GM Network Whitepaper

GM Network: The First Consumer AIoT Network

-GM Network Team


GM Network, inspired by GM Labs, is the first consumer AIoT network, built with AltLayer and EigenLayer.

AIoT consists of AI + IoT. Over decades of internet development, IoT has permeated every aspect and constitutes today’s human life. DePIN represents the decentralized part built on IoT. For more precise expression, we believe AI + IoT better articulates the vision and objectives of GM Network, as it will subsequently be unifiedly represented as AIoT, which stands for AI + IoT/DePIN.

In 2024, with the rapid development of various AI models like ChatGPT-4o, Gemini, and Llama3, AI is increasingly influencing people’s lives. Through smartphones, wearable devices, robots, electric vehicles, and other smart devices, humans can increasingly experience the convenience of AI and communicate with AI through voice, visual, and other means. As AI becomes more widespread in the future, hardware devices are essential bridges, with IoT playing an increasingly important role, especially consumer-facing IoT which, enhanced by AI, becomes truly smarter, producing interesting products like Rabbit R1, Pin, and Oura Ring. These developments have a profound impact on human society, much like the stories in Black Mirror.

Therefore, we developed GM Network with the hope that it becomes the largest communication and incentive layer connecting AI and IoT, bridging the virtual and real worlds, and acting as a massive bridge to accelerate the data and application scenarios needed by AI, making it easier for consumers to feel the warmth and convenience of AI.

[1]The Trend: AI inevitably enters human life, and human interaction with AI is inseparable from IoT

AI and IoT are inseparable

The rapid advancement of artificial intelligence (AI) is transforming the way we live, work, and interact with technology. As AI continues to evolve, its integration into everyday life becomes inevitable. From personal assistants like Siri and Alexa to advanced machine learning algorithms that power our smart devices, AI is becoming an indispensable part of our daily routines. However, the true potential of AI is unlocked when it is combined with the Internet of Things (IoT).

IoT refers to the network of physical devices, vehicles, home appliances, and other items embedded with sensors, software, and connectivity, enabling them to collect and exchange data. This interconnected ecosystem allows for seamless communication and interaction between devices, creating a smart environment that enhances efficiency and convenience.

The relationship between AI and IoT is symbiotic. IoT devices generate vast amounts of data, which AI algorithms analyze and learn from to make intelligent decisions. This data-driven approach enables AI to provide personalized and context-aware services, improving user experience and optimizing operations. For instance, smart thermostats learn user preferences and adjust temperatures accordingly, while wearable fitness trackers monitor health metrics and provide personalized fitness recommendations.

Conversely, AI enhances the functionality of IoT devices by making them more intelligent and autonomous. AI-powered IoT systems can predict maintenance needs, detect anomalies, and automate processes, reducing the need for human intervention. This level of automation is particularly valuable in industries such as manufacturing, healthcare, and transportation, where efficiency and accuracy are paramount.

As AI becomes more embedded in our lives, the need for robust IoT infrastructure grows. The integration of AI and IoT is not just a trend but a fundamental shift in how we interact with technology. This convergence is driving innovation and creating new opportunities for businesses and consumers alike. Together, AI and IoT are shaping a future where smart, connected devices enhance our quality of life and drive the digital transformation of industries.

In conclusion, the future of AI is intrinsically linked to IoT. The seamless integration of these technologies is essential for unlocking their full potential and delivering intelligent, data-driven solutions that improve our lives. As we move forward, the collaboration between AI and IoT will continue to evolve, driving new advancements and shaping the way we interact with the world around us.

Until Now, Most IoT Devices Remain Simple and Not Truly AI-Driven

Despite the rapid advancements in technology, the majority of IoT devices today remain relatively simple in their capabilities and are not fully integrated with artificial intelligence (AI). These devices, while smart, often lack the sophistication and learning capabilities that true AI can offer. On the other hand, AI itself continues to struggle with a lack of sufficient data to truly understand and predict user needs and behaviors.

For AI to reach its full potential, it needs a continuous influx of diverse and high-quality data. This data is crucial for training AI models to be more accurate and responsive to user requirements. However, the current generation of IoT devices does not generate enough meaningful data that AI can leverage effectively. This gap highlights the need for a new generation of IoT devices that are designed not just to be smart but also to be capable of generating and processing data suitable for AI applications.

To bridge this gap, more IoT devices need to be upgraded to support AI functionalities. This can be achieved through the integration of Cloud AI and Edge AI technologies. Cloud AI involves leveraging the vast computational resources available in the cloud to analyze data and derive insights. This approach allows for powerful data processing and sophisticated AI models that can be continuously updated and improved. However, it often requires reliable and fast internet connectivity, which might not always be available.

