Critino: Revolutionizing AI Training with Concrete Examples

Critino is a cutting-edge platform designed to transform how AI systems learn from human feedback. By replacing abstract rules with concrete examples and leveraging semantic search, Critino enables developers and businesses to create AI applications that consistently deliver desired outcomes. Our intuitive critique-based training system makes AI alignment more accessible, scalable, and effective.

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Key Features and Benefits of Critino:

1. Concrete Examples Over Abstract Rules:

   • Enable AI agents to learn and improve over time based on user feedback.
   • Instead of relying on vague or high-level instructions, Critino uses specific examples (critiques) to guide LLM behavior. This makes it easier to capture the subtleties of human-like responses.
   • For instance, if you want an LLM to handle customer complaints empathetically, you can provide critiques with real-world examples of how you or others have responded to similar situations.

2. Semantic Search with Structured Critique Format:

   • Match new queries with relevant critiques to ensure accurate and consistent AI responses.
   • Each critique contains:
     • Context: The background context in which the query arises.
     • Query: The specific input or question the LLM needs to respond to.
     • Optimal Response: The ideal or desired response for that query in that context.
     • Scenario: A generic description of the situation, enabling similarity searches for future queries.

3. Wide Range of Use Cases:

   • Critino can be applied to various domains, such as customer support, creative writing, technical assistance, and more.
   • It’s particularly useful for edge cases, where traditional prompt engineering might fail to produce the desired behavior.

4. Improved Consistency and Faithfulness:

   • By grounding the LLM’s behavior in real-world examples, Critino ensures that the model’s responses are more consistent with human expectations.
   • This reduces the likelihood of the LLM generating off-target or inappropriate responses.

5. Scalability and Adaptability:

   • Add unlimited critiques to handle a growing range of situations without being constrained by context size.
   • Users can continuously refine and expand their critique library to address new scenarios or improve existing ones.

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How Critino Works

1. Create Critiques:

   • Define the context, query, optimal response, and situation for each critique.
   • Example: For a customer service AI, a critique might include a sample complaint, context, and the ideal empathetic response.

2. Semantic Search:

   • Critino uses semantic search to match new queries with the most relevant critiques, ensuring accurate and context-aware responses.

3. Train Your AI:

   • Use critiques to guide your AI’s behavior, improving alignment with user intentions over time.

4. Scale and Improve:

   • Continuously add critiques to expand your AI’s capabilities and handle new scenarios.

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Roadmap

• Automated Critique Generation: Use AI to generate critiques from historical data or user feedback.
• Fine-Tuning Integration: Combine critiques with fine-tuning for even better model performance.

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Contributing

• Read the Contribution Guide for setup and workflows.