The world is getting increasingly interconnected, and there shall be greater convergence and integration going ahead. Two such concepts that shall soon touch for remarkable advancements are Blockchain and Artificial Intelligence (AI). The future will see artificial intelligence solutions sitting on top of the blockchain networks. What this shall do is increase machine learning capabilities and create a slew of new financial products.
Running through with the basics
So, what is blockchain? It is a digital ledger that records economic transactions and other aspects that carry value. One such blockchain network of note is Ethereum. A key consideration of blockchain is it enables unrelated parties to engage in transactions and share data on a common ledger. These transactions or data get validated through cryptography and consensus mechanisms such as Proof of Work. With this mechanism in place, people need not go through third-party validators for transactions.
Now, let us move to the other side of the gamut, Artificial Intelligence (or AI). It uses computers and electronic equipment for performing the human-like tasks of analysing, classifying and predicting data. AI stands out from the traditional software because it learns and improves over time as new data gets fed into it.
The connection between these two
What connects AI and Blockchain is that they both deal with data and value. But, if you were to differentiate between these two phenomena, note that blockchain takes care of the storage and sharing of the data or any unit of value. Artificial Intelligence, on the other hand, analyses the data and generates insights. These insights are then further used to create more value.
Another connection is that both stem from the gamut of Web 3.0. The guiding principles of Web 3.0 are open, decentralized and permissionless networks.
The areas where blockchain and AI can be combined
Machine learning models
The technology giant, Microsoft, has researchers working on improving machine learning models hosted on public blockchains. The collaboration is fruitful as, with blockchain, rewarding people that help to improve these models is now possible.
Although machine learning has undergone considerable advancements, the benefits of these advancements do not translate to the masses. The reason for this is that most of the cutting-edge machine learning systems are highly centralized. And what’s more, the proprietary datasets that are required are costly to recreate.
Once AI becomes decentralized and collaborative through blockchain, advanced machine learning models will feature day-to-day devices and applications such as laptops, mobile and browsers. This then will help to contribute to data and further improve the models.
Investment Assets Trade on Blockchain by AI agents
Currently, blockchain technology is for storing and trading financial instruments such as cryptocurrencies and security tokens. The market is only nascent, and even more so are the security tokens themselves. Getting to the numbers, the security token market cap, as of January 2020, was only a mere USD 52.7 million. The numbers talk reveals that there is not sufficient activity and data to apply AI to the financial products that trade through blockchain technology.
According to a presentation at the esteemed institute of MIT by the CEO of Chainhaus, Jamiel Sheikh, the blockchain-AI convergence is a four-stage process:
- Stage 1: Proof of concepts
- Stage 2: Assets Tokenization on blockchain
- Stage 3: Trade of digital investment assets on the blockchain network, powered by machine learning
- Stage 4: Artificial Intelligence as economic agents; these agents shall trade in investment assets
As of right now, the convergence has reached the second stage, where the tokenized assets get traded on blockchains. The next phase will see a taster of native digital assets. The tokens currently only represent underlying assets. By the next stage, they shall become the asset. The final level will see a range of evolutionary (genetic) algorithms. These algorithms shall then generate, test and trade in the multiple strategies to maximize profits. And the best part? All this shall embody minimal human supervision.
The values of the convergence: Blockchain-AI
Think of this as an advanced paradigm in the digital arena. The convergence shall contribute in the following ways:
Authenticity
The digital records of the Blockchain network render insights into the AI-backed framework. What the convergence will do is improve the trust and integrity of the data itself. With this, AI shall deliver profound and precise recommendations. Also, as blockchain stores and distributes the AI models, it offers an audit trail, which shall help enhance data security.
Augmentation
A further skill of AI is that it reads rapidly and comprehensively through all the data. What’s more, it shall help ease the understanding and correlation of the data. That is, the conversion of raw data into meaningful information will happen much quicker. The result will be better management and usage of data and model sharing. The future shall see a data economy that is ever more trustworthy and transparent.
Automation
A further benefit of this convergence will be the removal of friction. All the parties will now experience speedy and efficient transactions and validations. A classic example is smart contracts. The AI models will then render recommendations for expired products to recall. These models will also help execute transactions such as re-orders, payments and stock purchases.
Parting Words
The world is in for a royal rumble of recommendations and actions with this convergence. A stark development is in the supply chain of the crops with Bext360. The AI analyses and predicts the growth patterns of crops. The blockchain records the process information from seeding to the end product. What’s more, the convergence has also spiraled into the entertainment industry through AlphaNetworks. Given these developments, blockchain and AI are no longer throwaway buzzwords! They are here to make far-reaching changes to our everyday lives.
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