Transfer learning, where you take the knowledge of one model and just... paste it into another. Sounds like a great idea, right? I mean, who needs originality when you can just copy and paste?
But seriously, folks, transfer learning is more than just a fancy way of saying "I'm too lazy to train a new model." It's a technique where we take a pre-trained model, and use it as a starting point for our own model. It's like building a house on top of someone else's foundation, but without the structural integrity.
However, some of us might say that it's just a form of intellectual property theft, and that we should just come up with our own solutions. But hey, who needs originality when you can just copy and paste?