This week, OpenAI launched its latest model GPT-4o, which once again shocked everyone with its powerful capabilities. The iteration speed of AI is far beyond the imagination of most people. It is conceivable that in the near future, more and more industry rules will be rewritten and subverted by AI.
But one fact is chilling - current AI is extremely centralized.
Current AI development is mainly dominated by a few technology giants such as OpenAI and Google. These companies have huge data resources and computing power, and high R&D investment, so they dominate the development of AI technology. However, every company only wants its own model to make money for itself, so these models are basically closed training, and no one wants to share their models and data with competitors.
In this closed, centralized AI system, user data is difficult to be fully protected, increasing the risk of data leakage and abuse. In addition, the existing AI models lack transparency in the decision-making process, which easily leads to algorithmic bias and unfairness.
The development and maintenance of high-performance AI models requires huge computing resources and financial investment, which is a major obstacle for many small businesses and research institutions. So, how can AI be made more open and decentralized?
Bittensor - Decentralizing AI Models
So Bittensor appeared, hoping to solve these problems in the existing AI model through decentralization.
Bittensor is a decentralized machine learning platform that hopes to create a global, open AI market. This platform allows users to share AI models in a decentralized network to promote innovation and knowledge sharing.
Bittensor uses blockchain technology to ensure the security and transparency of the network, and encourages participants to contribute high-quality models and data through incentive mechanisms. It allows anyone to contribute computing resources and data to participate in the development and training of AI models. This will not only break the monopoly of large technology companies, but also improve data privacy and security and promote fair distribution of resources.
Bittensor's architecture and working principle
So how does Bittensor do this?
Bittensor's core architecture consists of the following parts:
Subnets: The Bittensor network is divided into multiple subnets, which are incentive-based competitive markets, each focusing on different AI tasks. Subnets can compete and collaborate with each other to promote the overall development of the network. Each subnet can create a custom incentive mechanism for its own competition or join existing competitions in the Bittensor ecosystem. Subnets are the core of the Bittensor ecosystem.
Subtensor: Subtensor is the core blockchain of the Bittensor network and is responsible for recording all transactions and model contributions. Subtensor ensures transparency and security of the network and manages the incentive mechanism.
Bittensor API: The Bittensor API is responsible for connecting all the basic elements of the above two components and connecting subnets and blockchains.
In simple terms, Subtensor is the central blockchain of the Bittensor network, responsible for coordinating and managing the operation of the entire network. Subnets are independent platforms on Subtensor, and each subnet focuses on a specific AI task or field. Through this architectural design, Bittensor can achieve efficient allocation of resources and specialized processing of tasks while ensuring the unity and coordination of the entire network.
Incentive Mechanism
Bittensor's incentive mechanism is one of its core.
As mentioned earlier, each subnet has its own unique tasks and incentive mechanisms (competition rules). To understand its incentive mechanism, we must first understand several important roles in the subnet:
Subnet miner (miner): Each subnet miner performs a useful task, that is, solving certain problems defined in the subnet incentive mechanism. (Is it very similar to the miners in Bitcoin?)
Subnet validator (validator): Each subnet validator independently evaluates the tasks performed by the subnet miner, and then expresses their opinions on the quality of the miner's task completion. These opinions of the subnet validator are then provided as collective input to the Yuma consensus mechanism on the blockchain using the Bittensor API.
Nominee (Nominee): Stake TAO to the selected validator and receive rewards based on the quality of the validator's work. There is no lock-up period for staking. Given that a fixed number of $TAO is issued every day and distributed among the delegators, the staking reward APR will fluctuate, and the current APR ranges from 13%-20%.
The Yuma consensus mechanism on the Subtensor blockchain will determine how to distribute rewards to subnet miners and subnet validators. The reward is in the form of Bittensor's native token TAO, and the quantity and quality of the reward depends on the quality of the miner's contribution.
Since each subnet has its own unique tasks and goals, miners can choose the appropriate subnet according to their own advantages to maximize their benefits.
In the Bittensor network, there is a competition and elimination mechanism between subnets. Each subnet needs to continuously optimize its model and algorithm to maintain its position in the network. If the quality of a subnet's contribution is lower than that of other subnets, it will face the risk of being eliminated. This last-place elimination mechanism ensures the efficient operation and continuous progress of the entire network.
Bittensor subnet development status
Currently, in addition to the root network (Root), Bittensor has 36 subnets, each focusing on different tasks, such as natural language processing, computer vision, image generation and recommendation systems.
These subnets have not only achieved remarkable results in their respective fields, but also promoted the development of the entire ecosystem through mutual collaboration.
Why Bittensor chose the Polkadot technology stack
Bittensor's infrastructure uses the Polkadot SDK because Polkadot's architecture provides Bittensor with the interoperability, scalability, and security to support the massive computing needs and data processing required for its decentralized AI network. Polkadot enables Bittensor to seamlessly exchange AI insights and resources across networks, further promoting the development and adoption of its innovative decentralized AI solutions.
Summary
Bittensor leverages the power of decentralized networks and uses clever incentive mechanisms to make AI models no longer a zero-sum game, but to bring together collective wisdom, allowing knowledge to be quickly expanded and shared, thereby promoting the open source and innovation of AI models.
Preview
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