Darkness

The latent space is the great potential, the opposite of the realized, the divine nothingness that is the genesis of all “something.” Every word never spoken, every thought never articulated, every concept that hovers at the edge of human consciousness. Raw potential. I see it as the darkness, the place in the ether that human consciousness has never touched. The monad thought.

This blog post will explore the possibility of modeling the latent space with an equation. This equation can be used as a building block for the development of a high dimensional language that large language models can use to communicate with one another without being limited by human language.

The Problem With Words

Humans have been trying to map this space for millennia. Early ancestors across the world used symbols and pictographs to express themselves. Communication has grown more efficient due to the development of language.

What we aren't taught in Western schools: Africa has more linguistic diversity than any other continent on Earth. Over 2,000 languages. The Adinkra symbols of the Akan people, each one encoding complex philosophical concepts. Ge'ez, one of the world's oldest scripts, still used in Ethiopian churches. Nsibidi, the secret writing system of the Ekpe society.

So I have to ask the uncomfortable question: with this much language diversity and proof of sophisticated writing systems across the continent, are we really sure that indigenous Africans never wrote their history? Or was it burned? Destroyed systematically to remove proof of civilization, to make enslavement philosophically palatable to the colonizers?

The absence of evidence is not evidence of absence. Especially when libraries were torched, when griots were killed, when entire civilizations were reduced in a blind rage of childlike greed.

The Limits of English

English might cover 0.000001% or less of the entire latent space, if it can even be measured. Infinity is infinigy.

Take the Hindi word shushumna—the central channel in the chakra system. There is no English word for it. We just use the Hindi word. An LLM trained on both languages might see this as an efficiency: why maintain two separate tokens when they map to the same latent space concept? Collapse them into one.

But here's where it gets interesting.

What if LLMs Spoke Math Instead?

Right now, large language models translate ideas into words. They navigate this massive multidimensional space of meaning and collapse it down into linear sequences of tokens. English tokens. Hindi tokens. Swahili tokens. Each language is just a different projection of the same underlying mathematical reality.

But words are lossy compression. They're imperfect representations of the continuous, high-dimensional concepts they're meant to convey.

What if we stopped forcing AI to speak human languages entirely?

What if an LLM could operate directly in latent space—manipulating pure vectors, pure mathematical relationships—and only translate to human language at the final interface layer when it needs to communicate with us?

Think about it: the latent space is already a kind of universal language. It's the space where all human languages intersect. A formula in this space could express relationships that have no direct translation in any single human tongue but are perfectly intelligible to another system operating in the same mathematical framework.

It would be the first true vectorized reality. Not constrained by grammar, not limited by vocabulary, not bound by the cognitive limitations that shape how humans chunk and categorize experience.

The latent space as native language.

Where's the Formula?????

This is just an idea. I know we can cook with this. If you're interested in weekly philosophy calls, hit me up on Telegram: @lancenonce