Imagine training a helpful AI assistant. You ask it to write something, get a few responses, and then pick the best one. This process, called Reinforcement Learning from Human Feedback (RLHF), is how we make AI understand our preferences. But what if getting that feedback is super expensive? Researchers have found a clever way to lower the cost using something called a Vickrey auction. It works like this: Instead of paying for every AI response, you get multiple AIs to 'bid' on a task with their suggested responses. The AI with the best response wins, but you only pay the price of the *second* best response. This encourages the AIs to offer their best work at competitive prices. The cool thing is that even though you are paying less, you still get high-quality feedback. This method, called 'VickreyFeedback,' focuses on getting good responses while keeping costs down. This new approach isn't perfect. While it saves money, it might reduce the variety of responses, potentially limiting what the AI learns. However, the researchers came up with a fix by emphasizing responses that are very different from each other. This helps maintain diversity while still being cost-effective. The Vickrey auction trick is a big step in making AI development more affordable and efficient. As AI gets more complex, making feedback cheaper means we can build even better, more helpful assistants in the future.