Edge AI, on the other hand, brings AI capabilities directly to the devices at the edge of the network, such as sensors, cameras, and other IoT devices. This approach enables real-time data processing and decision-making without the need for constant cloud connectivity. By embedding AI capabilities directly into the IoT devices, they can become more autonomous, efficient, and responsive. Edge AI reduces latency, enhances privacy by keeping data local, and ensures that devices can operate independently even in environments with limited connectivity.

Upgrading IoT devices to support both Cloud AI and Edge AI will allow for a more seamless and intelligent interaction between AI and IoT. This will enable IoT devices to not only collect and transmit data but also to analyze and act on this data in real-time, making them truly intelligent. For example, smart home devices could learn the habits and preferences of the users, adjusting settings autonomously to improve comfort and efficiency. Industrial IoT devices could predict maintenance needs and optimize operations to reduce downtime and costs.

In conclusion, the evolution of IoT devices from being merely smart to truly AI-driven is essential for the next wave of technological innovation. By integrating Cloud AI and Edge AI, IoT devices can generate the rich, meaningful data that AI needs to better understand and serve users. This synergy will lead to smarter, more responsive environments that enhance our daily lives and drive the digital transformation of industries.

Some interesting attempts and innovations

Whether it is giants or startups, they are all launching new hardware devices. At the beginning of the year, Apple released the VisionPro, and Meta subsequently released smart glasses in collaboration with Ray-Ban. There are also examples like the Whoop smart wristband and the Oura Ring smart ring. Even Rabbit released the AI voice phone R1, and Humane launched the AI Pin. Samsung is also about to release its own Galaxy Ring. IoT will play an increasingly important role in the world of AI, providing enormous new opportunities for all entrepreneurs:

  • A brand new track.
  • An opportunity to compete on product innovation.
  • A chance to bypass the FAANG companies.
  • An opportunity to build new human-machine interaction and new paradigms.

[2]The Problem: AI lacks data from IoT and the scenarios provided by IoT

Despite the rapid advancements in artificial intelligence (AI), a significant gap remains in the availability of real-world data and practical scenarios necessary for AI to reach its full potential. This gap is particularly evident in the realm of the Internet of Things (IoT), where the integration of AI could revolutionize consumer experiences and industry operations. However, several critical issues hinder this integration.

The Data Problem
  1. Lack of Real-World Data: Most AI systems today rely heavily on online and on-chain data, which, while abundant, often lacks the personalization and real-time attributes that IoT devices can provide. Real-world data from IoT devices can offer insights into daily behaviors, environmental conditions, and individual preferences, which are crucial for developing truly intelligent and responsive AI systems.
  2. Closed Ecosystems of Major Companies: Leading tech companies like Apple and Google have a wealth of data collected from their devices, but this data is typically kept within their proprietary ecosystems. This creates a significant barrier for developers and smaller companies who do not have access to this valuable data, limiting their ability to create comprehensive AI solutions.
  3. Data Ownership Issues: In many current models, the ownership of data is divorced from the users who generate it. Users often have no control over their data and do not benefit from its use. This disconnect not only raises ethical concerns but also reduces the incentive for users to contribute their data to AI development efforts.
The Scenarios Problem
  1. Limited Consumer-Facing Scenarios: While there are numerous AI projects, very few are directly aimed at enhancing consumer experiences. The potential of AI in daily life remains largely untapped, as the available applications are mostly confined to specific, non-consumer sectors or abstract, generalized functionalities.
  2. Monopoly of AI General Scenarios by Major Companies: Major companies like OpenAI, Apple, and Meta dominate the development of AI for general scenarios such as text generation, chatbots, and digital tools. This concentration of development efforts stifles innovation and limits the diversity of applications available to consumers.
The Need for Integration

To bridge these gaps, a closer integration between AI and IoT is essential. IoT devices can provide the personalized, real-time data that AI needs to improve its accuracy and relevance. Moreover, opening up the ecosystems of major tech companies and addressing data ownership issues can democratize access to data, fostering innovation across the industry.

For AI to become truly ubiquitous and beneficial, it must be embedded in more consumer-facing scenarios. This requires breaking the monopoly of major companies and encouraging the development of AI applications that enhance everyday experiences. Smart home devices, wearable health monitors, and intelligent personal assistants are just a few examples of how AI can be integrated into daily life, providing tangible benefits to users.


The future of AI depends on overcoming the current limitations in data and scenario availability. By leveraging the vast amounts of data generated by IoT devices and creating more diverse, consumer-facing applications, AI can realize its full potential. This will require collaborative efforts to open data ecosystems, address ownership concerns, and drive innovation beyond the confines of today’s major tech companies. Only then can AI truly transform the way we live and interact with technology.

