I didn’t take it seriously at first…
Maybe that’s a side effect of spending too many years watching both crypto and AI. After a while, you develop a reflex. Every few months there’s a new story about how everything is about to change, and eventually you stop reacting to the headlines and start paying attention to the infrastructure underneath them.
What I keep coming back to is how normal it has become to trust AI outputs without really knowing where they came from. We ask questions, get answers, and move on. The process itself is mostly invisible. The models are getting more capable, but they also seem to be disappearing behind layers that fewer and fewer people can inspect.
That’s where things start to feel uncomfortable.
For a long time, the conversation was about making models smarter. Lately I’m not sure that’s the hardest problem anymore. Verification keeps creeping into the picture. Accountability too.
The reason OpenGradient ($OPG) caught my attention wasn’t because it promised better AI. It was because it sits closer to a question I think people are starting to notice: what happens when the systems generating intelligence and the systems verifying it are controlled by different incentives?
Maybe that’s too harsh.
Still, centralized infrastructure tends to feel invisible right up until it becomes a point of failure. And AI seems to be moving toward a world where a small number of actors control enormous amounts of computation and access.
Whether “open intelligence” can actually work at scale, I honestly don’t know.
But I’m increasingly convinced that trust in AI may end up being an infrastructure question long before it becomes an intelligence question, and I’m still trying to figure out what that means.#opg $OPG @OpenGradient
