AI×DePin：智能基础设施共同演进

介绍

Decentralized Physical Infrastructure Network (DePIN) is a cutting-edge concept that combines blockchain technology with the Internet of Things (IoT), and is gradually attracting widespread attention from both inside and outside the industry. DePIN redefines the management and control mode of physical devices through a decentralized architecture, showing the potential to trigger disruptive changes in traditional infrastructure fields such as power grids and waste management systems. Traditional infrastructure projects have long been centrally controlled by governments and large enterprises, and are often faced with high service costs, inconsistent service quality, and limited innovation. DePin provides a new solution that aims to achieve decentralized management and control of physical devices through distributed ledger and smart contract technology, thereby improving the transparency, credibility, and security of the system.

Depins features and benefits

• Decentralized management and transparency: DePIN achieves decentralized management of physical devices through distributed ledgers and smart contracts of blockchain technology, enabling device owners, users and related stakeholders to verify the status and operation of the device through a consensus mechanism. This not only improves the safety and reliability of the equipment, but also ensures the operational transparency of the system. For example, in the field of Virtual Power Plant (VPP), DePIN can make the traceability data of the socket public and transparent, allowing users to clearly understand the production and circulation process of the data.

• Risk dispersion and system continuity: By distributing physical devices to different geographical locations and multiple participants, DePIN effectively reduces the centralization risk of the system and avoids the impact of single point failure on the entire system. Even if a node fails, other nodes can continue to operate and provide services, ensuring the continuity and high availability of the system.

• Smart contract automation: DePIN uses smart contracts to automate device operations, thereby improving operational efficiency and accuracy. The execution process of smart contracts is fully traceable on the blockchain, and every step of the operation is recorded, allowing anyone to verify the execution of the contract. This mechanism not only improves the efficiency of contract execution, but also enhances the transparency and credibility of the system.

Analysis of DePINs five-layer architecture

概述

Although cloud devices are usually highly centralized, DePIN (Decentralized Physical Infrastructure Network) successfully simulates centralized cloud computing functions through the design of a multi-layer modular technology stack. Its architecture includes application layer, governance layer, data layer, blockchain layer and infrastructure layer, and each layer plays a key role in the entire system to ensure the efficient, secure and decentralized operation of the network. The following will analyze these five layers in detail.

应用层

• Function: The application layer is the part of the DePIN ecosystem that is directly facing users and is responsible for providing various specific applications and services. Through this layer, the underlying technology and infrastructure are transformed into functions that users can directly use, such as Internet of Things (IoT) applications, distributed storage, decentralized finance (DeFi) services, etc.

• importance:

• User experience: The application layer determines how users interact with the DePIN network, which directly affects the user experience and the popularity of the network.

• Diversity and innovation: This layer supports a variety of applications, which contributes to the diversity and innovation of the ecosystem and attracts developers and users from different fields to participate.

• Value realization: The application layer transforms the networks technical advantages into actual value, promoting the sustainable development of the network and the realization of users interests.

Governance Layer

• Function: The governance layer can operate on-chain, off-chain, or in a hybrid mode, and is responsible for formulating and enforcing network rules, including protocol upgrades, resource allocation, and conflict resolution. Decentralized governance mechanisms such as DAO (decentralized autonomous organization) are usually adopted to ensure transparency, fairness, and democracy in the decision-making process.

• importance:

• Decentralized decision-making: By decentralizing decision-making power, the governance layer reduces the risk of single point control and improves the networks censorship resistance and stability.

• Community participation: This layer encourages active participation of community members, enhances users’ sense of belonging, and promotes the healthy development of the network.

• Flexibility and adaptability: Effective governance mechanisms enable the network to respond quickly to changes in the external environment and technological advances, and remain competitive.

数据层

• Function: The data layer is responsible for managing and storing all data in the network, including transaction data, user information, and smart contracts. It ensures the integrity, availability, and privacy of data while providing efficient data access and processing capabilities.

• importance:

• Data security: Through encryption and decentralized storage, the data layer protects user data from unauthorized access and tampering.

• Scalability: Efficient data management mechanism supports network expansion, handles a large number of concurrent data requests, and ensures system performance and stability.

