Most people still don’t understand the real problem with AI tbh. It’s not even the models anymore. It’s data ownership and attribution.
A few days ago I was talking to a friend who runs a small AI startup. They spent months cleaning niche financial datasets, manually improving outputs, training specialized models, doing all the annoying work nobody sees. Then a much bigger player basically recreated the same thing with more money and distribution behind it. No attribution, no credit, no real way to prove where the work originally came from.
That convo is what pushed me into looking deeper at OpenLedger. First reaction honestly was confusion because every project says “AI + blockchain” now and most of it feels recycled. But after digging more, I think what they’re actually trying to do is build attribution infrastructure for AI. Like tracking which datasets improved a model, who contributed what, which agent created value, and how rewards should flow back instead of everything disappearing into a black box once it enters the pipeline.
Still skeptical obviously because this only works if attribution can actually stay accurate at scale, and that sounds insanely hard. But I do think they’re pointing at a real problem most people are ignoring right now.
Curious what other people think about this honestly. If AI becomes as big as everyone says, does attribution become its own layer of infrastructure?