartphone to submit their answer, and results are aggregated and displayed instantly. PRS technology is used in lectures, corporate training, and conferences to increase participation, gauge understanding, and make sessions more interactive.
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