When AI Meets Unreal: The Dawn of Intelligent Digital Worlds

AI’s Rapid Progress

A decade ago, we were all asking ourselves if AI could take over the world, as portrayed in the movies, and if so, when? I guess that ‘WHEN’ is now!

We live in an era where AI is everywhere. It doesn’t just answer questions; it perceives environments and simulates behaviour. It even helps with homework and code, acting like an intelligent layer over our lives. Generative AI models like ChatGPT, Gemini, and Perplexity, to name a few, are surpassing expectations. They now converse naturally and improve daily, and do many of our jobs better than we do, and faster too.

With all the progress in AI, we can only imagine the endless possibilities ahead and the kind of integrations out there waiting to take us by surprise.

The Future of Gaming and Visualisation

Amid the boom and chaos, some things stay the same: the need to unwind with cool games to relax (unless you’re playing Elden Ring!) and the need to help industries visualise their vision.

Visualisation in this context can refer to Arch Viz, Digital twins, City twins, Product Visualisation, and more. While various tools help build all of this, one tool that always sticks out is the most popularly known Unreal Engine, unless you’ve familiarised yourself with it only through Fortnite.

Although Unreal Engine only started as a game engine, it's so much more today. From manufacturing and product visualisation to architecture, digital twins, films, and beyond, Unreal has found its place in nearly every industry that needs high-quality, real-time interactive experiences. It is no longer just for building games; it is redefining how we see and interact with the world.

Unreal Engine’s capabilities and its offerings to Digital Twins are outlined in this post

Unreal’s design capabilities have expanded drastically with features like Nanite, Lumen, World Partition, Pixel Streaming, in-house modelling and animating tools, and more, making it easier than ever to build immersive, visually pleasing environments at any scale.

While Games and Visualisation in general have used AI in small ways before, that’s changing now. With tighter and more powerful integrations, AI is now becoming a core part of how we build and experience virtual worlds.

Although Unreal has already changed how we build and experience digital spaces, combining AI will make Unreal the next major platform for intelligent simulation and autonomous environments.

The “What-if?”

Now that we are at a place that we never dreamed of, let’s dream of a world where these two tech-heavy, complex behemoths come together: AI and Unreal Engine. Let’s abandon all disbelief and imagine a world where Unreal can integrate fully with various LLMs and comes with a fully working offline/online AI model. Woah, too much to take in, right?

Let’s see what capabilities are possible with this integration -

1. Conversational Interaction

by using voice APIs, MetaHuman, and GPT integration to drive natural conversation with a visual response.

Let users talk to their Digital Twins:

• Example 1: “Give me a list of underutilised meeting rooms”.
• Example 2: “Find an optimal escape route from the facility”.

Create Endless Dialogue Trees:

• RPG and Telltale games could benefit from endlessly branching dialogues and conversations thanks to the GPT integration, minimising writing effort.
• Opens up possibilities to get multiple endings with minimal effort and opens up a brilliant way to play games, which feels almost natural.

2. Visual Understanding

AI models can actually “see” scenes and help build better worlds, by making use of models like SAM, OpenCV, DINO and more, along with lots of preprocessing or ML inference.

• Auto-detect missing safety gear in a simulation.
• Auto-detect anomalies and faults in Twins.
• Detect faces of meshes that are not visible to the camera and remove them to better optimise the scene.
• Learn the optimal way a scene in a Twin or a game is often visited and optimise rendering of underlying meshes and their LODs accordingly, integrating with Unreal’s own Nanite.

3. Autonomous Agents

making use of Reinforcement learning and Unreal environments.

• Train AI agents to navigate spaces, simulate occupancy, fire escape, perform tasks (PPM), and interact with the world.
• Fully intelligent agents in training sims, city planning, retail flow, and more, with the help of ML policies in addition to Unreal’s already powerful AI engine.

4. Predictive Operations and Simulations

Integrating real-time ML inference. Unreal could simulate AI models predicting:

• Maintenance needs.
• Energy spikes.
• Crowd Movement.
• Anomalies in Occupancy and AQI.