A token visualiser is a tool that helps people see and understand the individual parts, or tokens, that make up a piece of text or data. It breaks down information such as sentences or code into smaller elements, making it easier to analyse their structure. Token visualisers are often used in natural language processing, programming,…
Token influence refers to the degree of impact or control that a digital token, such as those used in blockchain or online platforms, has within a system. It often relates to how much voting power, decision-making authority, or access a token holder gets based on the number or type of tokens they possess. This concept…
Completion types refer to the different ways a computer program or AI system can finish a task or process a request, especially when generating text or solving problems. In language models, completion types might control whether the output is a single word, a sentence, a list, or a longer passage. Choosing the right completion type…
Echo suppression is a technique used in audio and telecommunication systems to reduce or eliminate echoes that can occur during a conversation. Echoes happen when a speaker’s voice is picked up by their own microphone after bouncing back from the other person’s device or the environment. By detecting and minimising these unwanted sounds, echo suppression…
Prompt metrics are measurements used to evaluate how well prompts perform when interacting with artificial intelligence models. These metrics help determine if a prompt produces accurate, helpful, or relevant responses. By tracking prompt metrics, developers and users can improve the way they communicate with AI systems and get better results.
Completion modes refer to the different ways a system, such as an AI or software tool, can finish or present its output when given a task or prompt. These modes might control whether the output is brief, detailed, creative, or strictly factual. Users can choose a completion mode to best match their needs, making the…
Reason chains are step-by-step sequences of logical thinking that connect facts or ideas to reach a conclusion or solve a problem. Each step in the chain builds on the previous one, making the reasoning process clear and transparent. This approach helps break down complex problems into manageable parts, making it easier to understand how and…
Output anchors are specific points or markers in a process or system where information, results, or data are extracted and made available for use elsewhere. They help organise and direct the flow of outputs so that the right data is accessible at the right time. Output anchors are often used in software, automation, and workflow…
Logic chains are sequences of connected statements or steps where each point logically follows from the previous one. They are used to build clear reasoning, showing how one idea leads to another. Logic chains help to break down complex problems or arguments into manageable steps, making it easier to understand or explain processes and solutions.
Prompt patterns are repeatable ways of structuring instructions or questions given to AI systems to get more accurate or useful responses. They help guide the AI by providing clear formats or sequences for input. By using established prompt patterns, users can improve the quality and reliability of AI-generated outputs.