AI Revolution: How Bittensor Reshapes Collective Intelligence Networks

Explosion of the AI Industry

The rapid development of artificial intelligence technology is leading us into a data-driven new era. Breakthroughs in fields such as deep learning and natural language processing have made AI applications ubiquitous. The emergence of ChatGPT in 2022 set off a boom in the entire AI industry, followed by a surge of various AI tools, such as text-to-video and automated office applications. The widespread application of AI technology has also been put on the agenda. It is expected that by 2030, the market value of the AI industry will reach 185 billion dollars.

However, the AI industry is currently dominated by a few tech giants, which brings challenges such as data centralization and uneven distribution of computing resources. The decentralized philosophy of Web3 offers new possibilities for addressing these issues and is expected to reshape the landscape of AI development.

In this wave of AI, a number of high-quality Web3+AI projects have emerged. Among them, Bittensor has seized a key opportunity - by leveraging the competitive and incentive mechanisms of blockchain, it has built an AI algorithm platform with its own filtering competition mechanism to retain the highest quality AI projects.

Overview of the Bittensor Project

Bittensor is a decentralized incentivized machine learning network and digital goods marketplace. It has the following features:

• Decentralized: Operates on thousands of distributed computer networks, solving the problem of data centralization.
• Fair incentive mechanism: Network rewards are proportional to contributions
• Provide machine learning resources: Offer services to individuals who need computational resources.
• Diversified digital goods market: Various forms of data can be traded.

The development process of Bittensor is relatively pragmatic:

• 2021: Created by technical experts using the Substrate framework
• 2022: Released Alpha version, verified feasibility; introduced Yuma consensus.
• 2023: Release of the Beta version, introduction of the token economic model TAO
• 2024: Adopt DHT technology to improve efficiency, expand subnetworks and digital goods market

The total supply of the Bittensor token TAO is 21 million coins, with a halving every four years. Currently, a block is generated every 12 seconds, with each block rewarding 1 TAO. These rewards are distributed to various subnets and their participants based on contribution.

TAO can be used to purchase network resources, data, and AI models, and it serves as a certificate for community governance. Currently, the total number of Bittensor network accounts exceeds 100,000, with non-zero accounts reaching 80,000. The price of the TAO token has increased several times over the past year, with a current market value of approximately $2.278 billion.

Subnet Architecture

The Bittensor network consists of multiple subnets, each containing validator and miner nodes. The subnets adopt a survival of the fittest mechanism, where poorly performing subnets and nodes will be eliminated.

Subnetwork roles include:

• Subnet owner: provides the underlying code and sets up the incentive mechanism
• Miner: Run servers to provide computing power
• Validator: Assess miners' contributions and earn staking rewards

The subnet distribution of rewards ( is generally allocated to owners, validators, and miners in the proportions of 18%, 41%, and 41%, respectively. The subnet consists of 256 slots, of which 64 are allocated to validators and 192 to miners.

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After registering a new subnet, there is a 7-day immunity period. The registration fee starts from 100 TAO and will double with repeated registrations. When the subnet positions are full, the subnet with the lowest emissions and not in the immunity period will be replaced by the new subnet. Therefore, subnets need to continuously increase their staking amount and efficiency to avoid being eliminated.

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Consensus Mechanism

The Bittensor network adopts multiple consensus mechanisms:

1. Proof of Intelligence ) PoI (: Miners prove their contribution by completing intelligent computing tasks.

2. Yuma Consensus:

   • Validators score based on task completion.
   • Validators with high staking volumes have a greater weight in scoring.
   • Filter out deviating results and allocate rewards based on comprehensive scores.
   • Follow the principle of data unawareness to protect privacy

3. MOE mechanism:

   • Integrate multiple expert sub-models
   • Different sub-models work collaboratively
   • Validators can score and rank expert models

These mechanisms collectively ensure the security of the network, data quality, and efficient use of resources.

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Main Subnet Projects

Currently, Bittensor has 45 registered subnets, 40 of which have been named. The main subnets include:

• Vision 19: Decentralized Image Generation and Inference
• Cortex.t 18: Provides text and image API services
• Text Generation #1: Bittensor's first subnet project

Other types of subnet projects include data processing, trading AI, etc. Subnet profits are considerable, but competition is fierce, requiring continuous optimization to avoid being eliminated.

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Development Prospects

1. Web3+AI will long be the market focus.

2. Bittensor combines technological innovation with market recognition

3. Subnet architecture lowers the threshold for AI project migration

4. The competition mechanism drives continuous optimization of projects.

5. Risk:

   • The increase in the number of subnets may dilute profits
   • Beware of the influx of low-quality projects

Overall, Bittensor provides new possibilities for the integration of AI and Web3 through innovative incentive and competitive mechanisms, and it is worth keeping an eye on its development.

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