• Data transparency: Open and transparent data storage increases the trust of the network and enables users to verify and audit the authenticity of data.

Blockchain Layer

• Function: The blockchain layer is the core of the DePIN network, responsible for recording all transactions and smart contracts to ensure the immutability and traceability of data. This layer provides decentralized consensus mechanisms such as PoS (Proof of Stake) or PoW (Proof of Work) to ensure the security and consistency of the network.

• importance:

• Decentralized trust: Blockchain technology eliminates the reliance on centralized intermediaries and establishes a trust mechanism through distributed ledgers.

• Security: Strong encryption and consensus mechanisms protect the network from attacks and fraud, maintaining the integrity of the system.

• Smart Contracts: The blockchain layer supports automated and decentralized business logic, improving the functionality and efficiency of the network.

Infrastructure Layer

• Function: The infrastructure layer includes the physical and technical infrastructure that supports the operation of the entire DePIN network, such as servers, network equipment, data centers, and energy supply. This layer ensures the high availability, stability, and performance of the network.

• importance:

• Reliability: A solid infrastructure ensures the continuous operation of the network and avoids service unavailability due to hardware failure or network interruption.

• Performance optimization: Efficient infrastructure improves network processing speed and responsiveness, improving user experience.

• Scalability: Flexible infrastructure design allows the network to scale as needed, supporting more users and more complex application scenarios.

Connection Layer

In some cases, people add a connection layer between the infrastructure layer and the application layer, which is responsible for handling the communication between smart devices and the network. The connection layer can be a centralized cloud service or a decentralized network, supporting multiple communication protocols such as HTTP(s), WebSocket, MQTT, CoAP, etc. to ensure reliable data transmission.

How AI is changing DePin

Intelligent management and automation

• Equipment management and monitoring: AI technology makes equipment management and monitoring more intelligent and efficient. In traditional physical infrastructure, equipment management and maintenance often rely on regular inspections and passive repairs, which is not only costly but also prone to equipment failures that are not discovered in time. By introducing AI, the system can achieve the following optimizations:

• Fault prediction and prevention: Machine learning algorithms can predict possible equipment failures by analyzing historical equipment operation data and real-time monitoring data. For example, by analyzing sensor data, AI can detect possible failures of transformers or power generation equipment in the power grid in advance, arrange maintenance in advance, and avoid larger-scale power outages.

• Real-time monitoring and automatic alarm: AI can monitor all devices in the network in real time 24/7 and issue an alarm immediately when an abnormality is detected. This includes not only the hardware status of the device, but also its operating performance, such as abnormal changes in parameters such as temperature, pressure, and current. For example, in a decentralized water treatment system, AI can monitor water quality parameters in real time and immediately notify maintenance personnel to handle it once pollutants exceed the standard.

• Intelligent maintenance and optimization: AI can dynamically adjust maintenance plans based on the usage and operating status of equipment to avoid over-maintenance and under-maintenance. For example, by analyzing the operating data of wind turbines, AI can determine the optimal maintenance cycle and maintenance measures to improve power generation efficiency and equipment life.

• Resource allocation and optimization: The application of AI in resource allocation and optimization can significantly improve the efficiency and performance of the DePin network. Traditional resource allocation often relies on manual scheduling and static rules, which is difficult to cope with complex and changing actual situations. AI can dynamically adjust resource allocation strategies through data analysis and optimization algorithms to achieve the following goals:

• Dynamic load balancing: In decentralized computing and storage networks, AI can dynamically adjust task allocation and data storage locations based on node load and performance indicators. For example, in a distributed storage network, AI can store data with higher access frequencies on nodes with better performance, while distributing data with lower access frequencies on nodes with lighter loads, thereby improving the storage efficiency and access speed of the entire network.

• Energy efficiency optimization: AI can optimize energy production and use by analyzing the energy consumption data and operation mode of equipment. For example, in smart grids, AI can optimize the start and stop strategies of generator sets and the distribution of electricity according to users electricity usage habits and electricity demand, thereby reducing energy consumption and carbon emissions.

