1、Project Overview

1.1 Business Summary

io.net is a decentralized GPU network designed to provide computing for machine learning (ML). It leverages over one million GPUs assembled from independent data centers, cryptocurrency miners, and projects like Filecoin or Render to access computational power.Its goal is to combine one million GPUs into the Decentralized Physical Infrastructure Network (DePIN), creating an enterprise-grade, decentralized distributed computing network. By aggregating global idle network computing resources (primarily GPUs at present), it aims to offer artificial intelligence engineers lower-cost, more accessible, and more flexible network computing resource services.For users, it serves as a marketplace for decentralized global idle GPU resources, allowing artificial intelligence engineers or teams to customize and purchase the GPU computing services they need according to their requirements.

1.2 Team Background

Ahmad Shadid is the founder and CEO, previously an engineer at WhalesTrader's quantitative trading system.

Garrison Yang serves as the Chief Strategy Officer and Chief Marketing Officer, previously holding roles as Vice President of Growth and Strategy at Ava Labs.

Tory Green operates as the Chief Operating Officer, bringing prior experience as COO at Hum Capital and Director of Corporate Development and Strategy at Fox Mobile Group.

Angela Yi, Vice President of Business Development, holds a degree from Harvard University and is responsible for strategizing and executing key initiatives in sales, partnerships, and vendor management.

In 2020, Ahmad Shadid encountered challenges with high GPU service fees while building a GPU computing network for the machine learning quantitative trading firm Dark Tick. The substantial demand for computing power and the associated high costs led them to explore decentralized distributed computing resources. Their solution gained attention at the Austin Solana Hacker House, leading to the establishment and expansion of io.net.

1.3 Product/Technology

The problems faced by market users:

Limited availability: Accessing hardware through cloud services like AWS, GCP, or Azure typically takes several weeks, and popular GPU models are often unavailable.

Limited choices: Users have little flexibility in terms of GPU hardware, location, security level, latency, etc.

High costs: Obtaining high-quality GPUs is very expensive, costing hundreds of thousands of dollars per month for training and inference.

Solution:

By aggregating underutilized GPU resources (such as independent data centers, crypto miners, and encrypted projects like Filecoin, Render, etc.) and integrating them into DePIN, engineers can access a large amount of computational power within the system. It allows ML teams to build inference and model-serving workflows across distributed GPU networks and leverage distributed computing libraries to orchestrate and batch training jobs, enabling parallelization across many distributed devices using data and model parallelism.

Additionally, io.net utilizes distributed computing libraries with advanced hyperparameter tuning to examine optimal results, optimize scheduling, and simply specify search patterns. It also employs open-source reinforcement learning libraries that support production-grade, highly distributed RL (reinforcement learning) workloads as well as simple APIs.

Product Components:

IO Cloud, designed to deploy and manage decentralized GPU clusters on-demand, seamlessly integrated with IO-SDK, offering a comprehensive solution for scaling AI and Python applications. It provides unlimited computational power while simplifying the deployment and management of GPU/CPU resources.

IO Worker, offers users a comprehensive and user-friendly interface to efficiently manage their GPU node operations through an intuitive web application. The product scope includes features related to user account management, compute activity monitoring, real-time data display, temperature and power consumption tracking, installation assistance, wallet management, security measures, and profitability calculations.

IO Explorer, primarily provides users with comprehensive statistical data and visualizations of various aspects of the GPU cloud, allowing users to easily monitor, analyze, and understand the complex details of the io.net network in real-time. It offers comprehensive visibility into network activities, key statistics, data points, and reward transactions.

Product Features:

Decentralized Computing Network: io.net adopts a decentralized computing model, distributing computational resources globally, thereby improving computational efficiency and stability.

Low-Cost Access: Compared to traditional centralized services, io.net Cloud offers lower access costs, enabling more machine learning engineers and researchers to access computational resources.

