"Our ultimate goal is to attract Web2 AI Builders into Web3."
Source: Chi_Labs
Host Blake: Today we have invited Michael, co-founder and CEO of 0G Labs. I am Blake, the host from Chi Labs.
Michael: At 0G Labs, our mission is to make AI a public good, which means providing an infrastructure that everyone can contribute to, especially ensuring it is transparent, secure, and verifiable. This requires a system that is completely different from black-box AI. We have built a modular multi-layer system: an infinitely scalable Layer1 (execution layer), a storage network designed for AI workloads, a computing network for inference and fine-tuning (verifiable based on TEE), a service marketplace, and AI alignment nodes that monitor drift and misbehavior. Together, this forms a decentralized AI operating system.
Why choose to create 0G in 2023?
Host Blake: Why did you decide to launch 0G in 2023? What was the spark at that time?
Michael: At that time, we saw ChatGPT take off from OpenAI, and we believed this was a breakthrough moment for AI. We could finally communicate with machines as if we were talking to a person, receiving responses in natural language, and the machine's answers were almost as effective as a human's. This was truly a landmark breakthrough.
But then we started to think: what will happen in five to ten years? What if some larger-scale use cases, especially those at the societal level, are truly driven by AI? For example, an airport run by AI. This future made us very uneasy because, in black-box AI systems, it is hard to know the source of the data, who labeled the data, what is happening inside the model, which version of the model you are getting, and how decisions are reviewed.
What pain points does 0G want to address in the AI and Web3 industries?
Host Blake: What pain points does 0G want to address in the AI and Web3 industries?
Michael: To truly own AI and be able to build "infinitely scalable" AI on-chain, we need to achieve several key infrastructure breakthroughs.
First is performance: how to create a powerful enough Layer1 to handle the heaviest data throughput use cases. In many cases, AI data centers can achieve throughput of hundreds of GB per second, even in the TB range. So we must design a high-performance system architecture.
Second is research: we need to figure out how to properly align AI and how to understand and build AGI in a decentralized context. Will AGI come from a single giant model, or from a combination of many small models? We lean towards the latter, but this requires a significant amount of research.
How do you hope 0G will be defined in five years?
Host Blake: How do you hope 0G will be defined in five years?
Michael: Our ultimate goal is to attract Web2 AI Builders into Web3.
When I envision 0G five years from now, I hope it will become the core hub for all mission-critical AI applications. For example, in societal-level scenarios such as manufacturing facilities, multi-robot systems, airports, and logistics systems, 0G should provide blockchain-based security and alignment mechanisms to ensure the operation of these systems. In this regard, I hope 0G will always be at the forefront and in a central position.
Of course, for some individual use cases, people can still use centralized AI or edge device AI to meet their needs. But when it comes to societal-level, mission-critical applications, 0G must be at the forefront, and all of this should be advanced through a community-centric approach, ultimately making AI a public good.
What is the core architecture of the decentralized AI operating system?
Michael: I have already mentioned some in the opening introduction. The core of 0G is a layered structure that allows each layer to perform different tasks required for building large-scale AI applications.
Typically, it includes the following parts:
● Computing / DePIN Layer: This part is not our own but connects to computing resources provided by partners (such as Aethir, Akash).
● Software Layer:
○ Layer1 (Execution Layer): Infinitely scalable.
○ Storage Layer.
○ Data Availability Layer.
○ Computing Layer: Supports inference and fine-tuning, using TEE (Trusted Execution Environment) to ensure verifiability.
○ Service Marketplace Layer: Similar to an App Store, allowing various services and public datasets to be integrated, completely open.
○ AI Alignment Nodes: Similar to a "police force," responsible for scanning model drift and negative behaviors, maintaining system health through penalty staking.
Each of these components has deep design space. For example, Layer1 itself is a modular architecture: modular execution layer, modular consensus layer, modular DA layer. Each layer has been optimized to the extreme and can be infinitely scalable, free from the limitations of traditional blockchain systems. For instance, some L2s may only achieve 500 TPS, while we use sharding methods to deploy any number of shards based on application needs, achieving any scale of TPS. This design philosophy runs through every part of the system.
What are the performance advantages of 0G compared to traditional L1?
Michael: Our core philosophy is parallelization. Whether it's storage, data throughput, or TPS, everything can be infinitely scaled through parallelization, achieving DA layer throughput of tens to hundreds of GB/s and hundreds of thousands of TPS.
How does 0G attract a developer ecosystem?
Michael: One of our design philosophies is to minimize the barriers for transitioning from Web2 to on-chain.
Through modular design, various infrastructure components can fit together tightly. If you use each part of 0G, they can achieve seamless collaboration. This provides a one-stop experience: developers do not need to go to 50 different places to assemble solutions. Additionally, the ecosystem is also part of the attraction. Accessing the largest ecosystem of Web3 × AI can provide a competitive advantage and facilitate interaction with others within the ecosystem. At the same time, we will provide substantial support, including incentives, mentorship, accelerators, and investments.
Host Blake: So developers will have mentorship support?
Michael: Yes, we provide not only mentorship support but also investment and assistance in various aspects of the entire ecosystem.
Are there early signs of a Killer App?
Michael: Initially, because Web3 was still very finance-oriented, early killer apps were likely to be tied to finance, such as:
● AI yield search agents
● AI circular leverage agents
● Other agents supporting financial operations
As time goes on, community participation in training and using models, where users provide computing power/data and receive tokens as compensation, will also become a direction for killer apps once the infrastructure is ready.
What experiences can ordinary users gain in the 0G ecosystem?