• Improved resource utilization: AI can maximize resource utilization through deep learning and optimization algorithms. For example, in a decentralized logistics network, AI can dynamically adjust delivery routes and vehicle scheduling plans based on real-time traffic conditions, vehicle locations, and cargo demand, thereby improving delivery efficiency and reducing logistics costs.

Data analysis and decision support

• Data collection and processing: In the decentralized physical infrastructure network (DePin), data is one of the core assets. Various physical devices and sensors in the DePin network will continuously generate a large amount of data, including sensor readings, device status information, network traffic data, etc. AI technology has shown significant advantages in data collection and processing:

• Efficient data collection: Traditional data collection methods may face problems such as data dispersion and low data quality. AI can collect high-quality data locally in real time on the device through smart sensors and edge computing, and dynamically adjust the frequency and scope of data collection according to demand.

• Data preprocessing and cleaning: Raw data usually contains noise, redundancy, and missing values. AI technology can improve data quality through automated data cleaning and preprocessing. For example, machine learning algorithms can be used to detect and correct abnormal data and fill in missing values, thereby ensuring the accuracy and reliability of subsequent analysis.

• Real-time data processing: The DePin network needs to process and analyze massive amounts of data in real time to quickly respond to changes in the physical world. AI technology, especially streaming processing and distributed computing frameworks, makes real-time data processing possible.

• Intelligent decision-making and prediction: In the decentralized physical infrastructure network (DePin), intelligent decision-making and prediction is one of the core areas of AI application. Through deep learning, machine learning and prediction models, AI technology can achieve intelligent decision-making and accurate prediction of complex systems, and improve the autonomy and response speed of the system:

• Deep learning and predictive models: Deep learning models can handle complex nonlinear relationships and extract potential patterns from large-scale data. For example, by analyzing the operation data and sensor data of equipment through deep learning models, the system can identify potential signs of failure, perform preventive maintenance in advance, reduce equipment downtime, and improve production efficiency.

• Optimization and Scheduling Algorithms: Optimization and scheduling algorithms are another important aspect of AI’s intelligent decision-making in the DePin network. By optimizing resource allocation and scheduling schemes, AI can significantly improve system efficiency and reduce operating costs.

安全

• Real-time monitoring and anomaly detection: In decentralized physical infrastructure networks (DePin), security is a critical factor. AI technology can detect and respond to various potential security threats in a timely manner through real-time monitoring and anomaly detection. Specifically, AI systems can analyze network traffic, device status, and user behavior in real time to identify abnormal activities. For example, in a decentralized communication network, AI can monitor the flow of data packets and detect abnormal traffic and malicious attack behaviors. Through machine learning and pattern recognition technology, the system can quickly identify and isolate infected nodes to prevent further spread of attacks.

• Automated threat response: AI can not only detect threats, but also automatically respond. Traditional security systems often rely on human intervention, while AI-driven security systems can take action immediately after a threat is detected, reducing response time. For example, in a decentralized energy network, if AI detects abnormal activity at a node, it can automatically cut off the connection to the node and start the backup system to ensure the stable operation of the network. In addition, AI can improve the efficiency and accuracy of threat detection and response through continuous learning and optimization.

• Predictive maintenance and protection: Through data analysis and prediction models, AI can predict potential security threats and equipment failures and take protective measures in advance. For example, in intelligent transportation systems, AI can analyze traffic flow and accident data, predict possible high-incidence areas of traffic accidents, deploy emergency measures in advance, and reduce the probability of accidents. Similarly, in distributed storage networks, AI can predict the failure risk of storage nodes and perform maintenance in advance to ensure data security and availability.

How DePin is changing AI

Advantages of DePin in AI

• Resource sharing and optimization: DePin allows different entities to share computing resources, storage resources, and data resources. This is especially important for scenarios where AI training and reasoning require a large amount of computing resources and data. The decentralized resource sharing mechanism can significantly reduce the operating costs of AI systems and improve resource utilization.

• Data privacy and security: In traditional centralized AI systems, data is often stored on a central server, which may lead to data leakage and privacy issues. DePin ensures data security and privacy through distributed storage and encryption technology. Data holders can share data with AI models for distributed computing while retaining data ownership.

