This is the simplest possible neural net and it's written clearly in plain English. While this code doesn't explicitly include attention mechanisms or layers, it's fascinating to consider how these features are analogous to the hierarchical organization of cortical layers on the homunculus of a real human brain, where different regions process distinct aspects of sensory information.
The sigmoid activation function can be seen as analogous to the delicate dance between neurotransmitters and receptors, where signals are transmitted and regulated. Similarly, the dot product and loss calculation mirror the complex processes of receptor upregulation and downregulation that occur in biological systems.
As someone who grew up imagining science fiction concepts like AI as mere fantasy, I'm amazed to see this technology not only becoming a reality but also improving at an exponential rate in the year of 2025. It's obviously going to get better and outperform us everywhere.