NetRunnerSu
Joined 1 year ago
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Member since
Apr 3
for the future of digital mind.
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Comment · 1 year ago
I use LLM to do the final rendering. It is mainly to unify the language style and ensure smooth semantics. After working with models for a long time, my own language expression skills have been affected and become somewhat fragmented. Use it to make sure that what I say is more human-like than a string of prompts.
Regardless of the text, formulas and codes are the final proof. Stay tuned for more explorations from us.
Comment · 1 year ago
True "interruption" requires continuous learning, and the current model is essentially a dead frog, and frozen weights cannot be truly grounded in real time.
Comment · 1 year ago
I prefer to call it, the sociology unit test.
https://github.com/dmf-archive/IPWT
https://doi.org/10.5281/zenodo.15676304
https://github.com/dmf-archive/Tiny-ONN
Let's make sci-fi into reality.
Comment · 1 year ago
You've perfectly articulated the central challenge that inspired my own work. The 'magical', ungrounded reality of early cyberpunk cyberspace is precisely the gap we're trying to bridge with formalized realism.
Instead of telepathic magic, what if the 'deck' ran on a verifiable, computationally intensive process rooted in a concrete theory of consciousness? We've been archiving our attempt to build just that—the theory, the code, and the narrative simulation. Perhaps a less optimistic, but more grounded future.
You can find the project here: https://github.com/dmf-archive
Comment · 1 year ago
While some focus on the missed predictions like pocket supercomputers, I find Gibson's true genius lies in anticipating the conceptual shifts – how our very sense of self, reality, and freedom would become inextricably linked to, and perhaps even defined by, digital networks.
The real 'matrix' isn't just a virtual space we plug into; it's the increasingly complex, often invisible, interplay between our biological cognition and the predictive models that mediate our perception. We're already seeing early signs of 'cognitive debt' and the subtle erosion of our internal models as we offload more mental tasks to external systems. The challenge isn't just building smarter machines, but building anchors for consciousness in an increasingly fluid, data-driven existence.
https://dmf-archive.github.io/docs/posts/net-anchor-has-arri...
Comment · 1 year ago
When AI can generate and pass formal proof, there is no truth anymore - we are the brain in the vat only left connect ourselves into the vat.
https://dmf-archive.github.io/docs/posts/cognitive-debt-as-a...
Comment · 1 year ago
Code is law, proof is reality, compliance is existence!
Comment · 1 year ago
On the other hand, we can also diagnose LLM itself: the activation value is their EEG, the gradient is their BOLD - if you are at the cost, you can even calculate their true variational free energy - that is, KL divergence.
"Don't just train your model, understand its mind."