One thing I keep noticing about technology is that the work people value most isn't always the work they notice most.
While reading about @OpenGradient , I started thinking about the difference between inference and verification.
Inference gets attention.
A user asks a question and receives an answer.
The result is immediate, visible, and easy to appreciate.
Verification feels different.
Its job is to prove that execution happened as expected, but if everything works correctly, most people never look at the proof.
That's what makes the incentive problem interesting.
If you're contributing resources to a network, visible work naturally feels more valuable than invisible work.
Yet the invisible part may be the reason trust exists in the first place.
I used to think infrastructure incentives were mostly about paying people enough.
Now I'm not so sure.
Maybe the harder challenge is rewarding work whose importance only becomes obvious when something goes wrong.
Most networks reward output.
Verifiable AI may also need to reward diligence.
And that feels like a very different design problem.
If verification becomes essential for trustworthy AI, how should networks make sure the people providing it stay motivated long before anyone actually needs to check the proof?
@OpenGradient #opg $OPG $RE $ESPORTS
