Founder of Network3: The synergy of DePIN-EdgeAI will change people's digital lives

Author: Gregory Pudovsky

The AI industry is under the monopolistic control of centralized companies, which adversely affects startups and ordinary users. However, web3 technologies like DePIN can intervene to democratize the AI industry.

In this interview, we discuss the relevance of DePIN in the AI industry, EdgeAI, and the collaborative potential between these technologies with Rock Zhang, the founder of Network3.

Q: Hello. Could you introduce yourself to our readers and share your professional journey?

Hi, I’m Rock, and I’m glad to be here. I am the founder of Network3, an AI Layer2 that helps AI developers scale reasoning, training, and validation of models using DePIN.

I am also the founder of Rock TechX, a platform that makes people's digital lives more secure. Prior to this, I was the product lead at iHealth Labs, socialbook.io, Anchorfree, and 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 technologies and the AI industry. However, I found that centralized companies dominate the AI field, creating privacy and fairness issues for users and startups.

Through Network3, I aim to create a fair competitive environment by building an AI Layer2 network for the AI industry. I believe that combining DePIN with AI will democratize the AI field by training small models using simple and idle edge devices.

Q: Before focusing on Network3, could you explain the general relevance of DePIN and its significance in the AI industry?

Decentralized Physical Infrastructure Networks (DePINs) enable users to contribute and maintain physical infrastructure through token-based incentives.

Typically, large companies control infrastructure management because it is a capital-intensive process with multiple logistical barriers. However, DePIN expands the infrastructure-sharing economy through collective ownership, decentralized costs, and decentralized security.

DePIN requires physical infrastructure and middleware for off-chain computation to process and analyze real-world data. This is where I believe DePIN can contribute to the AI industry.

Currently, some companies monopolize AI development by controlling large pools of data and cloud computing resources. As a result, startups need significant 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 network edge. Therefore, DePIN can directly contribute to EdgeAI and expand its possibilities.

Q: As we understand, EdgeAI is a relatively new advancement in the AI field, differing from traditional AI models. How does EdgeAI work, particularly in conjunction 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 various devices.

By processing data on edge devices, EdgeAI reduces latency, increases speed, and improves response times. It further minimizes bandwidth usage, enhances scalability, and provides more security and privacy to prevent data leaks.

DePIN and EdgeAI work together by leveraging IoT devices, providing computational power and direct access to datasets. These private and valuable data can be processed locally on devices without being sent to cloud servers, ensuring better privacy.

As local data becomes available for training AI models on edge devices, it accelerates the machine learning (ML) process. Additionally, it improves the accuracy of AI models by using real-time, localized data entries.

DePIN also ensures token incentives that encourage device owners to share processing power and personal data. The incentive model fosters active user participation and resource availability across geographical boundaries and demographics.

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 globally. Our protocol allows users to contribute to AI training by sharing internet bandwidth, IP addresses, datasets, and computational power of devices in exchange for token rewards.

Thus, Network3 does two things simultaneously. First, it transforms users' smart devices into physical assets that generate value, providing ongoing passive income. Second, it lowers the barriers to entry for startups in the AI field by facilitating fair resource sharing within our network.

Network3 combines privacy computing, edge computing, and federated learning to train AI models.

Privacy computing is conducted through Certificate-less Signature Encryption (CLSC) algorithms, providing encryption and signatures to ensure data confidentiality. Additionally, our data integrity verification mechanism prevents the transmission of forged data.

Network3's edge computing utilizes edge servers to offload computationally intensive tasks from terminal devices like smartphones to enhance our operational performance. Finally, our federated learning employs a local-global mechanism, proof of contribution, and incentive structures to promote participation in the ecosystem.

I am pleased to share that Network3 recently partnered with Jambo Phone, a web3 mobile device. This collaboration will make the Network3 application available on Jambo, enabling users in emerging countries to participate in the DePIN-EdgeAI space.

Q: How do you view the future of DePIN and EdgeAI? How will these technologies impact us?

I believe the synergy between DePIN and EdgeAI has the potential to fundamentally change our digital lives. It will encourage AI-based startups and internet users to collaborate in building a more human-centered and intelligent technology-driven future.

If you look at the Messari report from early 2023, it is projected that by 2028, the addressable market for the DePIN industry will reach approximately $3.5 trillion. Similarly, the EdgeAI market size is expected to grow to over $186 billion by 2032.

Therefore, we have data-driven market insights to reasonably claim that the future of DePIN-EdgeAI collaborative enterprises is bright. We just need the right tools to develop this emerging market and fully leverage it.

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