28.05.2023

Game changer: How AI is powering the future of development

AI is changing the game industry.

AI and video games have long been closely related. However, generative AI now has the power to utterly upend and change a whole sector of the economy.

AI has been a fundamental component of video games since the 1950s, when they first became popular. 

AI was utilized in video games 20 years before Atari released Pong. The 1951 mathematical strategy game Nim, in which two players alternately remove items from piles, is one of the earliest examples, in which a computer routinely defeated human players. In the same year, one of the earliest computer programs ever created was used to program a game of chess on the University of Manchester's AI Ferranti Mark 1 system.

Today's generative AI technologies have the power to revolutionize a sector that, according to a PwC analysis, could be worth $321 billion by 2026. 

Procedure for creating content

In particular, generative AI has the potential to revolutionize the video game business, as seen by the growing use of technologies like ChatGPT. With better visuals, audio, and gameplay mechanics than when they first debuted, video games have gone a long way since then. However, generative AI has the potential to advance them much further.

Procedural content creation is one of the major ways that generative AI may change the video game business. Automated creation of game material, including levels, maps, settings, and characters, is known as procedural content generation. This can help save time and money for game creators while giving gamers a more interesting and diverse gameplay experience.

Microsoft collaborated with the Austrian firm Blackshark.ai to train an AI to create a lifelike 3D world from 2D satellite pictures for the introduction of their ground-breaking flight simulator in 2020.

Blackshark's AI-driven technology allowed Microsoft's Flight Simulator to show the surface of the whole planet in 3D, with more than 1.5 billion lifelike structures, providing players the largest open world in video game history and an unsurpassed immersive 3D flight experience.

Blackshark created an innovative solution that combines the Microsoft Azure Cloud and AI to acquire insights about our globe based on Bing Maps data with a team of more than 50 AI professionals, geospatial engineers, data scientists, and real-time renderer developers.

A "demonstration of the power of AI," according to Stefan Habenschuss, Head of Blackshark's Machine Learning Group, "we have reconstructed roughly 1.5 billion buildings and detected over 30 million square kilometers of vegetation."

According to Blackshark Co-Founder and CEO Michael Putz, "In Flight Simulator, we look at 2D areas and then find footprints of buildings, which is actually a computer vision task." "However, if a building is obscured by the shadow of a tree, we actually need machine learning because then, due to the overlap of the shadow, it is no longer clear what is part of the building and what is not — but then, machine learning completes the remaining part of the building," the author said.

Gaming discussion on generative AI is becoming more and more common. Roblox said earlier this year that it was testing a tool that would speed up the creation and modification of in-game items by using AI to create the code. By inputting what they want to do in common English rather than sophisticated code, the tool enables anybody playing Roblox to construct objects such as buildings, terrain, and avatars, modify their look and behavior, and give them new interactive capabilities.

The venture capital company Andreesen Horowitz's James Gwertzman and Jack Soslow outlined how using generative AI can assist developers greatly in a blog post.

When discussion starts with the game developers integration of AI into their modus operandi, the greatest benefit for them comes regarding saving on time and money. In some cases the production of ready-made images takes up to an hour, whereas in the past it would take them a few weeks. Similar cost savings will be feasible across the whole manufacturing chain.

They assert that artists themselves are not at risk of being replaced by AI, despite these cost reductions.

"Nothing will happen to the artists. It does not imply that artists no longer need to complete all of the work themselves; instead, they may now provide the initial creative direction while delegating most of the labor-intensive and technical execution to an AI. In this way, they resemble the cel painters from the earliest hand-drawn animation periods, when armies of less expensive "painters" would laboriously paint the animation cels, filling in the lines after highly talented "inkers" had created the shape of the animation.

Managing legal challenges

The ownership of intellectual property rights is one of the key legal concerns underlying generative AI.

Who owns the copyright to these creations and how to prevent infringement - are issues that are brought up by AI systems' capacity to produce new works without human involvement.

Even though AI gets more established within the creative community, a number of AI creators deal with the issue of AI and intellectual property rights. "AI presents a couple of issues: who is the owner of the AI-produced material, and does using training data without permission from the data owners lead to violation of their copyright?

Who owns the copyright to the work created by generative AI is the first fundamental problem that is raised by this technology. Game makers won't be able to fully defend AI-generated material against infringement by other parties if ownership is unclear or if it is in the public domain.

The usage of data for the AI to practice on without the approval of the data owners leads to copyright breach, and this is a fundamental issue.When training data is used to create generative AI models and in the content that these generative AI models afterwards output, copyright infringement may happen.

So, even though AI promises nothing short of an industrial revolution, these challenging legal obstacles still need to be cleared before these models can be widely used throughout the gaming business.

Yasmin Anderson

AI Catalog's chief editor

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