How AI is Changing the 3D Rendering Industry in Fall 2024: Insights from 17 Years of Experience

3D rendering has seen tremendous changes over the past few decades. As we head into Fall 2024, one of the most significant technological developments reshaping the industry is artificial intelligence (AI). From automating repetitive tasks to generating highly complex visuals with just a simple text prompt, AI is fundamentally changing how 3D artists and designers approach their work. Having been in the industry for 17 years, we at RealSpace3D have experienced first-hand how AI is revolutionizing the rendering process, and we believe that this transformation is only beginning.

Introduction

This article will explore the current state of generative AI in 3D rendering, its capabilities, and its limitations. We will also delve into the practical applications of AI in conceptual renderings, generating elements, and idea generation. Finally, we’ll offer insights into the future potential of AI within the industry, informed by our nearly two decades of experience.

What Is Generative AI?

Generative AI refers to a class of artificial intelligence models capable of generating new content based on input data, such as images, videos, or even 3D models. This can include creating visuals from a text prompt or generating variations of an image based on an existing model.

In the context of 3D rendering, generative AI has become particularly useful because it can create detailed visuals without the need for a complex manual design process. For example, by inputting a simple phrase like "a modern office building with large glass windows," AI can produce a high-quality image that aligns with the description, convincingly capturing architectural styles, materials, and lighting.

The underlying technology typically involves deep learning models, such as Generative Adversarial Networks (GANs) and diffusion models, trained on vast images, textures, and 3D assets datasets. Once trained, these models can produce new images or models that mimic the characteristics of the training data.

In practical terms, generative AI empowers artists and designers by drastically reducing the time it takes to move from concept to visualization. This democratization of content creation allows for greater exploration, experimentation, and efficiency, but it’s important to remember that this technology, while powerful, also has its limits.

Where Are We Now?

As of 2024, AI has reached a stage where it can generate highly sophisticated and impressive imagery, often indistinguishable from manually created designs. This technology has introduced a paradigm shift in terms of speed and the types of visuals that can be generated.

The Quality of AI-Generated Images

AI-generated imagery has improved dramatically in recent years. These renderings' quality, detail, and accuracy can rival traditional methods, often produced in a fraction of the time. AI models can now create complex architectural designs, futuristic landscapes, and highly stylized images with nuanced lighting and textures.

Efficient Creation of Complex Designs

Traditional 3D modelling and rendering processes can be time-consuming, especially when dealing with intricate or highly detailed scenes. With AI, things that were once considered impractical due to time or resource constraints can now be realized. For example, creating sprawling cityscapes or intricate environmental designs with thousands of objects would take weeks or even months of manual labour. AI, however, can generate these types of scenes in hours.

Pushing Creative Boundaries

AI can create visuals that would be nearly impossible to conceive manually. By generating designs that blend various architectural styles, materials, or environments in novel ways, AI pushes the boundaries of what is possible. AI acts as a catalyst for creativity for designers looking to experiment with new forms and aesthetics.

While generative AI has dramatically benefited the 3D rendering industry, it still needs improvement. Understanding its limitations is essential to managing expectations and optimizing its use in professional workflows.

What Are the Shortcomings of Generative AI?

Despite its advancements, generative AI has several shortcomings that limit its applicability in certain aspects of 3D rendering.

Disobedience: Difficulty in Generating Specific Buildings or Surroundings

One of the most significant challenges with AI-generated imagery is the difficulty in producing specific, detailed environments, such as exact replicas of buildings or surroundings. AI is incredibly adept at producing general concepts and generating aesthetically pleasing visuals. Still, it often falls short when tasked with creating highly accurate models based on real-world locations or blueprints.

For instance, if a client requests a precise rendering of a particular building with intricate architectural details, AI might struggle to generate the exact design elements. This lack of control means that while AI can generate stunning visuals, it is often unreliable for projects requiring specificity, such as historical reconstructions or client-driven architectural visualizations.

