Unlocking the Future: Introducing Artificial Intelligence Token

The native asset of a blockchain network that can be traded, used as a store of value, and as a means of exchange is called a cryptocurrency. Because a cryptocurrency is directly issued by the blockchain protocol that powers it, the term “native currency of a blockchain” is frequently used to describe it. Cryptocurrencies are frequently used to reward users for maintaining the network’s security in addition to being used to pay transaction fees on the network.

Generally speaking, cryptocurrencies are used as a store of value or as a medium of exchange. An asset used to purchase goods or services is known as a medium of exchange.

An item that retains its purchasing power or can be converted into fiat money at a later time without suffering substantial losses is referred to be a store of value.

Generally speaking, cryptocurrencies display the following traits:

Decentralized, or at minimum independent of a centralizing issuing body. Rather, the management of transactions and issuance of cryptocurrencies is done by code.
based on Distributed Ledger Technology (DLT), such as a blockchain, which enables users to automatically and anonymously enforce the system’s regulations.
employs cryptography to protect the network infrastructure and underlying structure of cryptocurrencies.

What is a Crypto Token?

Tokens are units of value that blockchain-based organizations or initiatives create on top of pre-existing blockchain networks. They are also known as crypto tokens. Even though they frequently have close compatibility with the network’s cryptocurrency, they belong to a whole other category of digital assets.

Tokens are produced by platforms that build upon blockchains, while cryptocurrencies are the inherent assets of a particular blockchain technology. For example, ether (ETH) is the native cryptocurrency of the Ethereum blockchain. The native coin of the Ethereum blockchain is called ether, however, the Ethereum blockchain is also used by a wide variety of other tokens. Among the cryptocurrency tokens created with Ethereum are CryptoKitties, LINK, COMP, DAI, and so forth.

On the platforms for which they are designed, these tokens can be used for a wide range of purposes, including as playing games, accessing platform-specific services, and taking part in decentralized finance (DeFi) procedures.

For the purpose of establishing cryptocurrency tokens, there are a number of generally accepted token standards available, most of which are based on Ethereum. The two most popular token standards are ERC-721, which was created to support non-fungible tokens, or those that are singularly unique and cannot be exchanged for another token of a similar kind, and ERC-20, which permits the creation of tokens that can function within Ethereum’s ecosystem of decentralized apps.

Thousands of ERC-721 tokens and hundreds of distinct ERC-20 tokens are in use as of 2020. The number of various tokens is expected to continue growing at an astonishing rate as new tokens are created to address the growing use cases for blockchain technology. Cryptocurrency tokens are often transparent, programmable, trustless, and permissionless. To put it simply, programmable tokens operate via software protocols made up of smart contracts that specify the attributes and operations of the token as well as the rules of behavior for the network.

Anyone can use the system without requiring any special credentials if it is permissionless. Trustless systems function according to predetermined network protocol standards rather than being governed by a single, central authority. Lastly, transparency means that everyone can see and validate the protocol’s rules as well as its transactions.

What are Artificial Intelligence Tokens?

Artificial intelligence is also used by AI tokens, which are cryptocurrencies, to improve security, scalability, user experience, and other aspects. The taught AI may be utilized to automate tasks and improve cryptosystem security, theoretically. Digital money that can be utilized in AI-powered projects and applications is called Artificial Intelligence tokens. This covers decentralized exchanges or marketplaces, AI-powered investment protocols, text or picture-generating services, etc.

The business community, the cryptocurrency community, and numerous other industries have been talking a lot about ChatGPT since its launch. By the end of 2022, ChatGPT was becoming more and more well-known. This chatbot, created by OpenAI, can do multilingual activities like data processing and query response in addition to producing writing that appears human.

In the end, ChatGPT has enormous potential in the cryptocurrency sector. For instance, the creator of the Tron blockchain and token, Justin Sun, has provided an example of a possible AI-powered decentralised payment system that is based on and supports chatbots.

Perhaps ChatGPT’s surprising popularity has sparked curiosity in the community of AI technology as well as among cryptocurrency aficionados. To increase interest, Microsoft said that it will spend $10 billion in OpenAi, the makers of ChatGPT. Thus, by late 2022, several cryptocurrency tokens had increased in value by 75% or more.

As of February 2023, the entire market value of all AI tokens was 1.6 billion IS dollars, a negligible amount in comparison to the cryptocurrency market. Nevertheless, given that investors are gravitating towards AI, this is a quickly expanding industry.

How Artificial Intelligence Tokens work?

