Game Assets Creation With Generative AI Tools: A Tutorial

Both of these tools use generative AI, but have been trained on assets that have been released for re-use by Roblox’s community, and not on games created by the community. “Every creator on the platform can leverage these tools without sharing their data,” says Stefano Corazza, head of Roblox Studio. AI Dungeon, by comparison, is pulling out images and ideas from god-knows-where. An additional sector that can tremendously benefit from Generative AI is the game development industry. Generative AI facilitates the creation of new content rather than repetitive ones, providing a whole new experience to users.

It includes a wide range of features such as realistic physics simulations, advanced lighting and shading techniques, realistic hair and fur rendering, dynamic particle effects, and more. Coding tools like Copilot may provide moderate performance improvements for engineers, but won’t have the same impact… at least anytime soon. Games are the most complex form of entertainment, in terms of the sheer number of asset types involved (2D art, 3D art, sound effects, music, dialog, etc). Games are also the most interactive, with a heavy emphasis on real-time experiences. This creates a steep barrier to entry for new game developers, as well as a steep cost to produce a modern, chart-topping game.

Immersive Realism Beyond Imagination

One breakthrough moment for AI in gaming occurred in March 2016, when the computer program AlphaGo, developed by Google’s AI company DeepMind, challenged top player Lee Sedol at the strategy board game Go. AlphaGo demonstrated that a machine could become intelligent enough to beat the human champion at an ancient, highly complex game. Think Pac-Man eating up dots while being chased by ghosts, which are actually following set patterns, or Street Fighter, where you battle the computer in the guise of what are called non-playable characters.

In areas where data is scarce or imbalanced, generative AI can create synthetic data, enhancing the training of other AI models and improving their performance. For instance, an online publication could use generative AI to draft articles on a variety of topics. The AI could analyze trending topics, gather relevant information, and create a draft article, which can then be reviewed and edited by a human writer. This technology can be used in various sectors, including entertainment, fashion, and design.

Generative AI in Gaming: From Pioneering to Revolutionary

Now compare Red Dead Redemption 2 to Microsoft Flight Simulator, which is not just big, it’s enormous. Microsoft Flight Simulator enables players to fly around the entire planet Earth, all 197 million square miles of it. Microsoft partnered with blackshark.ai, and trained an AI to generate a photorealistic 3D world from 2D satellite images.

• This is useful when handling datasets lacking balance or when additional data is required to train machine learning models.
• Most of it isn’t good enough for shipping in a commercial title or is rather generic and derivative.
• Meanwhile, copyright law in the US and EU at minimum precludes AI from earning copyright on generated assets.
• At its core, Generative AI in gaming utilizes machine learning algorithms to analyze and learn from existing content.
• Allowing artists to easily generate textures based on text or image prompts will be hugely valuable towards increasing iteration speed within the creative process.
• More importantly, 60% do not expect AI to have a significant impact on the workforce.

The companies that were the first to notice this were mobile gaming companies like King, Playtika, and MoonActive. Now that data-driven approach is prevalent in every gaming company, including PC gaming and even in console games which were slowest to adapt this perspective. In fact, that is how all great internet businesses work if they want to continue to grow. All companies need to constantly be moving quickly, testing new features, and learning from their customer behavior. And given they generate so much data and behavioral user feedback, they are just better at this ongoing optimization cycle than companies in any other field. Even so, Sentis could prove alluring to developers looking for shortcuts—something all software developers, and game developers in particular, desperately need.

The algorithm adheres to specific rules and parameters, conjuring a fresh labyrinth of obstacles and treasures with every playthrough. With each step, players are thrust into a new and unpredictable world, where adaptability is key to survival. Generative AI operates using deep learning models, particularly Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These models are trained on vast datasets and learn to generate content by identifying patterns and features within the data. Through iterative processes, they refine their ability to produce increasingly convincing and diverse outputs.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

By using Generative AI, the development process gets accelerated, saving both time and effort for the game developers. This transformative technology opens up a realm of opportunities for both established game studios and up-and-coming indie developers. Embracing Generative AI isn’t just a step forward; it’s a monumental leap toward a future where games are more imaginative, cost-effective, and enthralling than ever before. Generative AI has the ability to adapt to individual player preferences and behaviors in real time. This means the challenges, enemies, and storylines adjust dynamically to suit the player’s style.

This technology addresses the growing need for high-quality visuals in various industries, including photography, e-commerce, design, and entertainment. The integration of AI-powered simulations, replicating features like weather dynamics and day-night transitions, has the potential to profoundly enrich the gaming experience. This innovation holds immense growth in fostering heightened player engagement and realism, two critical factors for market growth. This is where generative AI opens up transformative possibilities, according to the Andreessen Horowitz piece. It can take up to a decade to build the immersive but relatively small worlds in some of the most realistic games on the market. Already, we’re seeing the next generation of gaming companies embrace these ideas.

Most of these executives see generative AI improving quality and bringing games to market faster. Generative AI will also help make bigger, more immersive, and more personalized experiences a reality. Interestingly, only 20% of executives believe that generative AI will reduce costs, which might be a disappointment to some, given that top-tier games may cost as much as $1 billion to develop. As with any form of automation, there may be concerns about generative AI taking jobs.

By the end of this article, you’ll have a solid understanding of what is generative AI and how it can be a game-changer for your business. In this comprehensive guide, we will demystify what is generative AI, shedding light on its capabilities, applications, and potential impact on businesses. The panel was organized and moderated by Lightspeed partners Moritz Baier-Lentz, who heads the Yakov Livshits firm’s gaming practice, and Faraz Fatemi, who focuses on investments in consumer platforms. The two were joined by panelists Ken Wee, Chief Strategy Officer of Activision Blizzard, and Ankur Bulsara, Co-Founder and Chief Technology Officer of Scopely. We are failing your build and will give you one (1) opportunity to remove all content that you do not have the rights to from your build.

How Generative AI Can Be Applied to Game Development?

But it bears repeating because this is the origin of two advances that are still making games better today than they were even before. Games founders and their teams are faster than any other companies we see, and they understand user psychology and delight better than anyone. You can say that you want the world to be more dangerous, and the AI will figure it out, Penttinen said.

Additionally, more traditional media outlets like ESPN and the BBC are now covering esports events, and major brands are increasingly investing in esports sponsorships and partnerships. And, again, your AI companion will be different from someone else’s because it adapts to your personality and style of play. Then in 2016, Google’s AlphaGo AI defeated world champion Lee Sedol in a game of Go, a complex board game that had long been considered one of the most challenging games for AI to master.

Whether you’re a casual gamer seeking a relaxed experience or a hardcore enthusiast craving a challenge, the game tailors itself to you. Generative AI isn’t just about creating games; it’s about crafting worlds that adapt, evolve, and resonate with players on a deeply personal level. It’s about breaking free from the constraints of static content and inviting gamers into a realm of limitless possibilities. Despite its benefits, the adoption of Generative AI in gaming hasn’t been without criticism.

You can also validate the quality of the models in real time and test performance and latency to ensure that they meet specific standards before deployment. The creation of non-playable characters (NPCs) has evolved as games have become more sophisticated. The number of pre-recorded lines has grown, the number of options a player has to interact with NPCs has increased, and facial animations have become more realistic. Generative AI is poised to bring this vision to life by creating highly realistic virtual environments that defy the constraints of current technology.