🧠 Did you know that reinforcement learning is the driving force behind ChatGPT and other AI advancements?
It allows robots to walk, open doors, and even enables ChatGPT to simulate discussions with us (including reading and sending emails for you)! 🤖
🏆 Inspired by living beings, reinforcement learning teaches machines (or agents) to gather positive rewards and avoid negative ones in their environment.
They evolve to make better decisions through trial and error, much like how humans learn. 📈
An agent learns things like approaching a cake or dodging a fire via trial & error, determining favorable rewards.
Similarly, ChatGPT masters human-like answers and avoids “robot-like” ones in its environment.🍰🔥🗣️
🍕 Think of reinforcement learning as a mathematically-driven evolution, adapting to do better over time.
As for a more formal definition, Simplilearn defines reinforcement learning as:
“Reinforcement learning is a sub-branch of Machine Learning that trains a model to return an optimum solution for a problem by taking a sequence of decisions by itself.“
Whether for AI gaming, robotics, or ChatGPT, the learning logic remains consistent: explore, adapt, and improve! 🔍
In today’s video, I explain more about how reinforcement learning is the driving force behind ChatGPT and how it works.
Learn more in the video!
