Revolutionizing Game Development: Unity’s AI Advancements with Unity Muse and Unity Sentis

AI has already begun to be applied in areas where it is necessary to analyze and generate content. In particular, artificial intelligence is implemented in game and app development. AI is getting popular primarily due to its ability to significantly speed up and facilitate the content development process. Instead of spending several hours manually creating graphics for games and applications, you can use AI to generate the necessary components on its own simply. Then the developer will make their edits.

Therefore, it is not surprising that the number of companies using AI is growing. According to  Forbes Advisor, by 2027 the artificial intelligence market will be estimated at 407 billion USD. And 64% of enterprises believe that artificial intelligence will increase their productivity.

Unity, one of the most famous app manufacturers for portable gadgets, is among the companies that are already gradually introducing AI into their work. 

In this article, we will take a detailed look and analyze the new artificial intelligence developments from Unity and what they mean for the development of XR applications.

Leveraging Unity AI for App Development

Unity has been using AI for a few years now, but, firstly, it was mostly for marketing and non-game content to a wider audience. Like, for example, Luna, a platform that aims to improve the advertising strategy of brands. Or Supersonic which is a stand-alone platform that automates and accelerates game advertising.

Secondly, artificial intelligence and neural networks for gaming have previously been created only for developers who have special qualifications for working with applications. Like, for example, ML agents, which allow you not to code the behavior of digital elements, because these elements themselves (smart agents) are independently learning the algorithms of behavior in the environment. For example, in a game from Unity, you can hone the behavior of a digital corgi that runs after a stick. Or the behavior of racing cars, as in this video.

Read also: Transforming Reality: How AI Revolutionizes XR for Next-Level Experiences

“In the carting micro game, our ML agent scenes are typically set up with a few major components: the training environment, the level, that we want our agents to observe and familiarize with. Which, in our case, is our racetracks. The agents are the game objects we want to train. So, that they can accomplish a goal, such as driving without colliding with the track walls. And, finally — our academy, which collects all observations, done by our agents and trains them”, said Unity’s official video.

In March 2023, Unity announced their own AI game and application development features. Then there was the first presentation of an ecosystem with artificial intelligence, which operates according to the principle of many AI generators, such as Midjourney and ChatGPT.

A few days ago, new AI tools for developing games and applications were announced: Unity Muse and Unity Sentis, which we will discuss in more detail below. 

Unity Muse: Empowering AI Creativity

Unity Muse is the newest platform with artificial intelligence, the main purpose of which is to accelerate the creation of applications with 3D graphics. In particular, the option of this platform includes such basic functions as:

  • automatic creation of animated characters and digital doubles;
  • creation of the movements of the animated model — for example, jumps or backflips;
  • creating a texture for the environment;
  • addition to ready-made 3D models — for example, the video shows how you can highlight the roof area on the digital model of the house, enter a prompt and select several options for a red roof from the database.

“The Muse platform provides quick access to detailed information from the documentation and can also generate 2D sprites and 3D animations. This allows developers to quickly get the resources they need to create prototypes or new experiences without waiting for final versions of models and sprites. With Muse chat, developers can effectively communicate with other team members and get the help they need during development”, said Qualium Systems Unity tech lead Arcueid D’athemon.

The main difference between Unity Muse and ML agents is ease of use. The newest platform looks like a chat with a neural network and the principle of operation resembles the sensational ChatGPT. As mentioned above, the user enters the required prompt to generate the 3D content required for the application.

Harness the Power of Unity Sentis AI

Unity Sentis is a cross-platform tool that integrates AI into Unity applications. According to Unity’s official announcement, Sentis enables in-app digital models to work flawlessly on all operating systems, browsers, and devices that support Unity, from smartphones and tablets to game consoles and XR glasses.

Thus, applications with built-in AI models work more efficiently due to the fact that data is processed in real-time.

However, according to Arcueid D’athemon, Unity tech lead at Qualium Systems, the range of  Sentis options is wider, and the platform can also generate voice acting and animation for a character.

“It opens up opportunities to quickly create dynamically generated actions in the application that will depend on the environment or interaction with the user. With Sentis, developers can effectively create realistic character movements and high-quality voice acting that enriches the user experience”, said Arcueid D’athemon.