Refinement: Unintended Changes During Element Updates

Another limitation of AI is its holistic approach to image generation, making it difficult to refine specific rendering parts without affecting the entire image. This interconnectedness can frustrate designers trying to make small adjustments.

For example, if an artist wants to update the colour of a building's facade, AI might unintentionally alter other elements of the scene, such as the lighting or background objects. This can lead to unnecessary iterations and inefficiencies, as designers must wrestle with the model to produce their desired result.

Inability to Follow CAD Plans with High Precision

The most significant limitation of AI in 3D rendering is its inability to interpret and follow precise Computer-Aided Design (CAD) plans. Most architectural clients require renderings to adhere to strict measurements, tolerances, and other technical details that ensure the design is feasible and accurate. AI needs more precision and understanding to generate models that meet these stringent requirements.

This means that for projects requiring technical accuracies—such as architectural visualizations for real estate developers or engineering firms—traditional methods of modelling and rendering remain indispensable. AI might provide initial concepts or visual inspiration, but detailed CAD-based renderings require manual intervention from skilled artists and technicians.

What Are Some Current Applications Where AI Can Be Used?

Despite these limitations, there are many areas in which AI can be effectively integrated into 3D rendering workflows, adding value and streamlining the creative process.

Conceptual Renderings

One of the most powerful uses of AI in 3D rendering is in creating conceptual renderings. During the early stages of a project, designers often need to convey an idea or a concept without delving into exact specifications or details. This is where AI excels—by generating rough but compelling visuals that communicate a design's overall feel and direction.

For instance, a property developer might want to explore different architectural styles for a proposed building. AI can quickly generate multiple versions of the design, each with unique stylistic elements, allowing for faster decision-making and iteration.

Generating Elements for Compositing

AI can also generate specific elements or assets that can be composited into more significant scenes. For example, an artist working on an architectural visualization might use AI to create natural elements like trees, foliage, or even vehicles, which can then be integrated into a final rendering.

This ability to quickly generate assets for post-processing can save artists time while allowing them to focus on refining the overall composition of the scene. AI-generated assets can also add variety and realism to scenes without requiring the artist to create every element from scratch manually.

Idea Generation and Inspiration

For many designers, one of AI's most exciting uses is in idea generation and creative inspiration. AI models can produce visuals that blend different genres, styles, and influences in ways that might not occur to a human artist. By inputting various prompts, designers can explore various possibilities and quickly iterate on ideas.

This is particularly valuable for early-stage brainstorming sessions, where the goal is to generate as many ideas as possible before refining them into a cohesive concept. AI acts as a creative collaborator, helping to spark new ideas and uncover unconventional approaches.

Expediting Pre-Visualization in Film and Gaming

In the film and gaming industries, AI has found a home in the pre-visualization production stage. Pre-visualization, or “previs,” involves creating rough versions of scenes to help directors and designers visualize the final product before full production begins.

AI-generated previs allows directors to see how different environments, lighting conditions, or action sequences might look in the final production. This accelerates the planning process and provides valuable insight into the potential challenges or opportunities in a scene, enabling more informed decision-making before committing to costly production resources.

Conclusion

Artificial intelligence has undoubtedly transformed the 3D rendering industry, offering unprecedented efficiency, creativity, and speed capabilities. While generative AI can produce visually stunning and conceptually rich imagery, it has its limitations. From difficulty in generating specific environments to challenges in refining individual elements, AI still falls short in areas where precision and accuracy are paramount.

However, despite these shortcomings, AI is a valuable tool for designers, artists, and architects, particularly in conceptual rendering, generating assets, and providing creative inspiration. Its role in the 3D rendering workflow will likely continue to grow as improvements in AI technology address some of its current limitations.

At RealSpace3D, with 17 years of experience in the industry, we’ve seen firsthand how technology reshapes the creative landscape. AI is not a replacement for human talent and expertise but a powerful tool that can enhance creativity, improve efficiency, and unlock new possibilities. By combining the strengths of AI with the precision and insight of skilled artists, the future of 3D rendering is more dynamic and exciting than ever before.