Lately, scrolling through Twitter, I've noticed that decentralized AI projects are partnering up like bubble tea shops going on a franchise spree. One day they're doing a "strategic partnership" with a model team, the next day it's "co-building ecosystems" with a computing power platform, and the posters just keep getting flashier.
But all the hype is just that—when the party's over, everyone heads back home. To put it bluntly, the players in the Web3 AI space are like nomads; when the coin price spikes, they flood in, but when it dips, they bail with their nodes. This structure is super fragile; when the narrative shifts, the community vanishes faster than a desert turns to dust.
The project team is scrambling for partnerships, which really boils down to buying traffic and renting users. But when that rented traffic runs out, poof—people disappear. To truly retain users, partners need to plant their roots—models really need to run inference on your network, data must truly flow through the protocol, and developers gotta be using the SDK to create stuff.
I think $OPG gets this. It didn’t package itself as an "AI unicorn" but instead is straightforwardly building the decentralized AI infrastructure layer. The model teams, computing power providers, and data contributors aren't just there for photo ops; they're here to put in the work. #OPG
For model providers, it's a lightweight on-chain testing ground, and for @OpenGradient , every time a real model is integrated, the network gains more muscle.
If this model takes off, we'll need a new metric for evaluating AI projects. Forget about FDV and coin prices; focus on how many models are actually running in the network, how much data is genuinely flowing, and how much computing power is consistently online instead of just harvesting rewards.
By that time, value won't be on the candlestick chart, but in how many AI teams have made it their "default option."
But all the hype is just that—when the party's over, everyone heads back home. To put it bluntly, the players in the Web3 AI space are like nomads; when the coin price spikes, they flood in, but when it dips, they bail with their nodes. This structure is super fragile; when the narrative shifts, the community vanishes faster than a desert turns to dust.
The project team is scrambling for partnerships, which really boils down to buying traffic and renting users. But when that rented traffic runs out, poof—people disappear. To truly retain users, partners need to plant their roots—models really need to run inference on your network, data must truly flow through the protocol, and developers gotta be using the SDK to create stuff.
I think $OPG gets this. It didn’t package itself as an "AI unicorn" but instead is straightforwardly building the decentralized AI infrastructure layer. The model teams, computing power providers, and data contributors aren't just there for photo ops; they're here to put in the work. #OPG
For model providers, it's a lightweight on-chain testing ground, and for @OpenGradient , every time a real model is integrated, the network gains more muscle.
If this model takes off, we'll need a new metric for evaluating AI projects. Forget about FDV and coin prices; focus on how many models are actually running in the network, how much data is genuinely flowing, and how much computing power is consistently online instead of just harvesting rewards.
By that time, value won't be on the candlestick chart, but in how many AI teams have made it their "default option."