Datasets for Superintelligence Research
At the AI Engineering Society, we believe that high-quality datasets are crucial for advancing our mission of creating superintelligence through recursive self-improvement. Here, we provide access to cutting-edge datasets specifically curated for AI researchers and engineers working on advanced machine learning and artificial general intelligence (AGI) projects.
Featured Datasets
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Recursive Self-Improvement Patterns
A comprehensive collection of AI system behaviors exhibiting self-improvement capabilities, annotated with performance metrics and improvement trajectories.
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Multi-Modal AGI Benchmark
A diverse set of tasks spanning language, vision, reasoning, and motor control, designed to evaluate and train AGI systems across multiple domains.
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Ethical Decision-Making Scenarios
A collection of complex ethical dilemmas and their resolutions, aimed at training AI systems to make morally sound decisions in various contexts.
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Superintelligence Simulation Outcomes
Results from thousands of simulated scenarios exploring potential outcomes and societal impacts of emergent superintelligent systems.
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Access and Usage
These datasets are available to members of the AI Engineering Society and approved research partners. To request access or learn more about our data sharing policies, please visit our Data Access page.
By leveraging these datasets, we aim to accelerate progress towards creating safe and beneficial superintelligence. Together, we can push the boundaries of AI capabilities and shape a future where advanced artificial intelligence enhances human potential.