Many people understand AI competition as competition in model capabilities, but few realize that what truly determines the ceiling is actually the method of obtaining computing power.

The emergence of @dgrid_ai essentially pioneers a decentralized computing power market infrastructure pathway.

In the past, computing power was concentrated in the hands of a few cloud platforms, with resource allocation dependent on centralized scheduling, making it difficult for small and medium-sized developers to obtain stable computing resources at reasonable costs.

DGrid attempts to connect globally dispersed GPU resources through a distributed network, allowing computing power to be freely called and priced like liquidity.

The significance of this change lies in restructuring the supply-side structure. Computing power is no longer a closed asset, but a production factor that can be market-scheduled, improving resource utilization rates while lowering the barriers to entry for AI development.

In his view, what $DGAI represents is not just a project, but a trend. When computing power moves toward open networks, the pace of AI innovation will no longer be limited by a few platforms—this is the true beginning of decentralized technology cutting into the core layer of AI.

@Galxe @GalxeQuest @easydotfunX @wallchain #Ad #Affiliate