Decentralized computing is closely related to the AI field, providing services to the AI field in the form of computing power.

Author: Yuzhong Kuangshui

What exactly is decentralized computing?

Apart from io.net $AKT $AR $TAO, what other opportunities can we participate in?

The following content aims to discuss with everyone how I understand the track of decentralized computing after learning relevant knowledge.

Let's dive in ⬇️

1. What is decentralized computing for?

In other words, "computing," what do these protocols need to compute?

Simply put, computing is the processing of information data to achieve the desired output.

And the biggest demand for decentralized computing, or the demand that the market perceives, is AI training. Of course, this track still has many issues in data synchronization, network optimization, and data privacy and security.

Currently, the biggest solutions on the market should be io.net $AKT and $RNDR. However, as mentioned by Greythorn Asset Management, the complexity of creating and managing decentralized clusters on a large scale involves significant technical challenges, and they still have a long way to go (this statement is aimed at io.net, but applies to most).

Reference link: https://0xgreythorn.medium.com/io-nets-revolutionary-gpu-cloud-f18c06b944e4

2. Refining application directions

Let's take a brief look at the specific business of the decentralized computing projects mentioned earlier ⬇️

• io.net focuses on GPU computing power and has partnered with $RNDR, with applications in machine learning and artificial intelligence computing.
• $TAO acts as a computing power intermediary, matching the demand for AI training.
• The scalability of $AKT is higher than $RNDR, as it supports GPU, CPU, and storage computing, thus serving a more diverse customer base.
• The AO launched by $AR is a super-parallel computer modularly combined with Arweave, where AO is responsible for communication and parallel computing, and Arweave is responsible for storage and verification. Additionally, AO supports modular combinations.

The application direction of decentralized computing is closely related to the AI field, providing services to the AI field in the form of computing power. Essentially, we can break down Crypto+AI into: 1) What can Crypto do for the AI industry? 2) How can the AI industry empower Crypto? I have mentioned this in my previous articles. The way the AI industry empowers Crypto is through AI agents, such as $PRIME $OLAS. The basic idea of how Crypto can serve the AI industry is to provide computing power.

This is also the reason why the current computing power targets are being hyped and new computing power protocols are emerging.

In addition to computing power and applications, Crypto can also make some progress in terms of data and algorithms.

Currently, their main growth bottleneck lies in the acceptance of their cooperation forms by Web2 clients. In this regard, $AKT is doing relatively well.

3. Two Gems related to computing and data

Next, I will share a few Gems with you (I hold positions in all of them, do your own research before purchasing, and do not chase after me).

FluenceDAO @fluence_project

Official introduction: Fluence is a Web3-native computing platform for developing and hosting applications, interfaces, and backends on a permissionless peer-to-peer network. Fluence can read data from any public data source (IPFS, Filecoin, Arweave, Ceramic, Ethereum, Solana, Flow, etc.), perform computations on it, and store the newly computed data back into any of these repositories.

Background: FluenceDAO is an AI+DePin project that has partnered with Filecoin, and Solana Ventures is also paying attention to this project. The project is led by Multicoin, with 1kx and Signum Capital participating, and has raised $11 million. Fluence has created a network to provide users with a decentralized cloud computing platform + marketplace, managed by Fluence DAO and $FLT.

Currently, the price of $FLT is $0.6, MC 29.9M, FDV 599M.

More details: https://twitter.com/ahboyash/status/1770333758522323192

AIOZ @AIOZNetwork

Official introduction: AIOZ Network is a comprehensive infrastructure solution for Web3 storage, decentralized AI computing, live streaming, and video on demand (VOD). AIOZ Network's dCDN platform revolutionizes file storage and distribution in Web 3.0 Dapps, providing an affordable solution for file storage and media streaming. AIOZ Network's blockchain combines the robustness of Cosmos and the compatibility of the Ethereum Virtual Machine (EVM) (high compatibility and low cost).

Background: Previously, AIOZ focused on becoming the primary DePin infrastructure platform for storage and media streaming, and now AIOZ is moving closer to AI. Like io.net and FluenceDAO, it is building AI+DePin infrastructure. A few years ago, AIOZ joined the NVIDIA Inception program.

One distinctive feature of AIOZ is the dCDN (distributed content delivery network), where the network's edge nodes are responsible for running the network, and nodes running the network will be rewarded with $AIOZ tokens. A feature of dCDN is that it allows the network to expand infinitely. In other words, as demand grows, the number of edge nodes needs to grow to meet market demand (currently there are 80,000 nodes worldwide).

So, how does AIOZ integrate with AI?

AIOZ W3AI is an AI computing infrastructure that helps clients with distributed AI computing and ensures data privacy. Clients can access more AI models through the AI-as-a-service provided by AIOZ.

Interestingly, while reading the materials, I also noticed a concept that was mentioned multiple times: AI inference.

In the AI field, inference is the process of using trained machine learning models to draw conclusions from new data, and models capable of inference can do so without examples of the desired results. Simply put, AI training is the first phase of AI models, and AI inference is the application of AI models. In essence, AI inference is the process of testing the capabilities of AI models.

AIOZ's W3AI Marketplace allows nodes to store user data in a decentralized manner and directly execute AI tasks on user devices. This makes AI inference more cost-effective and private.

In simple terms, AIOZ is providing services to AI through edge computing.

More details: https://route2fi.substack.com/p/aioz-network-at-the-forefront-of

Currently, the price of $AIOZ is $0.8, MC 878M, FDV 878M.

Finally, let's discuss what I believe to be a trend in Crypto AI: a key trend in the future of Crypto AI is the refinement of segmented tracks, with higher granularity. Alongside competition, there will also be more modularized cooperation.

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