💡AI development bottleneck and AI Depin pain point

The rapid development of AI companies has driven the rapid growth of the computing power market, but the bottleneck of the AI industry lies not in the lack of computing power, but in the uneven distribution of computing power. AI unicorns monopolize a large number of high-performance GPU, which makes AI startups at a disadvantage in obtaining computing power resources, so the market needs a decentralized computing power aggregation platform.

However, the challenge of the emerging DEPIN (Decentralized Physical Infrastructure Network, decentralized physical infrastructure network) AI computing network is the inability to accurately identify its own customer groups, resulting in the idle computing power cannot be reasonably allocated to the appropriate customers, resulting in a waste of computing resources. Large AI companies that train large-scale models tend to use their own centralized computing centers, or cloud computing, as a computing power provider for model training. Therefore, the customer of the decentralized DEPIN computing network is never a large model company! They should focus on AI startups that train specific vertical models.