Introduction
Bittensor is a decentralized infrastructure that enables the building and deployment of machine learning models on the blockchain. It allows the training and sharing of Machine Learning models on a larger scale by leveraging blockchain computing power. The platform uses a digital ledger to record ranks and incentivize the production of machine intelligence by rewarding performance with TAO, the native cryptocurrency token of the Bittensor platform.
Innovation
Bittensor is an innovative project that provides a pure market for artificial intelligence, where consumers and producers of this valuable commodity can interact in a trustless, open, and transparent context. It offers a unique framework in which machine intelligence is measured by other intelligence systems, allowing researchers to directly monetize machine intelligence work, and consumers to directly purchase it. The constructed market uses a digital ledger to record ranks and to provide incentives to the peers in a decentralized manner.
Architecture
Bittensor comprises a network of computers that share representations with each other in a continuous and asynchronous fashion, peer-to-peer (P2P) across the internet. The system is designed to incentivize the production of machine intelligence by rewarding performance with TAO. Bittensor is an open-source protocol that powers a decentralized, blockchain-based machine learning network. The network uses a consensus mechanism called Proof of Intelligence, which rewards nodes that contribute valuable machine-learning models and outputs. In this mechanism, nodes must perform machine-learning tasks to demonstrate their intelligence. Nakamoto, the main network, is composed of two types of nodes: Servers and Validators. Servers are prompted for information by Validators and given assessments based on the value of their responses. These assessments are then relayed to the network blockchain, Subtensor, where TAO is distributed in proportion.
Code Quality
The code quality of Bittensor is well-maintained, with good documentation. The platform is properly tested, and there are no careless errors in the whitepaper.
Product Roadmap
There is no clear product roadmap available for Bittensor at this time.
Usability
Bittensor offers a significant advantage in enabling Machine Learning models to be trained and shared on a larger scale by leveraging blockchain computing power. However, the platform may not be user-friendly for beginners, as the architecture is complex and requires some technical knowledge to understand.
Team
The Bittensor team has a strong background in artificial intelligence, machine learning, and blockchain technology. The team members have relevant industry experience and academic backgrounds in their respective fields.
Conclusion
Overall, Bittensor is an innovative project that offers a unique framework for building and deploying machine learning models on the blockchain. The architecture is complex, and the platform may not be user-friendly for beginners. However, the code quality is well-maintained, and the team has relevant experience and expertise in their respective fields. Bittensor has a viable use case, and the project is protected from commonly known attacks.
Initial Screening | |||
Keep researching | |||
Does this project need to use blockchain technology? | Yes | ||
Can this project be realized? | Yes | ||
Is there a viable use case for this project? | Yes | ||
Is the project protected from commonly known attacks? | Yes | ||
Are there no careless errors in the whitepaper? | Yes | ||
Project Technology Score | |||
Description | Scorecard | ||
Innovation (Out Of 11) | 8 | ||
How have similar projects performed? | Medium | 1 | |
Are there too many innovations? | Regular | 2 | |
Percentage of crypto users that will use the project? | 6% – 10% | 3 | |
Is the project unique? | Yes | 2 | |
Architecture (Out of 12) | 11 | ||
Overall feeling after reading whitepaper? | Good | 2 | |
Resistance to possible attacks? | Good | 2 | |
Complexity of the architecture? | Not too complex | 2 | |
Time taken to understand the architecture? | 20-50 minute | 1 | |
Overall feeling about the architecture after deeper research? | Good | 4 | |
Has the project been hacked? | No | 0 | |
Code Quality (out of 15) | 15 | ||
Is the project open source? | Yes | 2 | |
Does the project use good code like C,C++, Rust, Erlang, Ruby, etc? | Yes | 2 | |
Could the project use better programming languages? | No | 0 | |
Github number of lines? | More than 10K | 1 | |
Github commits per month? | More than 10 | 2 | |
What is the quality of the code? | Good | 2 | |
How well is the code commented? | Outstanding | 2 | |
Overall quality of the test coverage? | Outstanding | 2 | |
Overall quality of the maintainability index? | Outstanding | 2 | |
When Mainnet (out of 5) | 5 | ||
When does the mainnet come out? | Mainnet Ready | 5 | |
Usability for Infrastructure Projects (out of 5) | 5 | ||
Is it easy to use for the end customer? | Yes | 5 | |
Team (out of 7) | 6 | ||
Number of active developers? | 5+ | 2 | |
Developers average Git Background? | Intermediate | 1 | |
Developers coding style? | Outstanding | 3 | |
Total Score (out of 55) | 50 | ||
Percentage Score | |||
Innovation | 14.55% | ||
Architecture | 20.00% | ||
Code Quality | 27.27% | ||
Mainnet | 9.09% | ||
Usability | 9.09% | ||
Team | 10.91% | ||
Total | 90.91% |