TAO rose 1.6 times in a week, and the interest rate cut trend rotated to the AI ​​sector

Author: Revc, Golden Finance

Foreword

Since the Federal Reserve started the interest rate cut cycle, the market value of crypto assets has increased by more than 300 billion US dollars. In the past week, MEME, AI and public chain sectors have rotated, and Bittensor (TAO) has led the AI ​​and public chain sectors with an explosive performance of nearly 66% increase in seven days, and the currency price has reached an 18-month high. Projects with strong narrative and broad application prospects are more likely to be favored by capital and users. Below we analyze the logic of Bittensor's outbreak and find the investment rhythm of this cycle.

Bittensorsharp performance factors

Bittensor’s rise in the past week is attributed to a combination of technological advances, strategic partnership development, community sentiment, and broad market dynamics, which are conducive to the performance of projects in the intersection of AI and blockchain, as the theme of the capital market over the past year has been AI. After sorting out, the specific reasons for Bittensor's rise are as follows:

Technology upgrade and innovation:

Bittensor announced the release of Bittensor v8.0.0, which introduced significant performance enhancements through the new BTCLI and Bittensor SDK.BTCLI is a tool used to interact with the Bittensor network. The code was rewritten this time to make the interaction more efficient.The Bittensor SDK separates auxiliary functions and becomes lighter and easier to deploy.This upgrade not only improves the user experience and interaction with the network, but may also attract more developers, users and investors.

Advances in AI training:

Bittensor’s announcement on decentralized large-scale language model (LLM) training, as well as mentions of network and EVM compatibility, shows that AI training methods are constantly innovating.Spurring interest and investment in TAO.

Strategic Collaborations:

Bittensor's disclosure of collaborations with entities such as @MacrocosmosAI, @manifoldlabs, and @const_reborn for distributed training demonstrates that Bittensor is expanding its ecosystem through partnerships. Collaborations can enhance Bittensor's capabilities, attract more users, and validate its technology to a wider audience, which can positively impact its market perception.

Increasing Practicality and Real-World Applications:

The practicality of distributed AI training is increasing. As Bittensor's technology is used more in real-world applications, its intrinsic value is likely to increase.

Network Growth and Impact:

As more participants join, the value of each node increases, and the concept of “network effect” may be realized. This growth can form a positive feedback loop, where increased participation increases value, which attracts more participants.

About Bittensor

Bittensor is an open source protocol designed to support decentralized machine learning networks based on blockchain. In this network, machine learning models can be trained collaboratively and rewarded with TAO tokens based on the value of the information they provide to the collective. TAO not only provides users with access to the network, but also allows users to adjust their activities according to their needs.

Bittensoruses blockchain technology to promote a new AI development and distribution strategy that emphasizes open access, decentralized governance, and the use of global computing power and innovation resources within an incentive framework.As an open source machine intelligence repository, Bittensor provides equal access to users around the world, promoting open, permissionless innovation. Rewards and network ownership are allocated based on the value of user contributions.

At its core, Bittensoris building a decentralized network that changes the way AI is developed, shared, and monetized. Through a peer-to-peer intelligence marketplace, miners are able to contribute to the training of machine learning models and receive corresponding token rewards.The platform's native cryptocurrency, TAO, is designed with a fixed total supply to incentivize users to participate in the construction of the network.

Bittensor’s architecture consists of subnets, subtensors, and the Bittensor API. Subnets are incentive-based competitive markets that focus on different AI tasks and can compete and collaborate with each other; subtensors are the core blockchains that record transactions and model contributions, ensuring network transparency and security; and the Bittensor API connects the two and coordinates the operation of the entire network.  

The incentive mechanism is the key to Bittensor. Each subnet has unique rules, and participants are divided into subnet miners, validators, and nominators. Miners solve tasks, validators evaluate miners’ work, and nominators stake TAO and receive rewards based on validators’ performance. Rewards are distributed in TAO tokens through the Yuma consensus mechanism. There is a competition and elimination mechanism between subnets to ensure continuous optimization and efficient operation of the network.

Bittensor allows machine learning models to be trained in a distributed network, forming a collaborative environment and ensuring that network contributors are compensated accordingly. Bittensorensures the integrity of its network through multiple security measures. The token-based incentive mechanism encourages miners to contribute value and decentralizes control to prevent a single entity from dominating the platform. In addition, the platform implements anti-cheating protocols and optional hotkey security features to maintain a fair and transparent ecosystem and protect users' data and transaction privacy.

Conclusion

The value of Bittensor depends on whether it can establish a decentralized advantage in the competition with centralized projects such as OpenAI. The short-term value depends on whether the AI ​​computing power model of each subnet can be directly combined with commercial scenarios, otherwise it is just a hyped AI bubble. The long-term value depends on whether the verification of AI calculation results, the effective workload evaluation of the model, the task distribution system and miner rewards can get rid of the dependence on Web2 projects.

In the Web2 market, the valuation of most AI projects is estimated by converting revenue into annuity, especially when they have been commercially operated for a period of time, the valuation system is relatively mature, and product revenue can be audited and confirmed because it is market-oriented. However, Bittensor has a major problem, that is, the total upper limit of token incentives has been determined, but the value of miners' contributions is not evaluated by income and scenarios. Token rewards are only distributed at the highest computing power level that can be achieved within its own system, resulting in a disconnect with the market. Therefore, commercialization as soon as possible rather than relying solely on network incentives can ensure the long-term development of the project. At present, TAO's daily transaction volume has decreased by 35%, and investors need to pay attention to related risks.