Notable developments are being seen in the field of artificial intelligence, but taking advantage of and accessing machine learning systems makes these quite challenging, particularly for people with restricted resources. Such systems happen to be highly centralized. Their datasets are required to train them, and predictions are usually sold on a per-query basis and are expensive and proprietary to develop on their own. Moreover, published machine learning models face the risk of turning out to become outdated when new information is not regularly given to retraining them. These can be considered as some of the pain points in the artificial intelligence industry.
Today, machine learning and blockchain technology are gaining strong thrust and momentum throughout the globe. Being a disruptive technology, blockchain is making a big splash with Crypto trading and invention. Alternatively, with descriptive and predictive algorithms, machine learning is making bulky waves in leveraging existing information to gain insights and identify patterns.
Combining blockchain technology and machine learning can make the artificial intelligence industry super disruptive. Both come with the potential to quicken analysis and data exploration as well as enhance the security of transactions. Moreover, distributed blockchain technology can be a proven and great input for machine learning, which needs big data sets for making quality predictions.
Where Does Machine Learning Come into Play?
Machine learning can be considered as software that transforms when it learns from new data. While the software can be considered as self-adaptive, it is not essential to add arbitrary rules manually. The best example of how machine learning works can be explained with the spam detection process. In the case of the spam detection process, the software continually enhances its ability to identify junk mails over time. This is carried out by understanding the construction of machine learning algorithms to make particular predictions on the information.
When blockchain technology and artificial intelligence converge, blockchain technology can benefit from the ability of artificial intelligence for accelerating the analysis of a huge amount of information. Putting artificial intelligence and blockchain together, in fact, can potentially develop a whole new paradigm.
By utilizing artificial intelligence and machine learning to govern blockchain, there is additionally an opportunity to increase security notably. Moreover, as machine learning works with a lot of information, it leads to an opportunity for building better machine learning models by taking benefit of the decentralized blockchain technology that encourages information sharing. When all information from silos converges, it might end up with new data qualitatively that is also a better set of information. Due to this, it might lead to the development of a qualitatively new machine learning model that can help derive new insights. This, in turn, can provide innovative opportunities to build a cutting edge next-generation business app.
It can turn out to be a game-changer for the insurance and finance industries because it can be utilized as a tool for identifying fraud. Additionally, it can benefit other industries far beyond insurance and finance as it is a shared and distributed ledger system with two patterns of machine learning use cases:
- Silo machine learning and predictive models for addressing particular segments of the blockchain.
- Model chains that can address the entire blockchain or a segment.
The silo machine learning or predictive model is not anything different from what people currently do with accessible information. But, model chains happen to be far more complicated and can adapt and learn quickly, provided the dependence of the chain.
How will Blockchain and Machine Learning Combine?
Machine learning refers to a technology that depends on extensive data quantities for accurate prediction and model building. When it comes to auditing, organizing and collecting this data concerning the accuracy, a lot of time happens to be invested. Here blockchain comes in. It helps decrease the time taken considerably by utilizing its applications. By utilizing smart contracts, information can be shared securely and directly in this case.
For instance, machine learning models for self-driving automobiles would lead thousands of terabytes of real car driving information. Conventionally, by utilizing various trackers, each of the information like brakes, driving speeds, and fuel consumption would be accumulated. After that, these data would be shared for processing where auditors analyze them and make it free of discrepancies and authenticated before sending it for the processing to the data scientists.
By utilizing digital signatures, smart contracts, however, could considerably enhance the entire process. For the security of the information accumulated, smart contracts can be readily programmed utilizing blockchain technology for directly sending the information from the automobile driver to the data scientist. The data scientists are likely to use this information for building various machine learning models. It indicates that the combination of blockchain technology and machine learning can act as a game-changer for various other technologies because it can add the creation of a new marketplace when it comes to data research.
Similarly, insurance and finance industries can gain a lot from this fusion as collectively they can be utilized in designing tools concerning fraud prevention and identification of frauds. Utilizing machine learning, industrialists can improve supply chain solutions and can also save billions of dollars every year by decreasing wastage and theft.
Benefits of Machine Learning and Blockchain Technology When Combined
When combined, machine learning and blockchain technology enhance and complement each other. It is completely up to the entrepreneurs to find ways for implementing the two for gaining the advantages of greater efficiency, deeper insights and more accountability. Let us check how combining machine learning and blockchain technology can be utilized for the advantages of an organization.
