Artificial Intelligence, Machine Learning, Internet of Things, Cloud, Blockchain – With the advent and adoption of these technologies, we are experiencing the next big technological revolution after the internet, popularly termed as “Fourth Industrial Revolution.” However, these technologies as a standalone are not enough to bring the much-needed change. The true potential of these technologies can be unleashed only when they can be used in parallel, and one such combination is Blockchain and AI.
According to an Artificial Intelligence Market Forecast by Tractica, the global AI industry is expected to grow from the present $9.5 billion to $118.6 billion by 2025. This fact is further strengthened by Deloitte’s Global Blockchain Survey 2019, in which 53% of all professionals responded that Blockchain is their organizations’ primary focus this year.
Both AI and Blockchain are very new to the industry. Many businesses are struggling to understand and implement them. In such a scenario, developing a relevant Blockchain AI project requires expertise and thorough research. To understand how these technologies can be used in combination, let us first briefly discuss their features, their pros & cons, and then we would comprehend how these two can complement each other.
Blockchain – The Trustless Technology
Blockchain is a distributed ledger or database, which stores data in the form of ‘blocks.’ Each block contains information about the previous block, thus forming a ‘chain.’ Using cryptographic encryption, the data on the Blockchain is made virtually tamper-proof and can only be appended. Any edits in the data can’t be made even by the originator of the data.
Blockchain involves peer-to-peer networks that validate each transaction based on the consensus of its participating members (referred to as nodes). Instead of relying upon a central authority, ‘trust’ within the Blockchain ecosystem is established through mathematical processes known as the consensus mechanism.
Any industry that involves large amounts of data, accessed by multiple stakeholders, can benefit from Blockchain implementation. It enables secure sharing and storage of data, and streamlined processes, where taking approvals or arriving at consensus are bottlenecks. However, the current consensus mechanisms deployed by popular Blockchains are resource-intensive, which significantly impact the scalability of the solutions developed based on this technology.
Artificial Intelligence (AI) – The Process Automation Technology
AI is the ability of computers to learn and simulate actions that otherwise are characteristics of human intelligence. AI works with neural networks that strive to emulate the structure and functions of the human nervous system, utilizing Machine Learning (ML). It facilitates the formation and functioning of these neural networks and intelligent algorithms.
AI itself has three different levels, based on the degree of intelligence achieved by the system. First, Narrow or Weak AI – involves algorithms that can perform specific tasks for which it is pre-programmed. Second, General AI – wherein the cognitive abilities of the system are expected to be on par with humans. Superintelligence is the final stage where the cognitive abilities of an intelligent machine would surpass that of an average human.
At present, only Narrow AI is pragmatic, while the other two are only theoretically possible. AI helps in automating the daily routine jobs performed by professionals that are repetitive in nature and do not require much decision making. Considering the volume and criticality of the data fed into the AI algorithm to make them perform as expected, the security of the data becomes a big concern for the businesses.
Blockchain and AI – A Complementary Relationship
When used in parallel, AI and Blockchain can eliminate the limitations of each other that hinder their scalability and adoption.
Massive (and exponentially increasing) energy consumption is a hindrance to the upscaling of the Blockchain technology. Proof of Work (PoW), the commonly used Blockchain consensus mechanism, involves a process of validation known as mining, which requires particular nodes called ‘miners’ to solve cryptographic mathematical puzzles. The process requires enormous computational power and specialized machinery, both of which consume much electricity.
Now, alternative consensus mechanisms such as Proof of Stake (PoS) are being explored, but they require intelligent task handing to work progressively. This is where AI can help by providing smarter alternatives for task handling and replace the present consensus mechanisms.
Data Distribution and Security
Access to large data sets, their seamless management, and data security are fundamental elements in the growth trajectory of AI.
Presently, most AI-based projects need to store data on centralized servers or the cloud. In such cases, there is a single-point-access to the data, which is more vulnerable to security attacks.
Being a decentralized system, Blockchain provides the ideal solution to centralized data storage. It allows AI-based systems to store their data on multiple systems spread across the globe and at the same time, access them seamlessly. It also enables access to a much-diverse data set, facilitating better and more profound learning of AI/ML algorithms.
The question of data security becomes even more pertinent when it comes to the applications of AI in industries involving sensitive data, such as healthcare and finance. In such industries, the cryptographic encryption provided by Blockchain is essential for ensuring complete protection of the data.
The users of Blockchain-based applications are empowered with full control over their data in terms of granting or revoking access.
Presently, it is the centralized platforms that monetize users’ data. Using Blockchain, users can monetize their data. It also means that users are more willing to share their information, and the data thus produced can be used for the development of AI systems.
It is a fact that AI can thrive in a genuinely democratic environment where providers and users of data can directly interact with each other, without relying on intermediaries.
Blockchain AI Projects
Let’s discuss some of the live projects using Blockchain and AI.
Based out of Amsterdam, this non-profit organization was formed in 2017. Following the visions of its Founder & CEO, Ben Goertzel, SingularityNET is a decentralized, AI marketplace.
Accessible to AI vendors and users, the platform facilitates the exchange of AI hardware or services, in return for other services or cryptocurrencies. For financial transactions on the network, the platform has a native cryptocurrency, namely the AGI token.
To ensure a safe environment for transactions, the platform also uses smart contracts that automate the process of compliance by digitally encoding the terms and conditions of the agreement.
The app provides the discovery services and matches AI vendors and users based on the details of the query and the services asked for. A service provider on the platform is known as an ‘agent.’ Although the project is still in its very early stages, it has the potential that inspired investors to pump in $36 million.
DeepBrain Chain (DBC)
This Singapore-based NGO was formed in 2015 by a group of 35 members, to construct a distributed AI platform using Blockchain.
It is a good instance of the relationship between Blockchain and Machine Learning, highlighting the possibilities of decentralized machine learning. Here, each node on the network acts as a training point for AI algorithms.
The DeepBrain Chain allows organizations or individuals to leverage the computational power of the nodes for their AI projects. Each node is classified based on its computational power. For transactions, the platform has a native cryptocurrency, commonly known as the DBC coin.
To enhance their potentials, and to take their endeavors a step further, DBC has partnered with SingularityNET in 2018. In this, ‘agents’ on the SingularityNET platform can leverage the computational power offered by the members of DBC.
Quite different from the above two, it is an investment management platform, founded in 2017 and based in Luxembourg. Using AI, it offers an automated solution for investors to create and manage their cryptocurrency portfolio.
For more excellent usability, the platform offers varying degrees of autonomy to the users. While individual investors can avail the fully autonomous versions, agencies and enterprises have the option for greater customization.
The platform involves AIEVE, a machine learning-based AI advisor, which can efficiently analyze market trends by leveraging data from a variety of sources. To make things better, the algorithm can process up to eight different languages.
Atreus, Peculium’s investment platform, enables investors to create and deploy smart contracts, meant to automate the process of compliance and return.
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