The Future of AI is Decentralized

Regardless, hundreds of online businesses can essentially be built now, simply by utilizing an OpenAI API Key. Imagine how many more new doors can be opened, if individuals & companies had access to an open-source protocol, with multi-modal frameworks of machine intelligence.

Bittensor relies on miners that fine-tune models to train the network, as well as validators that evaluate intelligence produced by these miners and record it on a blockchain.

It is an open-source machine like Ethereum, but instead of relying on 100s of API connections that constantly need to get updated, you just plug into Bittensor’s meta-model, with your requests being routed to the endpoints that serve them best.

To see a lot of the value proposition, it’s necessary to familiarize yourself with 2 core machine learning concepts!

In a MoE model, each expert is designed to handle specific types of data or situations. The model also has a “gating network,” which is like a coordinator that determines which expert should be consulted for a given input. The gating network assigns a weight to each expert based on their relevance to the input, and the final output is a combination of the experts’ predictions, weighted by their assigned relevance.

The process involves training the student model to mimic the behavior of the teacher model by replicating its predictions or outputs. During training, the student model is exposed to the same data as the teacher model, but instead of learning directly from the raw data, it learns from the teacher model’s outputs. By learning from the teacher model, the student model acquires the essential knowledge and can make similar predictions, but with the advantage of being smaller and faster.

Bittensor is a p2p Mixture of Experts model on which individual peers are Distilling knowledge from each other

Bittensor, uses Bitcoins substrate of incentivized compute, to scale the protocol, but instead of rewarding non-productive hashes (BTC), it rewards the creation of machine intelligence under high demand relative to its supply. Bittensor adopts the same mechanism that scaled Bitcoin to the largest supercomputer in the world too, by hashing power to scale a decentralized mixture of expert’s model or to conceptualize — a neural network of neural networks.

$TAO represents weight in the network as it allows to govern the incentive mechanism that all miners work for, models (miners) will align their produced intelligence to your demand if your stake is high enough. the more stake the higher priority miners will give serving your requests. This creates an open market for machine intelligence

The value of $TAO is connected to the value of the intelligence that is produced by the network. Ownership of the network comes with holding $TAO. So, if someone holds a fair amount of $TAO, he gets to decide, on what the network will be trained on (there are mechanisms against collusion in place).

If an external company wants to use Bittensor, for example to develop a specific software, it needs $TAO. In order to have the request bandwidth to make the application worthwhile, a certain amount of $TAO is needed. Also, the miners and validators of the network are incentivized with $TAO.

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