How AI and DEPINs Will Change Web3

Decentralized Physical Infrastructure Networks (DEPINs) are revolutionizing the use of blockchain technology to share resources across various sectors, promising significant advances, particularly in artificial intelligence.

What are DEPINs?

DEPINs, or Decentralized Physical Infrastructure Networks, utilize blockchain technology to decentralize and democratize access to essential physical resources. These networks allow everyone to contribute to and benefit from the global infrastructure, offering a fair alternative to centralized models dominated by large companies. By sharing resources such as computing power or storage, DEPINs promote a more efficient and accessible use of technology, reducing costs and increasing availability for all users, especially in the field of AI.

Challenges of Centralized Actors in AI

In the field of artificial intelligence (AI), comparing Decentralized Physical Infrastructure Networks (DEPINs) with centralized service providers, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, reveals several key differences, particularly in terms of flexibility, access, and cost.

• High Entry Barriers and Costs: Access to centralized platforms often involves substantial costs, especially for resource-intensive operations like deep learning model training. These costs can be a major hurdle for startups and independent researchers.
• Dependence and Risks: Centralization leads to dependence on these large companies, raising concerns about data control and security. Moreover, the risk of system failures and service interruptions remains a major concern.
• Scalability and Innovation: The ability to scale quickly and innovate can be hindered by the rigid structures and bureaucratic processes of centralized providers, thus limiting the rapid deployment of AI solutions and the ability to experiment.

Solutions Offered by DEPINs in AI

Decentralized Physical Infrastructure Networks (DEPINs) provide innovative responses to the current challenges faced in the AI sector, highlighting decentralization as a lever for efficiency and accessibility:

• Increased Computing Power: By distributing computing power across a decentralized network, DEPINs can effectively meet the growing demand, especially for training deep learning models. This approach maximizes the use of available resources and reduces dependence on traditional GPUs.
• Response to GPU Shortage: Relying on shared infrastructure, DEPINs mitigate the effects of GPU shortages by diversifying sources of computing power. This paves the way for more accessible and less expensive alternatives for AI developers.
• Reduced Costs for Training and Executing AI Models: Thanks to DEPINs’ collaborative approach, the costs associated with training and executing AI models are significantly reduced. Sharing computational resources allows for pooling expenses and making AI technologies more affordable for everyone.
• Improved Accessibility to Computing Power for Smaller Players: By eliminating financial and technical barriers, DEPINs democratize access to the computing power necessary for AI development. This increased accessibility stimulates innovation and promotes participation by independent researchers and small businesses.
• Increased Data Quality and Reduced Costs: DEPINs also facilitate access to high-quality data sets at reduced costs. Relying on mechanisms for equitable sharing and compensation, they encourage the creation and distribution of rich and diverse data sets needed for training AI models.

The DEPIN sector, based on a system similar to that of Airbnb, which revolutionized the way people travel by allowing homeowners to rent their unused spaces, similarly transforms the AI sector into the “Airbnb of computing power.” Just as Airbnb uses empty houses to meet accommodation needs, DEPINs utilize the unused computing power of computers worldwide for training and executing AI models.

Previously, just as hotels held the monopoly on accommodation, large companies exclusively controlled the computing power necessary for AI. Today, this dynamic is changing, opening the way for new possibilities of sharing and accessibility.

DEPIN Sector Projects

Here are some examples of innovative projects in the DEPIN sector:

• Filecoin (FIL): Filecoin aims to create a decentralized file storage system, allowing users to rent out their unused storage space in exchange for FIL, the network’s native token. This project seeks to make data storage more secure, efficient, and cost-effective.
• Render (RNDR): Render offers a decentralized platform for graphic rendering, using the unused computing power of participating computers to process 3D rendering tasks. Users who provide their computing power are rewarded in RNDR tokens.
• Ocean Protocol (OCEAN): Ocean Protocol is developing a decentralized platform for data sharing and monetization, facilitating secure access to data sets for training AI algorithms. OCEAN, the network’s token, serves as an incentive mechanism for data sharing.

Conclusion

In conclusion, the DEPIN sector represents a revolution in the use of blockchain, bringing innovative solutions to the challenges in the field of artificial intelligence. By democratizing access to the necessary physical infrastructure for AI, DEPINs promise improved accessibility, significant cost reduction, and increased availability of computing power. Projects like Filecoin, Render, and Ocean Protocol illustrate the disruptive potential of DEPINs to reshape sectors such as data storage, graphic processing, and secure information sharing. As DEPINs evolve within AI, the future holds great promise for innovation, efficiency, and international cooperation.