NIST AI RMF — the GOVERN function — AIML

Objectives

Identify the key rules and §§ that apply to nist ai rmf — the govern function.
Apply the AI-Modern-ML.Foundations.Governance knowledge element in a typical exam scenario.
Recognize common distractors and partial-credit answers.

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The GOVERN function cultivates a culture of risk management within the organizations that design, develop, deploy, evaluate, or acquire AI systems. GOVERN addresses organizational context, accountability structures, workforce diversity, equity, inclusion, and accessibility. It is cross-cutting and informs MAP, MEASURE, and MANAGE across the AI lifecycle. Organizations that skip GOVERN tend to operationalize technical controls without the policy and accountability scaffolding needed to sustain them under real-world pressure.

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3 quick questions — no score kept, just formative feedback.

Q1 · AI.LLM.Transformer
In scaled dot-product attention (Vaswani et al. 2017), the attention scores QKᵀ are divided by √d_k before softmax primarily to:

Answer choices A Reduce computational complexity. B Prevent the softmax from saturating as dimensionality grows. C Enforce positive attention weights. D Make attention permutation-equivariant.
Q2 · AI.LLM.Training
DPO (Direct Preference Optimization, Rafailov et al. 2023) differs from RLHF-PPO in that DPO:

Answer choices A Requires a larger reward model. B Uses no human preference data. C Directly optimizes the policy on preference pairs without training an explicit reward model. D Requires reinforcement learning through a simulator.
Q3 · AI.Foundations.DL
AdamW (Loshchilov & Hutter 2019) improves upon Adam by:

Answer choices A Using second-order gradients exclusively. B Decoupling weight decay from the adaptive gradient update. C Eliminating momentum. D Removing the bias-correction terms.

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