Blockchains and deep learning are two of the most promising technologies to emerge in the 20th century. Hailing the oncoming “decentralized revolution”, Bitcoin-loving venture capitalists are tripping over each other to disrupt every industry from flight insurance to bike-sharing. Meanwhile, significant sectors of the financial sector, transportation, infrastructure, and social media are already controlled mainly by various advanced machine learning algorithms. Decentralization is the result of putting the two hottest technologies of the century AI and Blockchain.
What is Decentralized Artificial Intelligence (AI)?
Machine learning, AI is not a new technology; it is around since the 15th century. But the basic idea is the same, so what we do we feed the ml model with data, and AI learns maths, the relationship between input data and output label with the help of function, and then we expect the model to predict the results. Now talking abt blockchain, years ago, a programmer released a paper on a cryptography mailing list detailing a system called bitcoins that allows two people to transmit value online without a third party, namely a bank. It has a 100 billion market cap as of yesterday, and none can hack it; it has been around for a decade. The underline data structure of bitcoin is blockchain. No one can modify this architecture; it’s an unalterable, immutable computerized data structure that no one owns. These two technologies can go very well together. AI is a probabilist; it’s all about giving the probability that something would happen the likelihood of a future. AI is always changing its updating itself learning abt the end. An AI is a set of algorithms that guess reality. The blockchains are, on the other hand, are not probabilistic; they are deterministic. You know precisely what going to happen. They are permanent and unchangeable. The Algorithms and cryptography to record reality. These two things can go together if we can break them down at what they are good at.
What can Decentralized Artificial Intelligence do?
Decentralized models can provide the opportunity to large companies that control huge datasets to be independent. Blockchain has paved the way for a decentralized ecosystem where data scientists, data providers, consumers, and all other involved parties collaborate to create AI architectures that eliminate the need for centralized control authority. Think of uber, for example, if a rider wants to find a cab, he needs a third party, namely uber, to find the driver, so uber takes charge of this. They also have a history of malpractices, but ideally, the rider wouldn’t have to depend upon uber; he can just find his driver, he would get paid more, and a rider has to spend less, and it would be better for both of them. It not just about earning money; it’s about acuity. It would be a community-owned model, a centralized authority, but all the people can be a part of this architecture.
The primary goal of a decentralized system is to create a centralized agent-free environment with more data security. Nowadays, we give our data to service providers like Uber and Facebook in return for services. This a problem because our data is the most valuable thing we have, and it’ll become more valuable as everything will slowly be automated. Our data will be the only valuable asset we have. So decentralized models are going to let parties make computations of datasets without any central authorities. It is still a futuristic thing, but it’ll be worth waiting.