Using the power of artificial intelligence, developers are building 92 Jeeto that learn from players and adapt to their unique playing styles and skill levels. They’re creating NPCs that feel more lifelike and natural in their interactions, crafting narratives that evolve based on player choices and designing environments that adapt to the gamer’s behavior.

The most common AI techniques used in video games today are simple pathfinding algorithms and State Machines. These deterministic systems are computationally cheap and easy to develop, understand, test, and debug. But they’re also limiting. By forcing designers to anticipate all possible scenarios and code their behavior explicitly, they limit how creatively the AI can respond.

Dynamic Story Generation in Games

A more promising approach to game AI is generative AI. This technology uses neural networks to create a wide range of images and text, then automatically adjusts them to produce a unique output. This can be used to create new quests and conversations, new maps, new characters and even whole game worlds.

Unfortunately, copyright concerns are hampering the wider adoption of generative AI in video games. The use of generative AI to generate games can easily cross the line into copyright infringement, says Jess. This is because the tools are often trained on vast amounts of text and pictures scraped from the internet, which can be argued to be a form of mass copyright infringement. However, some studios are starting to experiment with generative AI by creating their own internal data-sets or hiring third parties to advertise ethical tools that work on authorised sources.