Blockchain technology is the backbone of Bitcoin. While the most prominent and earliest real application of blockchain is Cryptocurrency, it isn't limited to it. Cryptocurrency is just the tip of the iceberg when it comes to blockchain technology. There’s a lot more to it. Along with blockchain, another concept that's in the spotlight is machine learning. And when you combine blockchain technology and machine learning, you simply tap into a gamut of possibilities for the tech world. Together, blockchain and machine learning can revolutionize the tech industry for good.
However, first things first.
What is Blockchain technology?
Blockchain is a type of Distributed Ledger Technology (DLT) and can digitally record transactions. The name itself reflects its function: Block + Chain. The USP of blockchain technology is it makes it next to impossible to modify or hack the system.
Components of Blockchain
Blockchain has three major components:
Blocks
Nodes
Miners
The entire blockchain system comprises of nodes that are transparent and connect to the distributed ledger, as shown below:
Blocks
Blocks are built in such a way that there is a certain storage capacity for it. Once the storage capacity of the block is filled, the data os stored in new blocks. These blocks are then linked or chained to the previous blocks. This way the data is structured into a linear and chronological chain of blocks.
When a block is generated, each block has two numbers making it unique. One is nonce, a 32-bit whole number that is generated randomly. This creates the hash__, a 256-bit number. Once the data or transaction is recorded in the block, the nonce is enabled which is the permanent number. The hash value, on the other hand, can be mined.
Nodes
Nodes are the type of electronic device which helps in maintaining the copies of the blockchain.
Miners
The validation process of each transaction is called mining. Miners secure the network and confirm every transaction.
Properties of Blockchain
Decentralized and Distributed: The blockchain is not owned by a single computer or organization. Each participant has a copy of the blockchain. The system is a distributed ledger connected via the nodes and is transparent. Every time a new transaction happens, it is recorded and added to each of the participants’ ledger. Each participant has a unique alphanumeric identification number that shows their respective transactions.
Secure: Each block has its own unique nonce and hash number. Along with this the blocks also have references to the hash and timestamp of the previous block. In case, any one value is misaligned, then cross-referencing with other values helps in the detection of the fraud making blockchain a secure system.
Immutable: Each validated transaction on the blockchain is unalterable.
Time-stamped: Each block when added to the chain is imprinted with an irreversible timestamp.
Concordance: To change any data or information on the blockchain, requires the validation of the transactions (or the mining process) not only for the block in which the data pertains but also in all the preceding and the succeeding blocks. Therefore, all the nodes must accept the needed change
How does blockchain function?
Steps of how blockchain functions are:
First, a transaction is requested and a block containing this transaction is created.
This block is then sent to a peer-to-peer network of nodes. It is passed from each node to authenticate the transaction request.
All nodes must validate the transaction before adding it to the blockchain.
Once the nodes verify the transaction, they receive a reward as ‘Proof of Work’.
On the validation of the transaction, a new block, which contains the requested transaction is added to the blockchain and the transaction is then complete.
Blockchain technology is used across various industries, such as banking & finance, payments, cybersecurity, smart contracts, supply chain, healthcare, legal contracts, state identification, and the company’s product inventory.
To learn more about blockchain, follow the blockchain timeline here. In addition, some blockchain project ideas are:
Crowdfunding with Trust using Smart Contract
Reduction of Insurance Frauds
Electronic Voting System
Securitization of Medical Records
Identification of Fake Product Systems
Tracking the exact location of Shipment and Food
Now that we know what blockchain is and how it works, let’s quickly go over what machine learning is.
What is Machine Learning?
We have talked about machine learning in great detail in our blogs over the years (and we continue to do so). To recapitulate –
Machine Learning, a segment of Artificial Intelligence (AI) is the study of algorithms and models that enables the system to automatically learn and improve themselves from the experience with minimal human intervention. This framework is dynamic and does not have predefined hard-coded rules.
If you are new to the concepts of machine learning, here are some reading materials for you to catch up:
If you want to step into the field of machine learning and looking for a comprehensive course, you can enroll in our great machine learning course, and learn from industry experts.
Machine learning takes historical data and identifies relationships among features. The machine then predicts new data using mathematical relationships to build a dynamic, accurate, and stable model.
Now, let us address the elephant in the room.
What happens when you combine Blockchain and Machine Learning?
At its core, blockchain technology is a decentralized, distributed, and irreversible ledger that stores encrypted data. It is known for its reliability and transparency. On the other hand, machine learning automates analytical model building, identifies patterns and trends, and makes decisions without any explicit programming. Both blockchain and machine learning is headed north in terms of growth. Predictions show that AI will contribute up to $15.7 trillion to the world economy by 2030, while blockchain will support the global movement and tracking of $2 trillion of goods and services by 2023.
The impact of Artificial Intelligence and Blockchain on the world economy is a testament in itself to where these technologies are going to take us in the future. Needless to say, Blockchain and Machine Learning together make a powerful combination set to revolutionize industries. The integration of Blockchain and Machine Learning, supported by blockchain app development services, offers:
(1) Open market for data
Artificial Intelligence and its sub-branches, Machine Learning and Deep Learning, thrive on data. Stalwarts and giants such as Google, Amazon, and Facebook have large data sources that offer valuable insights. However, these companies restrict access to and use of this data. Blockchain can help resolve this restriction. Blockchain's distributed system can share data with everyone on the network through peer-to-peer connections. Blockchain enables data access that can boost AI businesses and their processes. The more data we have, the better we can train models to derive meaningful insights.
