Term explanation
A .pps file is a legacy PowerPoint slideshow format that opens directly in presentation mode rather than the editing view. Double-clicking a .pps file launches the slideshow immediately, which made it popular for distributing finished presentations to audiences. The .pps format was later replaced by .ppsx as part of Office 2007's shift to an open XML-based file structure.
LIZ AI transforms PowerPoint files into living presentations. Whether you work with .pps or .pptx, LIZ connects your slides to live data — so the deck is always ready to run, with current content.
Learn more →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.
Learn moreThe Model Context Protocol (MCP) is an open standard developed by Anthropic in 2024 and widely adopted in 2025 by OpenAI, Google, and Microsoft. It defines a standardized way for AI agents to connect to external tools, data sources, and enterprise systems — without requiring custom integrations for every connection. MCP acts as a universal interface: an AI agent with MCP support can securely access databases, APIs, document repositories, and business applications using a consistent protocol, regardless of the underlying system. This dramatically simplifies how AI is embedded into complex enterprise environments.
Learn moreA 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.
Learn moreA 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.
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