Machine learning is a rapidly growing field of artificial intelligence that focuses on developing models and algorithms that learn from experience and improve without explicit programming being input by a human. Essentially, machine learning attempts to imitate the learning mechanism of the human brain. Since it involves independent learning, predicting, and decision-making, it’s seeing increasing investment and execution across several different industries, including crypto.
Blockchain is the core of the cryptocurrency industry, recording and confirming crypto trades as a decentralized, digital ledger. Blockchain makes it possible for crypto value to be transferred online without the need for a bank or intermediary to touch the data, or to make money from the process.
As these two technologies develop, they are beginning to converge. The combination promises huge potential for secure, decentralized, smart, and agile crypto transactions and systems.
Here are some of the key ways in which machine learning and blockchain benefit one another and impact cryptocurrency.
Decentralized AI training
Much of today’s artificial intelligence is centralized, and owned by corporations that use it for very specific applications. Decentralized AI occurs when blockchain networks create the training models. This allows AI to be trained on a collaborative model, distributed across teams. The blockchain network means data generated from the model is easier to share, and improvements can be made quickly where necessary. Using mechanisms such as crypto tokens to incentivize users to provide resources like storage for AI systems on decentralized networks means that there are more distributed networks for AI to be trained on.
Secure data sharing and enhanced security
Blockchain is hugely beneficial for the security of machine learning. Blockchain utilizes cryptography and once a block of data has been added to the chain, it cannot be removed or manipulated. This makes data sharing on blockchain networks very secure. Machine learning systems can therefore share their data much more privately and safely, allowing for multi-party computation for AI training.
Machine learning is also beneficial to the security of blockchain and its uses. Blockchain security can be further strengthened by machine learning algorithms that can quickly and effectively identify anomalies through the learning of data patterns to spot abnormal behaviors.
Autonomous agents
Machine learning and blockchain can be paired to create autonomous agents for crypto wallets. This creates AI bots that can transact independently, and self-sustaining AI agents that can carry out automatic negotiations and transactions.
Recently, Coinbase announced that it managed to achieve its first AI-to-AI crypto transaction powered by machine learning. In this transaction, one AI bot sold crypto to another, and these bots were developed to conduct other transactions with humans, merchants, and other AI bots. AI cannot own bank accounts, but they can ‘own’ crypto wallets.
Decision-making
Machine learning algorithms are perfect for optimizing decision-making processes. Blockchain-based systems that require voting for decision-making, such as decentralized autonomous organizations (DAOs), can be made more efficient by machine learning analyzing voting patterns and historical outcomes. This leads to more consensus-driven decisions and more informed DAOs.
Real-world use cases
Here are some of the use cases that flourish when machine learning and blockchain are combined:
- Credit risk assessment, using historical and broad data sets to determine the probability of default, etc.
- Interest rate determination.
- Decision-making for DAOs.
- Fraud detection, such as malicious programs used for crypto jacking or learning frequently used scams.
- Crypto trading, learning profitable trading strategies.
- Optimizing strategies for crypto mining.
A partnership built for crypto
Advancements in machine learning are pushing how blockchain technology can support crypto innovation, as well as its usability and application throughout DeFi. Whether that's in decision-making, AI bot autonomy, security and the training of future AI models, digital assets will continue to be innovated by advances in machine learning technology and its partnership with blockchain. As these two technologies are increasingly integrated, machine learning enhances the intelligence of blockchain, and blockchain helps to push how much machine learning can do. Together, they are reshaping the future of crypto and creating exciting new use cases.
