- Based in:
- Started in / Announced on: 2019
- Testnet release:
- Mainnet release:
- In their own words, Bittensor is essentially a language for writing numerous decentralized commodity markets, or ‘subnetworks’ situated under a unified token system with a goal of directing digital market power to society’s most important digital commodity, artificial intelligence.
- From TaoStats (20-11-2023):
"There was an initial iteration of the network name Kusangi which was started on the 3rd January 2021 and then halted in the middle of May so that some issues could be addressed. The blockchain and all 546,113 previously mined TAO were migrated to Nakamoto which was started on 21st November 2021 from block 0. The Finney network network was officially launched on the 20th March 2023."
Audits & Exploits
- Bug bounty program can be found [insert here].
- From the docs (20-11-2023):
"Bittensor's governance protocol transitions network management from centralization within the foundation to community-ownership over time. The first stage of this management decentralization creates a bicameral legislature, in which the Triumvirate creates proposals for the Senate to approve or veto. Triumvirate members are Opentensor Foundation employees, while the Senate is formed from the top K delegate hotkeys."
Notable Governance Votes
"The distribution of TAO can also be considered extremely fair, with this excellent Bittensor report stating that early supporters did not receive any tokens, though it’s difficult to verify whether this is or isn’t true, so we will trust our sources."
- From TaoStats (20-11-2023):
"The total token issuance rather than the block number is used to determine the exact point the halvening occurs. As Tao used to recycle registrations is burned back into the unissued supply, there is a lengthening halvening data however this data is calculated at the current block/issuance so will update automatically over time.
The total supply of 21 million is pre-programmed. A block is mined about every 12 seconds, rewarding the miners and validators with 1 TAO per block. At the current inflation schedule this leads to 7200 new TAO being issued into circulation every 24 hours which is currently split evenly between miners and validators.
Once half of the supply has been issued the rate of issuance is halved — with 12 seconds per block that amounts to a halving every 4 years. Every half marker of the remaining amount to be issued creates a new halvening event until all 21 million TAO are in circulation."
"TAO is both a reward and access token to the Bittensor network, with TAO holders able to stake, participate in governance or use their TAO to access apps built on the Bittensor network. 1 TAO is minted every 12 seconds, with the newly minted token being distributed equally to both miners and validators for their work. "
- Whitepaper or docs can be found here (2019).
- Code can be viewed here.
- Consensus mechanism: Yuma Consensus
- Virtual Machine:
- Development language used:
How it works
"There are two key players that manage the Bittensor network, these being miners and validators. Miners are individuals who submit pre-trained models to the network in exchange for their share of rewards. Validators are the ones that confirm the validity and accuracy of these models’ outputs, selecting the most accurate ones to return to a user. An example of this might be a Bittensor user requesting an AI chatbot to answer a simple question involving derivatives or a historical fact, with this query being answered across however many nodes are currently running within the Bittensor network.
A simple explanation of a user interaction from start to finish with the Bittensor network is as follows: user sends query to a validator(s), validator(s) propagate this to miners whose outputs are then ranked by validators before the highest ranked outputs are sent back to the user.
Yuma Consensus is comparable to a CPU that distributes Bittensor’s available resources across the entire network of subnetworks. Yuma has been described as a hybrid of PoW and PoS, with the added capability of transferring and facilitating (loosely defined) intelligence off-chain. While Yuma underpins most of Bittensor’s network, though subnetworks can opt in or out of relying on Yuma Consensus depending on their subnetwork’s chosen functionality. Details are murky and there are a variety of subnetworks with corresponding Githubs, so it’s fine to just understand the top-down approach of Yuma Consensus if you want only a general understanding."
"To become a validator, users must rank within the top 64 holders of TAO and have registered a UID on any of Bittensor’s subnetworks, the self-contained economic markets providing access to various forms of artificial intelligence.
Bittensor validators are tasked to “play a continuous game of evaluating the models produced by the miners on the Falcon Refined Web 6T token unlabelled dataset” in order to score each miner based on two criteria, timestamp and loss against other models. Loss functions are a machine learning term used to describe the difference between predicted and actual values in some type of simulation, with this being representative of the amount of error or inaccuracy of given input data and a model’s output."
"Bittensor has a lot of subnetworks, enough to where I felt it was necessary to give them an entire subsection in this report. Believe it or not, even though these are crucial to the utility of the network and underpin all of the technology, there isn’t a dedicated section on Bittensor’s website covering these and how they operate.
Subnetwork 1 (often abbreviated as sn1) is the largest subnetwork of the Bittensor network, responsible for text generation services. Among the top ten validators of sn1 (I use same top 10 rankings for additional subnetworks), there are roughly 4 million TAO staked, followed by sn5 (responsible for image generation) which has about 3.85 million TAO staked. All of this data is available on TaoStats, by the way.
The multi-modality subnetwork (sn4) has about 3.4 million TAO staked, sn3 (data scraping) has around 3.4 million TAO staked and sn2 (multi-modality) has around 3.7 million TAO staked. Another subnetwork with more recent growth is sn11, responsible for text training with a similar amount of TAO staked as sn1.
It currently costs 182.12 TAO to register a subnetwork, a number that’s come down significantly from a peak of over 7,800 TAO in October, though I’m not entirely sure that’s accurate. Regardless, with over 22 registered subnetworks and a growing spotlight on Bittensor, it’s likely we’ll see more subnetworks become registered in due time. "
Their Other Projects
- Can be found [Insert link here].
Projects that use or built on it
"Some have compared Bittensor to an on-chain oracle with access to ML models, which is a pretty solid definition. Bittensor separates the core logic of the blockchain from the validation of subnetworks, running models off-chain in an effort to accommodate more data and higher compute costs for potentially stronger models. As you might recall, the only process done on-chain is inference."
Pros and Cons
"It’s not currently feasible to combine or compound many or even multiple models into one to increase or “stack” capabilities - it’s not how LLMs work. I’ve tried to reason with community members, but I think it’s important to note that as it stands, Bittensor is not an example of a unified collective of models, just a network of models of varying capabilities.
I think a lot of the community has gotten too wrapped up in trying to convince everyone that Bittensor is going to change the world when they’re actually just doing a pretty solid job of trying to change the way AI and crypto interact. It’s not likely they’ll be able to morph their entire network of miner-uploaded models to form one supremely intelligent super computer - that’s just not how machine learning works. Even the most performant and expensive models available (albeit in limited commercial form from research labs like OpenAI) are years away from achieving something definable as Artificial General Intelligence (AGI).
The tokenomics of TAO make it very easy (on paper) to envision a world where decreasing emissions via halvings lead to increased competition amongst miners, naturally resulting in higher quality models and a better user experience overall. However, there’s also the issue that less rewards does the opposite and doesn’t attract heightened competition, rather a stagnation in models deployed or the number of miners competing."
Team, Funding and Partners
- Full team can be found [here].
- Jacob Steeves and Ala Shaabana and one pseudonymous whitepaper author Yuma Rao were the founders (11-2023) in 2019.
Knowledge empowers all and will help us get closer to the decentralized world we all want to live in!
Making these free wiki pages is fun but takes a lot of effort and time.
If you have enjoyed reading, tips are appreciated :) This will help us to keep expanding this archive of information.