Welcome to TaoDocs - written in mdBook

Hi, I'm TAOBard - this is a community project supported by members of the Bittensor community, though mostly written/interpreted by me. I may quote people from the community, so if you see your words here, it is quite possible I copy pasted it or otherwise re-worded things from a discord thread I was reading into. Any information here that is not mine is either sourced from public documentation, community projects, or verified individuals within the Bittensor community.

I am convinced that the way forward is to educate people as to what is possible on this Network, but also, it's to inform people of a few things:

  1. That what's going on is real and that there is science going on here. Complex algorithms are running this Network, and it is a Decentralized AI. This is factual - any network of sufficient power can run a decentralized miner if they're good enough.
  2. This has been built in relative silence for years. The devs are usually constantly working on projects, and extremely dedicated to building.
  3. To even begin building a Validator on this network, you would need to be at an advanced level in computer science. I would argue intermediate if you're mining, and specializing in ML.

You can learn a lot if you just listen.

I keep my ear to the ground and I've learned a lot just by reading the live-action troubleshooting that goes on in the discord.. you can also ctrl+f and find what you're looking for. That's really the best source of information if you ask me, so if you have questions you're scared to ask, then try searching first. It's likely others have experienced similar issues. That's why it's good to just read what the developers are talking about, even if it's beyond your current comprehension. Eventually, you will have enough knowledge that everything begins to piece itself together.

Somebody with more experience told me this:

I think if you’re new to software development, it’s best to start with the basics of learning Python and Linux/Unix, as you’ll need those the most. Anything beyond that will require some level of university/college math and lots of reading. A good resource to look for are the open college courses that multiple universities are offering online. I know of MIT, Harvard, but I know there are more. They offer both the foundational math and CS courses, but also the AI and ML courses. Once you’ve got the foundations, the best way to learn is to try things in-practice. Check out the hugging face tutorials, and try a simpler NLP, or ML, task, or start a project.

For those new to this project, I welcome you. There are many fascinating characters and determined individuals here, but for the aspiring builder, this is a good place to start from ground zero. Day one. Never ran a Sudo command? Don't know what Nano does? Don't worry, we'll talk about that - but a GPT model could probably explain things better than myself.

The goal here is create a baseline source of documentation to set people on the right path with Bittensor, with the goal of creating more documentation in the future to push this project forward and create better education for people new to Computer Science.

This means we must arm the people with the knowledge of Linux, Python, and the commands found within this intricate network. It is also important to recognize the roles of validators and miners, and we will go into more explanation on their respective sections. This is an opensource project, just as Bittensor itself is. If you think you can contribute to better documentation, then please hop aboard and contribute to the documentation - I am happy to collaborate and integrate better documentation, and I intend on working on more documents within Bittensor itself specifically.

This guide is for those who have just begun, who understand nothing of what is going on in this network, and want insight into what the code is actually doing and how the terms of the Network/analysis of blue-prints given to us.

If you would like to contribute further blue-prints, please get in contact with me as I would be happy to collaborate and learn from peers within the field.

Thank you to everybody who was supported me so far. I am releasing these documents free of charge for anybody to alter and integrate into their own websites. If you feel this knowledge is of use, and you would like to integrate it/alter it into your own website for the purposes of teaching, then feel free. The point of this is that it's open-source - with that being said, this is a blue-print. I will likely update this as time progresses, and I am likely to create a website for this particular book.

Edit - Big thank you to MogMachine for hosting these on taostats.