Blockchain and Machine Learning

Artificial intelligence (AI) and blockchain technologies are among the revolutionary trends in the field of IT of our time. All industries, research institutes and public organizations are doing this in order to have a good position in the future.

Thanks to solutions with a distributed registry or blockchain, confidential data remains strictly confidential, and at the same time, can be used for machine learning (ML) with external partners. These technologies provide full or detailed control of all access, which can be delegated and revoked upon request, without the need to share private cryptographic keys. Thus, the blockchain allows reliable processing of valuable data sets and at the same time accelerates the process of developing valid AI applications.

Artificial intelligence and algorithms trained by machine learning support companies, combined with distributed ledger solutions such as blockchain, in the development and use of new data sources. However, blockchain can greatly simplify, for example, the sharing of datasets, machine learning models, decentralized intelligence, security, data protection and making trustworthy decisions.

The difference between AI and ML

Although artificial intelligence (AI) and machine learning (ML) are often combined, they remain completely different technologies.

Artificial intelligence refers to the ability of a machine to perform intelligent tasks, and machine learning is an automated process of using a machine to identify significant patterns. This means that without machine learning, artificial intelligence as we know it would not exist.

On the other hand, machine learning, in turn, will have a significant impact on the development of blockchain in communication and network systems, including energy and resource efficiency, scalability, security, data protection and smart contracts. New business models may arise as a result of the interaction of machine learning and blockchain.

Reliable trading platforms

Because blockchain quickly builds trust between unknown parties, it also allows for reliable trading of sensitive data or data analysis through decentralized and encrypted data markets. For example, on Coinmarketrate.com You will find companies like Enigma or Ocean Pool that have developed blockchain-based protocols for such trading platforms. On these platforms, you can receive data and determine access rights.

The highlight is that vendors always retain control over their data, while other parties can use it, for example, for machine learning. This means that AI development is changing dramatically, as it can significantly increase the database. In addition, these trading platforms will actively promote trading using algorithms.

One of the suppliers of trading platforms is the global AI network SingularityNET. Here, developers can upload their algorithms as “AI agents” and offer them to other parties for use on their own data. However, the algorithms are only suitable for the tasks they have been taught. SingularityNET also offers its customers the opportunity to interact with other “AI agents”. In this way, much more extensive applications of artificial intelligence can be implemented.

Application areas in the industry

Both technologies can speed up data research and analysis and improve transaction security. In addition, blockchain can provide important input data for machine learning, which requires very large amounts of data. As part of the production process, innovative companies rely on blockchain-based solutions and smart contracts to enable analysis in the areas of transparency, security and compliance.

For example, machine learning prediction algorithms should be used to optimize machine maintenance plans. Quality control and product testing are also gradually being automated using adaptive vision and computer vision algorithms to successfully distinguish good products from defective ones. Car manufacturer Porsche is already using blockchain with machine learning to transfer data more securely and quickly and optimize services such as cashless payment in parking lots, seamless supply chain tracking or automatic driving functions.

Blockchain and machine learning significantly increase the transparency of the entire food industry supply chain. With the help of blockchain, it is now possible to track products and manage relevant financial transactions. Companies such as Unilever and Nestlé are considering using blockchain technology to combat food waste and pollution.

In the energy and utilities sector, blockchain technology helps facilitate the exchange of energy. This technology uses smart meters of microgrids together with smart contracts to perform and manage electricity transactions in a peer-to-peer network.

Industries around the world suffer from intermediaries that complicate transaction costs and make them more expensive. Blockchain technology has already revolutionized this model by simplifying the peer-to-peer infrastructure model for the user. However, the technology works even better when it is combined with machine learning.

Blockchain Increases Global Gross Domestic Product

The PricewaterhouseCoopers (PwC) “Time for Trust” study shows that next year blockchain technology will contribute about $66 billion to the global gross domestic product (GDP).

According to economists interviewed for the study, innovation can increase the volume of the global economy to 1.76 trillion US dollars by 2030. This corresponds to about 1.4% of global GDP. Experts also expect that blockchain technology will be used by most companies in the next five years.

The numerous possibilities of using blockchain provide many possible applications. For example, documents can be certified, data encrypted, digital assets can be created, and transactions processed in real time and protected from forgery. In the areas of public administration, education and healthcare alone, market researchers see about $576 billion in revenue from potential efficiency gains by 2030.

It looks even better with solutions for a clear definition of origin (Proof of origin): Up to US$ 963 billion is expected here for global GDP.

“The potential of the blockchain will not be exhausted if the company creates the technology only for internal use. The biggest advantage of blockchain is that it helps to strengthen trust between companies, and ensures equal exchange, excluding intermediaries,” explains Husen Kapasi, head of blockchain at PwC Europe.

The cryptocurrency market is growing

PwC also sees a thriving market for blockchain solutions for everything related to payments and financial instruments. It forecasts up to 433 billion US dollars for the expected global GDP by 2030.

“Since when Bitcoins first appeared in 2009, the cryptocurrency market has grown a lot. The financial industry’s interest in blockchain and crypto assets is growing,” said Thomas Schoenfeld, director of financial services at PwC.

Regulation is still driving these changes, and the current changes in the law on the custody of crypto assets and electronic securities are institutionalizing the crypto industry in the EU.

“Many previously resisted market participants recognize the opportunities emerging in this area. Currently, Germany is playing the role of a pioneer here in Europe. The main thing is that the regulatory rules do not move into the plane of continuous prohibitions, against the background of the creation of CBDC By the European Central Bank,” Schoenfeld said.