These definitions are from: https://academics.waldenu.edu/artificial-intelligence/glossary
Bias: The presence of systematic and undesired preferences or imbalances in the output generated by an AI model. Bias can emerge in various forms, such as in the content, language, or perspectives generated by the AI system.
Burstiness: The abrupt shifts in quality, coherence, or relevance often observed in AI generated content, particularly in writing. It refers to the inconsistencies in style, tone, or factual accuracy that can occur within a short span. Identifying burstiness helps distinguish AI-generated content from human-created content.
Generative AI: AI systems that can generate new content such as text, images, or music. It involves developing algorithms and models that can understand patterns in existing data and use that understanding to generate novel output.
Hallucinations: Misinformation or made-up information based on a pattern that the AI model has learned as part of its training. For example, the model could create references that do not actually exist.
Large Language Models (LLMs): Components of artificial intelligence developed based on the training of vast datasets of documents from various sources. The computer program analyzes data input and maps out words in the dataset. It next tries to predict which words are positioned before or after other words using predictive patterns of most likely combinations.
Output: The generated content produced by a generative AI system. It can be text, images, audio, music, video, or other data the model is designed to produce.
Probabilistic: In generative AI, probabilistic means that the models incorporate probability, which is used to estimate the likelihood of different outcomes and generate outputs that align with the learned probabilities.
Prompts: The initial input text or instructions given to a model to generate new content based on that starting point. It provides context and guides the model's output. The prompt can be a few words or sentences that set the tone or specify the desired content, and subjective experiences.
Sentient: The capability to possess consciousness, self-awareness, and subjective experiences. Achieving true sentience in AI systems is a topic of scientific exploration and philosophical debate.
Tokens: Discrete units used to represent meaningful components of text, such as words or phrases. Breaking down text into these units allows AI models to process and analyze language at a granular level, enabling tasks like language generation.
From Grammarly Blog - 9 Best Tips for Using AI Prompts for Writing
1 Create a . . .”
2 “Act as a . . .”
3 “Complete this sentence . . .”
4 “Mimic this style . . .”
5 “Give me examples of . . .”
6 “Show this as a . . .”
7 “Write a list of . . .”
8 “Compare . . .”
9 “Tell me about . . .” or “Explain . . .”
"Last but not least, with the entirety of the internet as their reference point, AI assistants can make great teachers. Simply ask one to tell you about or explain something, and it will usually respond with a clear and reasonable answer. Just be careful: There’s a lot of misinformation on the internet, so AI may cite incorrect sources and give you false information."
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