AI Games: Playing with Generative AI
Video games are being used to help train and test cutting-edge artificial intelligence (AI). And if successful, these game-based AI systems could be useful in developing real-world efficiencies across industries.

For example, one เว็บแทงบอล ฝากถอนเร็ว generative AI system called Muse was trained to learn to play the video game Bleeding Edge. It simulated 500,000 hours of gameplay, which is more than 50 years worth of human time! This is a huge amount of data, and it was enough to teach the system how to successfully play the game.

From Deep Blue to Dota 2: The Evolution of AI in Competitive Gaming

The idea is that as gamers continue to play the game, the generative AI will learn and adapt, making each new experience more challenging and engaging. This is an exciting idea and it could extend the life of video games by allowing them to be more engrossing, even after the player has finished the game multiple times.

Another advantage of generative AI is that it can offer more realistic and freeform gameplay. This means that players will interact with nonplayer characters in ways that are more natural and realistic. This will enhance the story-telling and add to the overall immersiveness of the game experience.

Developers have traditionally been a bit wary of AI that is nondeterministic. This is because unpredictability makes it difficult to debug and test AI behavior. However, this is changing as game developers are embracing AI that learns and evolves in their video games.