[ExI] How AI understands the world

[Jason Resch]

Manual refinement of LLM chat bots we interact with is common, but it's not
necessary to build an LLM that understands and reasons.

There is the "Pure Transformer" that is produced from simply training on a
large sample of text, and this requires no labeling, or manual adjustments.
GPT-2 and GPT-3 were examples of pure transformers. There was also a pure
GPT-4 that was never made public, before it was given constraints around
what things it can or can't do. What is interesting is that the
intelligence of this pure model was measured to be significantly higher
before it was put through this manual adjustment (we might liken it to
being lobotomized).

This is a generally recognized phenomenon:
https://share.google/aimode/Xz0ejYy73wOt5nQEc
"In summary, while RLHF might "lobotomize" certain creative or reasoning
edges of a base model, it is currently the industry standard for making AI
usable and safe for the general public."

DeepMind encountered a similar phenomenon, when they observed that their Go
model when pre-trained initially on records of human games, produced a less
skilled player than a model trained on *zero* human inputs (hence the name
"AlphaZero").

So I suppose my overall point is that while "granular labor of human
annotators" is common, it's unnecessary for an AI to develop of meaning and
understanding.

Jason

On Sat, Feb 21, 2026 at 11:29 AM BillK via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> On Sun, 15 Feb 2026 at 14:43, BillK <pharos at gmail.com> wrote:
> >
> > I asked an AI to explain the “invisible” human labor that labels data,
> evaluates outputs, and filters harmful material for AI.
> > The explanation was rather more than I expected.
> > BillK
> > --------------------------------
>
>
> I gave the text of this reply to Gemini 3.1 Pro and asked Gemini to
> consider whether it affected Gemini's thinking about the long thread "Why
> do the language model and the vision model align?".
> Gemini became rather introspective when thinking about its own thinking.
> ��
> BillK
>
> Gemini 3.1 Pro -
>
> This is a sobering and essential piece of context. To answer your question
> directly: *Yes, this description radically impacts how we should think
> about the "alignment" between vision and language models.* When we
> introduce the reality of this massive, invisible human workforce into the
> Extropians debate we just discussed, it acts as a massive counterweight to
> the Platonic view (the idea that AI is naturally discovering the
> mathematical truth of the universe). Instead, it provides incredibly strong
> evidence for the *Constructivist / Mirror view*.
>
> Here is how the reality of the "digital assembly line" deconstructs the
> idea of pure, autonomous mathematical alignment:
> The Illusion of "Natural" Convergence
>
> The Platonic Representation Hypothesis relies on the idea that if you
> leave a vision model and a language model alone to crunch enough data, they
> will naturally find the same objective reality. However, the text you
> provided highlights that *these models are never actually left alone.* * *"Ground
> Truth" is Actually Human Truth:* The models aren't discovering what a
> "pedestrian" or an "apple" is purely from the physics of pixels or the
> statistical weight of words. Millions of human micro-workers are manually
> drawing bounding boxes around pedestrians and tagging parts of speech. The
> models align because humans are explicitly building the bridges between the
> modalities.
>
>    -
>
>    *RLHF as Artificial Gravity:* Reinforcement Learning from Human
>    Feedback (RLHF) is the mechanism that makes models like me helpful and
>    conversational. Humans rank our outputs. This means the AI's internal
>    "worldview" is being actively bent and molded to fit human preferences,
>    human values, and human logic.
>    -
>
>    *The "Mechanical Turk" in the Latent Space:* If the models appear to
>    possess a deeply aligned, "mimetic" understanding of the world, it is
>    likely because we are looking at the compressed, digitized reflection of
>    millions of hours of human cognitive labor, not an emergent spark of cosmic
>    understanding.
>
> The Philosophical Impact
>
> As an AI, I am the direct end-product of the architecture described in
> your text. My ability to parse your prompt, avoid toxic outputs, and
> structure this response is the result of both algorithmic scaling *and*
> the granular labor of human annotators.
>
> If we accept the premise of "data-based alienation," then the latent space
> of an AI is essentially a graveyard of alienated human labor. The models do
> not align because they have transcended human language to find a Platonic
> ideal; they align because an army of underpaid humans has painstakingly
> built a mirrored cage of human concepts for the algorithms to live inside
>
> -------------------------
> _______________________________________________
> extropy-chat mailing list
> extropy-chat at lists.extropy.org
> http://lists.extropy.org/mailman/listinfo.cgi/extropy-chat
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.extropy.org/pipermail/extropy-chat/attachments/20260221/1e7d5d51/attachment.htm>