In the last decade, Artificial Intelligence (AI) and blockchain technology have emerged as two of the most innovative technologies. AI enables machines to assist humans in decision-making, whereas blockchain technology is a distributed ledger that enables secure, transparent, and tamper-proof applications. AI (Artificial Intelligence) and blockchain are proving to be a highly effective combination, enhancing nearly every industry in which they are implemented. AI can efficiently sift through massive datasets to generate novel scenarios and identify data-driven patterns. Blockchain facilitates the elimination of flaws and fraudulent data sets. New classifiers and patterns generated by AI can be authenticated using a decentralized blockchain infrastructure. The convergence of AI and blockchain technology has the potential to revolutionize numerous industries by enhancing their security, transparency, and overall efficiency.
How Blockchain and AI (Artificial Intelligence) Work Together
Blockchain networks are decentralized by design, ensuring that there is no singular point of control or failure. While decentralization improves security, it presents numerous scalability and efficiency obstacles. Enter AI, which is prepared to optimize blockchain data processing and storage. A significant limitation of blockchain technology is its comparatively lethargic transaction speed compared to conventional payment systems. By predicting and prioritizing transaction processing, AI algorithms can save the day, facilitating faster confirmation times and a seamless user experience.
In addition, these intelligent systems can identify patterns of network congestion, enabling the blockchain to adapt and maintain optimal performance dynamically. AI (Artificial Intelligence) continues to evolve. It can also strengthen the integrity of the blockchain network by detecting and preventing fraudulent activity. Algorithms utilizing machine learning (ML) examine transaction data to identify suspicious behavior and flag potentially malicious actors. This proactive security strategy can not only deter malicious actors but also enhance the network’s credibility.
How AI Can Add to Blockchain
The convergence of AI and blockchain creates perhaps the most trustworthy technology-enabled decision-making system in the world, which is virtually tamper-proof and provides accurate insights and decisions. It contains several benefits, like:
- Improved business data models
- Globalized verification systems
- Innovative auditing and compliance systems
- Intelligent finance
- Transparent governance
- Intelligent retail
- Intelligent predictive analysis
- Digital intellectual property rights
How Blockchain Can Add to AI
The addition of blockchain to AI can establish controls for AI models. Blockchain, when administered via a multi-user workflow interface, generates a tamper-evident audit trail for every aspect of AI model management, including:
- Verifiable id of all parties utilizing blockchain as a certificate authority
- Permanent record of the AI model’s original intent
- Document ongoing AI model governance, evaluations, and ratings
- Offering a single source of truth for all AI model components, including training data and algorithms
- Establishing a permanent record of AI engineers’ and MLOps’ experiments
- Providing consumer trust logos so that models’ blockchain histories can be readily validated
- To serve as a mobile memory repository for an AI model
Technical Enhancements That AI Can Enable
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- Security: With the implementation of AI, blockchain technology becomes safer by securing the deployment of future applications. It is exemplified by AI algorithms that increasingly determine whether financial transactions are fraudulent and should be blocked or investigated.
- Efficiency: AI can assist in optimizing calculations to reduce the miner burden, resulting in less network latency and faster transaction processing. AI enables the reduction of blockchain technology’s carbon footprint. In addition to reducing the cost imposed on miners and the amount of energy used, the replacement of miners with AI machines would also reduce the cost imposed on miners. As the data on blockchains grows minute by minute, AI’s data pruning algorithms can be applied to blockchain data to autonomously remove data that will not be used in the future. AI can even introduce new decentralized learning systems, such as federated learning or new data-sharing techniques, which make the system significantly more effective.
- Trust: The immutability of blockchain recordings is considered one of their unique selling points. Applied in conjunction with AI, clear recordings allow users to follow the system’s reasoning. In turn, this increases machine-to-machine interaction, allowing algorithms to share information and coordinate large-scale decisions.
- Better management: When it comes to deciphering codes, human experts become more proficient with experience. A mining algorithm powered by machine learning can obviate the need for human experience because it can virtually perfect its skills if fed the appropriate coaching data. Thus, AI also improves the management of blockchain systems.
- Privacy and new markets: Securing private data invariably results in its sale, leading to data markets/model markets. Simple and secure data sharing facilitates the growth of minor market participants. By employing “homomorphic encryption” algorithms, the privacy of blockchain can be enhanced. Using homomorphic algorithms, it is possible to execute direct operations on encrypted data.
- Storage: Blockchains are ideal for storing highly sensitive, personal data that can add value and convenience when processed intelligently by AI. This is exemplified by intelligent healthcare systems that make accurate diagnoses based on medical imaging and records.
Conclusion
The convergence of AI and blockchain technology is paving the way for smart contract ecosystems that are more intelligent, secure, and streamlined. It will be fascinating to observe the evolution of both AI and blockchain as they seek to enhance the user experience.
