
Artificial intelligence systems are no longer just tools following explicit rules; they are becoming ecosystems where layers collaborate in ways that even their creators don’t fully understand. Modern deep learning especially large-scale Transformers exhibits behaviors that push beyond traditional explainability. As these networks grow more complex, they begin forming internal representations and interactions that…

Artificial intelligence has reached a stage where models routinely display capabilities their designers never explicitly programmed. This is not science fiction; it is the central challenge of working with large modern architectures. These systems learn statistical abstractions at such scale that new behaviors emerge—behaviors the engineers neither anticipated nor fully understand. 1. The Nature…

The Shift Beyond CPUs and GPUs For years, artificial intelligence workloads relied primarily on central processing units (CPUs) and graphics processing units (GPUs). While GPUs revolutionized deep learning with their parallel processing capabilities, they were still general-purpose chips — not built specifically for AI. As models grew larger and more complex, the need for…