Ever wonder how cognitive science, psychology, learning science, and artificial intelligence fit together? How do these disciplines relate to and work with each other to further human progress and knowledge? What does it all mean when we pull these fields together, and what purpose does it serve?

In recent years, transformers have emerged as a dominant architecture in natural language processing (NLP) and deep learning. Their ability to handle long-range dependencies, scale efficiently, and generalize across a wide range of tasks has made them the go-to solution for many machine learning challenges. However, as with any model, transformers are not always the most fit-for-purpose solution when we consider factors such as task specificity, computational efficiency, and real-time performance.

Imagine controlling devices with just your thoughts—sounds like something out of Ghost in the Shell or Neon Genesis Evangelion, right? With Elon Musk’s Neuralink, that sci-fi future is becoming reality. As real-world tech catches up with anime's imagination, it's the perfect time to explore how these iconic man versus machine themes connect—and what they mean for our future.