Decentralized Computing Power platform: A new business model connecting AI companies with idle graphics cards

Recently, two artificial intelligence conceptual projects have successively held token generation events, which has led to some reflections.

This is actually a very classic business model: on one hand, there are some artificial intelligence startups and game rendering companies, and on the other hand, there are individuals who have idle high-performance graphics card resources. If there is a platform that can connect the needs and resources of these two parties, a typical platform business model is formed.

Some platforms have identified this market opportunity and are preparing to build a bridge connecting idle graphics cards with artificial intelligence or rendering companies. This idea makes sense, as many AI companies may not have the ability to purchase a large number of graphics cards on their own.

Artificial intelligence companies are reluctant to purchase large quantities of graphics cards for two main reasons: firstly, the cost is too high, and they prefer to have the flexibility to rent graphics cards whenever needed. Secondly, there is currently a tight supply of graphics cards internationally, and there are even some embargo situations. As a result, many companies have to choose some overseas third-party institutions for intermediary services, which also brings a lot of costs and potential risks. In this context, a decentralized infrastructure becomes particularly important.

However, this platform model faces a classic "which came first, the chicken or the egg" problem. AI startups join the platform because they believe there are enough GPU resources available, while those who own GPUs are willing to list their resources on the platform because they believe there will be sufficient orders. If the platform starts from scratch, without enough GPUs and companies participating, launching will be very difficult.

This is why these platforms need cryptocurrency, as it can help them break this cycle. Some platforms have chosen a "chicken first" approach. Even without orders, they can accumulate GPU resources through Token subsidies. They launched incentive programs, with hundreds of thousands of GPUs hanging on the platform during peak periods.

These decentralized computing platforms typically adopt a conventional and effective approach: their platforms support the use of fiat currency or stablecoins as payment methods, while also providing the option to pay with the platform's Token, which can waive certain fees. This approach does not force users to use the platform's Token, yet it provides some practical functionality for the Token. Regardless of the discount rate, this will encourage users who need to make payments to hold these Tokens, which is very beneficial for the decentralization of the Tokens.

When it comes to building ecosystems, different platforms may have different approaches. Some platforms have chosen an alternative strategy due to the large number of artificial intelligence classification platforms and intense competition. To gain an advantage in this competition, they have launched products such as virtual mining machines and physical mining machines. This approach is very effective in maintaining the community's basic support, as users are more inclined to stay in this community when they have some sunk costs on the platform.

Some platforms have also introduced the role of inspectors, who continually check the working status of graphics cards and the processing of orders, earning Token rewards through inspections. This practice can enhance the reliability and stability of the platform.

Overall, these decentralized computing platforms are trying different strategies to attract users and resources, building their own ecosystems. Their development will have a profound impact on the integration of artificial intelligence and blockchain technology.