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What are the benefits? Should AI use Blockchain technology?

Adam Mazzocchetti AI and Blockchain

Blockchain and artificial intelligence are two of the most promising technologies in blockchain technology for the future. Although the two technologies are very different, researchers have researched and discussed their combination.     

By definition, a blockchain is a distributed, decentralised, invariable register used to store encrypted data. Blockchain technology adds $3.1 trillion to the value chain, and artificial intelligence will add $15.7 trillion to the global economy by 2030. As a result, global GDP will rise by 14%, and blockchain technology will cause global economic activity to increase by $2.5 trillion.  

Of course, each of these technologies has its own degree of complexity, but because they can affect and implement data in different ways, merging them makes sense and takes data usage to a new level. AI, on the other hand, is a brain engine that enables analysis and decision-making – the creation of the data it collects. Both AI and blockchain are in a situation where both can benefit from and help each other. 

At the same time, integrating machine learning and artificial intelligence into the blockchain can improve the underlying architecture of the blockchain and increase the potential of AI. Blockchain can also make AI more coherent and understandable, so we can understand and determine why machine-learning decisions are made.  

Blockchain and its registers eliminate all data and variables that are involved in machine learning decision-making, from decision-making to data processing and execution.   

The way blockchain currently runs on standard computers shows that it takes a lot of computing power to do even basic tasks. Moreover, AI can significantly improve blockchain efficiency for humans or even standard computing. 

    

Use cases for  AI and Blockchain

Smart Computing Power 

For example, the hashing algorithm used to break up Bitcoin blocks adopts a brute force approach, which involves systematically listing all possible candidates for a solution and checking that each candidate meets the problem report before verifying the transaction. This is because running an algorithm to encrypt data from one computer to another requires a large amount of computing power. 

To this end, AI offers a much more efficient solution to the problem of the brute force algorithm. Imagine a machine – a learning algorithm that refines its skills by feeding it appropriate training data. 

Creating Diverse Data Sets 

For projects based on artificial intelligence, blockchain technology has created a decentralised and transparent network that anyone in a public blockchain network can access worldwide.   

While blockchain technology forms the basis for cryptocurrency management, blockchain networks can also be applied to a range of industries, creating decentralisation and allowing different algorithms to be built on different data sets. Singularity-net combines blockchain and AI to a decentralised, decentralised AI/blockchain network that can host different data sets and store data. APIs and API blockchains would enable intercommunication between AI and agents by creating them.    

Data Protection 

The progress of an AI is entirely dependent on data and data input, so you basically feed the AI with data. From this data it will receive information about the world and the things that are happening in it, and will be able to continuously improve. 

Blockchain, on the other hand, is essentially a technology that enables data to be stored encrypted in a distributed register. This allows a fully secured database that can be verified by all parties entitled to do so.  

Artificial intelligence applied to big data creates the perfect combination for managing large databases. When you combine blockchain with AI, you have a powerful combination of security, privacy, and the ability to store data in a secure and secure way.  

Medical and financial data is one of the most important pieces of data left to individuals and companies and their algorithms. Storing this data in a blockchain that can be accessed by AI, but only with your permission and only after going through the relevant procedures, could offer huge benefits such as personalised recommendations while keeping your data secure.   

Data Monetisation 

One of the disruptive innovations that could be made possible by combining these two technologies is the monetisation of data. Monetisation of the data collected is a key element of many of today’s disruptive technologies, such as blockchain and artificial intelligence (AI). The fact that others are deciding how to sell this data to make a profit for the companies shows that they are being armed. 

Blockchain allows you to cryptographically protect your data and use it as you like, but it also allows you to monetise it if you choose, without compromising your personal data. 

This is important to understand in order to combat distortion algorithms and to create diverse data sets in the future. For AI algorithms to learn and evolve, they need to buy data from their creators. The same goes for any AI program that needs data, such as search engines, machine learning, or even social networks. 

Developing and feeding AI is incredibly costly for companies that do not produce their own data, and the fact that this whole process has occurred before makes it easy for tech giants to exploit their users. We will have a data market that is otherwise too expensive and private, decentralised, but will also allow smaller companies to use artificial intelligence. This will make the artificial intelligence process more efficient than before, with less risk of the tech giant exploiting its users and more choice. 

Trusting AI Decision Making 

As AI algorithms become more intelligent through learning, it is becoming increasingly difficult for data scientists to understand how these programs come to certain conclusions and decisions. They will be able to process incredibly large amounts of data and variables, and they will have to learn from this.  

Blockchain technology offers the opportunity to process this in a much more transparent and transparent way, which greatly facilitates the review of the entire process. We can continue to review the conclusions of AI as long as we want to ensure that they reflect reality. This makes the decision-making process much more efficient, and blockchain technology offers an opportunity to review this entire process in a similar way to traditional data science.  

This is a necessary step before individuals and companies use AI applications to understand how they work and the information on which they base their decisions. With appropriate blockchain programming, we can monitor every step of data entry and derivation, and observers can be sure that the data is not manipulated. We can build on this by drawing conclusions from the AI programme, similar to traditional data science, but with a much more transparent and transparent process.  

Conclusion  

The combination of blockchain technology and artificial intelligence is still a largely undiscovered area, according to a new study by researchers at the University of California, Berkeley. 

Although the convergence of these two technologies has attracted considerable scientific attention, projects that address breakthroughs in this combination are rare. The combination of the two technologies has the potential to use data in ways that would not have been previously thought possible. Data is the basis for developing and improving AI algorithms, and blockchain allows individuals to monetise their produced data. Blockchain allows us to review the intermediate steps AI takes to draw conclusions from data and allows a more efficient way to review the data and the conclusions to be drawn from it. 

It is not yet clear how the interaction of these two technologies will develop, but the potential for real disruption is clear and is developing rapidly. AI can be incredibly revolutionary and needs to be designed with the utmost care, and blockchain can be very helpful, but It is not yet clear how this interaction between the two technologies will develop.