Difference between revisions of "Constitutional AI"
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[https://www.youtube.com/results?search_query=Constitutional+AI YouTube] | [https://www.youtube.com/results?search_query=Constitutional+AI YouTube] | ||
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[https://www.bing.com/news/search?q=Constitutional+AI&qft=interval%3d%228%22 ...Bing News] | [https://www.bing.com/news/search?q=Constitutional+AI&qft=interval%3d%228%22 ...Bing News] | ||
| − | * [[Reinforcement Learning (RL)]] | + | * [[Policy]] ... [[Policy vs Plan]] ... [[Constitutional AI]] ... [[Trust Region Policy Optimization (TRPO)]] ... [[Policy Gradient (PG)]] ... [[Proximal Policy Optimization (PPO)]] |
| − | * [[Assistants]] ... [[Personal Companions]] ... [[ | + | * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]] |
| − | * [[Generative AI]] | + | * [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]] |
| − | * [[Claude]] | + | * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]] |
| + | * [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]] | ||
| + | * [[Claude]] | [https://www.anthropic.com/ Anthropic] | ||
* [[Reinforcement Learning (RL) from Human Feedback (RLHF)]] | * [[Reinforcement Learning (RL) from Human Feedback (RLHF)]] | ||
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* [https://medium.com/mlearning-ai/paper-review-constituional-ai-training-llms-using-principles-16c68cfffaef Paper Review: Constitutional AI, Training LLMs using Principles] | * [https://medium.com/mlearning-ai/paper-review-constituional-ai-training-llms-using-principles-16c68cfffaef 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 intentions. 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. | ||
| + | * Constitutional AI is a technique that aims to imbue systems with “values” defined by a “constitution”³. | ||
| + | * This makes the behavior of systems both easier to understand and simpler to adjust as needed³. | ||
| + | * The system uses a set of principles to make judgments about outputs, hence the term “Constitutional”⁴. | ||
| + | * This approach makes the values of the AI system easier to understand and easier to adjust as needed⁴. | ||
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<youtube>5GqtRXY-80k</youtube> | <youtube>5GqtRXY-80k</youtube> | ||
Latest revision as of 08:55, 23 March 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Policy ... Policy vs Plan ... Constitutional AI ... Trust Region Policy Optimization (TRPO) ... Policy Gradient (PG) ... Proximal Policy Optimization (PPO)
- Artificial Intelligence (AI) ... Machine Learning (ML) ... Deep Learning ... Neural Network ... Reinforcement ... Learning Techniques
- Agents ... Robotic Process Automation ... Assistants ... Personal Companions ... Productivity ... Email ... Negotiation ... LangChain
- Artificial Intelligence (AI) ... Generative AI ... Machine Learning (ML) ... Deep Learning ... Neural Network ... Reinforcement ... Learning Techniques
- Conversational AI ... ChatGPT | OpenAI ... Bing/Copilot | Microsoft ... Gemini | Google ... Claude | Anthropic ... Perplexity ... You ... phind ... Ernie | Baidu
- Claude | Anthropic
- Reinforcement Learning (RL) from Human Feedback (RLHF)
- 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 intentions. 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.
- Constitutional AI is a technique that aims to imbue systems with “values” defined by a “constitution”³.
- This makes the behavior of systems both easier to understand and simpler to adjust as needed³.
- The system uses a set of principles to make judgments about outputs, hence the term “Constitutional”⁴.
- This approach makes the values of the AI system easier to understand and easier to adjust as needed⁴.
RL from AI Feedback' (RLAIF)
It is a process that involves training a preference model from a dataset of AI preferences and then using that preference model as the reward signal for training with reinforcement learning. RLAIF is a method for training a harmless AI assistant through self-improvement, without any human labels identifying harmful outputs. The only human oversight is provided through a list of rules or principles, and so the method is referred to as ‘Constitutional AI’. The process involves both a supervised learning and a reinforcement learning phase. In the supervised phase, an initial model is sampled from, then self-critiques and revisions are generated, and then the original model is finetuned on revised responses. In the RL phase, samples are taken from the finetuned model and a model is used to evaluate which of the two samples is better. A preference model is then trained from this dataset of AI preferences. The preference model is used as the reward signal for training with RL.