Distributed Cloud Clusters: The platform provides a distributed cloud cluster where users can select appropriate computational resources based on their needs and distribute tasks across different nodes for processing.

Support for Machine Learning Tasks: io.net Cloud focuses on providing computational resources for machine learning engineers, enabling them to more easily perform tasks such as model training and data processing.

1.4 Development Roadmap

According to the information disclosed in the io.net whitepaper, the project's product roadmap is as follows:January to April 2024: Full launch of V1.0, focusing on decentralizing theio.netecosystem to enable self-hosting and self-replication capabilities. 【1】

1.5 Funding Information

According to public news sources, on March 5, 2024, io.net announced the completion of a $30 million Series A funding round. Hack VC led the investment, with participation from Multicoin Capital, 6th Man Ventures, M13, Delphi Digital, Solana Labs, Aptos Labs, Foresight Ventures, Longhash, SevenX, ArkStream, Animoca Brands, Continue Capital, MH Ventures, Sandbox Games, and others.It's worth noting that after this round of funding,io.nethas an overall valuation of $1 billion.

2、Market Data

2.1 Official Website

Website Data from January 2024 to March 2024 indicates a total of 5.212 million visits, with an average monthly visit of 1.737 million and a low bounce rate of 18.61%. User visits are evenly distributed across regions, and direct and search visits account for over 80%, suggesting a low proportion of dirty data in the user data. They have a basic understanding of io.net and are willing to further explore and interact on the website.

2.2 Social Media and Community

3、Competitive Analysis

3.1 Competitive Landscape

The core business of io.net revolves around decentralized AI computing, with its main competitors being traditional cloud service providers represented by AWS, Google Cloud, and Microsoft Intelligent Cloud (Azure). According to the "2022-2023 Global Computing Power Index Assessment Report" jointly compiled by International Data Corporation (IDC), CCID Consulting, and the Global Industry Research Institute of Tsinghua University, the global artificial intelligence computing market is expected to grow from $19.5 billion in 2022 to $34.66 billion in 2026.【2】

In comparison to the sales revenue of major global cloud computing companies: In 2023, AWS cloud service sales revenue was $9.08 billion, Google Cloud sales revenue was $3.37 billion, and Microsoft Intelligent Cloud business sales revenue was $9.68 billion.【3】The combined market share of these three accounts for about 66% globally, and all three giant companies have market values exceeding one trillion dollars.

In stark contrast to the high revenues of cloud service providers, optimizing GPU utilization has become a focal point. According to a survey on AI infrastructure, the majority of GPU resources are underutilized — around 53% of respondents believe that 51-70% of GPU resources are underutilized, while 25% estimate utilization rates at 85%, and only 7% believe utilization exceeds 85%. For io.net, the significant demand for cloud computing and the issue of underutilized GPU resources represent market opportunities.

3.2 Competitive Advantages

io.net's greatest competitive advantage lies in its ecological position or first-mover advantage. According to official data, io.net currently boasts a GPU cluster exceeding 40K, over 5600 CPU units, and more than 69K Worker Nodes. It can deploy 10,000 GPUs in under 90 seconds and offers prices 90% cheaper than competitors, with a valuation of $1 billion. Not only does io.net provide customers with instant, license-free services at 1-2% of the cost compared to centralized cloud service providers, but it also offers additional incentives to compute providers through the upcoming IO token, helping to achieve the goal of connecting 1 million GPUs.

Furthermore, compared to other DePIN computing projects, io.net focuses on GPU computing power, with its GPU network scale exceeding similar projects by over 100 times. io.net is also the first in the blockchain industry to integrate cutting-edge ML technology stacks (such as Ray clusters, Kubernetes clusters, and giant clusters) into the GPU DePIN project on a large scale, placing it at the forefront not only in terms of GPU quantity but also in technical application and model training capabilities.

