Auguste Rodin, 1910, Robert MacCameron
The overloading of common terminology is well underway: new language models have “thinking” modes, “reasoning” capabilities! What this means, in practice, is that they’ve learned to produce a special kind of text, the conversion of the linguistic if-then into a dynamo that spins and spins and, often, magically — yes, it is magical — produces useful results.
But here is one distinction among many: this process can only compound — the models can only “think” by spooling out more text — while human thinking often does the opposite: retreats into silence, because it doesn’t have words yet to say what it wants to say.
Human thinking often washes the dishes, then goes for a walk.
If you redefine “thinking” to mean “arriving at a solution through an iterative linguistic loop” … yes, that’s what these models do. But that definition is pretty thin. We talk about humans thinking harder, which is not the same as thinking longer. I think most people know from experience that thinking longer generally just makes you anxious. But that’s what the models do, and not only longer, but in parallel, all those step-by-step monologues spilling out simultaneously, somewhere in the dark of a data center. “Quantity has a quality all its own,” said Stalin, maybe …
Well, okay — what does it mean for a human to think harder? Reasonable people will disagree (and in interesting ways) but, for my part, I think it means prospecting new analogies; sending your inquiry out away from the gravitational attractors of protocol and cliché; turning the workpiece around to inspect it from new angles; and especially bringing more senses into the mix. You’ll note these are challenging or impossible for systems that operate only on/with/inside language.
A couple of years ago, when I wondered if language models are in hell, I expressed my hope for the richness of multimodal training. So far, this hasn’t panned out. Rather than images pulling text into a richer, more embodied realm, the marriage seems to have gone the opposite direction, making images thin. The models chop them into sequences of tokens — big pictures become spindly threads, a bit sad — and feed them in along with everything else.
We are going to lose this battle over terminology — we have already lost it — but/and it’s useful to put a marker in the ground; a gravestone, you might call it; for words that once meant something.
Other useful words, still untarnished, include: imagination, ingenuity, insight. Clarity, most of all. Clarity is what Einstein was seeking when he sat and thought hard about the relative motion of magnets and conductors. He wanted to push through language, beyond it, beyond even the formalism of physics — because there wasn’t physics yet for the things he wanted to understand.
Think harder!
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