During this period, I have been looking at the documents, White Paper, and related materials of @0G_labs, summarizing a few key points to discuss the strengths of 0G:
1. Comprehensive decentralization to fill the gaps in the AI ecosystem.
Traditional AI systems are highly centralized, with data, models, and computing power monopolized by large companies. Users have neither control nor the ability to share in the profits. Currently, the "quasi-AI Layer 1" has achieved some decentralization in AI fine-tuning or incentive mechanisms, but core aspects such as training data and model storage are still centralized, which does not qualify as "true decentralization."
The deAIOS of 0G (Decentralized AI Operating System) is designed from the ground up around decentralization:
▪️AI Data Storage: 0G Storage can efficiently and securely store massive amounts of AI data (such as training datasets and model parameters), unlike Ethereum which is limited by small capacity (125KB/block), and can easily handle AI models that range from 100GB to 1TB in size.
▪️Data Availability (DA): 0G DA provides non-permanent storage, specifically optimized for AI applications and Rollup scenarios, supporting high-frequency read and write operations, as well as data validation.
▪️Power Market: 0G Compute allows GPU providers and AI users to match computing power demands through smart contracts, with costs lower than centralized cloud services, and also enables decentralized settlement.
▪️AI Product Trading: 0G Marketplace (in development) allows AI models, Agents, etc. to trade on-chain, similar to
▪️Governance Supervision: Alignment Nodes ensure the transparency and consistency of AI models, data, and node behaviors within the ecosystem, preventing "black box" operations.
In summary, 0G has moved every aspect of AI—data, models, computing power, transactions, governance—onto the blockchain, truly realizing "full-chain AI."
2. Modular design, flexible and efficient
The entire 0G system is modularized to the extreme:
▪️Technical Modules: 0G Chain, 0G Storage, 0G DA are independent, with clear functions. If an upgrade is needed for a specific module, only that part needs to be changed, without starting over.
For example, 0G Chain is EVM compatible, allowing developers to get started with familiar tools; 0G Storage is optimized for high-frequency read and write for AI, overcoming the performance bottlenecks of traditional decentralized storage such as IPFS and Filecoin.
▪️Ecosystem Modules: 0G Compute, Marketplace, Alignment Nodes and other modules can also serve AI and non-AI scenarios in Web3 or Web2 independently.
For example, 0G DA has already supported the Rollup requirements of Arbitrum and OP Stack, with strong cross-ecosystem compatibility.
This modular design allows 0G to flexibly adapt to the rapid iteration needs of AI technology and also to be "sold separately", serving a wider range of scenarios, with huge potential for the future.
3. 0G Chain——Fast, Compatible, AI-Friendly
0G Chain is the core of the 0G ecosystem, optimized specifically for AI applications:
▪️High Performance: TPS (transactions per second) exceeds 2500+, with a single shard even reaching 11000, far surpassing Ethereum (15-30 TPS). AI applications require frequent interactions, and the low latency and high throughput of 0G Chain are perfectly suited.
▪️EVM Compatibility: Developers can directly develop smart contracts using Ethereum tools, reducing the learning curve.
▪️Streamlined Verification: Only requires 50-200 validators (compared to Ethereum's millions), resulting in higher consensus efficiency, and AI trading doesn't have to wait half a day.
In simple terms, 0G Chain is both fast and user-friendly, making it easy for developers to use, and AI applications run smoothly.
4. Storage and DA tailored for AI
The scale of AI models and data is immense, traditional blockchains cannot accommodate them, and ordinary decentralized storage is too slow. The 0G solution is very hardcore:
▪️0G Storage: Divided into the log layer (for storing large data, like a hard drive) and the key-value layer (for fast read and write, like memory), it can efficiently handle AI training data, models, and inference data. Data is stored in a distributed manner using erasure coding technology, allowing recovery even if 30% of the nodes fail, making it safe and reliable.
▪️0G DA: Provides temporary storage for AI and Rollup, allowing for faster data retrieval and supporting high-frequency scenarios. In contrast, Bittensor relies on centralized storage for its AI data, while 0G decentralizes this aspect, filling a critical gap.
5. Ecological Construction
The 0G ecosystem has already taken shape, with impressive testnet data showing 24 million wallets and over 300 million interactions; collaborating with over 300 projects and integrating more than 450, covering fields such as AI, DeFi, gaming, and DePIN; selling over 85,000 aligned nodes, with 8,500 operators participating globally. It is clear that 0G's infrastructure is solid and its ecosystem development is comprehensive!
6. The Significance of Decentralization: Breaking the AI Monopoly
Centralized AI (like ChatGPT) is prone to forming "information silos", has limited training data, potential biases in the model, and is expensive. Decentralized AI of 0G has two major advantages: ▪️ Data sharing: Decentralized storage allows more people to contribute data, enabling AI models to train on a broader range of data, reducing bias and enhancing quality.
▪️Low-cost empowerment: Decentralized computing power and market reduce the cost of AI development and usage, allowing startups and ordinary users to also afford to engage with AI.
In simple terms, 0G makes AI no longer a toy for large companies, but a public resource for everyone.
0G is considered a better AI Layer 1 ecosystem primarily because it "full-stack" addresses the pain points of decentralized AI: from data storage, computing power allocation to model trading and ecosystem governance, 0G provides a complete set of modular and scalable solutions.
Moreover, the modular design of 0G and its EVM compatibility allow it to seamlessly integrate with both Web3 and Web2, serving both AI and non-AI scenarios, with potential far exceeding a single AI Layer1. Ecosystem data and collaborative projects also demonstrate that 0G is not just theoretical but is rapidly being implemented.
Although the ecosystem is still in its early stages, the actual implementation results of AI applications remain to be seen. Overall, the technological foresight and ecological ambition of 0G indeed give it an edge in the AI Layer 1 track!
#0GLabs #0g_galileo #kaitoyappers #KAITO #Starboard
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