Reinforcement Learning.
Learn what Reinforcement Learning means in modern search and SEO.
A machine learning paradigm where an agent learns by taking actions in an environment and receiving rewards or penalties.
Reinforcement learning (RL) is inspired by behavioural psychology: an agent takes actions in an environment, receives feedback in the form of rewards or penalties, and learns a policy that maximises cumulative reward over time. Unlike supervised learning, there is no correct answer provided—the agent must discover optimal behaviour through trial and error.
RLHF: Reinforcement Learning from Human Feedback
Modern LLMs like GPT-4 and Claude are fine-tuned using Reinforcement Learning from Human Feedback (RLHF). Human evaluators rate model outputs, and these ratings train a reward model that guides further training. This is why LLMs produce responses that feel natural and helpful—they've been optimised on human preference signals.
Marketing Applications
Reinforcement learning is used in automated bidding systems (Google Ads' Smart Bidding learns to maximise conversions), recommendation engines (Netflix, Spotify, TikTok's feed algorithms), and personalisation systems. It's the technology that optimises ad spend and content recommendations in real time.
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