🔔 Preface:

io.net is a decentralized computing network built on the Solana blockchain, focusing on solving computing challenges in the fields of AI and machine learning. It is an important member of the Depin and AI fields.

💥 Summary:

The latest news shows that io.net announced the launch of block rewards on June 26, providing rewards to supplier accounts that provide GPUs or CPUs on the IOG network.

Rewards are distributed hourly in the form of IO tokens, with 80% allocated to GPU and 20% to CPU.

1️⃣ Project Overview

io.net provides an open platform that allows global users to instantly access GPU and CPU resources without permission. These resources come from independent data centers and cryptocurrency miners, mainly using idle graphics cards for distributed computing power supply.

Currently, io.net has gathered more than 1 million GPU resources to meet the growing needs of AI computing.

2️⃣ Technical architecture and functions

On the technical level, io.net is built on the machine learning framework ray.io and supports a variety of AI application scenarios, including reinforcement learning, deep learning, and model optimization. Anyone can join the computing network as a worker or developer without additional permission.

The pricing of computing power is adjusted in real time based on market demand and resource supply to ensure efficient use of resources.

3️⃣ Native Token IO

IO tokens are the core of the io.net ecosystem, used as a medium of exchange and incentive mechanism. Users holding IO tokens can reduce or waive transaction fees in computing power transactions, and support the stable operation of the network and node activities by staking IO tokens.

Currently, the IO token market cap is $351 million, the fully diluted market cap is $2.955 billion, the total supply is 800 million IO, and the circulation quantity is 95 million IO, demonstrating its importance and potential in the cryptocurrency market.

4️⃣ Product composition

The architecture of io.net includes key components such as IO network, IO engine and IO Element. The IO network adopts a mesh VPN architecture to ensure ultra-low latency node-to-node communication, thereby efficiently sharing and processing GPU resources. The IO engine is a programmable computing layer built on this basis, supporting AI computing tasks such as batch reasoning, parallel training and hyperparameter adjustment.

5️⃣ io.net's three major products

IO Cloud: Deploy and manage decentralized GPU clusters, providing flexible solutions for AI and Python applications.

IO Worker: A service that provides real-time insights into computing devices, allowing users to monitor and operate devices.

IO Explorer: Provides comprehensive network statistics and visualization charts to help users easily monitor and analyze io.net network activity and reward transactions.

6️⃣ Core functions:

Batch Inference and Model Serving: Supports exporting the architecture and weights of trained models to shared object storage and executing inference tasks in parallel over a distributed GPU network.

Parallel training: Distributed computing libraries enable simultaneous training on multiple GPU devices, overcoming the memory limitations of a single device and the bottleneck of sequential processing.

Parallel hyperparameter tuning: Use the distributed computing library of advanced hyperparameter tuning to achieve parallel hyperparameter optimization and scheduling to obtain the best model training results.

Reinforcement Learning: Supports production-grade, highly distributed reinforcement learning workloads and provides easy-to-use API interfaces to help developers quickly deploy and manage reinforcement learning models.

7️⃣ Future Outlook:

With the launch of GPT-4 LLM (Language Model) by OpenAI and the rise of various AI text-to-image models, the number of applications based on mature AI technologies is increasing, and the demand for computing resources such as GPUs is rising sharply.

At the same time, according to Statista, the AI ​​market size has grown from $134.8 billion in 2022 to $241.8 billion in 2023, and is expected to reach $738.7 billion by 2030. The value of the cloud service market has also increased by about 14% due to the rapid growth in the AI ​​market's demand for GPU computing power.

🎯 Summary:

Io.net stated that its goal is to build the "GPU Internet" and create the world's largest AI computing DePIN to solve the GPU computing power shortage caused by the AI ​​boom. From this point of view, the project has a bright future and a strong background. This article does not constitute any investment advice! Investors need to carefully evaluate risks and market performance! #DYOR

🤝 Thank you everyone！