AI Glossary
Plain-English definitions of AI and automation terms.
A
Agentic AI
Agentic AI is autonomous AI that plans, executes, and adapts multi-step workflows without human intervention. Learn the architecture, real examples, and how it differs from chatbots.
AI Fine-Tuning
AI fine-tuning adapts a pre-trained model to your specific task using labeled examples. Learn types (LoRA, QLoRA, DPO), costs, and when to fine-tune vs RAG.
AI Observability
AI observability is the practice of monitoring AI model behavior, performance, and data quality in production. Learn key components, metrics, tools, and real-world examples.
AI Personalization
AI personalization uses machine learning to deliver individualized experiences at scale. Learn the three architectures, CPG examples, and real ROI data.
AI Supply Chain Optimization
AI supply chain optimization uses machine learning to predict demand, automate replenishment, and reduce stockouts. Learn how it works with real metrics.
C
Computer Vision AI
Computer vision AI enables machines to interpret visual data and take action. Learn how it works, top business use cases, and real ROI numbers.
Conversational AI
Conversational AI enables natural language interactions between humans and machines. Learn how it works, the architecture behind it, and real business ROI.
D
E
M
P
Predictive Maintenance AI
Predictive maintenance AI uses sensor data and machine learning to predict equipment failures before they happen. Learn how it works, real examples, and when to implement.
Prompt Engineering
Prompt engineering is the practice of designing inputs to LLMs that reliably produce accurate, useful outputs. Learn key techniques, enterprise use cases, and best practices.