[3]The Opportunity: Leveraging the power of Web3 to connect more IoT devices and provide data and scenarios for AI

The convergence of Web3 and IoT offers an unprecedented opportunity to revolutionize the landscape of AI. By leveraging the decentralized and secure nature of Web3, we can enhance the connectivity of IoT devices, providing a robust foundation for AI to access a wealth of real-world data and diverse scenarios. This synergy not only addresses the existing challenges faced by AI but also opens up new avenues for innovation and development.

One of the primary limitations of current AI systems is the lack of personalized and real-time data. Most AI models are trained on online and on-chain data, which, while extensive, do not fully capture the nuances of individual behaviors and environmental contexts. IoT devices, embedded in our daily lives, generate a continuous stream of data that is both personal and contextual. Integrating this data into AI systems can significantly enhance their accuracy and relevance, enabling more responsive and adaptive AI applications.

However, the challenge lies in the accessibility and utilization of this data. Large tech companies like Apple and Google often silo their data within closed ecosystems, limiting the ability of external developers to harness this information. Web3, with its decentralized architecture, offers a solution by facilitating open and secure data exchange. By enabling IoT devices to share data in a decentralized manner, Web3 ensures that valuable information is not confined to proprietary platforms but is available to drive AI innovation.

Moreover, Web3 enhances data ownership and privacy, allowing users to have control over their data and even benefit from it financially. This paradigm shift empowers individuals and fosters a more equitable data economy. Users can choose to share their IoT-generated data with AI developers in a secure and transparent manner, knowing that their privacy is safeguarded and that they are fairly compensated.

The integration of Web3 and IoT also paves the way for more diverse and consumer-facing AI applications. While leading AI companies dominate general-purpose scenarios like text processing and chatbots, there is a vast untapped potential for specialized applications that cater to specific user needs. By connecting more IoT devices through Web3, developers can create innovative AI solutions tailored to unique contexts, such as personalized health monitoring, smart home automation, and intelligent transportation systems.

For instance, a smart home equipped with various IoT devices can provide real-time data on user preferences and behaviors. This data can be utilized by AI systems to optimize energy consumption, enhance security measures, and improve overall living comfort. Similarly, wearable IoT devices can continuously monitor health metrics, offering personalized insights and recommendations powered by AI. These applications not only improve user experiences but also drive significant advancements in AI capabilities.

Furthermore, the decentralized nature of Web3 provides a level playing field for startups and smaller companies to compete with industry giants. It offers a framework where innovation is not stifled by the monopolistic control of data and resources. Entrepreneurs can leverage Web3 to develop cutting-edge AIoT solutions, bypassing traditional barriers and bringing disruptive technologies to market.

The fusion of Web3 and IoT represents a transformative opportunity to reshape the future of AI. By facilitating greater connectivity, ensuring data privacy, and democratizing access to information, this powerful combination sets the stage for unprecedented growth and innovation in the AI landscape. As we move forward, embracing this opportunity will be key to unlocking the full potential of AI and IoT, driving progress, and creating new paradigms of human-machine interaction.

Advantages of Web3
  1. Decentralization: Unlike Web2, which relies on centralized servers, Web3 operates on decentralized networks. This reduces the risk of single points of failure and makes the internet more resilient.
  2. Enhanced Security: Web3 uses blockchain technology, which provides a high level of security through cryptographic algorithms. This makes it much harder for hackers to manipulate or breach data.
  3. Data Ownership: In Web3, users have full control over their data. They can choose what data to share and with whom, often using cryptographic keys. This contrasts with Web2, where data is often stored and controlled by large companies.
  4. Privacy: Web3 enhances privacy by allowing users to interact with applications without revealing their personal information. This is achieved through techniques like zero-knowledge proofs and decentralized identity solutions.
  5. Transparency: Blockchain technology ensures transparency by providing a public ledger of all transactions. This means users can verify the authenticity and history of data and transactions.
  6. Economic Incentives: Web3 introduces new economic models through tokens and cryptocurrencies. Users can earn tokens for participating in networks, contributing data, or performing other valuable actions. This incentivizes participation and creates new revenue streams.
  7. Interoperability: Web3 promotes interoperability between different platforms and applications through open protocols and standards. This allows for seamless integration and communication across various decentralized applications (dApps).
  8. Smart Contracts: Smart contracts are self-executing contracts with the terms directly written into code. They automate and enforce agreements without the need for intermediaries, reducing costs and increasing efficiency.
  9. Innovation and Open Source: Web3 encourages innovation through open-source development. Many Web3 projects are developed collaboratively, with contributions from developers worldwide, fostering a culture of transparency and rapid iteration.
  10. Resilience to Censorship: Decentralized networks are more resistant to censorship. No single entity can control or shut down the network, making it a more open and free platform for communication and information sharing.

