AI Revolution: How Bittensor is Reshaping Collective Intelligence Networks

The rapid development of artificial intelligence technology is leading us into a whole new data-driven era. Breakthroughs in fields such as deep learning and natural language processing have made AI applications ubiquitous. The launch of ChatGPT in 2022 ignited the AI industry, followed by a series of innovative AI tools, such as text-to-video and automated office solutions. The widespread application of AI technology has also been put on the agenda, with the market value of the industry continuing to rise, expected to reach $185 billion by 2030.

However, the AI industry is currently dominated by a few tech giants, which brings a series of challenges such as data centralization and uneven distribution of computing resources. At the same time, the decentralized concept of Web3 offers new possibilities for addressing these issues. Within the framework of Web3's distributed network, there is hope to reshape the current landscape of AI development.

As the AI industry thrives, a number of high-quality Web3+AI projects have emerged. Among them, Bittensor has identified a critical gap - it has built an AI algorithm platform with an inherent filtering mechanism through blockchain competition and incentive mechanisms, aiming to retain the highest quality AI projects.

Innovation and Development of Bittensor

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

• Decentralization: Operating on a distributed computer network controlled by multiple parties to solve the problem of data centralization.
• Fair incentive mechanism: The rewards for subnets and nodes are proportional to their contributions.
• Provide machine learning resources: Offer services to individuals in need of machine learning computing resources.
• Diversified digital goods market: Various forms of data can be traded.

Unlike many high-valued VC projects, Bittensor is more like a fair, interesting, and meaningful geek project. Its development history is as follows:

• 2021: Created by a group of technical experts, built on the Substrate framework to develop the blockchain.
• 2022: Launched the Alpha version network, validating the feasibility of decentralized AI. Introduced Yuma consensus.
• 2023: Release of Beta version, introduction of TAO token economic model.
• 2024: Utilize DHT technology to improve data storage and retrieval efficiency, expand subnets and digital goods markets.

The total supply of Bittensor's token TAO is 21 million, halving every four years. It has been fairly launched with no pre-mining. Currently, a block is generated every 12 seconds, with each block rewarding 1 TAO. Rewards are distributed to each subnet based on contribution, and then redistributed to subnet owners, validators, and miners.

Currently, the total number of accounts on the Bittensor network exceeds 100,000, with over 80,000 non-zero accounts. In the past year, TAO has increased by several dozen times, with a current market value of $2.278 billion and a coin price of $321.

Subnet Architecture Implementation

The Bittensor protocol is a decentralized machine learning protocol that supports network participants in exchanging machine learning capabilities and predictions. Subnets are the most critical components within the Bittensor network.

Subnets can be seen as independently running codes that establish specific user incentives and functional mechanisms. Currently, there are 45 subnets aside from the root subnet, and this number is expected to increase to 64 between May and July 2024. The subnets include three roles: owners, miners, and validators.

Subnet emission is the reward distribution mechanism in the Bittensor network, typically 18% is allocated to owners, 41% to validators, and 41% to miners. A subnet has 256 slots, of which 64 are for validators and 192 are for miners. The performance of validators and miners determines their status and rewards in the network.

After the subnet registration, there is a 7-day immunity period, with an initial registration fee of 100 TAO. The registration fee will double for subsequent registrations. When all subnet positions are filled, the subnet with the lowest issuance that is not in the immunity period will be replaced by a new subnet. Therefore, subnets need to continuously increase their staking amount and efficiency to avoid being eliminated.

Innovative Consensus and Proof Mechanisms

The Bittensor network employs a variety of consensus and proof mechanisms:

• PoI( Proof of Intelligence ) mechanism: Miners prove their contribution by completing smart computing tasks.
• Yuma Consensus: Validators score based on task completion and input into the consensus algorithm. Validators with higher stakes have greater scoring weight.
• Data Unknowability Principle: Ensuring the privacy and security of data processing.
• MOE mechanism: integrates multiple expert-level sub-models to work collaboratively and improve overall performance.

Main Subnet Projects

Currently, Bittensor has 45 registered subnets, 40 of which are named. The top three subnets are:

1. Vision Subnet 19: Focused on decentralized image generation and inference.
2. 18th Cortex.t subnet: Build a cutting-edge AI platform, providing text and image services.
3. Subnet 1: A decentralized network for text generation.

Other subnets also include data processing large models, trading AI models, etc. Overall, the successful operation of subnets can yield considerable returns, but newly registered nodes require high-performance equipment and optimized algorithms to survive in the competition.

Future Outlook

• AI+Web3 will continue to be the focus of the market.
• The Bittensor project architecture combines technical and market support, with huge potential for future development.
• The subnet architecture lowers the barrier for AI teams to migrate to decentralized networks.
• It is necessary to pay attention to the risks that may arise from the increase in the number of subnets, such as the increase in miscellaneous projects and the decline in the revenue of individual subnets.

Bittensor provides new possibilities for the development of decentralized AI through its innovative subnet architecture and consensus mechanism. In the future, it is expected to play an important role in reshaping the AI industry landscape, but it also faces some challenges and uncertainties.