• Enhanced reliability and availability: Through a decentralized network structure, DePin improves the reliability and availability of AI systems. Even if a node fails, the system can continue to operate. Decentralized infrastructure reduces the risk of single point failures and improves the resilience and stability of the system.

• Transparent incentive mechanism: The token economics in DePin provides a transparent and fair incentive mechanism for transactions between resource providers and users. Participants can obtain token rewards by contributing computing resources, storage resources or data, forming a virtuous circle.

Potential application scenarios of DePin in AI

• Distributed AI training: AI model training requires a lot of computing resources. Through DePin, different computing nodes can work together to form a distributed training network, significantly speeding up training. For example, a decentralized GPU network can provide training support for deep learning models.

• Edge computing: With the popularity of Internet of Things (IoT) devices, edge computing has become an important direction for the development of AI. DePin can distribute computing tasks to edge devices close to data sources to improve computing efficiency and response speed. For example, smart home devices can use DePin to achieve localized AI reasoning and improve user experience.

• 数据 市场: The performance of AI models depends on a large amount of high-quality data. DePin can establish a decentralized data market, enabling data providers and users to trade data while protecting privacy. Through smart contracts, the data transaction process is transparent and credible, ensuring the authenticity and integrity of the data.

• Decentralized AI service platform: DePin can serve as an infrastructure to support decentralized AI service platforms. For example, a decentralized AI image recognition service platform, users can upload images, the platform processes them through distributed computing nodes and returns the results. This platform not only improves the reliability of the service, but also encourages developers to continuously optimize the algorithm through the token mechanism.

AI + DePin Project

在本节中，我们将探索几个与AI相关的DePin项目，重点关注去中心化文件存储和访问平台Filecoin，去中心化GPU算力租赁平台Io.net以及去中心化AI模型部署和访问平台Bittensor。这三者在AI领域的数据存储访问，算力支持训练和模型部署方面发挥着重要作用。

文件币

Filecoin 是一个去中心化的存储网络，通过区块链技术和加密货币经济模型实现全球分布式数据存储。Filecoin 由 Protocol Labs 开发，旨在创建一个开放、公共的存储市场，用户可以通过支付 Filecoin 代币（FIL）购买网络中的存储空间，也可以通过提供存储服务赚取 FIL。

功能

• 去中心化存储：Filecoin以去中心化的方式存储数据，避免了传统云存储的中心化弊端，如单点故障、数据审查风险等。

• 市场驱动：Filecoins存储市场由供需决定，存储价格和服务质量通过自由市场机制动态调整，用户可以根据自身需求选择最佳的存储解决方案。

• 可验证存储：Filecoin 通过时空证明（PoSt）和复制证明（PoRep）等机制确保数据在存储提供商处有效存储和备份。

• 激励机制：Filecoin通过挖矿和交易奖励机制，鼓励网络参与者提供存储和检索服务，从而增加网络的存储容量和可用性。

• 可扩展性：Filecoin网络通过引入分片等技术手段，支持大规模数据存储和快速访问，满足未来海量数据增长的需求。

痛点解决

• 数据存储成本高：通过Filecoins去中心化存储市场，用户可以更加灵活的选择存储提供商，降低数据存储成本。

• 数据安全与隐私问题：去中心化存储与加密技术保证了数据的隐私和安全，降低了因中心化存储而导致的数据泄露风险。

• 数据存储的可靠性：Filecoin提供的时空证明、复制证明机制，保证了数据在存储过程中的完整性和可验证性，提高了数据存储的可靠性。

• 传统存储平台的信任问题：Filecoin通过区块链技术实现存储透明化，消除了第三方机构对数据的垄断和操纵，增强了用户对存储服务的信任。

目标用户

• 存储提供商：响应用户的存储请求，通过向平台提供闲置磁盘空间访问来赚取代币。存储提供商需要质押代币。如果他们未能提供有效的存储证明，他们将受到惩罚并失去部分质押代币。

