io.net
The first 500 million tokens will be distributed according to the rules
Community: 250,000,000 IO, accounting for 50.00% of the total supply;
R&D and ecology: 80,000,000 IO, accounting for 16.00% of the total supply; Seed investors: 62,000,000 IO, accounting for 12.50% of the total supply;
A round investors: 51,000,000 IO, accounting for 10.20% of the total supply;
Core contributors: 56,500,000 IO, accounting for 11.30% of the total supply.
io.net has advantages over other projects.
In essence, the decentralized computing power projects that have emerged now belong to the category of Depin, and the Depin project on Solana has experienced a hot market last year, and the three concepts of AI, Solana, and Depin are superimposed together.
In addition to the good track selection, io.net also had in-depth cooperation with Render Network in the early days. At that time, RNDR was in an upward cycle, rising from less than $4 to $13 in two months.
The AI track has been selected for everyone. AI is a must-have. Now Nvidia has surpassed Apple's market value.
Moreover, Apple is no longer obsessed with power supply, but has transformed its layout to AI. AI computing power is still a blue ocean, and the potential of tokens related to AI token computing power is inevitable.
Io.net's biggest advantage is decentralized GPU
io.net's decentralized resource aggregation is one of its core functions, which enables the platform to use decentralized GPU resources around the world to provide necessary computing support for AI and machine learning tasks. The goal of this resource aggregation strategy is to optimize resource usage, reduce costs, and provide wider accessibility.
io.net's dynamic resource allocation and scheduling is one of the core functions of the platform. The key lies in efficiently managing and optimizing the use of computing resources to meet users' diverse computing needs. This system ensures that computing tasks can be executed on the most appropriate resources in an intelligent and automated way, while maximizing resource utilization and performance.
