Artificial Intelligence (AI): AI stands for artificial intelligence, which is the simulation of human intelligence processes by machines or computer systems. AI can mimic human capabilities such as communication, learning, and decision-making.
AI Model: An advanced algorithm that uses data to simulate aspects of human intelligence, such as understanding language or recognising patterns.
AI Query and Response: A process where a user poses a question or submits content, and the AI analyses the input to generate an informative, context-relevant response. Storypark Assist handles queries, like stories, to create valuable outputs for educators.
Data in Transit and at Rest:
Data in Transit: Information actively moving from one location to another, such as through a network or between applications.
Data at Rest: Information stored in databases, files, or other storage methods, where it’s not actively moving. For Storypark, data is secured both during transmission (transit) and in storage (rest).
Foundation Model: Large AI models trained on a broad spectrum of data, meant to be adapted for specific tasks.
Generative AI: Generative AI is a type of technology that uses AI to create content, including text, video, code and images. A generative AI system is trained using large amounts of data, so that it can find patterns for generating new content.
Hallucination: In the context of AI, hallucinations happen when the system generates inaccurate, incoherent, or nonsensical information, typically due to errors or limitations in its training, understanding, or processing capabilities.
Input and Output: Input refers to data provided by the user, and output refers to the AI's generated response. In Storypark Assist, inputs depend on the feature — for writing tools it's the text being worked on, while for drafting and Summary of Learning it can also include a small amount of context such as the child's first name and age, the service's curriculum settings, and any stories or notes the educator chooses to include. The output is the AI-generated draft, summary, or suggestions, which the educator can review, edit, or discard.
Large Language Model (LLM): A type of AI model specifically designed for understanding and generating human language. LLMs analyse large text datasets to identify patterns in language and can perform tasks like answering questions, summarising, or translating text.
Machine Learning (ML): A subset of AI where models learn from data patterns to improve their performance on tasks without explicit programming.
Metadata: Additional information about data, such as creation time, or author, which helps organise and interpret it.
Storypark Assist: Name for Storypark's AI add-on. Helps you write and review high-quality stories that align with pedagogical frameworks, freeing up time for other important work too. Takes a responsible approach while driving outcomes.
Trusted Boundary: A secure environment where sensitive data is managed and processed. This boundary ensures that any data handled within Storypark’s Assist features remains confidential and protected according to privacy standards.
User-Generated Content (UGC): Any content, such as text or images, created and shared by users rather than by the platform itself. In Storypark's case, this includes the stories, notes, and other text created by educators.