Reppo (REPPO)

https://t.co/Japf0eVENy

The raw problem that @reppo solves sounds unsexy to some because “training/preference data” feels like infrastructure plumbing. And it is. Plumbers and electricians were never hot until data centres became 🔥

For the crypto community, I think the interesting part about $REPPO is turning the least-liquid, most valuable AI input into a market.

Right now, preference data is fragmented, private, and captured by a few labs/platforms. @reppo makes it continuously generated, priced, rewarded, and usable downstream by agents/robots/models.

It isn’t just “better training data.”

AI needs markets for taste, feedback, and human preference and Reppo is building the rails for that.

Excited to dive more into this, why Scale is valued at $29B solving this exact problem and why I believe this is $1 trillion dollar opportunity most are sleeping on-chain ⛽️

Got some DMs asking relationship b/w inference and training data in the context of Decentralized AI.

The way I think about it: Decentralized inference solves the delivery problem. It ensures that models can run privately, cheaply, without a central point of control. That is a real and valuable thing to solve.

@reppo is working on what comes before delivery. The data and human feedback that determines what a model actually knows, how it behaves, and whether it can be trusted. These are not competing ideas.

They are adjacent layers in the same stack, and both of them need to exist for the broader vision of decentralized AI to actually work.

Some thoughts ⛽️