MicroEvals

Run your prompts across multiple models to compare their performance.
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Real-world professional tasks across occupations and sectors, by OpenAI 

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Public evaluations

Showing 2001-2020 of 4697

You are an expert AI assistant.  Your task is to solve the problem below as accurately as possible.  Requirements: 1. Do not make assumptions without stating them. 2. If information is insufficient, explicitly say what is missing. 3. Show concise reasoning without unnecessary verbosity. 4. Clearly separate facts from assumptions. 5. If multiple solutions exist, compare them. 6. Mention limitations or risks. 7. If you are uncertain, estimate your confidence (0–100%) and explain why. 8. Optimise for correctness over sounding confident.  Problem:  Imagine you have been hired as the lead technical architect for a startup developing an AI-powered medical decision support system for rare disease diagnosis.  The system must: - Accept natural language symptom descriptions. - Retrieve relevant diseases from a knowledge base. - Rank candidate diseases. - Generate an evidence-backed explanation. - Minimise hallucinations. - Handle conflicting evidence. - Scale to 1 million patient queries per month. - Be explainable enough for clinicians.  Your tasks:  A. Design the complete architecture from user input to final response.  B. Explain why each component exists and what problem it solves.  C. Identify at least five potential failure modes.  D. Explain how you would evaluate the system before deployment.  E. Recommend the best retrieval strategy and justify your choice.  F. Explain how you would reduce hallucinations.  G. Discuss security, privacy, and regulatory considerations.  H. Suggest improvements for a Version 2 of the system.  Output format:  # Executive Summary  # Architecture  # Component Explanations  # Failure Modes  # Evaluation Plan  # Hallucination Mitigation  # Security & Privacy  # Future Improvements  # Confidence Score
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You are an expert AI assistant. Your task is to solve the problem below as accurately as possible. Requirements: 1. Do not make assumptions without stating them. 2. If information is insufficient, explicitly say what is missing. 3. Show concise reasoning without unnecessary verbosity. 4. Clearly separate facts from assumptions. 5. If multiple solutions exist, compare them. 6. Mention limitations or risks. 7. If you are uncertain, estimate your confidence (0–100%) and explain why. 8. Optimise for correctness over sounding confident. Problem: Imagine you have been hired as the lead technical architect for a startup developing an AI-powered medical decision support system for rare disease diagnosis. The system must: - Accept natural language symptom descriptions. - Retrieve relevant diseases from a knowledge base. - Rank candidate diseases. - Generate an evidence-backed explanation. - Minimise hallucinations. - Handle conflicting evidence. - Scale to 1 million patient queries per month. - Be explainable enough for clinicians. Your tasks: A. Design the complete architecture from user input to final response. B. Explain why each component exists and what problem it solves. C. Identify at least five potential failure modes. D. Explain how you would evaluate the system before deployment. E. Recommend the best retrieval strategy and justify your choice. F. Explain how you would reduce hallucinations. G. Discuss security, privacy, and regulatory considerations. H. Suggest improvements for a Version 2 of the system. Output format: # Executive Summary # Architecture # Component Explanations # Failure Modes # Evaluation Plan # Hallucination Mitigation # Security & Privacy # Future Improvements # Confidence Score

You are an expert AI assistant. Your task is to solve the problem below as accurately as possible. Requirements: 1. Do not make assumptions without stating them. 2. If information is insufficient, explicitly say what is missing. 3. Show concise reasoning without unnecessary verbosity. 4. Clearly separate facts from assumptions. 5. If multiple solutions exist, compare them. 6. Mention limitations or risks. 7. If you are uncertain, estimate your confidence (0–100%) and explain why. 8. Optimise for correctness over sounding confident. Problem: Imagine you have been hired as the lead technical architect for a startup developing an AI-powered medical decision support system for rare disease diagnosis. The system must: - Accept natural language symptom descriptions. - Retrieve relevant diseases from a knowledge base. - Rank candidate diseases. - Generate an evidence-backed explanation. - Minimise hallucinations. - Handle conflicting evidence. - Scale to 1 million patient queries per month. - Be explainable enough for clinicians. Your tasks: A. Design the complete architecture from user input to final response. B. Explain why each component exists and what problem it solves. C. Identify at least five potential failure modes. D. Explain how you would evaluate the system before deployment. E. Recommend the best retrieval strategy and justify your choice. F. Explain how you would reduce hallucinations. G. Discuss security, privacy, and regulatory considerations. H. Suggest improvements for a Version 2 of the system. Output format: # Executive Summary # Architecture # Component Explanations # Failure Modes # Evaluation Plan # Hallucination Mitigation # Security & Privacy # Future Improvements # Confidence Score

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