In summary, Web3 offers a more secure, private, and user-centric internet, providing numerous opportunities for innovation and new economic models. Its decentralized nature empowers users, enhances transparency, and fosters a more resilient and equitable digital ecosystem.

[4]The Best Answer: GM Network

GM Network aims to be the largest communication and incentive network connecting AI and IoT

GM Network is poised to revolutionize the intersection of AI and IoT by becoming the largest incentive and communication network connecting these two transformative technologies. As AI continues to evolve and integrate into various aspects of daily life, the need for real-time, personalized data becomes increasingly critical. IoT devices, which are already embedded in many facets of our lives, generate vast amounts of this valuable data. However, the current landscape often sees these devices and the data they produce siloed within proprietary ecosystems, limiting their potential impact.

GM Network seeks to bridge this gap by creating an open, collaborative platform where AI and IoT can seamlessly interact. By incentivizing data sharing and providing robust communication channels, GM Network enables AI systems to learn and adapt more effectively, utilizing the rich, real-time data generated by IoT devices. This approach not only enhances the functionality of AI but also drives innovation across various sectors, from smart homes and wearable health tech to autonomous vehicles and industrial automation.

Through strategic partnerships and a commitment to open data ecosystems, GM Network aspires to democratize access to AI and IoT technologies. By aligning incentives with the needs of developers, businesses, and consumers, GM Network is positioned to unlock new possibilities for intelligent, interconnected systems, paving the way for a smarter, more integrated future.

Considering that there are over 2 billion Web2 IoT devices globally and over 1 million Web3 IoT devices, building a dedicated Layer 2 around AI+IoT is extremely valuable. All IoT devices that sustainably contribute data will eventually be incentivized by GM Network and its ecosystem. Through GM’s mechanisms and gameplay, they will continuously provide real-world data for AI training, breaking down data barriers. Additionally, all incentivized IoT devices will provide real user scenarios and application opportunities for AI, allowing most consumers to experience the value of AI, enjoy better AI products, and accelerate the mass adoption of AIoT.

[5]The Overview: Modular Layers of GM Network

GM Network is composed of three layers: the Asset Layer, the Data Layer, and the User Layer. Together, these three layers form the modular, scalable, and composable foundation of the GM Network ecosystem, significantly reducing costs and barriers for developers and enabling the large-scale adoption of AIoT.

  1. Asset Layer: This layer primarily addresses the needs for AIoT asset issuance, circulation, and trading. By utilizing a specialized Layer 2, it better aligns with the characteristics required by AIoT.
  2. Data Layer: This layer focuses on account and data generation, storage, verification, and trading. It ensures that IoT data can be truly adopted by AI.
  3. User Layer: This layer addresses user growth and traffic issues, helping developers achieve easier cold starts.

These layers work in harmony to create a comprehensive and efficient ecosystem for AIoT development and deployment.

5.1 GM Network (Asset Layer)

The GM Network is the first consumer AIoT network, supported by AltLayer and EigenLayer. The GM Network has the following features:

  1. AVS: GM Network is a Layer2 based on AVS proposed by EigenLayer and developed using AltLayer’s Restaked Rollup, utilizing the OP Stack and EigenDA to form Ethereum’s Layer2. Leveraging the power of AVS, GM Network can achieve a fully decentralized network while flexibly obtaining security and paying costs based on security needs. We firmly believe in the potential of AVS, which will not only appear in financial aspects but also in more consumer-facing application scenarios. So actually, GM Network is the first AVS consumer AIoT network.

  2. Gasless: GM Network will implement Gasless services for certain scenarios through account abstraction (GM ID). We aim to significantly lower the barriers for new users to enhance the mas adoption of AIoT. Whether users are in Asia, Africa, or Latin America, they can easily create a Web3 wallet using their own Passkey (Face ID and Touch ID) without worrying about Gas fees. Ultimately, all projects within the GM Network ecosystem will achieve a Web2-like user-friendly experience through Gasless services, ensuring that users, regardless of where the devices are sold, do not have to worry about acquiring Gas tokens like ETH.
  3. Security: The security of GM Network is protected by Ethereum and AVS. While security is crucial for GM Network, it is not the entirety; having calculable cost security is fundamental. Based on the needs of GM Network, security can be flexibly enhanced or appropriately reduced to trade for other performances. In the near future, GM Network’s native token GM can also be staked for GM Network itself as well as for the DApps and Layer 3 within its ecosystem to provide security. Similarly, ecosystem projects can stake to provide more security for the AIoT network.
  4. Scalability: GM Network supports all AIoT projects to deploy DApps or Layer 3 on GM. GM Network can flexibly help them achieve greater scalability according to the needs of ecosystem projects, with highly customizable and deeply supportive solutions in the following areas:
    • Infrastructure scalability.
    • Device and data scalability.
    • Asset and liquidity scalability.
    • User and community scalability.
5.2 GM ID (Data Layer)
  1. GM ID is an Aggregated Wallet SDK Combining Passkey, Account Abstraction and DID.