In the end, the combination of the input of the own neural network can change the process of the application use. For example, the user can directly interact with an NPC, while would respond to him with lines that are not pre-recorded. It enhances the immersive experience of gameplay, using the example of a virtual AI character named Orb.

Unity’s interest in AI in app development is evident with recent innovations such as Unity Muse and Unity Sentis. The first tool allows developers to quickly and efficiently create 3D models of game and non-game characters, environments, and textures. As for Sentis, this program allows you to modify the gameplay by introducing NPCs with their own artificial intelligence. Unity’s AI ecosystem continues to evolve, inspiring game and app developers to explore new horizons and reimagine what’s possible in interactive entertainment.

Latest Articles

June 27, 2025
Methodology of VR/MR/AR and AI Project Estimation

Estimation of IT projects based on VR, XR, MR, or AI requires both a deep technical understanding of advanced technologies and the ability to predict future market tendencies, potential risks, and opportunities. In this document, we aim to thoroughly examine estimation methodologies that allow for the most accurate prediction of project results in such innovative fields as VR/MR/AR and AI by describing unique approaches and strategies developed by Qualium Systems. We strive to cover existing estimation techniques used at our company and delve into the strategies and approaches that ensure high efficiency and accuracy of the estimation process. While focusing on different estimation types, we analyze the choice of methods and alternative approaches available. Due attention is paid to risk assessment being the key element of a successful IT project implementation, especially in such innovative fields as VR/MR/AR and AI. Moreover, the last chapter covers the demo of a project of ours, the Chemistry education app. We will show how the given approaches practically affect the final project estimation. Read

