Blockchain and AI - A Perfect Combination?
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The document discusses the integration of blockchain and artificial intelligence (AI), highlighting their combined benefits such as enhanced security, optimized energy consumption, and improved smart contracts. It also addresses challenges including privacy concerns, scalability, and a lack of regulations. Additionally, it emphasizes the importance of certification courses for professionals seeking to deepen their knowledge in this area.
Blockchain and AI - A Perfect Combination?
- 1. BLOCKCHAIN AND AI 101blockchains.com A PERFECT COMBINATION?
- 2. Why Learn Blockchain With Us? Trusted Strategic Practical
- 3. What is Artificial Intelligence? Artificial intelligence is a human- like intelligence simulation using computers. Typically, computer systems are programmed in a way that will help the AI to imitate human-like actions. Unfortunately, no AI can fully comprehend human activities or actions as they’re very complicated to simulate.
- 4. What is Blockchain? Blockchain is a distributed ledger system that eliminates the need for any centralized authority and offers security and privacy. This technology is perfectly suited to establish a fairer system that will eliminate corruption and fraudulent activities for good.
- 5. Benefits of Combining Blockchain and AI Enhancing Security Optimizing Energy Consumption Managing and Accessing the Data Market Decentralized Intelligence Improved Trust on Robotic Decisions Collective Decision Making Improving Smart Contracts High Efficiency
- 6. AI needs high volumes of data being fed continuously; blockchain can help to store these sensitive data securely. Using blockchain, experts can allow AI to use encrypted data without exposing them. AI can help to find out vulnerabilities in any blockchain application using the machine learning process. Enhancing Security
- 7. The public does not trust AI as it’s impossible to explain why an AI makes a certain decision. Blockchain can record all the decision-making processes and help AI to gain trust from the public. Blockchain can help AI be more transparent and help analyze the data created by any AI. Using blockchain, experts can be sure that all information relating to AI are tamper-resistant and authentic. Improved Trust on Robotic Decisions
- 8. Users can sell access to their personal data on the blockchain and create a new marketplace for data mining for AI. Smaller startups and companies can use blockchain to pool all of their information collection and challenge the tech giants with a strong AI presence. Blockchain ledger can act as the right training database as AI needs to become an expert on a subject matter faster. Managing and Accessing the Data Market
- 9. Data mining consumes a lot of energy, which negatively affects our environment. Machine learning can deal with this type of issue and can offer modern solutions to reduce energy consumption significantly. Blockchain coupled with AI can use AI’s machine learning capabilities to optimize their data consumption, which will lower prices for any mining hardware. Optimizing Energy Consumption
- 10. Blockchain uses smart contracts, which are not smart enough to detect any technical flaws themselves. Therefore, hackers can easily use any loophole to exploit the contracts. With AI, blockchain can help to audit smart contracts and get rid of all technical issues. AI can also review all conditions and adjust the smart contracts based on the requirements. Improving Smart Contracts
- 11. The robotic swarm ecosystem needs to make collective decisions frequently. However, this ecosystem lacks the environment to coordinate with each other. Blockchain’s distributed and decentralized environment can help to make decisions through majority voting. Using blockchain, every single vote can be verified, and the robotic swarm can take tamper-free decisions. Collective Decision Making
- 12. Instead of using a single agent to perform several sub tasks in blockchain AI, it can assign specific tasks to specific agents. All of these agents can have access to the common training data or ledger system to improve their learning capabilities from one another. Also, Cybersecurity AI agents can use the ledger system to coordinate security and solve any scheduling problems. Decentralized Intelligence
- 13. Business processes with multi-users such as business firms, stakeholders or governmental organizations are highly inefficient. With Blockchain AI technology, companies can enable Decentralized Autonomous Organizations without any of their flaws. This Blockchain AI-based DAO can offer fast and automatic verification of assets, value and data among various stakeholders or business participants. High Efficiency
- 14. Centralized data storage is highly susceptible to tampering and third-party attacks. Thus, they are not secured enough to store user information. With blockchain coupled with AI, companies can establish decentralized storage. Decentralized storage can offer cryptographically secured data, which is maintained by AI in a tamper- proof ledger system. Decentralized Storage
- 15. 8 5 % 1 5 % It e m 2 9 5 % It e m 1 5 % 9 0 % 1 0 % 60% 40% Ite m 2 70 % Ite m 1 30 % 6 5 % 3 5 % What Are the Challenges of Blockchain AI Technology? Privacy Concerns Lack of Regulations, Standards, and Interoperability Scalability and Side Chain Trusted Oracles Quantum Computing No AI-specific Consensus Protocols
- 16. Public blockchain ledgers are secured; however, they lack the means to offer user privacy as every information is on the public ledger. In blockchain AI technologies with IoT devices, the privacy concerns are alarming as IoT devices tend to collect consumers personal data. A private blockchain can offer privacy in this regard; however, they are limited in terms of accessing a large amount of data for AI to use. Privacy Concerns
- 17. AI needs to have scalability in order to function and learn properly. However, blockchain can’t offer a fully scalable system yet. Specifically, public platforms tend to lose their performance when a large amount of data needs to get processed at the same time. Blockchain needs more time to mature in order to offer AI the full functionality it needs. Scalability and Side Chains
- 18. Smart contracts heavily depend on oracles to pull data from the outside world to trigger an event as these contracts don’t have that function. Oracles are centralized rather than decentralized, which means they are susceptible to influences. In blockchain AI technology, depending on such Oracles to retrieve data can be problematic as it compromises data integrity. Trusted Oracles
- 19. Blockchain uses consensus protocols to maintain its integrity and security. These protocols are heavily based on blockchain technology itself. If you couple blockchain with AI, blockchain needs to offer AI-specific consensus protocols to enhance the quality of machine learning. Unfortunately, there aren’t any efficient AI-specific consensus protocols that can offer the highest level of security for AI. No AI-specific Consensus Protocols
- 20. To date, blockchain lacks the necessary structure for proper standards or regulations. Ethereum and other platforms do offer standards; however, these standards are not universal; thus, it creates conflicts between two different blockchain platforms. Without specific standards in place, an AI can’t communicate with another AI seamlessly using the platform. Lack of Regulations, Standards, and Interoperability
- 21. Blockchain’s reputation rests heavily on the fact that it can offer cryptography, which is almost unbreakable. But due to the emergence of Quantum Computing, blockchain can lose its value, as Quantum computers can crack the public key encryption. Blockchain AI systems need to offer quantum-safe encryption processes to safeguard the data from cyber-criminals. Quantum Computing
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