For a long time, I thought AI's biggest challenge was intelligence.

The assumption seemed obvious: make models smarter, give them more data, improve reasoning, and everything else would follow.

But the more time I spent watching the space, the more I realized intelligence may not be the hardest problem.

Trust is.

How do we know where an AI-generated output came from?

How do we verify the data behind it?

How do we build confidence in systems that are increasingly making recommendations, decisions, and predictions?

That shift completely changed how I look at AI infrastructure.

Recently, I started exploring @OpenGradient and what caught my attention wasn't another promise of smarter AI.

It was the focus on making AI systems more transparent, verifiable, and accountable.

As AI moves deeper into finance, research, governance, and everyday decision-making, verification may become just as important as intelligence itself.

That's why projects like @OpenGradient stand out to me. They're exploring how decentralized infrastructure can help create trust around AI rather than simply chasing larger models.

One thing I've changed my mind about is this:

The future of AI may not belong to the smartest system.

It may belong to the system people trust enough to depend on.

$OPG #OPG