Your session has been flagged for unusual activity.
Please confirm you're human to continue.
The work of making an AI system's behaviour match human intent and values — why a model follows instructions reliably and refuses harmful requests.
Alignment research aims to ensure capable models do what their designers and users actually want. Practical techniques include learning from human preferences (Christiano et al., 2017), instruction-following via RLHF (Ouyang et al., 2022), and rule-guided self-improvement as in Constitutional AI (Bai et al., 2022).
Alignment is an open problem, not a solved checkbox: as models grow more capable, specifying and verifying intended behaviour becomes harder, not easier.
Primary, peer-reviewed and archival sources for this definition.
Run the same prompt across ChatGPT, Claude, Gemini and Grok — grounded in your own sources, cross-checked against each other.
Try MultipleChat FreeContinue learning
See the AI subscription that replaces separate ChatGPT, Claude, Gemini and Grok accounts.
Multi-model AIRun the same prompt through ChatGPT, Claude, Gemini and Grok before trusting one answer.
GuideChoose the best model for writing, research, coding, documents, images and business work.
Buyer intentOne app for several frontier AI models, side-by-side comparison and model collaboration.
PlatformA professional workspace for using several AI models, comparing answers and creating deliverables.
Core conceptUse several frontier models together for stronger answers and fewer blind spots.
ComparisonCompare several AI answers side by side when the output matters.
WorkflowBuild a professional AI stack for documents, research, writing, images and automation.
Free toolsStart with free tools, then upgrade when multi-model workflows save real time.
