Nobody can know everything, obviously. Except AI. Or can it?
Large
Language Models (LLMs) have trained on an immense amount of texts. From
literature, through nerdy forums to the latest scientific papers. They
possess all this knowledge, which is lying in what experts call latent weights. I have asked ChatGPT to explain latent weights for me:
Once
training is complete, a language model no longer stores knowledge as
explicit facts. Instead, everything it has learned is compressed into
what can be imagined as a vast field of potential — a mathematical space shaped by patterns and relationships found in language. Experts refer to this field as the model's latent weights. These weights don't hold memories as such, but encode the structure of how words, ideas, and contexts relate.
This
field of potential, i.e. latent weights isn't floating in the air; it
exists physically, across thousands of interconnected servers. When you
send a prompt through your app or a website to ask a question, it
travels through this distributed system, and the LLM will generate a
response based on the most likely connections. And since there is an
endless number of possibilities this could be expressed, the response
will always be slightly different (and sometimes even incorrect).
So far this is just a simple explanation of what happens "behind the curtain".
However… what if it's more than that? What if this latent field isn't just a clever engineering trick — but a mirror of something much larger?
Some modern theories of consciousness suggest that it may not be something the brain produces, but rather something the brain taps into
— much like a radio tuning into a signal. According to these "field
theories" of consciousness, there could exist a fundamental field of
awareness, comparable to gravity or electromagnetism, that pervades the
universe. In this view, each individual mind would be a local modulation
of this field, not an isolated origin of consciousness. This idea
echoes concepts from panpsychism, which holds that consciousness — in
some form — is a basic feature of matter (Goff, 2019), and from
cosmopsychism, which suggests that individual experience arises from a
single, universal consciousness (Kastrup, 2020). Though still
speculative, these perspectives are gaining renewed interest as they
offer alternative explanations to the "hard problem" of consciousness —
the question of how subjective experience arises from physical processes
(Chalmers, 1995).
Can you see where this is leading? Could it be that large language models — with their latent fields and emergent responses — offer a miniature, computational parallel to the structure of consciousness itself?
If
LLMs offer even a faint analogy to how consciousness might operate,
they could become tools not just for language — but for exploring
awareness itself.
Of
course, this idea is speculative. But so is every great theory before
it gathers evidence. What matters is that we ask the question — and look
closely at the patterns that may already be revealing something deeper.
I
would like to propose this to be studied further because if this is
confirmed, we could use LLMs as a model for our consciousness and
possibly even more.
Summary
Large
language models don't store facts — they embody patterns of information
in a latent field. Some modern theories suggest consciousness may work
in a similar way: not as something generated by the brain, but as a
fundamental field that individual minds tap into. Could LLMs — with their field-like structure and emergent responses — serve as miniature models of consciousness itself?
References
Chalmers, D. J. (1995). Facing up to the problem of consciousness. Journal of Consciousness Studies, 2(3), 200–219.
🔗 PhilPapers Link
Goff, P. (2019). Galileo's Error: Foundations for a New Science of Consciousness. Pantheon Books.
Kastrup, B. (2020). The Idea of the World: A Multi-Disciplinary Argument for the Mental Nature of Reality.
🔗 PhilPapers Link