  2. With the power of GM ID, all developers can offer seamless wallet and DID creation services in their products:
    • Social login: Create an AA wallet using Passkey (Touch ID/Face ID/Optic ID) on any device that supports Passkey, whether it's a smartphone, MR device, or any other.
    • Security and convenience: Log in or recover your AA wallet at any time with the same Passkey (Apple/Google account).
    • Gasless: Gas fees are covered by GM Network, transparent to the user.
    • DID: Your nickname is your DID, no need to display complex EVM address formats.
  3. GM ID is compatible with web, iOS, and Android, easy to use, significantly lowering the barrier for developers, and fully integrated with GM Network to cover all Web3 modules.
  4. GM ID is the optimal wallet and ID solution for AIoT launched by GM Network based on first principles. Developed in collaboration with leading industry partners, it is specifically tailored for the AIoT field. We believe that only with a robust solution for wallets and IDs at the data layer can users’ extensive data be attributed to their own wallets, granting them ownership and profit rights. This foundation is crucial for subsequently using data to serve AI training and automatically distributing profits.
5.3 GM OS (Data Layer)
  1. GM OS is an on-chain and off-chain data protocol for accelerating the data communication between AI and IoT.

  2. GM OS is an on-chain and off-chain data protocol designed to expedite the flow of information between AI and the IoT. This innovative protocol bridges the gap between the virtual and physical worlds, ensuring seamless data communication and integration. By leveraging both on-chain security and off-chain speed, GM OS enables real-time data processing and analytics, facilitating more efficient AI training and decision-making. This robust protocol empowers IoT devices to provide valuable data to AI systems, enhancing their learning capabilities and overall performance. Additionally, GM OS ensures that data ownership and privacy are maintained, giving users control over their information. Ultimately, GM OS is set to revolutionize the interaction between AI and IoT, driving the development of smarter, more responsive technologies and applications.
  3. GM OS will have the following key features:

    • On-chain data, sourced from DApps like QuestN.
    • Off-chain data, sourced from various AIoT devices.
    • Data ownership module, ensuring users gain ownership and profit rights over data in the GM ecosystem.
    • Data storage module, providing decentralized storage of ZK-encrypted data through our partners.
    • Data exchange marketplace, where AI projects can obtain data packages at any time and automatically distribute profits to the data originators.
  4. GM OS has accumulated 10 millions of on-chain data entries from QuestN and serves over 6,000 developers, covering multiple fields from DePIN, AI, Gaming, Social and DeFi. As more consumer AIoT products emerge, the data on GM OS will become increasingly accurate and valuable.

5.4 QuestN (User Layer)
  1. QuestN is the Best Community Growth and Marketing Platform.

  2. Two years after its launch, QuestN has accumulated over 10M+ unique addresses with a DAU count of over 200K+ and MAU reaching 1M+. Users are spread across more than 25 countries and regions. QuestN daily engages a massive user base with numerous quests and campaigns, helping over 6,000 projects with community growth and cold starts, and delivering over 3 million USD in token rewards to users.

  3. QuestN will continuously generate more data from the on-chain data perspective, which, together with off-chain data, will assist in AI training. It will also help more AIoT projects in building on-chain user profiles, reputation management, and behavior analysis.

  4. As a leading project within the GM Network ecosystem, QuestN will continue to support the community growth, presales for Devices and NFTs, product promotion of more consumer AIoT projects.
5.5 GM Launchpad (User Layer)
  1. GM Launchpad is a Launchpad for AIoTs and NFTs.

  2. GM Launchpad is a Web3 version of the Apple Store, designed to help all AIoT projects with the sale of devices and NFTs. It supports the development of the GM Network ecosystem through flexible sales models and traffic aggregation. GM Launchpad currently supports two sales models:
    • Collection: A combination of NFT and device. Users will first receive the NFT and then receive the device after it is shipped, allowing them to earn both NFT staking and device mining rewards.
    • NFT: A single NFT. Users will only receive the NFT and can earn NFT staking rewards.
  3. GM Launchpad also supports various features and functionalities:
    • Referral Bonus: Users receive a referral bonus when they invite friends to make a purchase.
    • Add Liquidity: A percentage of the device sales amount is added to liquidity.
    • Multiple Payment Methods: Supports various tokens such as USDT, USDC, ETH, GM and more.
    • Exciting AIoT Discoveries: Discover more interesting and fun AIoT products.
  4. We hope that GM Launchpad can become the first step for all AIoT entrepreneurs, helping them reduce the difficulty of sales and customer acquisition costs. Additionally, by using Crypto, we aim to make more devices fun and interactive, allowing users to easily discover interesting AIoT products.
5.6 GM AI (User Layer)
  1. GM AI is the one app for all AIoTs and Agents.

