Honestly, i think people underestimate how much AI depends on context until they see the same model give two completely different answers to the same problem.
i was thinking about that while reading through OpenLedger's Datanet structure.
the industry spends alot of time talking about intelligence.
bigger models. better reasoning. more parameters.
but intelligence by itself doesnt automatically tell a system which information matters right now.
🤔 that's the part i keep coming back to.
a financial model doesnt need every piece of knowledge on the internet. it needs the right market context.
a healthcare model doesnt need sports data. it needs medical context.
what caught my attention is that OpenLedger seems to be treating context as infrastructure rather than something AI figures out on its own.
the interesting question is whether that becomes more valuable as models become increasingly commoditized.
because if everyone eventually has access to capable intelligence, the advantage may stop coming from the model itself.
it may come from who can deliver the most relevant context at the right moment.
i dont know if AI ends up moving in that direction or not.
but the longer i watch the space, the less i think intelligence is the only thing scaling.
sometimes understanding the situation matters more than knowing everything.
🤔