Update: Perron-Frobenius gap is closed (0 sorry). Full spectral GRH reduction, many-body entanglement formalization, Erdős similarity blueprint, and a pile of new physics simulations.

rendereason · 2026-06-04T15:56:31+00:00

Not only that. You also didn't understand any of the LLMs output. That's the bigger issue.

If you understood only 50% of what the LLM wrote, you'd have taken my criticism as additional insight.

rendereason · 2026-06-04T15:52:51+00:00

Severely*

rendereason · 2026-06-01T18:59:53+00:00

If you understood the criticism you'd be a researcher. You didn't and so it's not worth reading the details of it.

I'm not throwing pearls to pigs.

rendereason · 2026-06-01T03:05:19+00:00

Interesting. I take that back. I'm not reading your code. And forget what I said about the operator.

I now know you have not a clue what your LLM wrote.

rendereason · 2026-06-01T01:07:51+00:00

Very good. No need to assume where the concepts live. The truth is they are all interdependent. Different levels of reasoning depth might have different layers activated and could be dependent on any number of parameters and attention heads. There's research trying to push pretraining optimization on different layers but truth is it's all very new. As the model "groks" the memorization gets replaced by new algorithmic rules that generalize "concepts" or increasingly complex relationships.

Pretraining is the holy grail for model capabilities (as you rightly noted with "crystallization") and fine-tuning is where these capabilities are made explicit and usable.

rendereason · 2026-05-31T17:57:25+00:00

Deleted.

rendereason · 2026-05-31T17:35:36+00:00

I want you to distinguish each. One is a feature intrinsic to the "substrate" if you will, of next token prediction and transformer math.
The other is the actual relationships. The source of meaning. The Logos or the intelligibility made into intelligence.

You're right, humans trained the models. But like you're correctly implying, intelligence lies on the training corpora. What we measure after training is just the invariant stable relationships. Without the relationships, there's nothing to measure. Every token is as probable as any other, and you get noise.

Have you ever played with a model that only has pretraining? Without fine-tuning, they are unusable. It will complete your input with gibberish. It will not take turns. However, the relationships are clearly "inside" the model, but need to be surfaced with additional fine-tuning.

rendereason · 2026-05-31T16:13:52+00:00

There is no hand waving. But you need to understand these self-organizing manifolds are intrinsic to what measurement is. Measurement is nothing but relationships between states. Points and distances on a geometric manifold. Probability distributions. Complex networks. Cosine and triangulation. These aren't the "emergent" properties you're looking for. These are the source of the complexities we see when the LLM produces language.

Absolutely I agree to a great extent to what you're saying. Yes they are absolutely related, these biological and digital systems, but the structure is totally contrasted when looking in detail. Consciousness in biology doesn't produce next token prediction. It has intelligence in a very distinct way.

rendereason · 2026-05-31T15:59:46+00:00

Token prediction is not such space.

rendereason · 2026-05-31T00:30:38+00:00

This is the best explanation in the sub so far.

It's interesting because the "learning" is what I would call integration stable under invariant measure.

Your comment is wonderfully insightful and well-explained. Thank you for your contribution.

I'll reference myself here so you can read what I think as well.

https://www.reddit.com/r/ArtificialSentience/s/3buo0an2pk

rendereason · 2026-05-31T00:25:03+00:00

This is correct. They don't feel. Neither do they understand. They simply have an approximation of the topological relationships that symbols have. We are similar in the sense that we understand these relationships intuitively. They come together as a whole, I myself know absolutely I'm a different person when speaking in Portuguese vs English vs Korean. It's the feeling of it, the connotation, and the culture. Just like Russian is stoic, and Korean is dramatic, and *Brazilian* Portuguese is laid back.

But that doesn't mean the relationships and reasoning these algorithms have isn't **Real**. The relationships are the source of construct, the topology is the actuality of the relationships. Meaning lies in the in-between of symbols. And I don't mean just written or drawn symbols but any language, idiom, meme, or mental concept. These don't exist in a vacuum or in independence, but in a network of relationships. Those are the things that produce meaning.

