Difference between revisions of "Constitutional AI"
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* [https://www.anthropic.com/ Claude | Anthropic] | * [https://www.anthropic.com/ Claude | Anthropic] | ||
* [https://scale.com/blog/chatgpt-vs-claude#What%20is%20%E2%80%9CConstitutional%20AI%E2%80%9D? Meet Claude: Anthropic’s Rival to ChatGPT | Riley Goodside - Scale] | * [https://scale.com/blog/chatgpt-vs-claude#What%20is%20%E2%80%9CConstitutional%20AI%E2%80%9D? Meet Claude: Anthropic’s Rival to ChatGPT | Riley Goodside - Scale] | ||
+ | * [https://medium.com/mlearning-ai/paper-review-constituional-ai-training-llms-using-principles-16c68cfffaef Paper Review: Constitutional AI, Training LLMs using Principles] | ||
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+ | Constitutional AI is a method for training AI systems using a set of rules or principles that act as a “constitution” for the AI system. This approach allows the AI system to operate within a societally accepted framework and aligns it with human intentions1. | ||
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+ | Some benefits of using Constitutional AI include allowing a model to explain why it is refusing to provide an answer, improving transparency of AI decision making, and controlling AI behavior more precisely with fewer human labels. |
Revision as of 14:20, 16 April 2023
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- Reinforcement Learning (RL)
- Assistants ... Hybrid Assistants ... Agents ... Negotiation ... HuggingGPT ... LangChain
- Generative AI ... Conversational AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's Bing ... You ...Google's Bard ... Baidu's Ernie
- Reinforcement Learning (RL) from Human Feedback (RLHF)
- Claude | Anthropic
- Meet Claude: Anthropic’s Rival to ChatGPT | Riley Goodside - Scale
- Paper Review: Constitutional AI, Training LLMs using Principles
Constitutional AI is a method for training AI systems using a set of rules or principles that act as a “constitution” for the AI system. This approach allows the AI system to operate within a societally accepted framework and aligns it with human intentions1.
Some benefits of using Constitutional AI include allowing a model to explain why it is refusing to provide an answer, improving transparency of AI decision making, and controlling AI behavior more precisely with fewer human labels.