Bittensor：AI和机器学习的去中心化协议

The project introduction is a decentralized protocol focusing on machine learning, which is at the forefront of decentralized artificial intelligence. Through the use of blockchain technology, it aims to solve some core problems encountered in the traditional development process, such as the incentive mechanism of data ownership model training and the accessibility of services. At present, training machine learning models requires a lot of resources, and usually only big companies such as Google and others can afford it. It aims to decentralize the access and training of machine learning models and prevent censorship. Running decentralized machine learning model can prevent similar models trained by different companies from training in isolated islands, promote the complexity and composability of open development models, and accelerate the development of the field. The ecosystem is driven by its native tokens, promote cooperation through token reward contributions, and protect the blockchain ecosystem. One of its characteristics is a special subnet structure. These subnets are places where real value is created through competition and cooperation. Through this structure, innovation is encouraged and inclusiveness and quality are promised. The token economy that we attach great importance to is designed to encourage the practice of fair distribution, and ensure that the incentives among network participants are consistent. The design of tokens increases exponentially with the expansion of the base of network participants. At present, about the circulating tokens are currently pledged, which also reflects the high participation of the network, the core mechanism of the network, and the ecosystem of network ecological power is booming because of its unique subnet dynamics. Each subnet provides suitable rewards for various artificial intelligence applications. This setting shows its diversity. And innovation, which is also an area that many large-scale artificial intelligence companies may ignore. The single token ecosystem supports these activities, so that token owners have a great say in how artificial intelligence develops in the network. Machine learning methods and mechanisms connect several key types of participants in their networks. Miners are the core of internally driven innovation. Miners manage and run various models. Verifier layer plays a key role in maintaining the integrity and consensus of blockchain, ensuring that the network is in line with the existing. The enterprise layer is committed to developing cutting-edge applications and solving complex problems by using the capabilities of the network. The consumer layer provides end users and organizations with access to the solutions and services generated by the network, which realizes the safe and efficient cooperation between blockchain operation and artificial intelligence services, decentralizes the expert combination, and adopts a decentralized expert mixed model to improve the accuracy and efficiency of prediction through the cooperation of multiple professional models. This method combines the uniqueness of each model. Advantages to solve complex problems and achieve more accurate and comprehensive results exceed the traditional single model method. For example, when generating code with Spanish comments, the language ability of one model and the coding expertise of another model are combined to provide superior solutions. Intelligent proof is a way for the network to reward nodes that add useful machine learning models and results. It is similar to the way that blockchain networks use sums, but nodes do not solve mathematical problems but perform machine learning. Task to show its intelligence. If the machine learning work of a node is accurate and valuable, it has a better chance to be selected to add new blocks to the chain and earn tokens as rewards. In order to get rewards in the network, the server must not only generate valuable knowledge, but also gain the recognition of most verifiers. By adopting this consensus mechanism to stimulate valuable contributions, promote cooperation and protect blockchain tokens, which are the original cryptocurrency of the network and serve several key functions and purposes in the ecosystem. Incentive tokens are used to encourage various participants in the network to contribute computing resources to perform machine learning tasks. Miners will be rewarded with tokens for their contributions. This incentive mechanism encourages the provision of computing power to the network, which is very important for the decentralized machine learning process. Pledge is necessary for participants to participate in the network as miners and get rewards. Pledge tokens as collateral or a form of skin in the game helps to ensure that miners have the motivation to act in the best interests of the network. It also enables any participant to participate. The malicious behavior of the participants pays a high price, thus helping to protect the network security. Governance tokens can be used for the governance of the network. Token holders may be able to propose changes, vote on protocol upgrades or participate in other decision-making processes that affect the network. This is consistent with the decentralized spirit of blockchain technology, in which control rights are distributed among stakeholders rather than concentrated in a single institution. Transactions on the network, such as token transfer or the execution of smart contracts, may have to pay these fees. Fees are usually paid in tokens to compensate verifiers and miners for processing and protecting transactions on the blockchain. Economic model Tokens support the economic model of the network. It aims to balance the supply and demand of computing resources, adjust the incentives among participants and promote the exchange of value within the ecosystem. Users who need machine learning services provided by the network may need to use tokens to pay for these services. This creates a market for machine learning services, and tokens can be exchanged for computing work, for example. Data analysis model training or forecasting tokens is an indispensable part of network function, because it provides an economic and incentive structure to support decentralized machine learning market, and the interests of all stakeholders are coordinated through incentive measures based on tokens. Up to now, the current price of tokens is US dollars, and its market value ranks first in US dollars. It is a large encrypted asset with an important market share, and its hourly trading volume market value ratio is a relatively active market, which shows that the daily trading volume accounts for the total market. A small part of the value, its circulation supply accounts for the total supply, which shows that more than one-third of the maximum supply in the market is being traded or held. The maximum supply is a fixed supply ceiling. This design is to prevent inflation and may increase scarcity over time. After complete dilution, the market value will be US dollars. If all of them are calculated at current prices, the market value will reach nearly US$ 100 million, and it will be halved every four years like Bitcoin. Once the total issuance reaches half of the issuance rate, One block will be mined in half every second, which is equivalent to a halving event every four years, and then every halving event will occur at intervals corresponding to the remaining half to be issued until the total supply of 10,000 units enters circulation. If you want to buy, you can buy it through the decentralized exchange. There is an excellent team behind the financing situation. It is said that the company has a total of employees, some of whom have doctoral degrees in physics and artificial intelligence, and most of the members of the team have computer science, artificial intelligence and engineering background and experience. The co-founders are Jacob Stie. 比特币今日价格行情网_okx交易所app_永续合约_比特币怎么买卖交易_虚拟币交易所平台

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