Scientific Hypothesis Generation with Adaptive Thinking
This challenge focuses on developing an advanced AI agent capable of assisting in scientific discovery. Developers will build an 'AI Scientist Assistant' utilizing GPT-5 (or a similar cutting-edge model) and Sonnet 4.5 for specialized scientific reasoning. The agent will move beyond simple literature review to actively generate novel hypotheses, design experimental outlines, and interpret complex data. Key to this challenge is the implementation of 'extended thinking' patterns, where the agent breaks down complex scientific problems into smaller, manageable steps, reasoning through each with adaptive thinking budgets. Graph-based knowledge representation will be employed to integrate vast amounts of scientific literature, experimental data, and domain-specific ontologies, enabling semantic search and logical inference. The system will demonstrate the potential for AI to accelerate research cycles and uncover insights in fields like material science or drug discovery.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an extended thinking agent using GPT-5 and OpenAI o3 for scientific research, incorporating graph-based knowledge and adaptive reasoning.
How work is evaluated
The evaluation will assess the AI Scientist Assistant's ability to generate plausible and novel scientific hypotheses, its logical reasoning in breaking down complex problems, the accuracy of its data interpretation, and the efficiency of its adaptive thinking.
Challenge datasets
Public datasets, plus the private datasets you have access to.
What you should walk away with
Develop advanced RAG pipelines for contextual retrieval from diverse scientific sources.
Master extended thinking patterns for complex scientific problem-solving with GPT-5.
Implement graph-based knowledge representation for scientific data and literature.
Design and utilize adaptive reasoning budgets for dynamic resource allocation.
Integrate OpenAI o3 for specialized numerical or domain-specific computations.
Reference links and supporting material
Sample data for 2 tasks
Challenge setup
The evaluation will assess the AI Scientist Assistant's ability to generate plausible and novel scientific hypotheses, its logical reasoning in breaking down complex problems, the accuracy of its data interpretation,...
Challenge input
{ "scientific_problem": "string", "background_literature_summary": "string", "simulated_experimental_data": "string" }
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{ "generated_hypothesis": "string", "reasoning_steps": [ "string" ], "experimental_design_outline": "string", "adaptive_budget_usage": "number" }
- Generated hypothesis must be scientifically plausible given the input context.
- Agent must correctly call the specialized tool for data analysis.
- Hypothesis Novelty Score target: 4
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
No tool records are attached.
Evaluation contract
- Generated hypothesis must be scientifically plausible given the input context.
- Agent must correctly call the specialized tool for data analysis.
Metrics
- Hypothesis Novelty Score · Target 4
- Reasoning Step Coherence · Target 4
Workflow tasks
- Task 1
Input: { "scientific_problem": "string", "background_literature_summary": "string", "simulated_experimental_data": "string" }
Output: { "generated_hypothesis": "string", "reasoning_steps": [ "string" ], "experimental_design_outline": "string", "adaptive_budget_usage": "number" }
Execution harness: Python
- Task 2
Input: { "dataset_description": "string", "raw_numerical_data": "array<array<number>>", "question": "string" }
Output: { "interpretation": "string", "tool_calls": [ { "tool_name": "string", "input_params": "object", "output": "string" } ], "conclusion": "string" }
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.