Have you ever wondered how the fusion of blockchain and artificial intelligence could redefine the future? If yes, then Bittensor is probably your answer!
Bittensor, also known by the market ticker TAO, is an open-source, blockchain-based protocol that powers a decentralised machine learning network.
At its core, Bittensor enables the exchange of machine learning capabilities and predictions among participants in a network.
These machine learning models train collaboratively and are rewarded in TAO according to the informational value they offer the collective.
What is Bittensor?
The origins of Bittensor go back to 2019 when it was founded by Jacob and Ala.
The Bittensor protocol is aimed towards a future where artificial intelligence is traded in an open market, where both producers and consumers can benefit from an incentivised and transparent marketplace.
To achieve this vision, Bittensor utilises blockchain’s distributed ledger technology to develop and distribute AI technology with greater efficiency.
Additionally, Bittensor also offers an open-source repository of machine intelligence that is available to everyone, allowing for artificial intelligence innovation on a global scale without barriers to entry.
But how exactly does it all work?
How does Bittensor work?
Bittensor is a dual-consensus blockchain, using both elements of Proof-of-Work and Proof-of-Stake.The Bittensor blockchain is run by a network of miners, validators, and nominees. But, let’s quickly go through some definitions first.
Proof-of-Work is a consensus mechanism that was introduced with Bitcoin and is favored for its high level of security.
Under Proof-of-Work, all miners in the network compete to solve a complex puzzle, with the first to solve the puzzle being rewarded for doing so.
Typically, Proof-of-Work is deemed to be a very secure, but also very wasteful consensus mechanism in terms of energy, due to making the entire network compete to solve a puzzle before validating a transaction.
In short, only one person solves the puzzle while the rest of the energy is spent for nothing.
Bittensor aims to resolve this issue by not making the network compete to solve a puzzle, but instead work collaboratively to train AI models.
Bittensor then uses elements of Proof-of-Stake to validate the data put forward by the Proof-of-Work miners.
To quickly recap, Proof-of-Stake is an alternative to Proof-of-Work that typically works by semi-randomly selecting validators based on the amount they have deposited to the network.
To summarise, Proof-of-Stake is more energy-efficient and scalable than Proof-of-Work as it does not require 50% of the network to agree before confirming a transaction.
To break it down a bit further, and in the context of Bittensor specifically, the miners are those who train the models and are rewarded based on the quality of their work.
The validators then ensure the data provided by the miners is correct, and are also rewarded for verifying the transactions.
Finally, nominees are those who stake their TAO tokens to the validators of their choosing and are also rewarded based on the quality of their selected validator’s work.
Nominees increase the chances of validators being selected to verify transactions due to the nominees effectively increasing the overall deposit of the validator.
What Makes Bittensor Unique?
Bittensor wants to take away the centralisation of artificial intelligence that has currently been set by the likes of Meta, Microsoft, Google, and so on.
The main concept behind Bittensor is to compete with the few supercomputers available to these individual big companies by instead trying to utilise every computer available on the internet.
While AI is still very much a field in its infancy, one thing that Bittensor looks to eliminate is those datasets being created and released in a siloed way, which cannot be verified or checked and can have lasting ramifications for everyone.
In short, Bittensor believes the artificial intelligence produced will be better if everyone is involved during its creation.
To that aim, they have created their blockchain to be accessible and available to all.
So what about the Tokenomics?
TAO Tokenomics
TAO was fair-launched in 2021, meaning no tokens were pre-mined or available before the official launch.
The total supply of TAO is 21,000,000 with a halving cycle occurring every 10.5 million blocks.
Currently, the block rate is set at one block every 12 seconds, meaning the first halving event for the Bittensor network is likely to occur around August 2025.
As the project was fair-launched there is no initial token distribution. However, at present, there also isn’t currently a block or wallet viewer to see if any large whales are holding more than their fair share.
Just for clarity, the reason it is generally seen as a bad thing to have a singular wallet with a large holding of a specific token is due to their ability to manipulate the price by buying or selling.
For example, a common technique is for large whales to sell off large quantities of tokens, which forces small holders to sell out of their positions due to fear of falling prices, only for these whales to come back later and re-buy the tokens at a discounted price.
However, given the age of the project, it is not uncommon for there to be no block explorer just yet.
Although, it is something to consider carefully before parting with your hard-earned cash.
Bittensor has a legitimate use case and a practical application.
There is a good reason why this project has seen an increase in trading activity recently.
Of course, there is no guarantee at this stage they will be able to deliver on all that they promise.
However, they are correct when they suggest the future of AI should not be handled by individual corporations without any oversight.
The implications are immense and long-lasting for this disruptive new technology, and any platform that looks to take ownership of that away from individual corporations working behind closed doors and back to the people will likely do well should AI be one of the significant drivers of the next crypto bull run.