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Home web3.0 In the context of the traditional cloud computing market, dominated by concentrated giants

In the context of the traditional cloud computing market, dominated by concentrated giants

Apr 21, 2025 pm 05:30 PM
Blockchain tool ai binance Distributed deployment 2025 2025

Aethir is using its distributed GPU to compute power network to rebuild the distribution logic of the infrastructure.

In the context of the traditional cloud computing market, dominated by concentrated giants

In the context of the traditional cloud computing market, popular GPU computing power networks will rebuild the distribution logic of the infrastructure and be dominated by centralized giants. The project originated in 2023, integrating global idle GPU resources into the programmable computing market, and through token economics, a complete closed link from protocol design to commercial implementation has been achieved within two years. Its developmental trajectory not only reveals the explosive potential of Dides (a network of decentralized physical infrastructures), but also demonstrates the chemical reactions generated by the convergence of blockchain and artificial intelligence.

Capital layout and technology verification in the resource integration stage.

The completion of the previous round of financing of US$9 million in July 2023 is of great significance. Investor choices such as Hashkey Capital reflect the market’s long-term optimism about decentralized computing power, while the direction of funds illuminates Aethir’s differentiation path, rather than cloud computing in general, but in GPU-intensive scenarios. In the same year, through technical cooperation with layerzero, a full-chain plan for computing power resources was realized through a cross-chain protocol, thus laying the foundation for subsequent multi-chain deployment, thereby strengthening this positioning.

The launch of node sales marks a critical turning point in the beginning of the Internet’s cold. The distributed deployment of 425,000 GPU containers forms the physical basis. Compared with traditional cloud services, this decentralized architecture shows three times the advantages: the ability to smooth regional computing power shortages, compatibility of hardware heterogeneity, and the scaling characteristics with near-zero marginal cost. The community-driven resource summary model has begun to demonstrate economies of scale at this stage.

Economic model iteration and ecological niche structure.

2024 will be a critical year for Aethir's business logic to mature. Partnering with Eigenlayer has introduced a re-engineering mechanism that allows traditional GPU providers to convert hardware assets into revenue-generating assets. The design addresses the pain points of early liquidity shortages in the DEPIN network while creating a layered revenue structure – the base layer captures the calculation of power rental fees, the protocol layer captures the storage rewards, and the application layer shares service premiums. Link revenues of more than $126 million that year confirmed the economic viability of the model.

The multi-chain deployment strategy made a major breakthrough in the fourth quarter of 2024. After the interoperability between ETH, BSC and SOLANA was achieved through lyezero, the liquidity depth of ATH tokens increased by 300%, adding cross-chain settlements to be controlled within 12 seconds. This technological achievement lays the foundation for subsequent targeted expansion in the Solana ecosystem and provides a seamless experience for leveraging computing power in various on-chain AI applications.

The establishment of the TACOM fund demonstrates Aethir’s strategic thinking when building the moat. The $40 million investment fund has formed a closed cycle of "hardware resources-financial tools-application solutions" for GPUFI and AI infrastructure. By establishing a partnership with the Avalanche’s $100 million ecosystem fund, this vertical integration strategy continues to strengthen in 2025, constraining high-quality project parties through capital leverage to ensure stability in the demands of computing power networks.

Application layer penetration and market pricing power competition.

A series of actions in 2025 show that Aethir begins to compete for the power to set industry standards. Cloud gaming developers working with Xsolla plan to enter the cloud gaming market directly at an annual growth rate of 28%, while the $1 million funding is essentially a technology acquisition for gaming engine manufacturers. The partnership with SuperNet occupies the middleware layer of AI Depin by providing integrated training and inference services that can be done in the AI ??proxy track.

Exchange layout strategies are also important. From the perspective of secondary market liquidity, the dual listings of Coinbase and Binance are value anchors, while the launch of Binance's permanent contract attracted hedging demand. It is worth noting that the pace of ATH's communication list is highly coordinated with project milestones - each technological breakthrough or ecological cooperation is inevitably opening new trading channels within three months, and the release of liquidity of the program effectively supports token valuation.

The network impact behind the data.

In the industry coordinate system, 598,068,090 calculation times need to be viewed. This number equals the one-year computed output of 3,000 A100 GPUs uninterrupted, but the Aethir network actually utilizes dynamic scheduling of over 80,000 heterogeneous GPUs. The increase in resource utilization stems from its initial task fragmentation algorithm, which breaks down large model training (such as large model training) into micro-training performed across regions.

The geographical distribution of nodes shows a scattered feature. The coverage of 95 countries not only avoids single point of supervision risks, but also enables optimization of computational latency. Southeast Asian nodes mainly respond to game rendering needs, North American nodes perform AI inference tasks, and Western European node process process financial modeling-

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