Practices
10 entries in this category.
AI Governance & Ethics
The frameworks, policies, and practices organizations use to manage the risks and ethical implications of developing and deploying AI systems.
Prompt Engineering
Designing and iterating prompts to guide AI models toward reliable, useful outputs.
Model Evaluation
The process of measuring model performance, quality, and safety using defined metrics and test sets.
Hallucination
Instances where an AI model generates false, nonsensical, or unverified information, presenting it confidently as fact.
MLOps
Machine Learning Operations (MLOps) is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.
Prompt Injection / Jailbreaking
A security vulnerability where malicious input causes an LLM to ignore its original instructions and execute unauthorized actions.
Red Teaming
The practice of aggressively testing AI systems by simulating adversarial attacks to identify flaws, biases, or vulnerabilities.
Chain-of-Thought Prompting
A prompting technique that instructs an AI model to reason step-by-step before arriving at a final answer, significantly improving accuracy on complex tasks.
Reinforcement Learning from Human Feedback (RLHF)
A training technique that uses human preference ratings to fine-tune AI models to produce more helpful, accurate, and safe responses.
AI Workflow Automation
The use of AI models, agents, and integrations to automate multi-step business processes that previously required human judgment.