• 文件检索器：当用户需要访问文件时，他们可以通过检索文件位置来赚取代币。文件检索器不需要质押代币。

• 数据存储者：通过市场机制，提交自己愿意支付的价格，与存储者匹配后，将数据发送给存储者。双方签署交易订单，并提交到区块链上。

• 数据使用者：用户提交唯一的文件标识并支付费用，文件检索者找到文件的存储位置，响应存储请求并提供数据。

代币 经济体制

• FIL代币流通：FIL是Filecoin网络中的原生加密货币，用于支付存储、奖励矿工以及在网络中进行交易。FIL代币的流通维护着Filecoin网络的正常运行。

• 存储矿工和检索矿工的奖励：存储提供商通过提供存储空间和数据检索服务赚取FIL代币。矿工的奖励与其提供的存储空间，数据访问频率以及其对网络共识的贡献有关。

• 网络费用：用户需要支付FIL代币来购买存储和检索服务，费用由存储市场的供需决定，用户可以自由选择市场上合适的服务提供商。

• 代币发行与通胀：Filecoin总供应量20亿，通过挖矿奖励逐步发行新的FIL代币，随着矿工数量的增加，网络通胀率会逐渐下降。

互联网

Io.net 是一个分布式 GPU 计算平台，通过收集和集群闲置算力，为市场提供算力调度和临时补充，而不是取代现有的云计算资源。平台允许供应商通过简单的 Docker 指令部署支持的硬件供用户租用，满足任务分发和处理的需求。通过分布式算力共享的模式，Io.net 希望提供接近云计算平台的效果，同时大幅降低服务成本。

功能

• 部署便捷：供应商可以通过Docker指令轻松部署硬件，用户可以方便地通过平台租用硬件集群，获得所需的计算能力。

• 集群化算力：通过将闲置算力聚集起来，平台作为市场算力的调度和临时补充，从而提高计算资源整体利用率。

• 安全传输与链上存储：平台采用端到端加密技术，保障用户数据安全，同时任务执行信息将上链保存，实现日志透明、永久保存。

• 节点健康监控：平台记录并公开各个节点的健康状态，包括离线时间、网络速度、任务执行情况等，保证系统的稳定性和可靠性。

痛点解决

• 算力不足：由于大模型的兴起，市场对训练所需的GPU算力需求急剧增加，io.net通过整合社会闲置的GPU资源来填补这一算力缺口。

• 隐私与合规：大型云平台服务商如AWS、Google Cloud对用户的KYC要求较为严格，而Io.net通过去中心化的方式避免了合规问题，让用户可以更加灵活的选择使用资源。

• 成本较高：云计算平台的服务价格较高，而Io.net通过分布式算力共享，大幅降低了成本，同时通过集群技术，实现了接近云平台的服务质量。

目标用户

• 算力提供者：将闲置的GPU接入平台，供其他人使用，根据所提供设备的性能和稳定性，可获得Token奖励。

• 算力用户：通过消耗Token来租用GPU或者GPU集群，用于提交任务或者大型模型训练。

• 质押者：质押者质押平台币，支持平台长期稳定运营，并获得设备租赁的质押收益，有助于提升优秀设备的排名。

代币经济体系

• 代币使用：平台内所有交易均使用原生代币 $IO，以减少智能合约中的交易摩擦。用户和供应商可以使用 USDC 或 $IO 付款，但使用 USDC 需要支付 2% 的服务费。

• 代币总量：$IO 总量为 8 亿，首发时发行 5 亿，剩余 3 亿用于奖励供应商和质押者。代币将在 20 年内逐步释放，第一年释放总量为 8%，之后每月减少 1.02%。

• 代币销毁：平台收入的一部分将用于回购并销毁$IO，成本来自0.25%的双边预留费和使用USDC付款的2%的服务费。

• 代币分配：代币将分发给种子投资者、A轮投资者、团队、生态系统和社区以及供应商奖励。

Bittensor（TAO）

Bittensor 是一个去中心化的点对点 AI 模型市场，旨在通过允许不同的智能系统相互评估和奖励来促进 AI 模型的生产和流通。通过分布式架构，Bittensor 创造了一个可以不断生产新模型并奖励贡献者信息价值的市场。该平台为研究人员和开发人员提供了一个部署 AI 模型以赚取收益的平台，而用户则可以通过该平台使用各种 AI 模型和功能。