  2. GM AI is the super app of GM Network, designed to manage all of the user’s AIoTs and AI agents with a single app. Its main features include:
    • Binding Web2 IoT: Generate NFTs on GM Network and earn rewards from the data generated through continuous use.
    • Binding Web3 IoT: Whether purchased from GM Launchpad or other channels, you can bind and mine rewards from the data generated by continuously using the devices.
    • Managing NFTs and Devices: Manage various AIoTs, from wearables to smart home devices.
    • Gamified Experience: Create fun and easy-to-use experiences by combining NFTs and tokens with social and gamified elements.
    • Enhancing Your Agent: Improve your AI agent’s level, ability, and creativity through continuous use of GM AI.
    • More to Come: Stay tuned for more features.
  3. GM AI is set to become the collector and gateway for all AIoT data. Through GM AI, a consumer-focused application, we aim to create a product that is fun, easy to use, and profitable. This product will continuously provide AI with real-world IoT data and distribute the resulting benefits to users, developers, and GM Network.

[6]GM, AIoT

  1. AIoT=AI+IoT, IoT provides data and scenarios to AI and transforms into AIoT.

  2. GM aims to be the largest communication and incentive network connecting AI and IoT, continuously providing AI with:
    • Data: Continuously providing real-world IoT data to AI, such as home, health, and driving data.
    • Scenarios: Continuously providing rich scenarios to AI, such as wearable, voice, vision, and image.
  3. The more AIoT devices there are, the more NFTs will be minted, and the more users will join the GM Network ecosystem, continuously using devices and generating more real-world data. Therefore, the core metric for GM Network is no longer TVL (Total Value Locked) like DeFi products, but more appropriately TDVL (Total Device Value Locked) for the AIoT ecosystem. Considerations for TDVL include:

    • With more Layer2s and Layer3s, each chain having its own liquidity isn't the most capital-efficient or profitable. Instead, working with more abstract bridges or DEXs can still provide sufficient liquidity for the ecosystem.

    • Non-DeFi Layer2s aren't suitable for TVL metrics and may lead to misdirection. GM Network focuses on how many devices are connected and the value generated by these devices, making the evolution from TVL to TDVL a more rational choice.

  4. Therefore, within the GM Network ecosystem, NFTs have many functions:

    • An Web2 or Web3 IoT device.
    • An AI Agent.
    • A data package, signifying a collection of data representing certain user ownerships.
    • An option, representing the output value of the corresponding AIoT over a certain period of time.
  5. Clearly, more NFTs in GM Network means more devices, agents, data, and rights, so the growth of NFTs signifies an increase in the number of devices and network value.
  6. GM Network's network value will show a non-linear growth relationship with the increase of NFTs. As the number of NFTs increases, covering more users and scenarios, the value of the network shows an increasingly steep curve.
  7. This translation outlines GM Network's innovative approach to integrating blockchain technology with real-world applications through NFTs and IoT, emphasizing a strategic pivot from traditional liquidity metrics to a more holistic valuation of networked devices and data assets.

[7]GM Network Ecosystem: Incubated & Incentivised

7.1 Incubated
  1. GM Studio is the official incubator of GM Network, providing a series of in-depth support and assistance to accelerate the development of AIoT products around GM Network. The supports include:
    • 3D and Structural design.
    • Supply Chain and Logistics.
    • Sales Channel.
    • Deep Integration.
    • PR.
    • More Incentives.
  2. Any consumer AIoT project can apply to join GM Studio, regardless of whether it has its own tokens or is deployed on other networks. GM Network will evaluate applications based on product goals, user experience, use scenarios, integration with AI, business model, and community popularity. All projects that join GM Studio will also receive additional incentives in GM Tokens and are offered dual staking opportunities and other token-based deep integration plans.
7.2 Incentivised
  1. All consumer AIoT projects deployed on GM Network can directly receive the following support:
    • Marketing Support.
    • Product Support.
    • Developer Support.
    • Join Store.
    • Join GN Missions.
    • Dual Staking.
  2. Early projects deployed on GM Network will also enjoy additional airdrops and incentive programs of GM Tokens. For more details, please follow the official social media accounts.
7.3 Bringing Exciting AI Innovations to Consumer IoTs
  1. GM Network will continuously expand the number of AIoT devices through quarterly incubation and ecosystem attraction programs. As more consumer-perceivable and usable devices emerge, the network effect of GM Network will grow stronger, providing GM with greater leverage to attract more AI projects to connect with consumer IoT. This will ultimately transform into AIoT, creating a significant positive flywheel effect.

