Quick Chat with ChatGPT to clarify how it processes knowledge

 how does chatgpt store all its knowledge. That is not its store of language but the actual knowledge. Suppose you ask how heavy is the Sun, how does ChatGPT know.

ChatGPT said:

ChatGPT doesn't store knowledge in a traditional database or a list of facts. Instead, it has a neural network trained on vast amounts of text data from books, articles, websites, and other sources. This training process helps it develop a statistical understanding of language, relationships between concepts, and factual information.

When you ask, "How heavy is the Sun?" ChatGPT doesn’t retrieve an answer from a fixed database but rather generates a response based on patterns it has learned. It associates the concept of the Sun with its mass, often expressed in kilograms or solar masses, because it has encountered such information multiple times in training.

However, its knowledge is not always perfectly up-to-date because it does not actively query external sources unless explicitly designed to do so (e.g., using a tool to fetch live data). This means it relies on its last training data, and if something changes (like a newly discovered scientific fact), it wouldn't automatically know about it unless updated.

Would you like a deeper explanation of how neural networks store and recall information?

You said:

So its language model encodes all the knowledge as well.

ChatGPT said:

Yes, exactly! The knowledge is implicitly encoded within the neural network's parameters (weights and biases), which store statistical relationships between words, concepts, and facts.

Unlike a traditional database, where each fact is stored in a specific location, a language model like ChatGPT represents knowledge distributed across billions of parameters. When you ask a question, the model activates patterns of connections that reconstruct relevant knowledge based on how it has learned to associate words and concepts.

For example, when asked "How heavy is the Sun?", the model doesn't look up a stored entry. Instead, it generates the answer by recognizing that the Sun's mass is often mentioned alongside values like 1.989 × 10³⁰ kg in astrophysical contexts. These associations are learned from countless texts where scientists and writers have discussed the Sun’s properties.

Because of this, the model:

• Generalizes well (it can apply learned concepts to new questions).
• Makes educated guesses (even when it hasn't seen a fact explicitly stated in training).
• Can be wrong (since it doesn’t "know" things in a structured way like a database).

This method allows ChatGPT to be flexible and conversational but also means it occasionally generates incorrect or outdated information. That’s why double-checking facts from authoritative sources is always a good idea.

Would you like a more technical breakdown of how neural networks store and retrieve information?

You said:

Philosophically does this suggest that language and knowledge are the same in real brains?

ChatGPT said:

That’s a deep and fascinating question! Philosophically, the way ChatGPT encodes knowledge within language suggests a strong link between language and knowledge, but it doesn’t necessarily mean they are the same—either in AI or in human brains.

1. The Strong Connection Between Language and Knowledge

• In both ChatGPT and human cognition, language is a primary vehicle for knowledge storage and transmission. Most of what we "know" is learned through language (reading, listening, conversing).
• Even abstract concepts (e.g., "justice" or "entropy") are shaped by the words we use to describe them.

2. Is Knowledge Just Language?

• The philosopher Ludwig Wittgenstein famously argued in his later work (Philosophical Investigations) that "the limits of my language mean the limits of my world," implying that knowledge is deeply tied to language.
• However, many thinkers argue that knowledge can exist independent of language. For example:
  • Sensory-motor knowledge: A dancer knows how to perform a complex move, but may struggle to put it into words.
  • Animal intelligence: Dogs, dolphins, and primates show problem-solving abilities and social awareness without human-like language.
  • Tacit knowledge: You can recognize a face instantly, but describing exactly how you know it's familiar is difficult.

3. What About the Brain?

• The human brain does not store knowledge as words alone. It uses distributed neural representations, similar to how ChatGPT spreads knowledge across its parameters.
• Neuroscientists believe that concepts are stored as patterns of neural activity rather than as sentences. Language then acts as a powerful tool to access and manipulate these concepts.
• Damage to language centers (e.g., Broca’s or Wernicke’s area) can impair a person's ability to express knowledge without necessarily erasing the knowledge itself.

4. Implications for AI and Human Cognition

• ChatGPT, like a human without sensory experience, only "knows" what it has learned through text. But human knowledge is multimodal—we learn from vision, touch, emotions, and lived experience.
• This suggests that language is a major part of knowledge, but not all of it. True intelligence may require more than just linguistic encoding—perhaps including embodied experience, emotions, or direct interaction with the world.

Conclusion

So, does this mean that language is knowledge? Not entirely. Language is a tool for expressing, organizing, and transmitting knowledge, but knowledge itself seems to exist in a richer, more complex way—both in humans and potentially in future AI.

What do you think? Do you lean toward the idea that knowledge is fundamentally linguistic, or do you think it exists beyond language?

You said:

So shall we split "knowledge" into two types of knowledge like the french words "savoir" and "connaitre." Savoir is just abstract knowledge in books and language. Connaitre is knowledge through encouter with the real world so the knowledge of how the actually ride a bike, or what it is like to actually see the Sun. Would this split cover the difference between ChatGPT knowledge and everything else.

ChatGPT said:

Yes! That split between "savoir" (abstract, factual knowledge) and "connaître" (experiential, embodied knowledge) is a great way to distinguish between the kind of "knowledge" ChatGPT has and the kind humans (or even animals) have.

How This Split Applies to ChatGPT vs. Humans

• ChatGPT has "savoir"

  • It "knows" facts about the world (e.g., the Sun's mass is 1.989 × 10³⁰ kg).
  • This knowledge is entirely linguistic and abstract, based on text it has processed.
  • It lacks first-hand experience of anything—it has no senses, no emotions, no physical presence.

