I’ve been reflecting on how 𝑨𝑰 𝒂𝒈𝒆𝒏𝒕𝒔 built on large language models communicate, not with 0s and 1s but through tokens, hinting at a quiet shift in how information behaves.

💡 For decades, the 𝒃𝒊𝒕 was the indivisible unit of information: binary, context-free, and precise. But as autonomous agents reason and converse, the 𝒕𝒐𝒌𝒆𝒏 seems to have become a new kind of 𝒂𝒕𝒐𝒎𝒊𝒄 𝒖𝒏𝒊𝒕, one that carries meaning rather than just state.

Tokens are probabilistic, contextual, and relational. When agents “talk,” they do not simply exchange data; they negotiate intent, knowledge, and belief through the medium of language.

This changes everything. Information flow is no longer purely computational; it is…𝒊𝒏𝒕𝒆𝒓𝒑𝒓𝒆𝒕𝒊𝒗𝒆(!)

Systems are evolving from pipelines of data into 𝒏𝒆𝒕𝒘𝒐𝒓𝒌𝒔 𝒐𝒇 𝒖𝒏𝒅𝒆𝒓𝒔𝒕𝒂𝒏𝒅𝒊𝒏𝒈, where the integrity of meaning may soon matter as much as the integrity of bits once did.

It raises deep questions:

• How do we define entropy when the message’s value depends on shared context rather than probability?

• What happens when 𝒄𝒐𝒉𝒆𝒓𝒆𝒏𝒄𝒆, not compression, becomes the key optimization goal?

• Are we seeing the beginnings of a new information theory, one where meaning itself becomes measurable?

And yet, I can’t help but wonder if this new “information currency” is the endgame or just a phase… As multimodal reasoning deepens, weaving language with vision, space, and embodiment, information itself may evolve again toward richer, multidimensional units.

Perhaps this will ultimately bring us full circle, back to the substrate of computation (to bits, or even qubits) but this time infused with the semantics of thought…?

Of course, tokens may just be the visible layer of a deeper substrate. Beneath them lie the 𝒆𝒎𝒃𝒆𝒅𝒅𝒊𝒏𝒈𝒔: high-dimensional fields where meaning takes shape not as symbols but as geometry. If tokens are the visible colors of language, embeddings are the spectrum beneath (the full range of meaning our eyes can’t see directly but that shapes what appears). Perhaps the real revolution isn’t in the shift from bits to tokens, but in the emergence of these 𝒔𝒆𝒎𝒂𝒏𝒕𝒊𝒄 𝒎𝒂𝒏𝒊𝒇𝒐𝒍𝒅𝒔 – where information begins to resemble understanding.

#ai #agents #informationtheory