AI and blockchain are proving to be a pretty powerful combination, developing almost every industry in which they are applied. Blockchain and artificial intelligence combine to elevate everything from food supply chain logistics and healthcare record sharing to media royalties and financial security.
AI can effectively mine a huge dataset and create newer scenarios and discover patterns based on data behavior. Blockchain helps to effectively remove errors and fraudulent datasets. New classifiers and models created by AI can be validated and authenticated on a decentralized blockchain infrastructure. This can be used in any consumer-facing business such as retail operations. Data from customers via blockchain infrastructure can be used to create marketing automation via AI.
How Can Artificial Intelligence Be Added to Blockchain?
The convergence of artificial intelligence on the blockchain creates perhaps the world’s most reliable technology-enabled decision-making system that is virtually tamper-proof and provides robust insights and decisions. It has several advantages such as:
- Improved business data models
- Globalized verification systems
- Innovative audits and compliance systems
- Smarter finance
- Transparent governance
- Smart retail
- Intelligent predictive analytics
Technical Improvements that AI Can Deliver
Security: Blockchain with the application of AI technology becomes more secure, making future application deployments secure. A good example is AI algorithms, which are increasingly deciding whether financial transactions are fraudulent and should be blocked or investigated.
Efficiency: Artificial intelligence can help optimize computations to reduce miner overhead providing less network latency for faster transactions. AI enables to reduce the carbon footprint of blockchain technology. If artificial intelligence machines replace the work done by miners, the cost to miners will decrease with the energy expended. As data on blockchains grows every minute, AI’s data pruning algorithms can also be applied to blockchain data, which automatically prunes data that is no longer needed for future use. AI can even introduce new decentralized learning systems such as unified learning or new data sharing techniques that make the system much more efficient.
Trust: The cast-iron records of the blockchain are considered one of its USPs. Its implementation along with AI means users have clear records to follow the system’s thinking process. This helps bots trust each other, increases machine-to-machine interaction, and allows them to share data and generally coordinate decisions.
Better Management: When it comes to code cracking, human experts get better with practice over time. A machine-learning-powered mining formula can eliminate the need for human experience, as it can almost completely sharpen their skills if fed with the right coaching information. Therefore, AI also helps in higher governance of blockchain systems.
Privacy and New Markets: Securing private data always leads to its being sold, resulting in data markets/model markets. Markets are getting easy, secure data sharing that helps smaller players achieve Blockchain privacy can be further enhanced by executing “Homomorphic encryption” algorithms. Homomorphic algorithms are algorithms that use which operations can be performed directly on encrypted data.
Storage: Blockchains are ideal for storing highly sensitive, personal data that can add value and convenience when intelligently processed with artificial intelligence. A good example is smart health systems that make accurate diagnoses based on medical scans and records.
Artificial Intelligence and Blockchain Applications
Intelligent Computing Power
It will run on a blockchain with all its encrypted information If you were, you want an enormous amount of processing power in a laptop. For example, hash algorithms used for mining Bitcoin blocks take a “brute force” approach, which consists of systematically ranking all possible candidates for the solution and checking whether each candidate meets the wording of the question before approving a deal. AI gives the US a chance to maneuver far from that and tackle tasks with a very smart and economical approach. Imagine a machine learning-based algorithm that, when fed with appropriate training data, can improve its skills in ‘real time’.
Building Various Datasets Information
Unlike transaction-based projects, blockchain technology creates suburban, transparent networks that can be accessed by anyone anywhere in the world in the case of a public blockchain network. By making the APIs Associate in Nursing on the blockchain, it allows AI agents to communicate. As a result, various algorithms can be designed on various information sets.
Data Protection Information
Blockchain is essentially a technology that allows data to be stored encrypted on a distributed ledger. It allows the creation of completely secure databases that can be reviewed by approved parties. Medical or financial data is too sensitive to be delegated to a single company and its algorithms. Storing this data on a blockchain that can be accessed by an AI, but only with permission and after going through appropriate procedures, can give us tremendous advantages of personalized recommendations while keeping our sensitive data safe.
Data Monetization
Another turbulent innovation that can be made by combining 2 technologies is knowledge validation. Monetizing collected data is a huge source of income for large companies like Facebook and Google. The fact that others decide how to sell data to profit businesses shows that data is being used as a weapon against us. It’s important to understand this in order to combat biased algorithms and generate diverse datasets in the future. The same is true for AI programs that require our knowledge. For AI algorithms to learn and improve, AI networks will need to purchase data directly from their creators through data marketplaces. This would create the entire method much more accurate than it currently is, without the tech giants exploiting their users. Such an information marketplace would also open up AI for smaller companies. Developing and nurturing AI is incredibly expensive for companies that don’t generate their knowledge.
Relying on Artificial Intelligence Decision Making
Using blockchain technology, there is an immutable record of all data, variables and processes used by AIs for decision making processes. This makes it much easier to supervise the entire process. With proper blockchain programming, all steps from data entry to results can be observed and the observing party will make sure that this data has not been tampered with. It creates trust within the results drawn by artificial intelligence programs. This is a necessary step as individuals and companies will not start using AI applications if they do not understand how they work and what information they base their decisions on.
Real-Life Applications
1. FINALIZE
Finalize blockchain for building applications aimed at improving civil infrastructure and is a software platform that uses machine learning. The company’s tools automate and accelerate construction industry workflow, management and verification processes, and its technology integrates with wearable devices to meet safety regulations. Finalize aims to make key processes more efficient while maximizing return on investment in an industry whose revenues are projected to reach $15.5 trillion by 2028.
2. BLACKBOX AI
Blackbox AI develops artificial intelligence tools for emerging technologies. The company’s engineers are creating a customized information architecture that powers everything from machine learning and natural language processing to blockchain tools. In addition to developing infrastructure for blockchains, the company also offers consulting services focused on how its products can maximize a blockchain’s potential. Blackbox AI engineers are some of the world’s largest technology organizations (including Apple, Intel, NVIDIA, and MIT) and have designed AI-based tools for everything from virtual reality to natural language processing.
29186
