作者： Gregory Pudovsky
The AI industry is under the monopolistic control of centralized companies, which has an adverse impact on startups and ordinary users. However, web3 technologies like DePIN can intervene and democratize the AI industry.
In this interview, we discuss the relevance of DePIN in the AI industry, EdgeAI, and the potential for collaboration between these technologies with Rock Zhang, founder of Network3.
Q: Hello. Could you please introduce yourself to our readers and share your professional journey?
Hi, I'm Rock, and I'm glad to be here. I'm the founder of Network3, an AI Layer2 that uses DePIN to help AI developers reason, train, and validate models at scale.
I am also the founder of Rock TechX, a platform that makes people's digital lives safer. Prior to that, I was the product leader at iHealth Labs, socialbook.io, and Anchorfree, as well as 360.
My academic background is in science and business, having studied at Beijing Institute of Technology, Tsinghua University, Beihang University, National University of Singapore, and Stanford Graduate School of Business.
As an entrepreneur and technology leader, I am passionate about decentralized technology and the AI industry. However, I find that centralized companies dominate the AI space, creating privacy and unfairness issues for users and startups.
Through Network3, I am trying to create a level playing field by building an AI Layer2 network for the AI industry. I believe that combining DePIN and AI will democratize the AI field by training small models using simple and idle edge devices.
Q: Before we focus on Network3, can you explain the relevance of DePIN in general and in the AI industry in particular?
Decentralized Physical Infrastructure Networks (DePINs) enable users to contribute to and maintain physical infrastructure by exchanging token incentives.
Typically, large companies control infrastructure management because it is a capital-intensive process with multiple logistical hurdles. However, DePIN expands the infrastructure sharing economy through collective ownership, distributed costs, and decentralized security.
DePIN requires physical infrastructure and middleware for off-chain computing to process and analyze real-world data. This is where I think DePIN can contribute to the AI industry.
Currently, a few companies monopolize AI development by controlling large data pools and cloud computing resources. As a result, startups need huge capital expenditures to run AI models or access shared data. Users also compromise data sovereignty and privacy without any economic benefits.
DePIN decentralizes the AI industry by distributing data processing across multiple devices at the edge of the network. Therefore, DePIN can directly contribute to EdgeAI and expand its possibilities.
Q: As far as we know, EdgeAI is a relatively new development in the field of AI and is different from traditional AI models. How does EdgeAI work, especially with DePIN?
EdgeAI deploys AI algorithms and models on smartphones and home-based IoT devices. It does not rely on centralized cloud data processing, but analyzes data locally on each device.
Because EdgeAI processes data on devices at the edge of the network, it reduces latency, increases speed, and improves response time. It further reduces bandwidth usage, enhances scalability, and provides more security and privacy protection to prevent data leakage.
DePIN and EdgeAI work together by leveraging IoT devices, providing both computing power and direct access to data sets. This private and valuable data can be processed locally on the device without being sent to a cloud server, ensuring better privacy.
It accelerates the machine learning (ML) process as local data can be used to train AI models on edge devices. In addition, it improves the accuracy of AI models by using real-time, localized data entry.
DePIN also ensures token incentives that encourage device owners to share processing power and personal data. The incentive model promotes active user participation and resource availability across geographic boundaries and demographic groups.
At Network3, we enable AI algorithms to work directly on edge devices, combining DePIN and AI.
Q: Please tell us more about your company Network3. How does it combine DePIN and AI to help developers and users?
Network3 is an AI Layer2 that serves AI developers around the world. Our protocol enables users to contribute to AI training by sharing Internet bandwidth, IP addresses, data sets, and computing power of devices in exchange for token rewards.
Therefore, Network3 does two things at once. First, it transforms users’ smart devices into physical assets that generate value, bringing continuous passive income. Second, it lowers the entry barrier for startups in the AI field by promoting fair resource sharing within our network.
Network3 combines privacy-preserving computing, edge computing, and federated learning to train AI models.
Privacy computing is performed through the certificateless signature encryption (CLSC) algorithm, which provides encryption and signature to ensure data confidentiality. In addition, our data correctness verification mechanism prevents the transmission of forged data.
Network3's edge computing uses edge servers to offload computationally intensive tasks from end devices such as mobile phones to improve our operational performance. Finally, our federated learning uses local-global mechanisms, proof of contribution, and incentive structures to promote participation in the ecosystem.
I am happy to share that Network3 has recently partnered with Jambo Phone, a web3 mobile device. This collaboration will make Network3 applications available on Jambo, enabling users in emerging countries to participate in the Decentralized Edge AI space.
Q: What do you think about the future of DePIN and EdgeAI? How will these technologies affect us?
I believe that the DePIN-EdgeAI synergy has the potential to fundamentally change our digital lives. It will encourage AI-based startups and Internet users to collaborate and build a humane and smart technology-driven future.
If you look at a Messari report from early 2023, the addressable market for the DePIN industry is expected to reach approximately $3.5 trillion by 2028. Similarly, the EdgeAI market size is expected to grow to over $186 billion by 2032.
Therefore, we have data-driven market insights and can reasonably claim that the future of the DePIN-EdgeAI collaborative enterprise is bright. We just need the right tools to tap into this emerging market and make the most of it.
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