How can artificial intelligence education be decentralized?

The current artificial intelligence market is largely controlled by global technology giants, such as Microsoft, Google, Tesla and Meta.

If this continues, we will see exclusive dominance in the AI ​​field in the long run. As a result, it will lead to a lack of transparency in unfair pricing and we will probably have no say in how things work.

This is where decentralized artificial intelligence comes into play. Decentralized artificial intelligence refers to a model that enables the dissociation of data processing without the difficulty of sharing overall knowledge. In other words, it allows you to process data independently. As a result, you can create better, unique results and solutions that were not previously possible with a centralized AI system.

If you’re not sure what a centralized AI system is or how it works, you may want to go through Jennifer Quentoh’s Machine Learning and Artificial Intelligence tutorial.

That said, let’s take a closer look at decentralized artificial intelligence.

What is decentralized artificial intelligence?

Decentralized artificial intelligence is the separation of learning and intelligence into two different devices and organizations. And then train the machine learning model on locally available data.

This method allows you to combine knowledge from a myriad of local datasets without compromising on actual raw data between devices, locations, and organizations.

Decentral AI is becoming more popular because it provides better privacy and efficiency than centralized artificial intelligence.

If you are not sure where this will be implemented, it will play an important role in hospitals and autonomous vehicles (allowing them to take advantage of knowledge centrally while storing sensitive data on local servers).

The role of blockchain in AI decentralization

Blockchain provides a much-needed basis for the decentralization of artificial intelligence. The first generation of decentralized artificial intelligence apps is taking advantage of smart compacts and DApps to see how the last points of an AI app will interact with each other.

Similarly, digital tokens are still relevant in the decentralized AI world because they offer the process of compensating data scientists for their contributions. They also influence how the model will benefit all parties involved.

The potential for decentralized AI in the real world

As we mentioned above, decentralized AI is very useful and has a lot of applications in the real world. Industry experts predict that over the next ten years, devices and applications that use decentralized AI networks will probably benefit from all the devices that preceded them and are currently connected to the network.

They will be able to collect, convert and take advantage of all the data in the existing system. Also, there will be specific structures that make it easier for people to understand how things work.

Federated learning

Federated learning refers to the learning architecture for artificial intelligence systems that run on distributed topologies, such as smartphones. Launched by Google, Federated Learning is an alternative to centralized AI training, where different device models can contribute to training while protecting device data.

This means that applications can use federated learning to train or optimize AI independently without the need to trust a centralized authority.

Homomorphic encryption

Homomorphism is the process of mapping a mathematical set to another set or creating a result within oneself that confirms that the elements of the first set are mapped to another set.

Homomorphic encryption ensures that these calculations are performed using ciphertext to create an encrypted result. It is considered one of the greatest inventions in the cryptographic industry of the last decade.

Because of homomorphic encryption, decentralized AI users can contribute to training a model in a way that is encrypted by other parties, ensuring privacy and confidentiality.


The future of AI is decentralized AI. Although this is an early stage, businesses that use decentralized AI will soon surpass those that are not. If you think artificial intelligence can be beneficial to your business, it’s time to test decentralized AI.

Still in doubt? Shoot in the comments, and we’ll address all your concerns as soon as possible!

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