The Coming Convergence of NFTs and Artificial Intelligence

Today, the cryptocurrency market consists of over 700 tokens that are trading on public exchanges. As decentralized applications become more prevalent, there is increased scope for these digital assets to influence various industries. Digital collectibles, crypto-gaming, and prediction markets all stand to benefit from blockchain technology. But one underutilized space, in particular, might see significant effects if introduced to NFTs: artificial intelligence (AI).

Supporting the AI industry requires humongous amounts of data, computing power, and an army of talented engineers. It’s no secret that this type of centralized setup isn’t likely sustainable as demand grows exponentially. Luckily, blockchain technology has emerged as a way out thanks to its decentralized attributes which allow it to support processing tasks amongst many different nodes simultaneously. In this way, blockchain development companies are revolutionizing the AI industry.

In addition, Blockchain has been instrumental in providing digital assets which have become integral to many applications associated with artificial intelligence companies. For example, Golem Network intends to provide access to computing resources through its peer-to-peer network where users earn tokens for connecting their hardware and sharing their excess capacity on the GNT marketplace (Golem Network Token, 2018). Additionally, platforms such as SingularityNet and Ocean Protocol partner with AI companies to enable the sharing of datasets and provide utilities for data and models (AI Crypto Team, 2018; Synapse Foundation, 2018).

With this in mind, crypto-collectibles might be the best way to facilitate integrations between NFTs and AI. Let’s take a look at some popular products that are already being used today.

1) Cryptokitties

When Cryptokitties hit the market in late 2017, people were taken aback by its ability to congest entire networks. But beyond clogging Ethereum’s network, Cryptokitties demonstrated how NFTs can serve as an infrastructure for digital art. Much like the physical world, these unique tokens represent one-of-a-kind pieces that are capable of being traded with other collectors. We’ve already seen some examples of how this might play out with limited edition prints and petrified wood but this is just scratching the surface in terms of what’s possible in this space.

2) CryptoPunks

A similar concept to Cryptokitties, CryptoPunks stands out because it doesn’t represent something organic but rather uniquely computer generated. A spin on self-replicating artificial life algorithms popularized by John Conway, CryptoPunks use randomly generated pixel values to determine the appearance of their character. What’s unique about these tokens is that they can be used to represent anything from a musician to a politician. The possibilities are endless and the only limitation is the creator’s imagination.

3) Decentraland

As one of the earliest virtual realities to hit the market, Decentraland has been around for quite some time. What makes it an attractive option for AI integrations is its ability to support 3D rendering and user interactivity. Additionally, Decentraland offers an owner-based governance model which gives users more control over what gets created on the platform. This creates opportunities for developers to experiment with new ideas and creations without having to worry about censorship or third-party involvement.

4) Airbloc Protocol

With the idea behind Airbloc Protocol, businesses who need to collect data can purchase information directly from users. By purchasing tokens, these organizations are able to reward users for sharing their personal data with them. This creates an efficient environment where everyone benefits and networks remain healthy (Airbloc Protocol Team, 2018). With this in mind, this could be a great way to integrate NFTs into existing AI applications. For example, users can offer up their device performance data in exchange for tokens which can then be used on other platforms like Decentraland.

This is just the tip of the iceberg when it comes to what’s possible in terms of integrating NFTs and AI applications. As entrepreneurs and developers continue to experiment in this space, we’re bound to see some incredible things as a result. Even top web development companies are shifting their focus on NFTs, blockchain and AI.

How Artificial Intelligence Is Being Used in Business Today

There are many different ways that artificial intelligence can be used in business today. Some of the most common applications include marketing, human resources, and finance.

In marketing, AI can be used to create targeted ads and recommendations. This can help businesses to create more effective marketing campaigns and improve their customer service.

In human resources, AI can be used for things like screening job applicants and analyzing employee data. This can help businesses to save time and money while still getting the best possible results.

In finance, AI can be used for tasks like budgeting, forecasting, and risk analysis. This can help businesses to save money while still getting the best possible results.

It is quickly becoming one of the most important tools that businesses have at their disposal. So far, AI has shown itself to be a valuable asset for companies of all sizes and industries. As the technology continues to evolve, it is likely that even more businesses will start to reap the benefits of AI.

As artificial intelligence (AI) becomes more sophisticated, businesses are starting to use it for a variety of purposes. Here are some of the most common AI ways that is being used in business today.

1. Automated customer service

Many businesses now use chatbots to provide automated customer service. Chatbots can handle common customer service tasks such as answering questions and resolving complaints. They can also help customers book appointments and track orders. This can free up human employees to handle more complex tasks.

2. Fraud detection

Businesses use AI to detect fraud by analyzing large amounts of data quickly. This allows them to identify patterns that may be indicative of fraudulent activity. In AI, fagging unusual spending activity prevents credit card fraud.

3. Employee performance management

AI can be used to monitor employees’ work and provide feedback on their performance. For example, AI is being used in some companies to identify which job applicants will be a good fit for certain positions. Similarly, it can predict how effective new training programs will be and provide real-time feedback based on each employee’s progress.

4. Personalisation of marketing content

Many businesses already use customer data to personalize their marketing materials such as targeted advertisements and promotional offers. However, AI can make this process more sophisticated by analyzing large volumes of data in real-time and providing even more personalized options for customers