(2) Enhanced security and large-scale data management
Blockchain's decentralized ledger provides a safe, secure space to store and share encrypted data for machine learning. As we know, blockchain blocks have unique identifiers and are time-stamped to detect fraud and prevent hacking. Also, every new transaction goes through multiple nodes for verification, and the data isn't stored in a single place, making it highly secure.
Machine Learning can benefit from this connection because it needs large amounts of data to learn from. It also helps Blockchain boost security by flagging gaps based on historical data and analysis. Additionally, developers can use smart contracts to set in permissions levels, control the data flows, and track the digital identity.
(3) Provide trust
Sharing data of any nature requires trust, especially on the networks. Blockchain is traceable and auditable, with a vast interconnected network that can track machine-to-machine communication in Machine Learning.
It also makes Machine Learning more coherent and understandable as every decision in Machine Learning can be traced back to its origin. This helps to build trust and reliance on this advanced technology. Additionally, Blockchain started with Bitcoin, which means trading digital currencies anyway needs strong trust to start with!
(4) Accurate model predictions
The fundamental principle of a good model is good data. It is strongly emphasized that garbage in (poor data) leads to garbage out (a poor model). Blockchain ensures that high-quality data reaches machine learning algorithms. Blockchain systems are immutable, meaning the data cannot be altered, and they solve redundancy by cross-referencing and authenticating every transaction. This, in turn, helps build better models with higher predictive power.
(5) High computing power
Blockchain and Machine Learning joining hands will not only provide access to more and larger data, but the duo can also become the next supercomputer! Participants or users on the network can connect and add more computing power by sharing it, bringing more neon bulbs to their combined computational capacity.
How is this combined technology useful?
The combined technology is used by some of the companies in the following way:
Amsterdam-based SingularityNET is a decentralized marketplace for Artificial Intelligence algorithms. It is an open-source protocol and a collection of smart contracts that lets AIs coordinate at scale. Smart contracts are programs that automatically execute when certain predefined conditions are met. These agreements, codes, and programs are stored on the blockchain network. SingularityNET focuses on creating a ‘self-maintaining network powered by AI.’ Its high-level network architecture diagram as follows:
SingularityNET’s humanoid robot, Sophia, uses blockchain technology to improve its intelligence for answering questions and interpreting situations in real time.
The robot has a younger sister, Grace, in development, focused on eldercare and healthcare robotics, and will employ OpenCog proto-AGI architecture along with “a customized array of neural networks.”
DeepBrain Chain (DBC) is another blockchain-based computing platform for Artificial Intelligence. The platform is operational on a decentralized neural network focusing on reducing the participant’s costs for the processing power.
Another application of Blockchain and Machine Learning is Numerai. It is a blockchain-based hedge fund that uses ML. It uses these technologies to change the fund manager's incentive and compensation structure.
Blockchain and ML in automobile
The German automobile maker Porsche AG is the first carmaker to employ blockchain technology in a car by partnering with a Berlin-based AI company, XAIN. The drivers gather real-time traffic data with the help of their smartphones. This data is locally encoded in the blockchain and shared with other drivers. Other users can access it temporarily as well. The owner also receives a notification about who accessed it, where, and when. Since on the blockchain, the data is easily traceable, auditable, and securitized, and useful for autonomous driving and for predictive purposes as well.
Application of blockchain and ML in software and cyber security
Colony is a platform that uses decentralized autonomous organizations (DAO) to connect with professionals. They call themselves a platform for open organizations. They use Artificial Intelligence to match individuals with companies and focus on building an ecosystem for blockchain companies. Here’s more detailed information on DAO –
The cybersecurity environment can heavily leverage the combination of Blockchain and Machine Learning. Together, they can detect potential cyberattacks and provide stronger security. Blockchain with its double security gates of the nonce, hash value with authentication of transaction requests at every nodal level, adds an extra layer of shield to this already decentralized distributed network. Also, the Machine Learning models are trainable to detect real-time threats and these models can learn the behavior of the attackers.
Blockchain and machine learning: FAQs
Is it good to learn Blockchain?
Blockchain offers cutting-edge technology and is an emerging skill in the IT industry. It promises a high-paying career because it requires expertise in cryptocurrency. Various industries use it, and it will soon be a high-demand skill. Along with this, by learning how blockchain works one can make wiser investments, trade, and shortlist initial coin offerings (ICO) as well.
What is data sharing in Blockchain?
Blockchain is a data structure that shares or distributes digital data across a distributed network rather than keeping it with a single provider. This enables data sharing on a blockchain.
Each participant, or node, has a copy of the blockchain, and every new recorded transaction is added to the participant’s ledger. A blockchain is a decentralized, distributed ledger.
How do I start a career in Blockchain?
If you are a beginner, start with the basics: what blockchain is and what miners are. To start a career in the blockchain, you need to know:
Cryptography
Distributed Computing and Shared Ledger
Consensus or Trust Mechanism
Mechanism Design
Smart Contracts
Blockchain and Machine Learning together here not only stay but change the way the world functions. These technologies are extremely powerful on their own, and together they are nothing less than disruptive.