AI tokens leverage blockchain technology to create a decentralised, profit-driven ecosystem that fosters the development, application, and adoption of artificial intelligence. The stages to comprehend how Artificial Intelligence tokens function are as follows:

Data Aggregation Artificial intelligence (AI)-driven : cryptocurrencies gather a plethora of data from multiple sources, such as news articles, social media posts, historical market data, and more. The foundation for more research is this huge dataset.

Analysing Data and Identifying Patterns : Modern machine learning algorithms are applied to the acquired data in order to thoroughly assess it and identify significant trends, patterns, and correlations. This research makes it easier to understand market fluctuations and potential trading opportunities.

Forecasting the Market : The AI system uses the insights gleaned from data analysis to build predictive models that forecast probable market behaviour. These models help make decisions about when to purchase, trade, or hold different cryptocurrencies more intelligently.

Developing The Approach : On the basis of market projections, the AI system develops comprehensive trading strategies. These methods outline the actions to be followed in order to maximise profits or minimise losses and span a wide range of scenarios.

Evaluation of Risk : Any trading endeavour involves risk, and cryptocurrencies powered by artificial intelligence (AI) employ historical and real-time data to evaluate risk factors. This assessment aids in the modification of trading strategies to bring them into compliance with reasonable risk criteria.

Execution of Smart Contracts : Smart contracts are used by AI cryptocurrencies to ensure trade autonomy, security, and transparency. These self-executing contracts are programmed with predetermined rules, and trades are executed automatically when certain conditions are satisfied.

Monitoring in Real Time : The AI system continuously monitors the performance of the portfolio and the situation of the market as transactions are executed. This vigilance allows for swift adjustments in the event of unexpected market moves.

Assessment of Performance : A component of post-trade analysis is evaluating the outcomes of completed trades. The AI system closely studies its successes and setbacks so that it can learn from the past and modify its strategy accordingly.

Tokenization of AI Tokens

AI models, datasets, and algorithms are represented as tradable tokens on a blockchain through tokenization. Tokenizing their creations, developers may now effortlessly distribute, market, or grant licences for AI innovations to other participants in a decentralised ecosystem. Tokenized AI models have several applications such as natural language processing, image recognition, data analysis, and more.

Decentralised Marketplaces for AI :

Decentralised artificial intelligence marketplaces are virtual shops where individuals or companies can trade AI tokens for models, data, or services. The aforementioned markets aim to eliminate intermediaries, provide transparency, and encourage collaboration between AI developers and users. Users may profit by selling tokens to the market by offering their data, algorithms, or computational power.

AI Model Training and Data Sharing:

Training AI models requires a large computational footprint. People can be encouraged to donate their computer power or data sets for AI training by offering tokens for AI. By rewarding participants with tokens, AI projects can have access to a greater range of resources and potentially accelerate the development of state-of-the-art AI models.

Consensus And Governance

AI tokens can potentially be used for consensus and governance inside AI initiatives or communities. Token holders may be given the ability to vote on proposals for changes, additions, or alterations to the AI ecosystem. This ensures that decisions are made decentralised, considering the interests of the community.

Obstacles And Things To Take Into Account

Although the concept of AI tokens has potential, there are some disadvantages that need to be considered. Ensuring the quality and reliability of AI models available in markets, addressing prejudice and ethical concerns with AI, and creating a secure and expandable blockchain infrastructure are all crucial elements.

Top AI Tokens

The Graph (GRT): A protocol called The Graph allows data from blockchains to be indexed and queried in a manner akin to how Google indexes and queries data from webpages. Blockchain data can be difficult to index, but The Graph seeks to solve this problem by breaking up the data into smaller “subgraphs.”

At the time of writing, the value of its native cryptocurrency, GRT, which is based on Ethereum, was approximately INR 6.88, having peaked at approximately INR 205.68 in February 2021.

SingularityNET: With the use of the blockchain network SingularityNET, anyone may create, distribute, and profit from AI services. Users can peruse and pay for AI services in the platform’s native cryptocurrency, AGIX, in its internal marketplace.

Without having to completely create applications for end users, developers can profit from AI models and solutions. In a similar vein, programmers may purchase AI models and solutions to incorporate into their apps.

At the moment, AGIX is valued at about INR 13.77. AGIX reached its highest point in January 2018 at about INR 131.91.

Fetch.ai: Fetch.ai is a blockchain-based AI and machine learning platform. The main goal of Fetch.ai is to automate corporate processes, including trading and data processing. FET, the network’s native coin, is used to fund transactions.

