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AGI Development Depends on Defining the Capabilities People Actually Need Basics Theory

AGI Development Depends on Defining the Capabilities People Actually Need

Learn how to define “AGI enough” by naming real workflows, decomposing capabilities, and measuring reliability with scenario-based tests, trust, and responsibility.

Gabrielle Bennett
Experimental AI Research Can Produce Useful Results Without Full Understanding Basics Theory

Experimental AI Research Can Produce Useful Results Without Full Understanding

How experimental AI research yields useful results before full understanding, and how to validate, monitor, and ship models safely despite black-box behavior.

Juliana Daniel
AI Safety Depends on How Models Behave in Real-World Use Basics Theory

AI Safety Depends on How Models Behave in Real-World Use

AI safety depends on real-world behavior: why lab evals miss workflow risks, and how to test in context, design guardrails, and monitor post-launch.

Aldrich Acheson
Ten Uncomfortable Ideas That Challenge Common AI Assumptions Basics Theory

Ten Uncomfortable Ideas That Challenge Common AI Assumptions

Explore 10 uncomfortable ideas that challenge common AI assumptions in health apps: data myths, fluent chatbots, feedback loops, bias, alignment and accountability.

Tessa Rodriguez