We all know that artificial intelligence (AI) and blockchain happen to be the two most disruptive technologies for the B2B environment. While Blockchain is the distributed database system popular mainly for democratic access to data and robust data security measures, artificial intelligence (AI) on the other hand is capable of mimicking human intelligence to perform a whole array of tasks across digital platforms. While Blockchain security is the new height for data security, AI is the new pinnacle of computing power. Now, these two technologies are joining hands to deliver more efficiency and context-aware output for the users.
Most experts are of the opinion that the coming together of these two technologies will have serious implications across business niches and applications in the years to come. These two technologies can also alter the business paradigm for organizations across various needs ranging from data security, business analytics, marketing and sales, supply chain management and logistics and several others. In the years to come, we can see Blockchain and AI-based applications for AI marketplaces, predictive models for hedge funds and investment management platforms.
Complementary Role of AI and Encryption
Blockchain is considered as an ideal technology to store sensitive and personal data that have a mission-critical role in different contexts of our lives. The precise diagnosis carried out by the modern healthcare systems on the basis of our medical records and scans is a nice example of the intelligent data protection and accessibility ensured by encryption.
Blockchain ledger system is known to store data in an encrypted state and this requires the private keys to be kept in a safe and secure manner. This is where AI can play a big role in strengthening the encryption-based security further. AI-powered algorithms by ruling the encryption for data sets can control access to mitigate security risks.
Blockchain Explaining AI-Based Decisions
There are many decisions taken by the AI-based systems and algorithms that are really hard for general human understanding. Because of handling a large number of variables and metrics for arriving at a decision, the AI-based decision-making processes tend to be incredibly complex.
But human minds are often intrigued by the logic behind such decisions and so there is no dearth of effort to understand the AI-based decisions. Actually, such understanding will also enrich human comprehension about variables and the logical process undertaken by machines. For future scientific innovations, human understanding of AI-based decisions is crucial.
This is where the Blockchain ledger system can help by recording all the AI-based decisions and conclusions for every data point. When the entire maze of decisions across a multitude of data points is registered within blocks of data, the auditing of the decision-making process becomes easier than ever before. Based upon such auditing and understanding of AI decisions, future AI algorithms and utilisations can be designed more appropriately.
More Efficient Handling of Blockchain by AI
Computers in spite of their faster computational capabilities have always been very stupid simply because to perform any task you need to instruct them explicitly. Only with detailed and very explicit instructions computers can get a task done. This is why for managing Blockchain data a huge amount of computing power is required. The primary objection to the Blockchain database has been this need for a huge volume of computing power. The data mining tasks associated with cryptocurrencies spent a huge amount of computing power ever since the Bitcoin came and Blockchain technology took shape.
Instead of applying all possible combinations of characters to match encryption and verify transactions, AI-powered intelligent data mining can save a lot of these computing power and manpower. Just imagine how efficient and productive data mining efforts can be if intelligent technologies like AI and Machine Learning are utilized in this process. With the AI-based algorithms being capable of getting proactive data training, more effective and efficient data mining output in far less time is expected. This is why AI power can actually help to manage blockchain-based database systems better than humans.
The Coming Together of Blockchain and AI
The biggest impetus for bringing together blockchain and AI has actually originated to make use of Big Data analytics. Big Data analytics which basically involves digging huge volumes and a variety of data for relevant and context-aware insights and revealing relations of different data points is relied upon to understand customer intent, predict customer behavior, trends and to target customers with the most appropriate advertising and marketing plan. When enterprises try to have a deeper understanding of customers to cater to services and products better, they depend upon data-centric insights offered by Big Data Analytics.
AI by providing the most relevant data-driven insights and by coming out with appropriate decisions, further augment the capacity of data Analytics and data-centric business processes. On the other hand, Blockchain by helping with the democratic access to this huge volume of data while completely preventing all tampering and breaching efforts, give AI-powered data analytics the befitting data ledger system.
In this respect, the example of DeepBrain Chain, the distributed AI-powered computing platform deserves our attention. According to the company, DeepBrain Chain boasts of a marketplace of resources for AI hardware computing. This marketplace of AI computing resources can be accessed by all participants in the system. This is the first of its kind distributed ledger system for AI computing resources.
Conclusion
With so much on offer from these two promising and era-defining technologies, they are very likely to join hands and deliver a more formidable force for the computing of the future years. While Blockchain will continue to remain as the most accessible and fully tamper-proof database ledger system, AI will continue to address the shortcomings and lack of computing prowess of humans with more proactive and constantly learning intelligent systems. Their unified and complimenting power will continue to evolve and spread across new use cases and contexts.
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