June 27, 2025
What Are Spatial Anchors and Why They Matter

Breaking Down Spatial Anchors in AR/MR Augmented Reality (AR) and Mixed Reality (MR) depend on accurate understanding of the physical environment to create realistic experiences, and they hit this target with the concept of spatial anchors. These anchors act like markers, either geometric or based on features, that help virtual objects stay in the same spot in the real world — even when users move around. Sounds simple, but the way spatial anchors are implemented varies a lot depending on the platform; for example, Apple’s ARKit, Google’s ARCore, and Microsoft’s Azure Spatial Anchors (ASA) all approach them differently. If you want to know how these anchors are used in practical scenarios or what challenges developers often face when working with them, this article dives into these insights too. What Are Spatial Anchors and Why They Matter A spatial anchor is like a marker in the real world, tied to a specific point or group of features. Once you create one, it allows for some important capabilities: Persistence. Virtual objects stay exactly where you placed them in the real-world, even if you close and restart the app. Multi-user synchronization. Multiple devices can share the same anchor, so everyone sees virtual objects aligned to the same physical space. Cross-session continuity. You can leave a space and come back later, and all the virtual elements will still be in the right place. In AR/MR, your device builds a point cloud or feature map by using the camera and built-in sensors like the IMU (inertial measurement unit). Spatial anchors are then tied to those features, and without them, virtual objects can drift or float around as you move, shattering the sense of immersion. Technical Mechanics of Spatial Anchors At a high level, creating and using spatial anchors involves a series of steps: Feature Detection & Mapping To start, the device needs to understand its surroundings: it scans the environment to identify stable visual features (e.g., corners, edges). Over time, these features are triangulated, forming a sparse map or mesh of the space. This feature map is what the system relies on to anchor virtual objects. Anchor Creation Next, anchors are placed at specific 3D locations in the environment in two possible ways: Hit-testing. The system casts a virtual ray from a camera to a user-tapped point, then drops an anchor on the detected surface. Manual placement. Sometimes, developers need precise control, so they manually specify the exact location of an anchor using known coordinates, like ensuring it perfectly fits on the floor or another predefined plane. Persistence & Serialization Anchors aren’t temporary — they can persist, and here’s how systems make that possible: Locally stored anchors. Frameworks save the anchor’s data, like feature descriptors and transforms, in a package called a “world map” or “anchor payload”. Cloud-based anchors. Cloud services like Azure Spatial Anchors (ASA) upload this anchor data to a remote server to let the same anchor be accessed across multiple devices. Synchronization & Restoration When you’re reopening the app or accessing the anchor on a different device, the system uses the saved data to restore the anchor’s location. It compares stored feature descriptors to what the camera sees in real time, and if there’s a good enough match, the system confidently snaps the anchor into position, and your virtual content shows up right where it’s supposed to. However, using spatial anchors isn’t perfect, like using any other technology, and there are some tricky issues to figure out: Low latency. Matching saved data to real-time visuals has to be quick; otherwise, the user experience feels clunky. Robustness in feature-scarce environments. Blank walls or textureless areas don’t give the system much to work with and make tracking tougher. Scale drift. Little errors in the system’s tracking add up over time to big discrepancies. When everything falls into place and the challenges are handled well, spatial anchors make augmented and virtual reality experiences feel seamless and truly real. ARKit’s Spatial Anchors (Apple) Apple’s ARKit, rolled out with iOS 11, brought powerful features to developers working on AR apps, and one of them is spatial anchoring, which allows virtual objects to stay fixed in the real world as if they belong there. To do this, ARKit provides two main APIs that developers rely on to achieve anchor-based persistence. ARAnchor & ARPlaneAnchor The simplest kind of anchor in ARKit is the ARAnchor, which represents a single 3D point in the real-world environment and acts as a kind of “pin” in space that ARKit can track. Building on this, ARPlaneAnchor identifies flat surfaces like tables, floors, and walls, allowing developers to tie virtual objects to these surfaces. ARWorldMap ARWorldMap makes ARKit robust for persistence and acts as a snapshot of the environment being tracked by ARKit. It captures the current session, including all detected anchors and their surrounding feature points, into a compact file. There are a few constraints developers need to keep in mind: World maps are iOS-only, which means they cannot be shared directly with Android. There must be enough overlapping features between the saved environment and the current physical space, and textured structures are especially valuable for this, as they help ARKit identify key points for alignment. Large world maps, especially those with many anchors or detailed environments, can be slow to serialize and deserialize, causing higher application latency when loading or saving. ARKit anchors are ideal for single-user persistence, but sharing AR experiences across multiple devices poses additional issues, and developers often employ custom server logic (uploading ARWorldMap data to a backend), enabling users to download and use the same map. However, this approach comes with caveats: it requires extra development work and doesn’t offer native support for sharing across platforms like iOS and Android. ARCore’s Spatial Anchors (Google) Google’s ARCore is a solid toolkit for building AR apps, and one of its best features is how it handles spatial anchors: Anchors & Hit-Testing ARCore offers two ways to create anchors. You can use Session.createAnchor(Pose) if you already know the anchor’s position, or…