Helps manage the data market
Significant organizations like Amazon, Facebook and Google can access huge pools of information that might be handy for artificial intelligence processes; however, each of these information remains inaccessible to others. By leveraging blockchain technology, small companies and startups can challenge these big tech giants by accessing the identical pool of information along with the same artificial intelligence.
Information within a blockchain remains well secured due to its implicit encryption. Blockchain technology remains perfect concerning the storage of extremely sensitive personal information like medical notes or personal recommendations. When it comes to security improvements, there is another angle. Blockchain technology is secure in its space, but additional layers and applications might be vulnerable. Machine learning can help predict possible deployment or system breaches of blockchain applications.
Helps optimize energy consumption
Being a pretty energy consuming method, data mining refers to one of the significant struggles of the present world. But, science has proven that machine learning can easily deal with this concern. By training artificial intelligence, companies can manage to reduce the energy consumption utilized for cooling their information centres by almost 40%. The identical principle can be utilized for data mining which might lead to reduced costs.
Impact of Blockchain Technology and Machine Learning in Industries
Machine learning and blockchain technology are revolutionizing new industries by transforming their business models, behaviour as well as user experiences. Here is how machine learning and blockchain technology are making strides in numerous industries.
Food and logistics
Machine learning and blockchain technology are increasingly decreasing end-to-end challenges of the supply chain within the industry of food by enabling transparency and accuracy. With blockchain technology, now it is possible to manage associated financial transactions and trace sources of food. Lately, various companies collaborated with food industries and launched microfinancing strategies for blockchain-based food vendors. These are some of those projects that cannot succeed without applying machine learning techniques.
In this case, scientists analyze purchase information from mobile devices and then implement machine learning algorithms for predicting creditworthiness and determining credit scores. With that being stated, lenders receive the insurance required for facilitating repayment and lending utilizing the blockchain hyper ledger. Moreover, various organizations are also considering blockchain development for dealing with food disasters like contamination and wastage.
Being a part of the manufacturing process, organizations have begun depending on smart contracts and blockchain-based processes for enabling security, transparency, compliance checks and production. Rather than planning maintenance schedules based on fixed machine learning, predictive algorithms are being utilized for creating flexible strategies at specific times they need to happen. Product testing and quality control have additionally turned out to become progressively automated with computer vision and adaptive algorithms being utilized to automatically detect faulty products and goods, particularly in sensitive environments.
Energy and utilities
In the utilities and energy industry sector, blockchain happens to be helping to conduct seamless energy exchanges. For example, an energy-based organization can apply blockchain power consumption and production in a peer-to-peer strategy. Smart energy microgrids are additionally increasing its popularity as a medium for developing sustainable energy resources. It can also enable energy conservation generation and reading for regional communities. It is such a technology that utilizes microgrid smart metres collectively with smart contracts for managing and tracking energy transactions.
Potential of Blockchain to be Driven by Quality Data
Blockchain technology comes with real potential as it works with quality data. Presently, data science needs to deal with a lot of pain points related to bad data. Maximum data sources presently are loaded with quality problems like missing data value, errors, junk and duplication. Due to this, if you do not have quality data for working with, you really cannot build high-level machine learning models.
As blockchain technology remains exclusively concentrated on actual transactions, there is very little space for junk. It indicates that the quality of high-level data is likely to empower the algorithms based on the same for being more progressive.
Machine learning and blockchain can be considered as a match made in heaven and is likely to form the base of all the prospective future technologies. There are, nevertheless early days, and technology possesses a long wait to proceed before we begin witnessing actual valuable results.
Future of Blockchain Technology in Machine Learning
Global industries are plagued by intermediaries hu complicate and enhance the prices of business transactions. Blockchain consulting and technology has already disrupted that particular model by enabling peer-to-peer blockchain infrastructure model for users. This innovation even works better when blended with machine learning, and blockchain professionals remain at the centre of it. Cryptocurrency and machine learning could transform the world of financial transactions, and, as time passes, people are going to witness more industry and technology disruptions as a result of blending blockchain emerging technologies and machine learning.
Machine learning and blockchain ideally complement each other and are pretty much the two basic pillars on which future and prospective innovations happened to be built. Machine learning and blockchain together can make groundbreaking innovations, when it comes to the near future, thereby making the human presence more safe and secure.