FET’s value decreased from its peak of approximately INR 85.64 in September 2021 to around INR 18.70 at the time of writing.

Ocean protocol: Ocean Protocol is a platform built on the Ethereum blockchain that enables companies and individuals to trade and profit from data and data-driven services. This might entail providing researchers and startups with access to data without requiring data holders to give up their rights.

After peaking at over INR 139.82 in April 2021, OCEAN is currently trading at about INR 19.69.

iExec RLC:

An AI blockchain platform called iExec enables users to access on-demand cloud computing resources and make money off of their computer power.

The native cryptocurrency of iExec, RLC, is utilised to cover platform service costs. RLC hit an all-time high of about INR 984.90 in October 2021, and it is currently trading at about INR 128.03.

Numerai:

As a hedge fund, Numerai is an AI blockchain network that makes investments in international stock markets through machine learning and artificial intelligence.

The native money of Numerai, called Numeraire (NMR), makes network payments easier. It peaked in 2017 at about INR 13,004.49, and is presently trading at about INR 1,302.40.

dKargo: A blockchain called dKargo employs AI to address trust concerns in the logistics industry. This is accomplished by giving participants reliable data, which is made possible by blockchain technology’s irreversible nature.

The value of DKA, the native token of Kargo, has decreased to about INR 1.97 from about INR 53.19 in the winter of 2021.

Phala Network: Another blockchain technology enhanced by AI for cloud computing, Phala Network focuses on privacy. It is marketed as a decentralised substitute for well-known cloud computing providers like Google Cloud and Amazon AWS.

Phala Network cloud services are paid for with PHA, the native currency of the network. It peaked in May 2021 at about INR 98.49, and it is presently trading at about INR 10.83.

Cortex: An artificial intelligence model can be uploaded and run on the blockchain platform Cortex. The concept is that decentralised apps (dApps) and smart contracts can both benefit from AI integration.

As of the time of writing, CTXC was worth about INR 20.69. It was trading for about INR 147.79 in May of 2018.

*Market capitalization numbers current as of March 6, 2023.

Ethical considerations surrounding AI Tokens

The broader use cases for blockchain technology and AI, as well as the ethical implications of AI currencies, are critical. Being open and responsible is crucial, which necessitates complete disclosure of all information regarding how AI operates, renders decisions, and handles data.

Maintaining data privacy is essential; in order to prevent misuse, user data should only be collected with consent, maintained safely, and used responsibly. It is necessary to continue researching the possibility of prejudice in AI systems since biases in training data could lead to biassed outcomes.

It’s also critical to carefully evaluate how AI currencies will alter present labour markets and employment patterns in order to ensure that technological advancements benefit society without causing undue disruption.

Following legal and regulatory frameworks is essential as a last line of defence against any legal ambiguity or violations. As the use of AI coins increases, stakeholders will need to address these moral dilemmas to enable responsible development and application in a constantly evolving technological landscape.

Potential of AI Tokens

The market is still unaware of the full possibilities that applying AI to the still-developing cryptocurrency space can bring. However, movement brought about by the combination of crypto and AI may portend a promising future. Modern AI technology may soon bring about a revolution in the field of digital assets.

The following are some instances of how AI is used in the bitcoin industry:

Corruption in the bitcoin market might be controlled by utilising an AI algorithm in combination with technologies for identifying or preventing it. Artificial Intelligence has being applied more in the banking industry to counteract real-world financial misconduct. A poll conducted by NVIDIA predicts that 10% of financial users would employ AI-based anti-corruption technologies in their companies by 2021.
The danger associated with investors making haphazard investments would be reduced by using AI to create simulations for estimating the value of digital assets.
Reducing the involvement of people as the medium in order to increase the efficacy of blockchain’s decentralisation.
Lowering the likelihood of financial loss by helping users make wiser selections.
Letting AI assess the state of a particular digital asset based on opinions expressed by the public.
AI may be incorporated into government policy to control the digital asset tax and prevent money laundering.

Conclusion

In the future, there could be more fascinating integrations between blockchain and AI with AI tokens. It’s likely that these tokens will play a major role in facilitating decentralised AI networks and the seamless interchange of AI services and data.

As AI algorithms get increasingly complicated, AI tokens may encourage innovation by compensating customers, data providers, and developers of AI software.

Ethical concerns including accountability, transparency, data privacy, and bias reduction must be addressed in order to facilitate the ethical and equitable development of AI tokens. Combining blockchain with AI has the potential to change industries, enhance automation, and provide new job opportunities.

Send Us A Message