June 2, 2025
Extended Reality in Industry 4.0: Transforming Industrial Processes

Understanding XR in Industry 4.0 Industry 4.0 marks a turning point in making industry systems smarter and more interconnected: it integrates digital and physical technologies like IoT, automation, and AI, into them. And you’ve probably heard about Extended Reality (XR), the umbrella for Virtual Reality, Augmented Reality, and Mixed Reality. It isn’t an add-on. XR is one of the primary technologies making the industry system change possible. XR has made a huge splash in Industry 4.0, and recent research shows how impactful it has become. For example, a 2023 study by Gattullo et al. points out that AR and VR are becoming a must-have in industrial settings. It makes sense — they improve productivity and enhance human-machine interactions (Gattullo et al., 2023). Meanwhile, research by Azuma et al. (2024) focuses on how XR makes workspaces safer and training more effective in industrial environments. One thing is clear: the integration of XR into Industry 4.0 closes the gap between what we imagine in digital simulations and what actually happens in the real world. Companies use XR to work smarter — it tightens up workflows, streamlines training, and improves safety measures. The uniqueness of XR is in its immersive nature. It allows teams to make better decisions, monitor operations with pinpoint accuracy, and effectively collaborate, even if team members are on opposite sides of the planet. XR Applications in Key Industrial Sectors Manufacturing and Production One of the most significant uses of XR in Industry 4.0 is in manufacturing, where it enhances design, production, and quality control processes. Engineers now utilize digital twins, virtual prototypes, and AR-assisted assembly lines, to catch possible defects before production even starts. Research by Mourtzis et al. (2024) shows how effective digital twin models powered by XR are in smart factories: for example, studies reveal that adopting XR-driven digital twins saves design cycle times by up to 40% and greatly speeds up product development. Besides, real-time monitoring with these tools has decreased system downtimes by 25% (Mourtzis et al., 2024). Training and Workforce Development The use of XR in employee training has changed how industrial workers acquire knowledge and grow skills. Hands-on XR-based simulations allow them to practice in realistic settings without any of the risks tied to operating heavy machinery, whereas traditional training methods usually involve lengthy hours, high expenses, and the need to set aside physical equipment, disrupting operations. A study published on ResearchGate titled ‘Immersive Virtual Reality Training in Industrial Settings: Effects on Memory Retention and Learning Outcomes’ offers interesting insights on XR’s use in workforce training. It was carried out by Jan Kubr, Alena Lochmannova, and Petr Horejsi, researchers from the University of West Bohemia in Pilsen, Czech Republic, specializing in industrial engineering and public health. The study focused on fire suppression training to show how different levels of immersion in VR affect training for industrial safety procedures. The findings were astounding. People trained in VR remembered 45% more information compared to those who went through traditional training. VR also led to a 35% jump in task accuracy and cut real-world errors by 50%. On top of that, companies using VR in their training programs noticed that new employees reached full productivity 25% faster. The study uncovered a key insight: while high-immersion VR training improves short-term memory retention and operational efficiency, excessive immersion — for example, using both audio navigation and visual cues at the same time — can overwhelm learners and hurt their ability to absorb information. These results showed how important it is to find the right balance when creating VR training programs to ensure they’re truly effective. XR-based simulations let industrial workers safely engage in realistic and hands-on scenarios without the hazards or costs of operating heavy machinery, changing the way they acquire new skills. Way better than sluggish, costly, and time-consuming traditional training methods that require physical equipment and significant downtime. Maintenance and Remote Assistance XR is also transforming equipment maintenance and troubleshooting. In place of physical manuals, technicians using AR-powered smart glasses can view real-time schematics, follow guided diagnostics, and connect with remote experts, reducing downtime. Recent research by Javier Gonzalez-Argote highlights how significantly AR-assisted maintenance has grown in the automotive industry. The study finds that AR, mostly mediated via portable devices, is widely used in maintenance, evaluation, diagnosis, repair, and inspection processes, improving work performance, productivity, and efficiency. AR-based guidance in product assembly and disassembly has also been found to boost task performance by up to 30%, substantially improving accuracy and lowering human errors. These advancements are streamlining industrial maintenance workflows, reducing downtime and increasing operational efficiency across the board (González-Argote et al., 2024). Industrial IMMERSIVE 2025: Advancing XR in Industry 4.0 At the Industrial IMMERSIVE Week 2025, top industry leaders came together to discuss the latest breakthroughs in XR technology for industrial use. One of the main topics of discussion was XR’s growing impact on workplace safety and immersive training environments. During the event, Kevin O’Donovan, a prominent technology evangelist and co-chair of the Industrial Metaverse & Digital Twin committee at VRARA, interviewed Annie Eaton, a trailblazing XR developer and CEO of Futurus. She shared exciting details about a groundbreaking safety training initiative, saying: “We have created a solution called XR Industrial, which has a collection of safety-themed lessons in VR … anything from hazards identification, like slips, trips, and falls, to pedestrian safety and interaction with mobile work equipment like forklifts or even autonomous vehicles in a manufacturing site.” By letting workers practice handling high-risk scenarios in a risk-free virtual setting, this initiative shows how XR makes workplaces safer. No wonder more companies are beginning to see the value in using such simulations to improve safety across operations and avoid accidents. Rethinking how manufacturing, training, and maintenance are done, extended reality is rapidly becoming necessary for Industry 4.0. The combination of rising academic study and practical experiences, like those shared during Industrial IMMERSIVE 2025, highlights how really strong this technology is. XR will always play a big role in optimizing efficiency, protecting workers, and…



Let's discuss your ideas

Contact us