Artificial Intelligence in Video Games: A Perfect Couple

The gaming industry is a remarkably thriving space. This industry was always “married” to technological advances. From the first rudimentary games like Pong, invented over 50 years ago, to advanced VR games of the modern day, enabling incredible emersion through hardware like haptic suits. It has always been a race to build better, more immersive, and more entertaining games.

But the products of the video game industry are just as much about the software as they are about the hardware. Innovations in the gaming industry are a blend of both. That’s why everyone who played their fair of video games (or still does) is not alien to the concept of AI. For gamers, AI has always meant the way the game responds to their interactions. Gamers don’t want characters blindly surrendering to them during a match or non-player characters (NPCs) staring blankly at a wall. AI could make or break the game.

So even before the term "AI" entered the mainstream, popularized by tech giants like Google and Apple, gamers had been familiar with the concept. Some people think that games laid the foundation of AI as we know it, as games were one of the first software systems interacting with humans on a rather high level.

However, AI now means a lot more in the context of modern tech. And that also rings true for the video game industry. The applications of artificial intelligence in gaming now transcend the boundaries of in-game experience, affecting game design and business use cases.

Let’s take a closer look at some of them. While they may not seem to hold direct value for gamers, they change the way video game companies develop, promote, and manage games and in-game experiences.

For a while, the evolution of graphic design in games was heavily tied to the performance of the hardware. That’s why when Crysis came out in 2007, only the best PCs could run it smoothly. Even today, some computers have issues running the game above 60fps. Many software technologies introduced in that game were far ahead of their time.

But that’s no longer the case for even mid-range graphics capabilities, with hardware being able to process tons of data and create realistic renderings in real time without performance issues. That’s why video game companies are actively exploring the capabilities of AI in games, enabled by powerful hardware and major developments in all the flavors of AI (deep learning, etc.). The effect is bilateral.

Some of the most powerful AI systems can only be built with the help of hardware created by companies in the video game industry. That’s why companies like Nvidia are actively investing in companies like H2O.ai, which are at the forefront of artificial intelligence. That said, artificial intelligence has a significant impact on the quality of video game graphics.

There are research initiatives and experimental projects that use artificial intelligence to produce smoother image renders. These developments can improve both the quality and the rendering speed since AI can be taught to recognize the optimal final shape of the render and pre-populate it.

A project by Nvidia and Remedy Entertainment uses AI to create high-quality facial animations out of audio. Yes. Audio. The system can recreate facial expressions using just the audio that you supply. No need to have actual people filmed and then transformed into graphics. Yet, this tech still can’t match professional actors, as demonstrated by Andy Serkis below:

Neural networks that power systems like the infamous Deepfake videos are used for in-game rendering and graphics improvements. Even people inexperienced in machine learning and AI can build a system that improves video game graphics. Like Chintan Trivedi, who improved FIFA graphics and even managed to insert his face into the game.

We already mentioned that video games are a great environment for AI. And so we wanted to briefly reverse things around and talk about the influence of video games on the development of AI.

Games offer a unique environment for problem-solving skills. Many games challenge creativity on a whole different level. That’s why they’re perfect for testing AIs. For example, the OpenAI project created an AI without any goals (it wasn’t given an outcome that it should aim for), so the AI simply started exploring the games out of what humans call "curiosity." No other environment provides this kind of research opportunities.

Not to mention that games offer almost infinite possibilities, which means data to train AI could be generated almost infinitely too. For example, the number of possible plays for chess is higher than the number of atoms in the observable universe. That’s why it takes an AI to beat a real grandmaster. A hard-coded machine usually doesn’t have the "creativity" required to make such complex decisions.

The modern gaming industry is a cut-throat business. The staggering growth attracts new players. There are tons of development tools that allow almost anybody to create games. And platforms like Steam allow those indie developers to have a market. The rules of the game are even more brutal in mobile gaming, a market that’s been exploding for the past couple of years. Today, it’s a $50 billion industry.

Naturally, getting ahead of the competition through any means possible is exceptionally important, especially when it’s hard to differentiate. For example, card games and other gambling sites are a hugely competitive market. When you can’t differentiate in a market like that, you go for marketing and customer analytics as some of the few available growth drivers.

Luckily, there are tons of applications for AI in this specific domain:

• Predicting player churn
• Predicting likelihood of upsell/cross-sell of in-game currency or upgrades
• Predicting the next best marketing action through better marketing attribution

These are just some examples, but the list is endless. There are plenty of custom-made, open-source, and enterprise solutions. Most of such systems are aimed at retail and other consumer-centric industries, but their capabilities could be adapted for the gaming industry too with the help of AI consultants.

As you can see, artificial intelligence in games is not a new concept. It may have even been spawned thanks to video games. And it’s obvious that some of the biggest innovations in AI research are generated with the help of games. We haven’t even covered some of the bleeding-edge innovations, like integrating AI into VR and AR experiences. It’s an exciting time—we’re witnessing the first steps to the singularity.

The gaming industry is as complex as it can get. From AAA game dev studios to gambling corporations. From single-person development companies to crowdsourced game development teams. There is a breadth of products and a breadth of data, which can be used to make gaming experiences more engaging, realistic, and lucrative for startups and enterprises alike.