Teaching AI to Learn from Mistakes
Think about how you learned to ride a bike. No one handed you a physics textbook or a manual. You learned through trial and error—a scraped knee here (a penalty), a thrilling moment of perfect balance there (a reward). Over time, your brain intuitively learned the right actions to stay upright and move forward. What if an AI could learn the same way? Not by analyzing a massive, pre-labeled dataset, but by interacting with a world and learning directly from the consequences of its actions?
