AI Model Alignment: Beyond Simple Filters to Layered Control

The distinction between "uncensored" and "aligned" AI models is often oversimplified, with alignment being a multi-layered process rather than a simple filter. This process begins with a base model, which is then fine-tuned using techniques like Reinforcement Learning from Human Feedback (RLHF) or Reinforcement Learning from AI Feedback (RLAIF) to favor preferred outputs. Finally, system prompts and output classifiers add further layers of control and safety at inference time. Different AI platforms can exhibit vastly different behaviors even with identical base models, solely based on their configuration of these latter layers. AI

IMPACT Clarifies the technical underpinnings of AI model behavior, enabling more informed evaluation of AI chat platforms.

RANK_REASON The item provides a technical explanation and analysis of existing AI model alignment techniques rather than announcing a new model or product.

Read on dev.to — LLM tag →

• reinforcement learning from AI feedback
• reinforcement learning from human feedback
• Transformer++

• model release

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