How Machine Learning Benefits the NFT Gaming Economy
Machine learning is a branch of artificial intelligence (AI) that uses and analyzes data to build prediction models and facilitate decision-making without explicit programming or instructions. It is a field of computer science that aims to improve itself by imitating how humans absorb and learn new data.
Machine learning is an important and advanced part of data science that uses complex algorithms to find patterns and relationships in any data set. It can then simplify this data to make information more comprehensible, sometimes by reducing dimensionality. This technology can be applied across various industries, including NFT gaming, which uses non-fungible tokens to represent characters and items, and enforces specific rules of gameplay and player interactions.
Through machine learning, NFT games can analyze player behavior to identify patterns and preferences. This helps developers to carefully design new projects and update existing ones with features that retain old users and attract new ones. Machine learning can also help developers in relatively new fields like crypto casinos to update their platforms with features crypto enthusiasts may consider attractive. There are already several sites where you can use Ethereum and other crypto assets to gamble, that can benefit from merging their use of cryptocurrencies with machine learning. Crypto casinos utilizing this technology can tend better to a growing number of crypto enthusiasts who enjoy online gambling.
Another advantage machine learning brings to NFT gaming is the dynamic pricing of in-game NFT assets. This advantage also involves scrutinizing player behavior, but fuses that with an analysis of general market dynamics. From the analysis, machine learning algorithms can predict asset value and set a dynamic system, which helps players and collectors make educated decisions on trading NFTs - suggesting when to buy, sell, or hold on to their assets.
Machine learning can also tailor the gaming experience to individual player preferences. Specific items can be introduced to players based on their gaming style instead of a broad experience geared at all players. Depending on the analysis completed by machine learning algorithms, there could be differences in features like rewards, difficulty, and access to specific gaming items.
NFT gaming design can also benefit significantly from machine learning. The technology can help developers design in-game assets, player characters, and gaming landscapes. Machine learning adapts to player needs and individual experiences and uses an analysis of these factors to create an increasingly immersive experience for players.
According to Mordor Intelligence, the global NFT gaming market is expected to rise at a compound annual growth rate (CAGR) of 14.84% from $410.92 billion in 2023 to $820.78 billion in 2028. This points to a large market that can be even larger if fused with machine learning. However, despite all of the benefits machine learning brings to NFT gaming, there are a few concerns.
For instance, machine learning may encroach on player privacy because these algorithms need nearly unfettered access to player data to function adequately. In addition, there is the worry that developers may tweak machine learning models to apply changes that prioritize profits over fairness and transparency. Unfortunately, there also is the fear that regulatory restrictions may stifle the growth of machine learning models and applications. If government regulations prevent easy access to player data, NFT gaming platforms and projects would be unable to properly apply machine learning to improve the average player’s experience.
