AI for speech synthesis refers to the use of artificial intelligence to generate human-like speech from text. This technology converts written words into spoken language, making it possible for computers and devices to talk in realistic voices. AI models learn from large amounts of recorded speech to produce natural-sounding audio, including variations in tone and…
AI for language learning refers to the use of artificial intelligence technologies to help people learn new languages more effectively. These systems can adapt to each learnernulls needs, providing personalised exercises, feedback, and conversation practice using natural language processing. AI tools can also detect mistakes, suggest corrections, and simulate real-life conversations to help users gain…
AI for Tutoring refers to the use of artificial intelligence to help students learn by providing explanations, feedback, and practice questions. These systems can adapt to each student’s progress, helping them understand concepts at their own pace. AI tutors can work alongside teachers or independently to support learning in a wide range of subjects.
AI for Entertainment refers to the use of artificial intelligence technologies to create, enhance, or personalise experiences in areas like music, film, video games, and interactive media. These systems can generate new content, predict audience preferences, and automate tasks such as editing or animation. The goal is to make entertainment more engaging, efficient, and tailored…
AI for gaming refers to the use of artificial intelligence techniques to enhance video games. It helps create smarter computer-controlled characters, improves game design, and adapts gameplay to individual players. AI can make games more challenging, realistic, and engaging by allowing non-player characters to react intelligently to player actions.
Prompt-driven personalisation is a method where technology adapts content, responses, or services based on specific instructions or prompts given by the user. Instead of a one-size-fits-all approach, the system listens to direct input and modifies its output to suit individual needs. This makes digital experiences more relevant and helpful for each person using the service.
Workflow-constrained prompting is a method of guiding AI language models by setting clear rules or steps that the model must follow when generating responses. This approach ensures that the AI works within a defined process or sequence, rather than producing open-ended or unpredictable answers. It is often used to improve accuracy, reliability, and consistency when…
Hierarchical Prompt Execution is a method of organising and processing prompts for artificial intelligence systems in a step-by-step, layered manner. Instead of handling a complex task all at once, the system breaks it down into smaller, more manageable parts, each handled by its own prompt. These prompts are arranged in a hierarchy, where higher-level prompts…
A use-case-based prompt taxonomy is a system for organising prompts given to artificial intelligence models, categorising them based on the specific tasks or scenarios they address. Instead of grouping prompts by their structure or language, this taxonomy sorts them by the intended purpose, such as summarising text, generating code, or answering questions. This approach helps…
Structured prompt design patterns are repeatable ways to organise and phrase instructions for AI language models, making their outputs more accurate and consistent. These patterns use specific templates, formats or rules to guide the AI in understanding and responding to tasks. By applying these patterns, users can reduce ambiguity and help the AI focus on…