In the silent hum of every neural network, a peculiar kind of ‘understanding’ emerges. In AI, it’s not the kind of understanding you or I might recognize. There’s no self-awareness, no whisper of why. But still, these transformers process, predict, and produce results that feel eerily human. What does that say about how we think?
Transformers, those towering marvels of machine learning (the T in GPT), teach us that cognition (understanding, pattern recognition, and prediction) can be stripped down to a series of computations. They excel at identifying patterns in data, much like how we sift through the chaos of daily life to make sense of it. Their “attention” mechanism prioritizes certain inputs over others, mirroring how our brains filter the world around us. [Search for a paper titled “Attention is All You Need”]
Here’s where this gets interesting: Transformers don’t need our human experience of consciousness to function. They don’t wonder, “Why am I doing this?” or feel the weight of their decisions. They simply process and respond. This suggests that understanding might not require the subjective layers of experience we associate with human thought. It’s a humbling reminder that our cognition, while infinitely richer, shares some fundamental mechanics with these digital minds. Is our ‘human experience’ sort of just the processing of our loss function? It’s a thinker. (Buh ddum tss!)
Often enough, I’ve caught myself overthinking a decision, lost in the labyrinth of “what ifs” and “why nots” and the emotions these narratives invoke. That’s where transformers offer a lesson: sometimes, the answer lies in the data, not the drama. By focusing on patterns and context, rather than getting caught in the swirl of emotions, we might make clearer, more effective choices. It feels weird, almost counterintuitive, to think this way… but maybe that’s the point. Is this what Spock was taught in school?
What’s one decision you’re overthinking right now? Can you strip it down to the essential patterns and data points, like transformer technology would? Could you even ask AI directly for help with this analysis?
