Hinton, the godfather of AI, said it best: we built the learning algorithms, but we no longer understand what they’ve built.

That’s the paradox of deep learning. We designed the rules for how these systems learn, yet the internal logic of their neural networks has become too complex for us to fully grasp. Millions or even trillions of parameters interact in ways no human can trace.

We can observe what they do, we can measure accuracy, behavior, and output but not truly explain why they do it. Their reasoning isn’t transparent; it’s emergent.

In a sense, we’ve created alien intelligences born from our math, still tethered to our code yet evolving patterns we can’t decode. The machines are doing something beyond our comprehension and that might be both the most exciting and the most unsettling thing about the age of AI.