Michael: I have already mentioned some, such as mentorship support, marketing, and investment. Our goal is to quickly build a large-scale ecosystem that attracts the best builders to deploy their models, data, and computing power. To achieve this, every part of the team needs to invest substantial resources. We always see ourselves as a provider of competitive advantages, allowing anyone who joins 0G to benefit from it.
JT: Besides the functions of other public chains, as Michael mentioned earlier, we also have many extended functions. Our overall advantage is that, in addition to on-chain functions, we also provide computing power, storage, and support for all-chain AI. As a user or project party, you can find different use cases on the 0G platform, or you can deploy fully decentralized AI applications yourself, which is something many other chains may not be able to achieve.
How to balance the scale of airdrops with long-term user retention?
Michael: This is a very tricky question. On one hand, we need to recognize the contributions of community members, such as their participation in the testnet or support in promotion. On the other hand, we do not want everyone to just complete tasks for short-term incentives and then leave when the mainnet goes live.
Our solution is to set part of the airdrop as vesting, such as the distribution of Yapper or certain NFT rewards. This mechanism allows everyone to stay in the ecosystem for a longer time.
We always adhere to a long-term mindset—because our mission is to make AI a public good. This is not a one- or two-year endeavor, but a long-term effort that requires continuous community effort and deep participation.
JT: We have launched an airdrop check and registration tool, providing Yapper and other content creators with an incentive while offering ongoing rewards through the Infofy platform, but continuous contributions are needed to unlock them.
How will 0G avoid FUD similar to Movement and RedStone?
Michael: To some extent, it is difficult to completely avoid FUD because everyone wants to maximize their airdrop. No matter what is given, there will always be someone who feels it is not enough, which is the difference between perception and reality.
We have also learned many key lessons: separating the mainnet launch from airdrops/listings is detrimental to the community and can create unnecessary FUD. It is necessary to distinguish between true users/long-term users and witch attacks, which is difficult, but we continuously invest in identification and filtering. We have implemented these lessons into our current decision-making, breaking down airdrops into different parts: social tasks/community rewards, testnet participation. The participation mindset of these two groups is different, and different reward dimensions have been designed over a long time to attract more long-term participants.
For testnet participants: we hope they will also deploy on the mainnet because the mainnet metrics are real, and participating in the mainnet qualifies them for community rewards. In short, we design with a long-term mindset. However, filtering true users from witches is challenging, but we continuously invest in improvement. Airdrops will be divided into different parts, with different reward dimensions designed.
JT: We will segment different groups: testnet runners, community active participants, social media task participants, Yapper, early OGs, NFT holders. Everyone can receive rewards from different dimensions, but the overall concept is to reward long-term contributors.
How does the team ensure fairness and positivity for early supporters?
Michael: In addition to community rewards like airdrops, greater benefits should come from long-term interaction with the ecosystem. For builders: there will be retrospective community rewards, investments, mentorship, etc. For ordinary users: the value of tokens will grow over time through continuous support and mission consensus.
JT: We give early OGs high weight in Discord and have issued the One Group Grivity NFT (free/0.1 ETH minting, which peaked at 1.8–1.9 ETH). There are concentrated incentives around the TGE, and long-term incentives will shift towards ecosystem projects. Binding wallets + Twitter + Discord, multiple participants can receive multiple rewards.
What role can the community play in designing incentive mechanisms?
Michael: We are open to listening to community feedback as part of our governance mechanism. The community can propose new incentive mechanisms and reward methods. We will establish a Security Council to adopt suggestions. Incentive mechanisms can certainly be one of them. The 0G Foundation quickly adjusted based on community feedback on the initial version of the token economics; we held meetings until 4–5 AM to complete the revisions.
JT: The community can actually play a significant role in designing incentive mechanisms. As Michael mentioned, community users can propose what they want 0G to do and provide suggestions, and the team will adjust and change based on this feedback. For example, we previously released a version of the token economics, and the community provided a lot of feedback and suggestions. Our team quickly made modifications based on these opinions, and the final feedback was very positive. This is a relatively important example. I remember we even held meetings overnight until 4 or 5 AM just to respond quickly to the community's voice.
Key Goals for the Next 12–24 Months
Michael:
There are two main aspects:
● Build the largest Web3 × AI ecosystem: Improve key infrastructure, new verticals, and critical services around trends like robotics, attracting top AI dApps and top agents to build on 0G.
● Infrastructure benchmarking/catching up with centralized black-box AI: Strengthen verifiable mechanisms, support model training at any scale, and further enhance Layer1 performance to fully bring anything from Web2 on-chain.
JT: The goal is to make 0G an all-chain evolvable AI ecosystem, reaching the level of first-tier Web2 infrastructure in about two years while maintaining transparency and decentralization.
Judgment on Industry Trends (AI Infra, RWA + AI, Stablecoins, etc.)
Michael:
● Stablecoins: Large institutions are discussing replacing bank rails with stablecoin rails, which will integrate with AI agents in the future.
● RWA + AI: For example, tokenized hedge funds + collateralized stablecoin borrowing + circular strategies, where AI agents can monitor interest rates and risks, automatically rebalancing.
● Robotics: Household and factory robots will become widespread, but safety and alignment are key; otherwise, the consequences of a breach could be severe.
JT: Now everyone is starting to use stablecoins more and more, and many institutions have indicated they will use stablecoins to replace banks for transfers. At the same time, RWA plus AI is also a very promising topic. For instance, someone might stake tokens and then borrow stablecoins; at this point, AI can help with risk balancing and position management just before they reach the liquidation line. Your earlier addition was very complete, and I would like to add a bit more: Michael previously mentioned the Jackson Hole meeting, which was actually a very important meeting held last month near Denver, USA, where many American institutions and officials discussed how to better integrate traditional banking with the crypto industry, including policy aspects and future development directions. Michael also participated in this meeting as a representative of 0G.
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