Competitors and Comparative Advantages
Last updated
Last updated
The decentralized computing power market is in its early stages of development, with the AI computing market being the most potential-rich and demanding in terms of development challenges, hardware requirements, and funding needs. Some representative projects are exploring the use of blockchain and distributed computing technologies to meet the demands for AI training and inference, each with its own strengths and limitations.
Render Network
Provides a full-service management flow from development, deployment, launching, distribution, to trading, attracting developers and users.
However, it currently resembles a decentralized cloud platform concept and has not yet achieved complete decentralization of computing power.
Fetch.AI
Attempts to use blockchain and distributed computing to meet the demands for AI training and inference.
However, it is still some distance from actual implementation in the AGI computing power market.
io.net
An advanced decentralized GPU computing network that offers machine learning engineers access to distributed cloud clusters at relatively low costs. By aggregating idle GPUs from independent data centers, cryptocurrency miners, and projects like Filecoin and Render, it provides computing power to users, but currently resembles a decentralized cloud platform more than a fully decentralized computing network.
Gensyn
Has designed an intricate game system at the validation and incentive layers to quickly pinpoint errors.
However, the system lacks many details, such as how to set parameters to ensure reasonable rewards and penalties without making the barriers too high.
Compared to these similar projects, DSC also has several unique advantages:
Own Distributed Storage System:
Unlike Render Network and io.net, which focus more on the concept of decentralized cloud platforms, DSC possesses its own distributed storage platform. This not only supports more complex data processing needs but also enhances data security and privacy.
Cloud Computing Services for B2B and B2C:
Planned for launch in the third quarter of 2024, DSC products will allow users to rent cloud computing power based on their needs. This flexibility meets the diverse requirements of customers from small development teams to large corporations, thus strengthening its market competitiveness.
Incentive Mechanism:
DSC utilizes its Web3 architecture to offer a token economy system, incentivizing users to contribute idle computing resources, promoting efficient resource use and network growth. This model is similar to the incentive strategies of Fetch.AI and Gensyn, but DSC's implementation is more comprehensive, covering validation, transactions, and settlements.
Emphasizing Environmentally Friendly AI Development:
DSC reduces the carbon footprint of AI development by utilizing dispersed GPU resources, aiming to provide a more sustainable model for AI development.
Global Node Network:
DSC plans to expand its nodes globally, which will greatly enhance the system's redundancy and fault tolerance, ensuring service continuity and stability even if some nodes experience failures.
