Blockchain technology has created waves in the world of IT and fintech. The technology has a number of uses and can be implemented into various fields. The introduction of Artificial Intelligence Training (AI) makes blockchain even more interesting, opening many more opportunities. Blockchain offers solutions for the exchange of value integrated data without the need for any intermediaries. AI, on the other hand, functions on algorithms to create data without any human involvement.
Integrating AI into blockchain may help a number of businesses and stakeholders. Read on to know more about probable situations where AI integrated blockchain can be useful.
Creating More Responsive Business Data Models
Data systems are currently not open, and sharing is a great issue without compromising privacy and security. Fraudulent data is also another issue which makes it difficult for people to share data. Ai based analytics and data mining models can be used for getting data from a number of key players. The use of the data, in turn, would be defined in the blockchain records, or ledger. This will help data owners maintain the credibility, as the whole record of the data will be recorded.
AI systems can then explore the different data sets and study the patterns and behaviors of the different stakeholders. This will help to bring out insights which may have been missed till now. This will help systems respond better to what the stakeholder wants, and guess what is best for a potentially difficult scenario.
Creating useful models to serve consumers
AI can effectively mine through a huge dataset and create newer scenarios and discover patterns based on data behavior. Blockchain helps to effectively remove bugs and fraudulent data sets. New classifiers and patterns created by AI can be verified on a decentralized blockchain infrastructure, and verify their authenticity. This can be used in any consumer-facing business, such as retail transactions. Data acquired from the customers through blockchain infrastructure can be used to create marketing automation through AI.
Engagement channels such as social media and specific ad campaigns can also be used to get important data-led information and fed into intelligent business systems. This will eventually help the business cycle, and eventually improve product sales. Consumers will get access to their desired products easily. This will eventually help the business in positive publicity and improve returns on investments (ROI).
Digital Intellectual Property Rights
AI enabled data has recently become extremely popular. The versatility of the different data models is a great case study. However, due to infringement of copyrights and privacy, these data sets are not easily accessible. Data models can be used to show different architectures that cannot be identified by the original creators.
This can be solved through the integration of blockchain into the data sets. It will help creators share the data without losing the exclusive rights and patents to the data. Cryptographic digital signatures can be integrated into a global registry to maintain the data. Analysis of the data can be used to understand important trends and behaviors and get powerful insights which can be monetized into different streams. All of this can happen without compromising the original data or the integrity of the creators of the data.