Training
Alignment
Alignment is the work of making an AI system behave the way its developers and users actually intend.
In depth
Alignment is the work of making an AI system behave the way its developers and users actually intend. Anthropic's 2021 paper framed an aligned assistant as helpful, honest, and harmless. The InstructGPT paper described base GPT-3 as not aligned with its users because it produced untruthful, toxic, or unhelpful output. In practice, alignment covers training methods such as RLHF and Constitutional AI, plus evaluations that check whether a model follows instructions, tells the truth, and refuses harmful requests.
Primary source: arxiv.org
Example
In practice, alignment covers training methods such as RLHF and Constitutional AI, plus evaluations that check whether a model follows instructions, tells the truth, and refuses harmful requests.
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FAQ
Common questions
What is Alignment?
Alignment is the work of making an AI system behave the way its developers and users actually intend.
Why does Alignment matter for AI developers?
Alignment sits in the Training part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Alignment?
Developers Digest publishes tutorials and videos that cover Training topics including Alignment. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Training
RLHF (Reinforcement Learning from Human Feedback)
A training technique that fine-tunes a model using human preference judgments.
Training
Instruction-Tuned Model
A base model that has been further fine-tuned on tasks phrased as natural-language instructions so it responds to requests instead of just continuing text.
Training
DPO (Direct Preference Optimization)
A training technique that aligns language models with human preferences without needing a separate reward model.
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