Source: DODO Research
The combination of AI and blockchain is a hot topic in the industry, and developers are also actively exploring the possibility of this integration. At present, blockchain technology is regarded as an ideal choice to solve many problems such as "inability to use AI services and computing resources normally", and many projects have explored their own paths in this field.
Today, Dr.DODO will take you to understand the projects that have performed well in the AI and computing market.
Projects focusing on AI in the blockchain field can be mainly divided into three tracks:
Computing resource sharing:Blockchain technology can build a distributed cloud computing platform to achieve the sharing and efficient use of computing resources. Through smart contracts, idle computing resources can be leased to required computing tasks, thereby improving resource utilization and reducing costs. Representative projects include: io.net and Aethir.
AI data security and verifiable computing:Both AI and blockchain technology need to process large amounts of data. The blockchain storage network provides a secure way to store and transmit data, while AI generates valuable information by analyzing this data. Combining the two can protect user privacy while providing a reliable data source for AI. Currently, the project representing this direction is Arweave.
Decentralized AI:Deploying AI models on blockchain networks can achieve decentralized artificial intelligence services, which improves the reliability and stability of the system and reduces the risk of single point failures. Currently, the project representing this direction is Bittensor.
io.net, which was recently launched on Binance, is currently the hottest in the current track. io.net is a decentralized GPU network designed to provide huge computing power for machine learning applications. Their vision is to unlock fair access to computing power by assembling more than one million GPUs from independent data centers, crypto miners, and projects such as Filecoin, making computing more scalable, accessible, and efficient.
io.net offers a completely different approach to cloud computing, leveraging a distributed and decentralized model to provide users with more control and flexibility over computing power, with services that are permissionless and low-cost. According to io.net officials, their computing power is 90% lower than centralized service providers such as Amazon AWS, and the combination of all these factors makes io.net a leader among decentralized providers.
Source: io.net
Aethir offers a disruptive but highly viable solution to the complex problem of efficient use of global computing resources. Their network aggregates and intelligently reallocates new and idle GPUs from enterprises, data centers, cryptocurrency mining operations, and consumers. The market opportunity for better reallocation of GPU capacity is very broad, and Aethir hopes to increase the current global GPU computing availability by more than 10 times.
A key feature of Aethir is its focus on repurposing existing idle resources rather than requiring node participants to purchase new hardware. Typically, the underutilized GPU capacity of a device is estimated to be between 50% and 75%, indicating that there are a large number of computing resources that can be tokenized. Aethir aims to take advantage of these abundant idle resources by targeting small and medium-sized data centers and enterprises.
Aethir's tokens are currently listed on exchanges such as OKX Bybit. Previously, it raised $9 million in a Pre-A round of financing, led by well-known institutions such as Sanctor Capital and Hashkey.
Source: aethir.com
AO is a distributed, decentralized, participant-oriented computing system based on Arweave. The core goal of AO is to provide a computing service that does not require trust and collaboration and has no practical scale limitations, providing a new paradigm for applications combined with blockchain. Compared with other high-performance blockchains, AO supports the storage of large amounts of data, such as AI models. Unlike Ethereum, AO allows any number of parallel processes to run simultaneously within a computing unit, coordinated through open messaging without relying on centralized memory space.
The launch of AO by Arweave means moving from the decentralized storage track to the broader field of decentralized cloud services. Its permanent on-chain storage is no longer just for user data, but hopes to become a permanent host for cloud computing, focusing on large-scale verifiable computing.
Arweave also announced the token economy between its dual tokens $AR and $AO a few days ago. According to the official statement, $AO is a 100% fair issuance token with no pre-sale and pre-allocation. The total supply of $AO is 21 million, with a halving cycle of 4 years, distributed every 5 minutes, and a monthly distribution of 1.425% of the remaining supply.
Approximately 36% (100% in the first four months plus 33.3% thereafter) of $AO tokens are distributed to $AR holders every 5 minutes, and these tokens incentivize the security of Arweave, the base layer of AO.
The remaining approximately 64% of $AO tokens are allocated to bridge users to provide external benefits and incentives for introducing assets into AO.
Source: https://ao.arweave.dev/
The training of AI models requires a lot of data and computing power, but the high cost has led to the monopoly of these resources by large enterprises and research institutions. This centralization limits the use and cooperation of AI models and hinders the development of the AI ecosystem. Bittensor (TAO) is committed to building the world's first blockchain neural network so that network participants can exchange machine learning capabilities and predictions.
Bittensor hopes to promote the sharing and collaboration of machine learning models and services in a peer-to-peer manner. TAO is technically challenging to implement and is still a long way from practical application.
Source: https://futureproofmarketer.com/blog/what-is-bittensor-tao
These AI + blockchain projects are likely to change the future distribution of computing resources. Decentralized ownership, collaborative cross-cluster decentralized regional deployment will pave the way for a new wave of economic and technological progress. These projects are ambitious and hope to change the future landscape of cloud computing and AI applications and shape a more interconnected, efficient, and innovation-driven global cloud economy. In the context of countries actively promoting productivity transformation, these development directions are worth our in-depth exploration. However, since this field requires stronger technical support and more financial support, the entry threshold for project parties is not low. It is still in the trial stage. Whether it can be implemented in the future and become an infrastructure that is actually used by people remains to be seen.
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Hui Xin