Domain: AI Economics & Strategy

110 terms

Depth vs Width Intermediate

Tradeoffs between many layers vs many neurons per layer.
Edge Inference Intermediate

Running models locally.
Emergent Abilities Intermediate

Capabilities that appear only beyond certain model sizes.
Emergent Coordination Intermediate

Coordination arising without explicit programming.
Entropy Intermediate

A measure of randomness or uncertainty in a probability distribution.
Explainability Requirement Intermediate

Legal or policy requirement to explain AI decisions.
Explainable Credit Model Intermediate

Credit models with interpretable logic.
Exploration-Exploitation Tradeoff Intermediate

Balancing learning new behaviors vs exploiting known rewards.
Expressivity Intermediate

The range of functions a model can represent.
Fair Lending Intermediate

Ensuring models comply with lending fairness laws.
Fisher Information Intermediate

Measures how much information an observable random variable carries about unknown parameters.
Flat Minimum Intermediate

A wide basin often correlated with better generalization.
Fraud Detection Intermediate

Identifying suspicious transactions.
Gating Network Intermediate

Chooses which experts process each token.
Gradient Clipping Intermediate

Limiting gradient magnitude to prevent exploding gradients.
Gradient Leakage Intermediate

Recovering training data from gradients.
Gradient Noise Intermediate

Variability introduced by minibatch sampling during SGD.
Hessian Matrix Intermediate

Matrix of second derivatives describing local curvature of loss.
High-Frequency Trading Intermediate

Ultra-low-latency algorithmic trading.
Highway Network Intermediate

Early architecture using learned gates for skip connections.
Human Oversight Intermediate

Required human review for high-risk decisions.
Inductive Bias Intermediate

Built-in assumptions guiding learning efficiency and generalization.
Inference Cost Intermediate

Cost to run models in production.
Information Gain Intermediate

Reduction in uncertainty achieved by observing a variable; used in decision trees and active learning.
Key-Value Cache Intermediate

Stores past attention states to speed up autoregressive decoding.
KL Divergence Intermediate

Measures how one probability distribution diverges from another.
Latency SLA Intermediate

Guaranteed response times.
Learning Rate Schedule Intermediate

Adjusting learning rate over training to improve convergence.
Loss Landscape Intermediate

The shape of the loss function over parameter space.
MAP Estimation Intermediate

Bayesian parameter estimation using the mode of the posterior distribution.