Author: dt
Translated by: Lisa
The combination of AI and blockchain is a highly anticipated topic in the industry, with developers actively exploring the possibilities of this fusion. Currently, blockchain technology is seen as an ideal choice for solving various problems such as “inability to utilize AI services and computing resources effectively.” Many projects have already carved out their own paths in this field.
Today, Dr. DODO will take you through projects that are performing well in the AI and computing power market race.
AI + Blockchain
Projects focusing on AI in the blockchain field can mainly be divided into three tracks:
1. Computing power sharing: Blockchain technology can build a distributed cloud computing platform, enabling the sharing and efficient utilization of computing resources. Through smart contracts, idle computing resources can be leased to tasks that require them, thereby improving resource utilization and reducing costs. Representative projects include io.net and Aethir.
2. AI data security and verifiable computing: Both AI and blockchain technologies handle large amounts of data. Blockchain storage networks provide a secure way to store and transmit data, while AI analyzes this data to generate valuable information. Combining the two can protect user privacy while providing reliable data sources for AI. Currently, Arweave represents this direction.
3. Decentralized AI: Deploying AI models on blockchain networks can provide decentralized artificial intelligence services, enhancing system reliability and stability while reducing the risk of single points of failure. Bittensor is a representative project in this direction.
io.net
Recently launched on Binance, io.net is currently a hot topic in this track. io.net is a decentralized GPU network designed to provide massive computing power for machine learning applications. Their vision is to unlock fair access to computational power by assembling over a million GPUs from independent data centers, crypto miners, and projects like Filecoin, making computations more scalable, accessible, and efficient.
io.net offers a completely different approach to cloud computing, using a distributed and decentralized model to provide users with more control and flexibility over computing power. Their service is permissionless and cost-effective. According to io.net, their computing power is 90% lower than centralized service providers like Amazon AWS, making io.net a leader among decentralized providers.
Aethir
Aethir offers a disruptive yet highly feasible solution to the complex problem of efficiently utilizing global computing resources. Their network aggregates and intelligently reallocates new and idle GPUs from enterprises, data centers, crypto mining operations, and consumers. The market opportunity for better reallocating GPU capacity is vast, and Aethir aims to increase global GPU computing availability by over 10 times.
A key feature of Aethir is its focus on reusing existing idle resources rather than requiring node participants to purchase new hardware. Typically, the underutilized GPU capacity of a device ranges from 50% to 75%, indicating a significant amount of computing power that can be tokenized. Aethir aims to leverage these abundant idle resources by targeting small to medium-sized data centers and enterprises.
Aethir’s token has already been listed on exchanges such as OKX and Bybit. Previously, they raised $9 million in pre-A round financing, with leading investors including Sanctor Capital and Hashkey.
Arweave
AO is a distributed, decentralized, participant-focused computing system based on Arweave. The core goal of AO is to provide a trustless and collaborative computing service without practical scaling limits, offering a new paradigm for applications combined with blockchain. Compared to other high-performance blockchains, AO supports storing large amounts of data, such as AI models. Unlike Ethereum, AO allows any number of parallel processes to run within a computation unit, coordinating through open message passing without relying on centralized memory space.
By launching AO, Arweave is transitioning from decentralized storage to a broader field of decentralized cloud services. Their permanent on-chain storage aims to become a permanent host for cloud computing, focusing on large-scale verifiable computing.
Recently, Arweave also announced the token economy between $AR and $AO. According to the official statement, $AO is a token with 100% fair distribution, with no presale or pre-allocation. The total supply of $AO is 2.1 million, with a halving cycle of 4 years, distributed every 5 minutes, with a monthly distribution of 1.425% of the remaining supply.
Approximately 36% of $AO tokens are allocated every 5 minutes to $AR holders, incentivizing the security of AO’s underlying layer – Arweave.
The remaining approximately 64% of $AO tokens are allocated to bridge users, providing external revenue and incentives to bring assets into AO.
Bittensor
Training AI models requires a significant amount of data and computing power, but high costs mean that these resources are mostly monopolized by large enterprises and research institutions. This centralization limits the use and collaboration of AI models, hindering the development of the AI ecosystem. Bittensor (TAO) aims to establish the world’s first blockchain neural network, allowing network participants to exchange machine learning capabilities and predictions.
Bittensor hopes to facilitate the sharing and collaboration of machine learning models and services in a peer-to-peer manner. While technically challenging, TAO is still a distance away from practical applications.
Author’s Viewpoint
These AI + blockchain projects are likely to change the future landscape of computing resource allocation. Decentralized ownership and collaborative cross-cluster deployment pave the way for a new wave of economic and technological progress. These projects have ambitious goals, aiming to reshape the future landscape of cloud computing and AI applications, shaping a more interconnected, efficient, and innovation-driven global cloud economy. Given the active promotion of productivity transformation in various countries, these development directions are worth exploring in depth. However, due to the need for stronger technical support and more funding, the entry barriers for project teams are not low. Currently, these projects are still in the trial stage, and whether they can be implemented as actual infrastructure for people to use remains to be seen.
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