Each term is defined by its impact on both your customers and your team. And to highlight the real-world applications of generative AI, we put it to work on this very article. Our experts chimed in on key terms, and we let a generative AI tool lay the foundation for this glossary. All the definitions needed to be human-edited before publication, but it still saved a lot of time.
Generative AI Terms by Topic (AI) Artificial neural network Increased Intelligence CRM with AI Deep learning Generative AI Generator GPT Machine ew leads learning NLP Parameters Transformer Training and learning with AI Conversational AI Discriminator (in GANs) GAN Generator Rooted in the context Hallucination LLM Model Predictive AI Prompt Engineering Reinforcement learning Sentiment Analysis Supervised learning Unsupervised learning Validate ZPD Ethics of AI Anthropomorphism Ethical Maturity Model in AI Explainable AI (XAI) Human in the Loop (HITL) Machine Learning Bias Defense of prompts Red Teaming Safety Toxicity Transparency No data retention Anthropomorphism It is the tendency for people to attribute human motivations, emotions, characteristics, or behaviors to AI systems .
For example, thinking that the model or output is “bad” based on the responses it provides, even if it is not capable of feeling emotions, or potentially believing that the AI is sentient because it is very good at imitating human speech. Although it may recall something familiar, it is crucial to keep in mind that AI, no matter how advanced, does not have feelings or consciousness. It is a brilliant tool, not a human being.