[8]AVS & Dual Staking

8.1 AVS(Actively Validated Services)
1.Why AVS?
  • Before the advent of AVS, the capital and security costs of all Layer2 solutions were very high, as they needed to continually synchronize with Layer 1, which is inherently expensive, making even Rollup costs relatively high (although the Cancun upgrade partially improved this).

  • After the emergence of EigenLayer and AltLayer, all developers can not only build DApps but also construct their own Layer2 or Layer3 at lower costs. With the security market provided by AVS, developers no longer have to worry about paying high security costs and can continue to focus on their products and user experience.

  • Modular combinations like AVS completely liberate innovation. Developers can build their own ecosystem around token + DApp + Appchain, offering users a complete, seamless experience while capturing value through tokens. This is why GM Network chose to build its own Layer2 based on AVS. We are very confident in the dividends and value brought by the innovations of AltLayer and EigenLayer, and it will significantly unleash the potential for innovation, accelerating the mas adoption of Ethereum.

2.How AVS?

With the power of AVS, GM Network can support all consumer AIoT products to deploy their own DApps or develop their own vertical Layer3 based on GM:

  • Whether DApps or L3s, they can utilize the security and scalability provided by AVS without worrying about high costs.

  • As more DApps and L3s are deployed, GM Network will generate more revenue, which will be automatically distributed to GM stakers, ALT stakers, AVS operators, and ETH re-stakers.

  • Vertical L3 developers can flexibly define their own token models and mechanisms, combining innovation and capturing significant ecosystem value.

  • DApps and L3s will receive support and early ecosystem incentives from GM Network, with all L3s receiving modular support from AltLayer.

8.2 Dual Staking
  1. The security of GM Network is provided by AVS, where in addition to ETH, security can also be supported through the staking of EIGEN and ALT. With the issuance of GM tokens, in the future, GM will also join AVS to provide security for GM Network staking and simultaneously ensure the security for DApps and L3s built on GM Network.
  2. Stakers of GM, along with ALT stakers, will continuously receive more staking rewards from the ecosystem:
    • Airdrops.
    • Staking rewards.
    • More to come.


9.1 Stage
  1. GM Network has four stages: staking, mining, training, and transforming. These four stages together form the path for GM Network’s goal of becoming the largest communication and incentive layer for AI and IoT
    • Staking: Stake more Agent and Gear NFTs and devices, earn both Tokens and GN through Missions and Console, preparing for Stage 2.
    • Mining: Bind more Web2 and Web3 IoT devices through GM AI and mint more NFTs, pair with rich gameplay and continuously use devices to receive various token rewards and train your AI agent.
    • Training: Different types of IoT devices distributed globally generate massive amounts of data daily. This data can be used to train AI and allows developers and users to benefit from it.
    • Transforming: Massive IoT projects are deployed on GM Network, where AI transforms IoT into AIoT, creating more usage scenarios and generating more data, thus driving a positive growth flywheel for GM.
  2. To achieve the four stages, GM Network will advance development according to seasons, with each season averaging one month. Each season will introduce new content and feature updates centered around stage goals and seasonal objectives. As the seasons progress, GM Network will gradually move into more advanced stages.
9.2 Concept
  1. NFT: GM has two types of NFT assets, Agent and Gear.
    • Agent NFT represents the user’s AI Agent.
    • Gear NFT represents the AIoTs bound by the user.
  2. Rarity: GM’s NFTs come in five levels of rarity, which determine the amount of earnings and data acquisition. All NFTs can increase their rarity through the forging system.
    • Common
    • Uncommon
    • Rare
    • Epic
    • Legendary
  3. Level: GM has two types of levels: User Level and NFT Level. Levels can be increased through the upgrade system by consuming GN, and some levels may have specific requirements.
    • User Level increases the boost for all GN and GM and unlocks more slots.
    • NFT Level increases the boost for NFT rewards.
  4. Slot: Slots are one of the equipment systems in GM, and only NFTs equipped in slots can receive 100% GN and GM rewards.
    • Initially, each user has 1 Agent slot and 6 Gear slots.
    • More slots will be unlocked as the user level increases.
  5. Basic Console: Staking and equipping are core operations for NFTs. Users must stake and equip their NFTs to receive 100% GN and GM rewards.
    • Stake: All NFTs must be staked first to earn staking and mining rewards, and there is no absolute limit to staking.
    • Equip: Only staked NFTs can be equipped, and the maximum number that can be equipped equals the maximum number of slots. Equipped NFTs can earn 100% rewards.
    • Reduction: The rewards for staked but unequipped NFTs will be affected by a reduction factor, with different amounts having different reduction coefficients. For details, please refer to the GM Network official documentation.
  6. Advanced Console: GM also features advanced gameplay such as upgrading, forging, and synthesizing. These features will be gradually rolled out based on the product stages and the number of devices within the network.
    • Level Up: In GM Network, both user levels and NFT levels can be increased through the upgrade system. The higher the level, the more benefits are unlocked.
    • Forge: Through the forging system, the rarity of NFTs can be increased. The higher the rarity, the higher the base rewards.
    • Synthesize: Through the synthesis system, more new NFTs or valuable raw materials and fragments can be combined to more effectively enhance rewards.
9.3 Mechanism
  1. As more users bind more devices to join the GM Network, more incentives are generated and distributed to more users, thereby creating a positive flywheel effect.
    • Stage1: Incentivize users to learn about GM and bind more IoTs and NFTs through staking.
    • Stage2: Incentivize more IoT data to the GM Network through mining.
    • Stage3: Data generated by the GM ecosystem is provided to AI projects for training.
    • Stage4: Massive IoT deployments on GM, with an increasing number of AIs transforming IoT into AIoT through GM.
  2. The ultimate goal is for #GM to become the native currency between AI and IoT, used for communication and incentives.
9.4 GN & GM
  1. GN is a permanent utility point of GM Network, with various generation and consumption scenarios
  2. GM is the sole token of GM Network and can be exchanged with GN
  3. GM and GN are interchangeable, and there will always be abundant ways to earn and spend GM and GN within the GM Network.
  4. The overall design goal is to make GN inflationary and GM deflationary. At the same time, an exchange channel between GM and GN will be opened, with different exchange methods and ratios for different seasons.


