Difficulty: Advanced
Optimal pathfinding algorithm.
AI selecting next experiments.
Hardware components that execute physical actions.
Market reacting strategically to AI.
Isolating AI systems.
AI tacitly coordinating prices.
Ensuring AI systems pursue intended human goals.
Tradeoff between safety and performance.
Deep learning system for protein structure prediction.
Rules governing auctions.
Model that compresses input into latent space and reconstructs it.
AI proposing scientific hypotheses.
System that independently pursues goals over time.
Expected causal effect of a treatment.
Learning action mapping directly from demonstrations.
Agents communicate via shared state.
Stored compute or algorithms enabling rapid jumps.
Directed acyclic graph encoding causal relationships.
Sum of independent variables converges to normal distribution.
Control using real-time sensor feedback.
Agents have opposing objectives.
Modeling chemical systems computationally.
Sensitivity of a function to input perturbations.
Space of all possible robot configurations.
Modeling interactions with environment.
Continuous loop adjusting actions based on state feedback.
Agents optimize collective outcomes.
Agents fail to coordinate optimally.
Normalized covariance.
Willingness of system to accept correction or shutdown.