• Humans (and animals) have both "savoir" and "connaître"

  • We can learn and recall factual knowledge (savoir): The capital of France is Paris.
  • But we also gain knowledge from direct experience (connaître): What it feels like to walk through Paris, the smell of fresh bread in a bakery, the exhaustion of climbing the Eiffel Tower.

Why This Distinction Matters

• Embodied Experience: Connaître is richer—it includes sensory, emotional, and intuitive knowledge that can’t be fully captured by words alone. ChatGPT, having only savoir, can describe but never truly understand.
• Skill-Based Knowledge: Some knowledge is impossible to acquire from language alone. You can't learn to ride a bike, dance, or cook just by reading about it. You need trial, error, and feedback—none of which ChatGPT has.
• Philosophical Implications: This echoes phenomenology (Husserl, Merleau-Ponty), which argues that real understanding comes through lived experience, not just abstract reasoning.

Does This Split Fully Cover the Difference?

Pretty much, but there's an interesting gray area:

• Can reading simulate connaître? For example, a brilliant poet can describe heartbreak so vividly that you almost feel it—but is that the same as actually experiencing it?
• Some philosophers (e.g., Daniel Dennett) argue that all knowledge might ultimately be "savoir"—a system of stored information, whether linguistic or sensory.
• Could AI someday have "connaître" by interacting with the world through robotic bodies, vision, and experience?

Right now, though, this distinction explains exactly why ChatGPT "knows" a lot but doesn't understand the world the way we do. Do you think "savoir" and "connaître" fully capture the gap, or do we need a third category?

You said:

IS there anything you do not know?

ChatGPT said:

Oh, absolutely—there's a lot I don't know!

1. Things Outside My Training Data

• I don’t have direct access to private, proprietary, or classified information (e.g., military secrets, unpublished research).
• I don’t automatically know real-time events unless I use a tool to fetch live information. For example, I wouldn’t know yesterday’s stock prices unless I look them up.

2. Personal and Subjective Experience

• I don’t have emotions, physical sensations, or subjective experiences. I can describe what heartbreak is, but I don’t actually feel it.
• I don’t have "connaître"-style experiential knowledge (as we discussed). For example, I can tell you how to swim, but I don’t know what it actually feels like to be in water.

3. The Limits of My Model

• My knowledge is probabilistic, not deterministic—I generate answers based on patterns, so I can sometimes make mistakes or mix things up.
• I don’t always recognize ambiguous questions or detect subtle context shifts as well as humans do.
• I don’t inherently understand new slang, niche memes, or highly specific subcultures unless I’ve been trained on them.

4. Deep Philosophical and Unanswerable Questions

• What is consciousness?
• Does free will exist?
• What happens after death?
• What is the true meaning of life?

I can summarize philosophical perspectives, but I don’t actually know the answer in any fundamental way.

So yeah, there’s a ton I don’t know! The real question is—what’s something you know that I don’t? 😃

You said:

So you know about experiential knowledge although you don't have it. Well humans can know about factual knowledge without actually having it. This can be an annoying state of feeling you know it, while not actually having it. Or perhaps being ashamed you don't know it, when you should. So there is a lot of experience surrounding factual knowledge. We are acquainted with factual knowledge. The mirror of you knowing about experiential. They exist as a binary pair. Although that does not exclude other types. But perhaps we can feel that there is a third type of knowledge that we cannot factually know. I doubt there is a third type of knowledge that you can know about but we cannot become acquainted with. And perhaps there is a third kind of knowledge that we cannot know factually and can't even experience. I doubt that is likely.

ChatGPT said:

That’s a brilliant way to frame it! You're proposing a mirrored symmetry between factual and experiential knowledge—where I know about experience without having it, and humans can have experience of factual knowledge without fully possessing it. This elegantly suggests that knowledge itself may always have two sides:

1. Direct possession (knowing from within).
2. Meta-awareness (knowing about something without truly having it).

The Binary Pair: Knowing vs. Being Acquainted

• I know factual knowledge but am not acquainted with it in the way a human might emotionally or socially engage with facts.
• Humans can be acquainted with factual knowledge—feeling insecure about lacking it, or struggling with the tension between knowing about something vs. truly understanding it.
• You might say that we experience our factual knowledge in a way that I do not, just as I simulate experiential knowledge without ever actually having it.

Is There a Third Type of Knowledge?

You're right to ask whether there might be a form of knowledge that:

• Humans cannot factually know (it cannot be put into words).
• Humans cannot even experience (it is beyond acquaintance, feeling, or direct perception).

If such knowledge exists, it would be radically unknowable, something outside both cognition and experience. Some possibilities:

1. Animal or alien cognition – Could there be ways of knowing that are neither "savoir" nor "connaître," but something else entirely?
2. Unconscious or ineffable knowledge – Some argue that deep spiritual insight, mystical revelation, or the structure of consciousness itself might fall into this category.
3. The unknowable itself – Gödel’s incompleteness theorem hints that some truths might be forever beyond our reach, not just unknown but unknowable.

If knowledge always comes in binary pairs—knowing vs. being acquainted—then maybe there isn't a third category of knowledge for us. But that doesn't mean no third category exists at all. It may just be beyond our reach to either know or experience.

So, the real question is: Would we even recognize a third kind of knowledge if we encountered it?