Distributed Intelligence
Convergence of Artificial Intelligence and Blockchain will lead to new possibilities. This article talks about how Artificial Intelligence is and can add value to the existing blockchain technology.
Fundamentally blockchain and Artificial Intelligence are non-convergent technologies, trust is enforced by decentralization in the former while the later is relies on centralization of data. Hence, at a fundamental level Artificial Intelligence cannot provide value to the decentralized implementation of blockchain albeit, it can be leveraged to improve the technology stack itself at a broad level.
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My readers are predominantly AI/Data Science focused so let me go over briefly on the fundamentals of blockchain.
A blockchain can be defined as an immutable ledger(database) for recording transactions, maintained within a distributed network. (Source. Arxiv)
The data is stored in structures called blocks, which are connected to each other in a chain through a hash (each block linked to the previous block via its hash). To add a block to the blockchain, mining is used. Mining means solving the “mathematical hash algorithm” which is also “proof of work” (Nakamoto, 2008) to arrive at the correct answer. To learn a little more about Bitcoin and Blockchain in really Laymen’s terms please visit — Laymen’s guide. To learn in detail about how mining and hashes work, please visit — how does bitcoin blockchain mining work?
Adding a block requires a ton of energy and hardware capacity. Some variations of the of these problems also include the Byzantine-fault-tolerant algorithm (Castro and Liskov, 2002) and the Quorum slicing (Mazieres, 2016). Blockchains may execute arbitrary, programmable transaction logic in the form of “smart contracts”, as exemplified by Ethereum.
Blockchain provides a decentralized model for security and privacy where Trust is embedded in the distributed network and not centralized with institutions or gatekeepers. With this change in the architecture there are different problems of energy consumption, efficiency in a decentralized network and problems related to mining which might arise. These problems can be solved partially or the efficiency of their solutions can be improved by AI.
Improvements of AI on Blockchain:
Security: The Blockchain itself is a very secure technology. However, a lot more data and analysis of that data from blockchain applications can be used to recognize discerning patterns in that data to inform the AI algorithm and yield insights. Owners and operators of critical blockchain applications might want insurance contracts against cyber-attacks and harmful conditions and a smart contract can be used to determine when the payout event is triggered (Levine, 2014).
Privacy: Our information (social,health and public) information is stored in databases centralized with different companies which are private and public. Blockchain can enable privacy by securely helping us store all our information only sharing what we want to share with the people whom we want to share it with. ‘Homomorphic Encryption’ allows for computations to be done on encrypted data without decrypting the data first. The Enigma project (Zyskind et al., 2015) which was developed into ShareMind is used by the Government in Estonia for their citizens. For complexity reduction and optimization for the Enigma concept deep learning is employed.
Mining Hardware: Mining requires special mining hardware. Computations for Artificial Intelligence require special GPUs for processing. At a hardware level, both AI and mining require differentiated hardware for the purpose of complex calculations. AI Crypto is in this space. As hardware for mining evolves it will include components which can leverage AI to improve the mining efficiency.
Energy (Energy consumed by mining): Artificial intelligence for energy conservation in buildings (Dounis, Anastasios, 2010) already helps in improving energy conservation using AI. Mining also consumes a lot of energy. Porsche is testing blockchain and artificial intelligence applications in its smart vehicles.(Source. Bitcoinist) The Porshe Panamera model already uses blockchain technology, which XAIN introduced using an energy-efficient mining process. This is a field to watch out for as AI is mature to tackle the energy problem and energy used in mining is primed for disruption.
Transaction Verification and Efficiency: Blockchain maintains a ledger for recording transactions. Time and money can important areas to improve transaction efficiency. Cost per transaction on blockchain needs improvement. Right now it takes an average time of 78 minutes to confirm a bitcoin transaction, according to Blockchain.com. Artificial Intelligence might be used to improve node selection for execution of proof of work. Transaction verification is another area where AI can be leveraged. (Arxiv- BlockChain and Artificial Intelligence). For verification, AI can be used to select heuristic strategy automatically to need-to-prove conjecture’s features and the corresponding axioms.
In conclusion, Artificial Intelligence and Blockchain are both disruptive technologies in their own right. This article explains how skill in one domain can be leveraged elsewhere which is a fundamental thought for any new technology. There are companies which have already started working in this vertical where the non convergent technologies have some convergence. Trust and Integrity are fundamental selling points of blockchain and infusing Artificial Intelligence should not disturb that balance. All we can do is wait and watch as to where this will take us, but rest assured the future will be bright.
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The sole motivation of this blog article is to learn about AI technologies and how they can help blockchain. All data is sourced from online public sources and research papers(cited). I aim to make this a living document, so any updates and suggested changes can always be included. Please provide relevant feedback.
