What Exactly Is Decentralized Computing?

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

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

Let’s dive in ⬇️

1. What exactly does decentralized computing do?

In other words, what do these protocols compute?

Simply put, computation involves processing information data to achieve desired output results.

The primary demand for decentralized computing, or what the market perceives as the primary demand, is AI training. Of course, this track currently faces many issues regarding data synchronization, network optimization, and data privacy and security.

Currently, the most prominent 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 (while this statement was made specifically about io.net, it applies to most).

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

2. Refine application directions

Let’s take a simple look at the specific businesses of the decentralized computing projects mentioned earlier⬇️:

• io.net: Focuses on GPU computing power and has partnered with $RNDR. Its application direction includes machine learning and artificial intelligence computation.
• $TAO: Acts as a computing power intermediary, matching demands for artificial intelligence training.
• $AKT: Offers higher scalability compared to $RNDR, supporting GPU, CPU, and storage computing. Therefore, its customer base is more diverse.
• $AR: Introduces AO, a hyper-parallel computer modularly combined with Arweave. AO handles communication and parallel computing, while Arweave manages storage and verification. Additionally, AO supports modular combinations.

The application direction of decentralized computing is strongly linked to the AI field, providing services to the AI industry in the form of computing power. Essentially, we can break down Crypto+AI into two aspects: 1) What can Crypto do for the AI industry? 2) How can the AI industry empower Crypto? This has been mentioned in my previous articles. One 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 by providing computing power.

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

In addition to computing power and applications, Crypto can also make contributions at the data and algorithm levels.

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 calculation and data

Here are a few gems I’d like to share with you (I hold positions in them, so I have a vested interest; do your own research before buying and don’t let me be your bag holder).

1️⃣ 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.), compute on it, and store the newly computed data back into any of these repositories.

Background Introduction: FluenceDAO is an AI + DePin project that has already partnered with Filecoin and caught the attention of Solana co-founders. The project is led by Multicoin Capital with participation from 1kx and Signum Capital, raising a total of $11 million. Fluence has created a network to provide users with a decentralized serverless computing platform and marketplace, managed by the Fluence DAO and the $FLT token.

Currently, $FLT is priced at $0.6, with a market cap (MC) of $29.9M and a fully diluted valuation (FDV) of $599M.

For more information, read:

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

2️⃣ AIOZ @AIOZNetwork

Official Introduction: AIOZ Network is a comprehensive infrastructure solution for Web3 storage, decentralized AI computing, live streaming, and video-on-demand (VOD). The AIOZ Network’s dCDN platform transforms file storage and distribution in Web 3.0 Dapps, providing affordable solutions for file storage and media streaming. The AIOZ Network blockchain combines the robustness of Cosmos with the compatibility of the Ethereum Virtual Machine (EVM), offering high compatibility and low costs.

Background Introduction: Previously, AIOZ focused on becoming the primary DePin infrastructure platform for storage and streaming. Now, AIOZ is moving towards AI integration, similar to io.net and FluenceDAO, aiming to create AI + DePin infrastructure. A few years ago, AIOZ joined the NVIDIA Inception program.

A unique feature of AIOZ is its dCDN (decentralized content delivery network). The network’s edge nodes operate the network and are rewarded with $AIOZ tokens. One notable aspect of the dCDN is its ability to scale infinitely, meaning the number of edge nodes needs to grow to meet market demand as demand increases (currently, there are 80,000 nodes globally).

So, how does AIOZ integrate with AI?

AIOZ W3AI is an AI computing infrastructure that helps customers perform distributed AI computations while ensuring data privacy. Customers can access more AI models through the AI-as-a-service provided by AIOZ.

Interestingly, while reading the materials, I noticed a frequently mentioned concept: AI inference. In AI, inference is the process of using a trained machine learning model to draw conclusions from new data. An AI model capable of inference can make predictions without needing examples of the desired outcomes. Simply put, AI training is the first stage of an AI model, and AI inference is the application of the AI model. Inference essentially tests the AI model’s capabilities.

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

In summary, AIOZ is leveraging edge computing to provide services for AI.

For more information, read:

https://route2fi.substack.com/p/aioz-network-at-the-forefront-of?utm_source=post-email-title&publication_id=1272881&post_id=142885111&utm_campaign=email-post-title&isFreemail=true&r=

Currently, $AIOZ is priced at $0.8, with a market cap (MC) of $878M and a fully diluted valuation (FDV) of $878M.

Finally, let’s talk about what I see as the future trend in Crypto AI: A significant trend will be the increased granularity and specialization of subfields. While competition will intensify, more modular collaborations will also emerge.

Disclaimer：

1. This article is reprinted from [雨中狂睡’s Newsletter]. All copyrights belong to the original author [雨中狂睡]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.
3. Translations of the article into other languages are done by the Gate Learn team. Unless mentioned, copying, distributing, or plagiarizing the translated articles is prohibited.