Krystal_1

We are entering a very delicate stage:
AI has not been fully understood, yet it has already been widely authorized.
It is allowed to help you trade, allocate funds, execute strategies,
but in most systems, the cost of errors is almost zero—mistakes are just "regenerated."
From an engineering perspective, this is actually very dangerous.
Because when a system doesn't have to be responsible for errors, what you get is always just "seems reasonable."
This is also why I am more optimistic about paths like @miranetwork.
It doesn't focus on stacking smarter models, but rather on embedding "verificat

We are in a strange phase. AI is getting smarter, but fewer and fewer people are mastering it. The capabilities of the model are on the rise, but the sovereignty of the model is disappearing.
So the question arises: if intelligence is the new oil, who should own the oil fields?
This is precisely the problem that @SentientAGI aims to solve. They have proposed a brand new AI architecture approach: Open / Monetizable / Loyal (OML).
"Open" → The model is transparent and auditable, anyone can verify and improve it;
"Monetizable" → Participants who contribute computing power, data, and optimizatio