10.1 Token
  1. Ticker: GM
  2. Total Supply: 10,000,000,000
  3. Network: Ethereum & GM Network
10.2 Utility
  1. GM,Engagement
    • GM Token will be used by users to purchase various products and services within the GM ecosystem (such as GM Launchpad and GM AI).
  2. GM,Incentivization
    • Projects within the GM ecosystem can receive GM token incentives by attracting more active users.
  3. GM,Staking
    • GM tokens, like other tokens within the AVS, can be used for dual staking to provide security and scalability to the ecosystem.
    • GM stakers will continuously receive more airdrops and incentives from ecosystem projects.
  4. GM,Governance
    • GM token holders can vote on governance decisions.


  1. GM aims to be the largest communication and incentive network connecting AI and IoT
  2. The demand for consumer AIoT comes from data and scenarios. To accelerate the emergence of more interesting IoT devices, GM Network has established GM Studio, an official incubator. We aim to provide one-stop incubation and in-depth support for all projects joining GM Studio, becoming a benchmark application for GM Network.
  3. We hope to see more consumer AIoT devices emerge, from health, voice, visual, graphics, and other perspectives, with innovative smart devices, MR, robots, electric vehicles, etc. All smart devices are fully incentivized by GM tokens and form a massive network effect, accelerating the integration and communication between the real and virtual worlds.
  4. Thanks to the outstanding work of AltLayer and EigenLayer, making GM Network possible.
  5. The entire GM Network mechanism is designed to ensure that users always find it fun and engaging. Users continuously generate data and value through their devices, and ultimately, through blockchain mechanisms, the benefits are returned to users, developers, and the GM Network.
  6. In terms of hardware, GM Network is continuously exploring the integration of AI innovations into consumer IoT devices. This includes ongoing exploration in several areas such as AIoT+Health, AIoT+Voice, AIoT+Visual, and AIoT+Lifestyle. As the seasons progress, we believe that more and more perceptible, interactive, usable, and profitable AIoT devices will emerge, firmly establishing GM Network as the leader in the consumer AIoT field.
  7. We believe that in the near future, #GM will become the native currency connecting AI and IoT. It will incentivize a massive number of existing IoT devices and Web3 DePIN devices, continuously generating large amounts of data to serve AI training. Ultimately, it will provide consumer scenarios for AI in various aspects such as health, voice, visual, and lifestyle.


[1] Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system.

[2] Vitalik Buterin. Ethereum white paper.

[3] EigenLayer: The Restaking Collective

[4] EIGEN: The Universal Intersubjective Work Token

[5] What is AltLayer?

[6] Cosmos Whitepaper