The emerging decentralized protocol platform io.net recently announced the completion of a $30 million Series A financing led by Hack VC, with participation from top investment companies including Multicoin Capital, 6th Man Ventures, and Delphi Digital. This financing action not only demonstrates the market potential of io.net, but also attracts widespread attention in the industry.

Additionally, since io.net launched its “Ignition” program, its number of GPU miners has surged from 26,000 to 51,000 in just ten days. This growth rate significantly reflects the attractiveness of its technology and the promotion of practical applications.

Meanwhile, io.net founder and CEO Ahmad Shadid has said that the IO token is expected to be launched on April 28, which will further expand its influence in the cryptocurrency market.

With the strengthening of capital and technical foundation, io.net is rapidly becoming the focus of attention in the field of blockchain technology. Subsequent content will further explore the technical details and market strategy of io.net.

Analyzing io.net’s decentralized computing revolution and predicting the future trend of AI computing

Before discussing io.net's business model, it is key to understand the application of decentralized computing power in AI computing. AI technology has evolved from simple CPU-based models to complex deep learning and large models that rely on GPUs and TPUs, and the demand for computing resources has increased dramatically in this process.

From decision trees to giants: the evolution of machine learning computing requirements

1.1980s-2000s: Machine learning relies on simple algorithms such as decision trees and SVMs, and the computing requirements can be met by personal computers.

2. After 2006: With the rise of deep learning, the demand for GPUs increased, especially when processing large data sets.

3.2018 to present: Large models such as BERT and GPT have further increased the demand for high-performance computing clusters.

io.net: Reshaping the future of computing, a new era of decentralized GPU networks

io.net significantly reduces costs and improves computing efficiency by building a decentralized GPU computing network and utilizing globally distributed idle GPU resources.

1. Cost efficiency:

Compared with traditional centralized computing centers, io.net's decentralized model reduces the need for large-scale hardware procurement and maintenance, significantly reducing initial investment and operating costs.

2. Technical implementation:

Cluster computing: Using Ray and Kubernetes technologies, io.net optimizes resource management and the allocation of computing tasks, improving execution efficiency.

Privacy and security: The security and privacy protection of data transmission are enhanced through mesh VPN and data flow obfuscation technology.

3. Market positioning:

io.net's service costs are 90% lower than those of traditional cloud service providers and can be deployed within seconds. This rapid response capability meets the market's high demand for efficiency.

The elastic resource combination and instant deployment provided give io.net a significant competitive advantage in the fields of AI and machine learning, especially in the processing of complex tasks that require large amounts of computing resources.

Through decentralized and efficient computing resource aggregation, io.net not only optimizes costs and resource utilization, but also improves service security through innovative privacy protection technologies. These competitive advantages indicate io.net's important position and development potential in the global AI computing power supply market.

Revealing the transformation of AI computing mode: io.net’s breakthrough and advantages in the field of decentralized computing power

In the latest episode of the MindChats podcast, Ahmad Shadid, founder and CTO of io.net, discussed in depth the fundamental differences between centralized and decentralized AI and the advantages of each. The discussion revealed the potential of decentralized AI in optimizing the allocation of computing resources, reducing costs, and improving system scalability and flexibility.

From Centralization to Decentralization: Data Storage Innovation for AI Systems

Centralized AI systems rely on large data centers to centrally process and store data. Although this approach speeds up data processing and simplifies data management, it also has obvious disadvantages:

High cost: Building and maintaining data centers requires huge amounts of capital.

Limited scalability: When demand grows, expanding existing systems is complex and expensive.

Security risks: Centralized data storage increases the risk of data leakage.

Unlocking the future: Three major advantages of decentralized AI

Decentralized AI processes and stores data through a distributed network, overcoming many limitations of centralized systems:

Cost efficiency: Reduced reliance on large physical facilities and reduced maintenance costs.

Powerful scalability: Easily expand the system by adding more nodes without large-scale upfront investment.

Data security: Decentralized storage and encryption technologies reduce the risk of centralized attacks.

Decrypting io.net: How to optimize AI computing needs with a decentralized model

Shadid explained how io.net leverages a decentralized model to optimize AI computing needs:

Resource aggregation: Integrate idle GPU resources around the world to form a powerful distributed computing network.

Dynamic resource allocation: Dynamically adjust resources according to demand to improve computing efficiency and reduce energy consumption.

Economic incentives: Introduce Web3 incentive mechanism to encourage individuals and enterprises to share computing resources and further reduce costs.

Privacy protection: Use advanced encryption and privacy technologies to ensure data security.

This discussion not only clarified the differences between centralized and decentralized AI, but also demonstrated how io.net solves the challenges of cost, scalability, and data security through its decentralized platform. io.net's practice shows that decentralized computing is not only feasible, but also superior to traditional models in key aspects, especially in improving cost efficiency and system flexibility.

io.net promotes decentralized computing power innovation, and its market and economic model outlook attracts attention

In the io.net ecosystem, the native cryptocurrency IO Coin and its protocol token are crucial. It not only simplifies the payment process for AI startups and developers, but also ensures that computing power providers, especially GPU resource providers, can obtain fair economic returns. The introduction of IO Coin makes deployment and computing costs more transparent, while incentivizing participants to continue to contribute their idle computing resources.

io.net pays special attention to the construction of its economic model to ensure that transactions within the ecosystem are not only fair but also efficient. The network uses IOSD Credits pegged to the US dollar to settle fees, and each model deployment and computing task is paid for in tiny transactions through IO coins. For GPU suppliers, whether they rent GPUs directly or participate in network model inference, IO coins ensure that they get the rewards they deserve.

In addition, io.net also plans to introduce a fully decentralized pricing scheme, which will price miner hardware through an open and transparent benchmarking tool, similar to speedtest.net, to ensure a fair and transparent market environment. This pricing mechanism will take into account multiple factors, including hardware performance, Internet bandwidth, and regional differences, to adapt to market demand and resource availability.

Although io.net has established a huge GPU network on the supply side, far exceeding other competitors such as Akash Network, the growth on the demand side is still in its early stages, with low chip task load. However, with the cultivation of the market and the continuous optimization of product experience, it is expected that demand will gradually increase.

In general, io.net has provided strong support to AI startups and engineers through its innovative decentralized computing power platform and economic incentive mechanism, promoting the development and application of technology. Looking ahead, as technology matures and market activities increase, io.net is expected to play a more important role in the global AI computing power supply market.