In 2022, Vitalik floated the idea of “soulbound NFTs”, NFTs that would be linked to your identity forever.

Today, with zkML (which I’ll explain in a bit), I think we can go further: NFTs that will live a life of their own, and decide by themselves when to change owner. I call these Self-willed NFTs.

The simple explanation here is that an NFT could represent an agent with its own personality (potentially secret), that people could try to seduce into updating their ownership.

Of course, you could still allow monetary-based transfer of ownership, but these concepts are taboo in countries with a complicated history like the US.

Anyway, self-willed NFTs can be truly realized through two technologies:

• LLMs, this should be obvious
• zkML, which allows someone to prove that the agent took a deterministic step according to their personality, values, and information available to them

Time to introduce zkML in a few sentences. LLM inference can be seen as a function of two inputs: the model and the prompt, and one generated output. Adding “zk” to it allows you to hide the model, or (part of) the prompt, or the output, or a combination of all three. While maintaining the integrity of the computation of course.

A self-willed NFT could thus have a secret personality committed on-chain (a hash of a pre-prompt), and zkML could be used to prove that some public inference is the correct result of a secret pre-prompt and prompt, as well as a configured and agreed model.

Then the agent could also control tools like a “change of ownership” tool in order to update this. Of course you would have to set a temperature of 0 to prevent abuse from the operator, and also assume that an operator has access to the pre-prompt (or you could have a trusted setup and then an MPC to hide the pre-prompt forever…)

You can imagine that conversations with the LLM could be rate-limited and gated (and ordered) on-chain, via a token, and potentially even private between the self-willed and the NFT.

zkML has seen a lot of advances, notably ICME’s Jolt Atlas, Zkonduit’s EZKL, the Mina zkML library, PSE’s circom-ml library, the work of Modulus Labs, and the work of Daniel Kang. Check it out, it’s a really interesting subfield of ZK! (or a subfield of AI, whichever you’re from.)