As io.net continues to develop, if it can increase its GPU capacity to compete with centralized cloud service providers with 500,000 concurrent GPUs, it will be able to offer services similar to Web 2 at a lower cost. Moreover, by establishing close cooperation with major DePIN and AI players (including Render Network, Filecoin, Solana, Ritual, etc.), io.net has the opportunity to gradually establish itself as a leader and settlement layer in the decentralized GPU network space, bringing vitality to the entire Web 3xAI ecosystem.

3.3 Risks and Challenges

io.net is an emerging computing resource aggregation and distribution platform deeply integrated with Web3, and its business overlaps significantly with traditional cloud service providers. This poses risks and obstacles both technically and in the market positioning.

There are technical security risks associated with io.net being a nascent platform. It has not undergone extensive application testing or demonstrated the ability to prevent and respond to malicious attacks. Handling massive amounts of computational resources for access, distribution, and management lacks corresponding experience or practical validation, making it susceptible to common technical issues such as compatibility, robustness, and security. Moreover, any issues that arise could be fatal for io.net, as customers prioritize their security and stability and are unwilling to foot the bill for such incidents.

Market expansion is progressing slowly for io.net. It directly competes with traditional cloud service providers like AWS, Google Cloud, and Alicloud, and even with second-tier or third-tier service providers. Despite offering more favorable costs, io.net's service and market system targeting B-class customers are just beginning, which differs significantly from the existing market operations in the Web3 industry. Therefore, its progress in market expansion is not ideal at the moment, which could directly impact its project valuation and token market performance.

Latest Security Incident
On April 25th, io.net Founder and CEO Ahmad Shadid tweeted about a security incident involving the io.net metadata API. Attackers exploited the accessible mapping from user IDs to device IDs, resulting in unauthorized metadata updates. While this vulnerability did not affect GPU access, it did impact the frontend display of metadata to users. io.net does not collect any Personally Identifiable Information (PII) and does not disclose sensitive user or device data.
Shadid stated that the io.net system is designed to self-heal, continuously updating each device to help restore any erroneously changed metadata. In response to this incident, io.net expedited the deployment of user-level identity authentication integration with OKTA, which will be completed within the next 6 hours. Additionally, io.net introduced Auth0 Token for user authentication to prevent unauthorized metadata changes. During the database recovery period, users will temporarily be unable to log in. All normal uptime records remain unaffected, and this will not impact supplier compute rewards.

4、Token Valuation

4.1 Token Model

io.net's token economic model will have an initial supply of 500 million IO tokens at genesis, divided into five categories: Seed Investors (12.5%), A Round Investors (10.2%), Core Contributors (11.3%), Research and Ecosystem (16%), and Community (50%). As IO issuance incentivizes network growth and adoption, it will grow to a fixed maximum supply of 800 million IO tokens over 20 years.

The reward model adopts a deflationary approach, starting at 8% in the first year and decreasing by 1.02% per month (approximately 12% per year) until reaching the 800 million IO limit. With reward issuance, the shares of early supporters and core contributors will continue to decrease, and after all reward allocations are completed, the community's share will increase to 50%.【4】

Its token utility includes providing incentives for IO Workers, rewarding AI and ML deployment teams for continuous network usage, balancing demand and supply, pricing IO Worker compute units, and community governance.

To avoid payment issues due to IO token price fluctuations, io.net has developed the stablecoin IOSD, pegged to the US dollar. 1 IOSD is always equal to 1 USD. IOSD can only be obtained by destroying IO tokens. Additionally, io.net is considering mechanisms to improve network functionality. For example, IO Workers may be allowed to increase their likelihood of being leased by pledging native assets. In this case, the more assets they commit, the greater their chances of being selected. Furthermore, AI engineers pledging native assets will have priority access to high-demand GPUs.