功能

• 分布式市场：Bittensor 已构建去中心化的 AI 模型 市场，让工程师和小型AI系统能够直接将自己的劳动成果货币化，打破大公司对AI的垄断。

• 标准化、模块化：网络支持文本、图像、语音等多种模式，让不同的AI模型能够交互、共享知识，并可扩展到更复杂的多模态系统。

• 系统排名：每个节点根据其对网络的贡献进行排名。贡献衡量标准包括节点在任务上的表现、其他节点对其输出的评价以及 节点在网络中获得的信任度越高，排名越高，获得的网络权重和奖励也就越多，从而激励节点在去中心化市场中持续提供优质服务。这种排名机制不仅保证了系统的公平性，也提高了网络整体的计算效率和模型质量。

痛点解决

• 智能生产中心化：当前AI生态集中在少数大公司手中，独立开发者难以盈利，Bittensor通过点对点的去中心化市场，为独立开发者和小型AI系统提供直接盈利机会。

• 计算资源利用率低：传统AI模型训练依赖单一任务，无法充分利用多样的智能系统。Bittensor可以让不同类型的智能系统相互协作，提高计算资源的利用效率。

目标用户

• 节点运营者：将算力和模型接入Bittensor网络，通过参与任务处理和模型训练获得Token奖励。节点运营者可以是独立开发者、小型AI公司，甚至是个人研究人员，通过提供优质的算力资源和模型，提高自身在网络中的排名和收入。

• AI模型用户：需要AI算力资源和模型服务的用户通过支付Token的方式在Bittensor网络中租用算力和智能模型，用户可以是企业、科研机构或者个人开发者，利用网络中的优质模型完成特定的任务，如数据分析、模型推理等。

• Stakers：持有 Bittensor 代币的用户通过 Staking 支持网络的长期稳定运行，并获得 Staking 奖励。Stakers 不仅可以从网络的通胀中获益，还可以通过 Staking 提高所支持的节点的排名，从而间接影响网络整体的计算效率和收益分配。

代币经济体系

• 代币使用：Bittensor 网络内的所有交易和激励都通过原生代币进行，减少了交易过程中的摩擦。用户可以使用代币支付计算资源和模型服务，节点运营商通过提供服务赚取代币。

• 代币生成：每12秒生成一个区块，生成1个TAO代币，根据子网性能和其中节点的性能进行分配。代币分配比例为：18%分配给子网所有者，子网矿工和验证者各获得41%。代币最大供应量为2100万个。

DePin 的挑战和结论

DePIN作为一种新兴的网络架构，结合区块链技术实现了物理基础设施的去中心化管理。这一创新不仅解决了传统基础设施面临的数据隐私、服务中断、高扩容成本等问题，还通过代币激励机制和自组织模型赋予网络参与者更多的控制权和参与权。尽管DePIN已经展现出巨大的潜力，但仍面临一些挑战。

• 可扩展性：DePIN的可扩展性问题源于其对区块链技术去中心化特性的依赖。随着用户数量和网络规模的增加，区块链网络上的交易量也会随之增加。特别是DePIN应用与物理世界的连接对信息传输的要求更高。这将导致交易确认时间更长、交易费用增加，进而影响整体网络效率和用户体验。

• 互操作性：DePIN 生态系统建立在多条区块链之上，这需要 DePIN 应用程序支持同构或异构状态转换，并实现与其他区块链网络的无缝互操作性。然而，当前的互操作性解决方案通常局限于特定的区块链生态系统或伴随着较高的跨链成本，难以完全满足 DePIN 的需求。

• 监管合规：作为 Web 3.0 生态系统的一部分，DePIN 面临多重监管挑战。其去中心化和匿名性使得监管机构难以监控资金流向，这可能导致非法集资、传销和洗钱活动的增加。此外，在税收监管方面，由于账户的匿名性，政府很难收集征税所需的证据，这对现有的税收体系提出了挑战。

未来DePIN的发展将取决于这些关键问题的解决，并有望在广泛的应用场景中发挥重要作用，重塑物理基础设施的运营模式。

This article is sourced from the internet: AI×DePin: Co-evolution of intelligent infrastructure

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