A lot of folks think the core of AI is the model.
But I'm starting to feel that the biggest issue for AI in the future might not be intelligence, but trust.
When I first came across OpenGradient Chat at @OpenGradient , I wasn't curious about what questions it could answer; I was thinking: why does AI need to be on-chain?
After digging into it, I realized it's trying to tackle a more foundational issue.
When AI Agents start helping users make decisions, execute tasks, and generate profits, who actually owns that value?
Most AI today are essentially centralized black boxes.
You don't know where the data comes from.
You don't know what's happening during the reasoning process.
And you definitely don't know where the profits ultimately go.
If the identity of the AI, the data sources, the execution process, and the profit distribution can't be verified, then what they call the AI Economy is still just platform economics.
This is also the problem OpenGradient aims to solve.
Traditional Chats focus more on the answers.
OpenGradient Chat, on the other hand, emphasizes the identity, process, and ownership behind those answers.
With On-chain Identity, AI Agents gain traceable on-chain identities.
Through Verifiable AI and provable computations, the execution process can be recorded and verified.
With Data Ownership and contributor incentives, data providers are no longer just giving away value for free; they can participate in value distribution.
This makes me think of a question many overlook:
Is the model really going to be the most valuable thing in the future?
Models will become more abundant.
Parameters will get cheaper.
What might actually be scarce are trustworthy data, credible identities, and the rights to value flow within the whole AI network.
From this perspective, OpenGradient isn't just building an AI Chat.
It's more like constructing an AI Infrastructure that records, verifies, and allocates the relationships between AI Agents, data contributors, and users.
If this path holds, then the competition in the future won't just be about model parameters, but about who controls the value flow across the entire AI network.
What $OPG captures might not just be a single AI narrative, but the ongoing ability to capture value in the future AI Economy.
#OPG $OPG @OpenGradient
But I'm starting to feel that the biggest issue for AI in the future might not be intelligence, but trust.
When I first came across OpenGradient Chat at @OpenGradient , I wasn't curious about what questions it could answer; I was thinking: why does AI need to be on-chain?
After digging into it, I realized it's trying to tackle a more foundational issue.
When AI Agents start helping users make decisions, execute tasks, and generate profits, who actually owns that value?
Most AI today are essentially centralized black boxes.
You don't know where the data comes from.
You don't know what's happening during the reasoning process.
And you definitely don't know where the profits ultimately go.
If the identity of the AI, the data sources, the execution process, and the profit distribution can't be verified, then what they call the AI Economy is still just platform economics.
This is also the problem OpenGradient aims to solve.
Traditional Chats focus more on the answers.
OpenGradient Chat, on the other hand, emphasizes the identity, process, and ownership behind those answers.
With On-chain Identity, AI Agents gain traceable on-chain identities.
Through Verifiable AI and provable computations, the execution process can be recorded and verified.
With Data Ownership and contributor incentives, data providers are no longer just giving away value for free; they can participate in value distribution.
This makes me think of a question many overlook:
Is the model really going to be the most valuable thing in the future?
Models will become more abundant.
Parameters will get cheaper.
What might actually be scarce are trustworthy data, credible identities, and the rights to value flow within the whole AI network.
From this perspective, OpenGradient isn't just building an AI Chat.
It's more like constructing an AI Infrastructure that records, verifies, and allocates the relationships between AI Agents, data contributors, and users.
If this path holds, then the competition in the future won't just be about model parameters, but about who controls the value flow across the entire AI network.
What $OPG captures might not just be a single AI narrative, but the ongoing ability to capture value in the future AI Economy.
#OPG $OPG @OpenGradient