If you want to understand Bittensor, read on…

At its highest level, Bittensor is an open-source protocol underpinned by a blockchain-based network that incentivizes the creation of artificial intelligence; connecting both produces and consumers of A.I by matching supply & demand in an open, decentralized marketplace, with the network’s native token TAO facilitating it all.

What is the Bittensor Network?

A fundamental prerequisite for training and running machine learning models is having appropriate hardware to train and run the models on. The more powerful the hardware is, the better and more complex the models can become. As demand for better and more complex A.I models grows, the computational (read: hardware) requirements grow concurrently. So as this dynamic manifests over time, there is constant growth in the computational requirements needed to more efficiently process increasing volumes of data, and most hardware required to meet todays demands has already been rendered obsolete to those without the enormous resources available to keep up with this growth (97 TRILLION gigabytes of data exists in the world at the moment, and that number is growing exponentially). Since the compute and thus resource requirements to create competitive models that are able to serve todays increasingly complex needs have become so incomprehensibly large, the A.I market has become siloed and centralized by the likes of Google, Microsoft, Meta, IBM, etc.

The A.I landscape…

At a basic level, an A.I model is an algorithm that is able to efficiently organize, process, and reference data patterns in order to produce an inference in response to a specific input, which is subsequently stored, learned, and iterated on further. A.I models are trained on sets of data to influence the types of responses it produces. For example, a language model could be taken and trained on a corpus of Shakespeare’s works, and would thereafter be able to respond to queries related to what it has learned (i.e: write a summary of King Duncan’s role in Act 2 of Macbeth, or even: write a short piece of verse in Shakespearean style on the social dynamics of a bee colony)

What is an A.I / Machine Learning model?

What if there were a way to democratize the production of and access to A.I? Well in order to achieve that, the limitations caused by the growing computational requirements would need to be solved. So how could this be solved? Decentralization! To provide some context on this concept, the largest supercomputer in the world is the Bitcoin Network - by an enormous margin (256x more powerful than the next 500 largest supercomputers combined to be exact [Forbes]). How has the Bitcoin Network achieved this? DE-CENTRALIZATION, i.e. distributing computing power across different nodes (computers) that sit all over the world, and organizing this computing power around a common goal - in Bitcoin’s case, solving complex equations to earn BTC. But what if instead of using all this computing power to solve arbitrary functions solely as a means to earn a virtual currency, large scale distributed computing power was directed towards running very large and very complex A.I models capable of producing outputs (intelligence) far superior to what any centralized system could produce in isolation? Well, the Bittensor network does just that: It enables the coordination of distributed computing power through an incentivized arena that rewards it native token, TAO, in exchange for creating intelligence of value.