grpo
Applied AI interview questions tagged grpo, across every topic.
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Concepts behind "grpo"
The curriculum that explains the ideas these questions test.
Core
Inference-Time Compute and Reasoning ModelsInference-time (test-time) compute is the idea that spending more computation at generation, longer chains of thought, sampling multiple attempts, or search, reliably improves answers on hard problems, a scaling axis distinct from making the model bigger. Reasoning models (o1/R1-style) are trained, often via RL on verifiable rewards, to produce long internal reasoning and exploit this. Applied-AI interviews probe it because it changed how hard problems are solved and introduced a real latency/cost trade-off: route easy queries to fast models, reserve reasoning models for genuinely hard ones.🧠 Foundations of LLMs & GenAISign in
Advanced
Policy Optimization: PPO and GRPOPPO and GRPO are the reinforcement-learning algorithms that optimize an LLM against a reward, the RL step in RLHF and in training reasoning models. PPO is the established workhorse, updating the policy in small, clipped steps to stay stable; GRPO (used by DeepSeek-R1) drops PPO's separate value network and instead normalizes rewards within a group of samples, which is simpler and cheaper for LLMs. Applied-AI interviews probe it because it explains how alignment and reasoning training actually run, and why RL on verifiable rewards scales.🧠 Foundations of LLMs & GenAI🔒 Premium
Advanced
Training Reasoning Models: RLVR, PRM vs ORMReasoning models like o1 and R1 are not just bigger instruct models: they are trained with reinforcement learning where the reward comes from checking whether the final answer is correct, which teaches the model to generate long internal chains of thought. This page covers RL with verifiable rewards (and GRPO specifically), the split between process reward models that score each step and outcome reward models that score only the answer, and how that choice shapes test-time search. Applied AI interviews probe it to see if you understand where the reasoning ability actually comes from.🧠 Foundations of LLMs & GenAI🔒 Premium