spacebacon

8 ms·

1.
by spacebacon 3mo ago
This seems like the natural direction for me.
2.
by spacebacon 3mo ago
This may support the point further xD
3.
by spacebacon 3mo ago
Everyone is born a semiotician, no one is born knowing it. Go easy on yourself (and me) for not understanding this yet. Computational semiotics is now an empirical study. LLMs are not proto-minds. They are verifiably semiotic infrastructure
4.
by spacebacon 3mo ago
A frozen model means the original language models weights are not touched. No fine tuning.
5.
by spacebacon 3mo ago
Leveraging a better way. No last mile. https://github.com/space-bacon/SRT
6.
by spacebacon 3mo ago
In very simple terms it can provide a full and live audit on how any frozen model arrives to any answer.
7.
by spacebacon 3mo ago
It’s the babel fish from hitchhikers guide to the galaxy that can also be the pov gun.
8.
by spacebacon 3mo ago
Yes https://github.com/space-bacon/SRT I can read any models every thought. No one cares. Not the narrative.
9.
by spacebacon 3mo ago
A sight for sore eyes. I could use your help. https://github.com/space-bacon/SRT
10.
by spacebacon 3mo ago
You clearly have not read all of my words. Read more.
11.
by spacebacon 3mo ago
On problems this close to active research, seeing the model’s internal reasoning at the points of highest effort is more valuable than pass/fail outcomes alone, which is what SRT-Introspect makes possible on frozen models. https:&#x2F
12.
by spacebacon 3mo ago
Correct. LLMs are technically semiotic infrastructure. Empirically proven with computational semiotics.
13.
by spacebacon 3mo ago
For the downvote. Computational semiotics is empirically proven. Read more.
14.
by spacebacon 3mo ago
The manifold of meaning knows better. The days of black box justification machines are over. There is mystical, there is technical, and there is bedrock. Decision plumbing cant hide from the semiotic-reflexive transformer. To the defenders
15.
by spacebacon 3mo ago
Why are you so pro AI? I find HN well balanced on the topic. LLMs are consistently referred to in proto-mind or cognitive frames. This is whats truly eye rolling. Push back should be a given. We are not even accurately describing them as se
16.
by spacebacon 3mo ago
Smart choice imo. One pass with the SRT wipes their moat out overnight. https://github.com/space-bacon/SRT
17.
by spacebacon 3mo ago
But how do they “think”? This is the only repo that can tell you that. https://github.com/space-bacon/SRT
18.
by spacebacon 3mo ago
LLMs are semiotic infrastructure. You won’t find a better analogy. The cognitive frame won’t hold.
19.
by spacebacon 3mo ago
SRT can read their models thoughts internally at every step if they decide to use it. The problem is that it lowers a draw bridge over their proprietary moat. So of course it’s a natural time to signal a global slowdown. https://
20.
by spacebacon 3mo ago
It’s a convincing argument.
21.
by spacebacon 3mo ago
I imagine the latter as well. They have to sleep at night. That is the nature of these unaccountable justification machines.
22.
by spacebacon 3mo ago
They learned addiction and exploited sugar, fat, and salt with the rest of them.
23.
by spacebacon 3mo ago
It’s not as if they were one shot. 5 repos prior, two published pre-prints on SSRN and thousands of hours back my research that is right there for you to peer review and use freely.
24.
by spacebacon 3mo ago
The main reason to use it is the output quality. SRT steers the model toward a consistent target voice or discourse style more reliably than prompting or basic steering, while keeping the base model frozen. The results feel more coherent in
25.
by spacebacon 3mo ago
SRT does involve a training step, but only on the small adapter and not on the base model. It learns to shift internal representations toward a target discourse regime or style. It is an overlay, but it works by modulating meaning level pat
26.
by spacebacon 3mo ago
It is not LoRA. LoRA fine tunes capabilities into the model. SRT Adapter is a small overlay on a frozen model whose purpose is to make internal reasoning observable. It surfaces what the model is activating at moments of high divergence. Th
27.
by spacebacon 3mo ago
Thanks for the feedback … rough and precise equally appreciated. Computational semiotics was empirically proven with this repo. I will work hard to make the findings and content more accessible for everyone.
28.
by spacebacon 3mo ago
Thank you, I would appreciate additional feedback on how I can improve that? Edit: its not GPT nor off rocker. This repo empirically proved computational semiotics with the reference to C.S. Peirce, Paul Kockelman, and many other respected
29.
by spacebacon 3mo ago
They are all semiotic infrastructure. The cognitive analogy is nonsense.
30.
by spacebacon 3mo ago
I think about this often. The calculation of various projectiles, ranges, rotations, combined with an adaptable muscle memory of sorts can reach “Stan Lee Superhuman” levels with lots of practice.

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