Bittensor is an open-source protocol that powers a scalable, decentralized neural network. The system is designed to incentivize the production of artificial intelligence by training models within a blockchain infrastructure and rewarding performance with a custom digital currency.
The network is composed of several thousand nodes, each containing a machine learning model. All nodes are assigned the task of parsing a massive collection of text data, working collaboratively to extract semantic meaning. By way of a consensus mechanism, the system is designed to reward the most value-producing nodes, such that the digital token reaches equivalency with the quality and quantity of representational knowledge in the system.
Ultimately, our vision is to create a pure market for machine intelligence.
Bittensor is an internet-scale mining network that encourages miners to host and train machine learning models. The network uses token-based incentives to promote its growth and to distribute value directly to the individuals providing that value. Bittensor is an open network, accessible to all participants, and no individual or group has full control over its learning, profit generation, or access.
Some key features of Bittensor include:
- Querying the Bittensor network as a client
- Running and building Bittensor miners and validators for mining TAO
- Pulling network state information
- Managing TAO wallets, balances, transfers, etc.
This documentation is divided into several sections to help people get started with Bittensor and Computer Science in general:
- Introduction: An overview of Bittensor and its key features (this section)
- Skills Required: This is computer science, but for those new to this field, some basics are explained for you.
- Usage: Guides on how to use Bittensor as a client, miner, and validator.
- API Reference: Detailed information on Bittensor's API and its various functions.
- The rest of it: Answers to the enigma that is this network and how it functions from the perspective of code, computer science, and the construction of a Neural Network.
We hope you find this documentation helpful as you explore and use Bittensor. If you have any questions or need further assistance, the Bittensor Discord is a great place to learn about the project. Taostats.io is also a great place to see an overview of everything.
As the writer of this documentation, TAOBard, I hereby declare this:
○ I acknowledge most of this is interpretations of AI, but I believe I have sufficiently looked through and read everything and believe it will help any beginner.
○ You are free to alter, download, interpret and otherwise build upon this notebook to create better versions of this documentation.
I intend on releasing further documentation pending further experimentation and consultation with others in the community. I will announce things later on in time through My Twitter
Thank you, and I hope my contribution can spark a new wave of documentation for the Network. Some parts are taken from previous documentation, but I have added a great many files and information with this interpretation of documents. I look forward to learning more and both updating this documentation, but also, to integrate it into a website somewhere and from there, build more mdBooks about other things.
Somebody mentioned I should leave a donation address here - so if you feel so inclined, I would be most grateful. 5Cysz8fsZdCycYicdqxUtbycV9ccBbFsyvkbpnZknRZvKCFR - I will continue to work on furthering documentation, and will have another book sometime soon.