DECENTRALIZED SUPERCOMPUTERS (AI)

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AI training requires a lot of computer power in addition to high-quality data from which the algorithms may learn. Artificial neural networks (ANNs), a form of computing system, are frequently used in AI algorithms. ANNs consider numerous examples as they learn to complete jobs. These ANNs frequently need significant computing capacity to process millions of parameters and complete a specific task.

Why can't computational power be shared over a blockchain network if data can? Users can effectively rent their computers' processing capacity in a peer-to-peer (P2P) marketplace in some blockchain implementations to those looking to carry out complicated computations. By offering users tokens in exchange for their processing power, they are encouraged to do so.

On these computer platforms, AI systems might be trained more cheaply and effectively. While early application cases mostly concern 3D computer graphics rendering, attention may eventually shift to AI.

Companies that provide processing power may experience an increase in competition as these Decentralized Applications (DApps) grow. Large amounts of computer power will be used more effectively if individuals are given the option to make money by renting out their unused capacity. Theoretically, every single CPU or GPU in existence may serve as a node in a decentralized supercomputer while not in use.

These two technologies will surely have an influence over the long term if they can live up to their potential. Despite the fact that many businesses employ them individually, there are some fascinating use cases where they can be merged.

By combining blockchain technology and AI at the same time, more innovation may be discovered as both technologies advance. Although it is difficult to predict the outcomes, it is a given that they will improve many facets of our economy.

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