4.2 Token Mechanism

The IO token mechanism primarily serves two major groups: demand-side and supply-side. For demand-side participants, each computational job is priced in USD, and payment is held by the network until the job is completed. Once node operators configure their reward shares in both USD and tokens, the USD portion is directly allocated to the node operators, while the portion allocated to tokens is used to burn IO tokens. Subsequently, all IO tokens minted as computational rewards during this period are distributed to users based on the USD value of their coupon tokens (compute points).

For supply-side participants, rewards include availability rewards and computational rewards. Computational rewards are for jobs submitted to the network, where users can choose their time preferences for "deployment duration in hours" and receive cost estimates from the io.net pricing oracle. Availability rewards, on the other hand, involve the network randomly submitting small test jobs to assess which nodes run regularly and are capable of accepting jobs from the demand side.

It's worth noting that both supply-side and demand-side participants have reputation systems in place, accumulating scores based on computational performance and network participation to earn rewards or incentives.

Additionally, io.net has established ecosystem growth mechanisms, including staking, referral rewards, and network fees. IO token holders can choose to stake their tokens to node operators or users. Once staked, stakers receive 1-3% of all rewards earned by participants. Users can also invite new network participants and share a portion of the future earnings of these new participants. Network fees are set at 5%.

4.3 Valuation Analysis

As we currently lack precise revenue data for projects within the same industry, we cannot accurately assess valuation. Therefore, our evaluation primarily relies on comparisons with Render, another AI+DePIN project, for reference.

As shown in the figure, Render Network is currently the leading project in the AI+Web3 sector for decentralized GPU rendering solutions, with a total GPU resource of 11,946 and a current market valuation of $3 billion (fully diluted valuation of $5 billion). On the other hand, io.net has a total GPU resource of 461,772, which is 38 times that of Render. Currently valued at $1 billion, io.net is comparable to Render in terms of core GPU capabilities. Therefore, based on the core comparison dimension of GPU supply, io.net's market valuation is likely to exceed Render's, or at least be on par with it.

Render Network had 9,420,335 Frames Rendered and a GMV of $2,457,134 in 2022. Currently, Render Network's Frames Rendered is 31,643,819, which suggests that the total GMV is approximately $8,253,751.

In comparison, io.net had a GMV of $400,000 over four months. Assuming io.net maintains this average growth rate, its GMV for 12 months would be $1,200,000. To reach the current GMV of Render Network, io.net would need to grow approximately 6.8 times. Considering io.net's current valuation of $1 billion, and integrating the above analysis, io.net's market valuation could potentially exceed $5 billion during a bullish market cycle.

5、Summary

The emergence of io.net has filled a void in the decentralized computing field, offering users a novel and promising way of computation. With the continuous development of fields like artificial intelligence and machine learning, the demand for computational resources is steadily increasing, giving io.net high market potential and value.

On the other hand, despite the market assigning io.net a high valuation of $1 billion, its products have not undergone market validation, posing uncertainties in terms of technology. Additionally, its ability to effectively match supply and demand is a key variable determining whether it can reach new market valuation highs. Currently, while io.net's platform has shown initial achievements on the supply side, it has yet to fully leverage demand, resulting in underutilization of its overall GPU resources. Effectively mobilizing demand for GPU resources is a challenge the team must address.

If io.net can swiftly onboard demand from the market side without encountering major risks or technical issues during operations, given its AI+DePIN business attributes, its overall business will kickstart a growth cycle, making it one of the most prominent projects in the Web3 domain. This also implies that io.net will be a highly attractive investment target. Let's continue to monitor and carefully verify its progress.

Reference Resources
【1】https://www.coincarp.com/fundraising/ionet-series-a/

【2】https://medium.com/ybbcapital/promising-sector-preview-the-decentralized-computing-power-market-part-i-368c0621021a

【3】https://www.crn.com/news/cloud/2024/aws-vs-microsoft-vs-google-cloud-earnings-q4-2023-face-off?page=2

【4】https://www.chaincatcher.com/article/2120813

Note: All of the above opinions are not investment advice. If there are any inappropriate points, please feel free to leave a message to correct them.

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