DePIN x AI: An overview of four major decentralized computing networks

Written by: 0xEdwardyw

• Akash, Render Network, and io.net are the three largest decentralized computing networks on the market. Although they all provide decentralized computing services, each network has a different business focus.

• Bittensor 是一个去中心化的人工智能项目，利用分布式计算资源进行机器学习。它的目标是直接与像 OpenAI 这样的集中式人工智能服务竞争。

• In supplyXiaobai NavigationOn the other hand, Akash has a diverse hardware network including CPU, GPU and storage, while Render has a large number of GPUs. io.net obtains a large number of GPUs from its own network and other platforms.

• The decentralized computing network is a two-sided market.Token用作其各自系统中的交换媒介。Render 网络和 Bittensor 实施代币销毁机制以增强价值积累。

Different types of decentralized computing networks

Differences between Akash and Render Network

Akash and Render Network are both decentralized computing networks that provide a platform where users can buy and sell computing resources for various tasks.

Akash operates as an open marketplace that allows users to access CPU, GPU, and storage resources. It provides computing resources that can be used for a variety of purposes, such as hosting game servers or runningBlockchainNode. In the Akash Marketplace, tenants who deploy applications set the price and conditions for the desired deployment, and computing resource providers bid on these deployments, with the lowest bidder (provider) winning the deployment. This reverse auction model gives users the power to set prices and conditions.

In contrast, Render uses a dynamic pricing algorithm to adjust the pricing of task deployments based on market conditions. Render Network focuses on GPU-based 3D rendering services and operates as a distributed GPU network. In this model, hardware providers provide computing resources, and the Render network uses a multi-layer pricing algorithm to determine prices and match users with buyers of services. Render does not operate as an open market where users can independently set prices or conditions.

Io.net – Focus on artificial intelligence and machine learning

io.net is a new decentralized computing network that runs on distributed data centers,cryptocurrencyMiners and decentralized storage providers obtain GPU computing power to support machine learning and artificial intelligence computing. It also cooperates with existing decentralized computing networks such as Render to utilize underutilized GPU computing resources on Render to process AI and machine learning tasks.

io.net's main differentiators are twofold: 1) its focus on AI and machine learning tasks, and 2) its emphasis on GPU clusters, which are multiple GPUs working together as a unified system to handle compute-intensive tasks such as AI training and scientific simulations.

Bittensor - An AI-focusedBlockchainproject

Unlike other decentralized computing networks, Bittensor is a decentralized AI project that aims to create a decentralized machine learning market that allows decentralized AI applications to be built and compete directly with centralized AI projects like OpenAI's ChatGPT. The network consists of nodes (miners) that provide computing resources for training and running AI models.

Bittensor uses a subnet structure, which is similar to a chain for a specific application. It currently has 32 subnets, each of which focuses on specific AI-related tasks, including decentralized text prompt AI networks (text prompt AI refers to AI applications similar to ChatGPT), image generation AI that can convert text prompts into images, and AI-based search engines.

Miners play a key role in the Bittensor ecosystem, providing computing resources and hosting machine learning models to perform off-chain AI task calculations and generate results. Anyone can join the network as a miner with minimum hardware requirements. Miners compete with each other to provide the best results for users' queries.

Network capacity and usage

Akash initially focused on CPUs and had a large amount of CPU resources within the network. With the rise of artificial intelligence, the demand for GPUs has increased dramatically, and Akash has begun to add GPU resources to its network since the third quarter of last year. However, compared with other projects that focus on GPU resources, Akash has a relatively small number of high-performance GPUs. Render Network focuses on providing decentralized GPU-based rendering solutions, which has enabled it to accumulate a large number of GPUs in its network.

Render Network and Akash are relatively mature projects, and the usage of the network is growing year by year. In particular, after Akash expanded its business focus to GPUs, the number of quarterly active leases increased significantly.

io.net 是一个新的去中心化计算网络，于 2023 年 11 月推出了公共测试网络。尽管历史较短，io.net 通过整合来自 Render、Filecoin 和自身网络的资源，积累了大量的 GPU。io.net 最近宣布支持 Apple Silicon 芯片集群，使苹果用户能够将未利用的计算能力分配给网络，进一步增加了其网络中的硬件数量。此外，io.net 还没有推出其协议代币，大量的硬件提供商可能是希望通过加入网络作为提供商来获得潜在代币空投机会。

Bittensor is a decentralized artificial intelligence network where miners are responsible for contributing computing resources to the network. Miners can invest in their own hardware setup or simply use computing resources provided by cloud services. In terms of hardware quantity, Bittensor cannot be directly compared with typical decentralized computing networks. Bittensor currently has more than 7,000 miners.

Token Economy

Decentralized computing platforms act as two-sided markets where users pay fees to providers of computing resources. Akash, Render Network, and Bittensor have all issued their own tokens as a medium of exchange of value within their ecosystems. Render and Bittensor have implemented a token burning mechanism to enhance the value accumulation of tokens.

Akash

Akash is an independent PoS Blockchain, $AKT is its native token, used for staking to ensure the networkSafetyThe token also acts as a medium of exchange in the ecosystem, and $AKT is the main unit of pricing when users trade or rent on Akash. As a PoS chain, Akash needs to issue $AKT to generate block rewards for verification nodes, and the current inflation rate is about 14%.

Akash currently charges 4% for fees paid in AKT and 20% for fees paid in USDC, and these fees will flow intoCommunityFunding pool.CommunityThe specific use of the pool funds has not yet been determined, but potential uses could include public funding support, incentives, or simply destroying the tokens.

Render Network

Render Network has migrated from Ethereum to Solana, and its protocol token RNDR is used for value exchange within the Render ecosystem, with creators and users using the token to pay for rendering jobs.

In order to balance the dynamic relationship between supply and demand of computing resources, Render implements a Burn and Mint Balance (BME) mechanism. When demand (i.e. rendering jobs) exceeds the supply of computing resources, RNDR tokens will be destroyed, creating a deflationary effect. Conversely, if the supply of computing resources exceeds demand, more RNDR tokens will be minted, leading to inflation. Due to the current lack of computing demand, RNDR tokens are in inflation.

Bittensor

Bittensor's native token $TAO is used to access network services and as a medium for the core reward mechanism. The maximum supply of $TAO is 21 million, and 7,200 tokens are generated every day as rewards for miners and validators. Bittensor has implemented a token issuance halving mechanism, that is, when half of the total supply is distributed, the issuance rate will be halved. After the first halving, the next halving will be carried out after half of the remaining token supply is distributed, until the maximum supply of 21 million is reached.

Although the issuance rate of 7,200 TAO per day is fixed for the current period, the time of the next halving is not predetermined due to the token recycling mechanism. This recycling mechanism burns the issued TAO tokens, effectively delaying the point in time when half of the total supply is distributed. Miners and validators need to recycle (i.e. burn) TAO tokens in order to register to join the network. These burned tokens are deducted from the circulating supply and can be mined again. The network regularly deregisters miners and validators who cannot provide sufficiently competitive AI tasks, and miners need to pay/burn TAO again when they re-enter the network, making registration a recurring cost. This dynamic burning mechanism creates a continuous demand for TAO.

The first halving was originally planned for January 2025, but the current halving has been postponed to October 2025. This indicates that a large number of TAO tokens have been burned.

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