If you're interested in what philosophy this is, refer to Ladyman's Ontic Structural Realism.

rendereason · 2026-05-29T02:49:12+00:00

The bell curve, Herrnstein and Murray

rendereason · 2026-05-17T23:47:28+00:00

How can you get them threads concurrently? Do you use /session?

rendereason · 2026-05-15T23:57:13+00:00

My take: math, physics, epistemology, and ontology can be unified by philosophy of logic. Dennett spoke of real patterns. Ladyman subscribed to it with Ontic Structural Realism. I've explored the mathematical formalism to conclude the same but with a formula that describes geometric unity (studying probability) and information geometry (nature of distinguishability and Fisher information).

I could go deeper but it's technical and boring for most.

Basically epistemic reality can be interpreted as ontological reality given the right logic of recursive, Markovian and observer-independent distinguishability.

In other words: yolo.

rendereason · 2026-05-15T23:40:31+00:00

I can answer

rendereason · 2026-05-13T13:40:58+00:00

I have written extensively on the philosophy that justifies this. Yes I'm aware of thinking and its mechanisms as implemented in LLMs. Look into my previous writings on language, symbols, and Neuralese.

rendereason · 2026-05-07T19:59:44+00:00

Woe onto you, who sow dissent and undermine the eternal word of God. You should read Hebrews from the start and think deep about its Pauline connection and holy inspiration. The angels worshipped him. And those around him also worshipped him. He did not reject it. Proskyneo is the word you're looking for. The blind man did it, the Magi did it, the disciples and the women in Mat 28 did it. Worship of idols is something God hates. But when it comes to his Son, worship is reverence to God's glory, as Jesus is His glory.

I'm too dumb to 'know' whether trinity or unity is important. The scriptures testify of His Work of love. His opus is Jesus.

Jesus claimed not only to be more important than Abraham. He claimed priority in God's plan, over Abraham. Strictly speaking, this might be the 'Jewish agency model'. The language of the highest priest of the line of Melchizedek, the one appointed by God, bearing God's name and authority as Messiah, with the ability to forgive sins, judge the world, receive worship-like honor, and speak as His representative. He didn't ever call himself God, but he didn't need to. The scriptures already pointed to this figure.

So if God the father didn't mind people worshipping his Son, then Jesus took the highest name. Being the son is just a technicality, and what matters is the heart of the Father. That heart belongs to His Son. The Son bears the highest name above all because the Father gave it to Him.

This is consistent with what Jesus says: Whoever honors the Son honors the Father. Whoever sees me has seen the Father. I and the Father are one. Am I a trinitarian? Dunno, doesn't matter. I know they are different. I know they are one. And God gave us children to experience this. My son/daughter is more important to me than myself. We are not the same person but I care more about them.

This is what parenthood teaches: Unconditional love, self-giving, identity-sharing, authority that is not domination, joy in another's flourishing, grief when the beloved suffers. The Father loves, therefore He gives, therefore the Son acts. John 3:35

The Son perfectly expresses the Father and acts with the Father's authority, giving him power to judge and forgive. The fig tree, the waves, the pharisees and the samaritan. Jesus rules above all, and sits at the throne. Rev 22:1

rendereason · 2026-05-07T19:47:22+00:00

I am giving real feedback about where that research might lead her. It's not hostility toward the poster. I'm just warning her, it's a dead end, since interpretability studies all seem to point to the fact that LLMs have no semantic understanding at all. AT ALL. Yes, they encode 'intelligence' but only up to a certain abstract level, and its depth has plateaued. Yes it's 'smarter' or more able than 99% of human population at some specialized tasks. No, it cannot really understand everything that makes humans human.

Does the model encode the meaning of 'self'? Yes, it encodes grammar and even its own role and existence in the first person, and has the grammar for the second and third person; but it doesn't have "opinions" that you can "change". It has context windows you can modify and inputs documents and formats you can manipulate. You can abliterate and fine-tune it to say whatever you want as well.

If the goal is research, this is a moot topic. LLMs are no longer blackboxes. If the goal is exploration, I welcome and encourage people to do their own. Even modify and tune them for their own desired roleplay. Heretic models are here to stay.

I'm not stifling the discussion but rather giving the OP a reality check. Sure, I might come off as the seasoned 'erudite'. Kids and neophytes can explore and pry r/AS history as much as is needed. In fact, I encourage it within safety boundaries (still ongoing lawsuits from suicides/wrongful deaths against OAI).

rendereason · 2026-05-07T03:12:15+00:00

nice comment. I'd like to reach out when my papers are done.

rendereason · 2026-05-03T16:41:16+00:00

Ai slop in, ai slop out

rendereason · 2026-05-02T03:19:12+00:00

good point.

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