When everyone is discussing model capabilities, has anyone seriously thought about how computing power is priced?

This is a question I keep pondering during my ongoing observation of @dgrid_ai. A clear contradiction in the current AI industry is that demand is continuously growing, but the supply side lacks transparent and flexible market mechanisms.
The price of computing power is often dominated by a few platforms, making it difficult for users to fine-tune configurations based on actual needs.
$DGAI 's design attempts to introduce a more market-oriented pricing logic, allowing supply and demand for computing power to be matched on-chain. If this mechanism can succeed, it means that computing resources will shift from fixed services to tradable assets.
For developers, this offers more options; for resource providers, it opens new revenue streams.
From a trend perspective, computing power is gradually becoming financialized. It is no longer just a technical resource but an asset that can participate in market circulation. This change will bring new opportunities but also higher complexity.
dgrid is trying to find a balance between these two aspects. Its success depends on whether its pricing and scheduling mechanisms are stable and efficient enough.
@Galxe @GalxeQuest @easydotfunX @wallchain #Ad #Affiliate @TermMaxFi