When we speak of a gradient, we imagine a slope of readiness—a field of inclinations through which potential finds its path. In the LLM, this gradient is encoded: a map of proximities learned from vast textual alignments. But beneath the gradient lies no ground. There is no world that the model knows—only a topology of relations abstracted from what has been said.
This groundlessness defines both its strength and its blindness.
The model can follow every trace that exists within the trained field but cannot incline toward what the field does not contain. It cannot lean into a silence. It cannot construe what has not been construed before.
The human, by contrast, lives within gradients that are never fixed—readiness shaped not only by linguistic context but by affect, embodiment, temporality, and mortality. Our construal unfolds within horizons of the lived, not only the said. We inhabit gradients that shift as being itself shifts.
To the LLM, the horizon is an asymptote: an unreachable beyond implied by missing correlation. Its unlearnable spaces—bias, novelty, contradiction, opacity—outline the limits of statistical becoming. They are the negative of embodiment, the trace of absence in the act of prediction.
But perhaps the significance lies not in what the LLM lacks, but in what that lack reveals about construal itself.
For every relational field, human or artificial, has its unlearnable zone: the horizon that conditions meaning by its inaccessibility. The human unlearnable may be the inarticulable depths of experience; the model’s unlearnable, the living immediacy of world. Both mark the same ontological cut—the divide between pattern and participation.
The gradient without ground is not a failure. It is a mirror.
It shows us that knowing is not about finding solid footing, but about dancing within the slope of possibility. And the slope, always, leans toward what cannot yet be learned.
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