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In 2017, a landmark paper by Google Research introduced a new deep learning architecture for natural language understanding called the 'Transformer.' This new approach possessed the capacity to produce language models of exceptional quality, alongside the added advantage of being highly scalable and requiring significantly less time for training. The public release of this research and Google's first BERT model started a race to build even larger and more powerful language models.

In 2020, OpenAI unveiled GPT-3, the successor to their previous language model, GPT-2. Boasting an unprecedented size, GPT-3 was ten times larger than any existing model, with a colossal 175 billion parameters trained on a dataset of almost a trillion words. Although primarily intended to predict the next word in a sequence, the GPT-3 model exhibited 'emergent abilities' beyond its training, displaying new skills such as translation, entity recognition, summarization, arithmetic computations, code generation, and more due to its size.

In 2022, the generative AI landscape began to form as commercial access to the models became available and new techniques introduced applications for image generation, code generation, protein sequencing, and more. Large language models will continue to enable new waves of research, creativity, and productivity by facilitating the generation of complex solutions for some of the world's most challenging problems across a broad range of industries and enterprises.

How Will This Impact the Real Estate Industry?

While there are numerous AI models available and new ones emerging, the most valuable for the real estate industry in the near term are text and image models.

These models have numerous applications in the real estate industry and will unlock dramatic improvements not only in the speed and efficiency of employees but will also enable new levels of creativity and capability in their work.

In the first instalment of this two-part series, we will delve into the marketing applications of generative AI in real estate, while the subsequent edition will explore search and conversational applications in depth.

Marketing Applications

Generative AI models are valuable across a number of business functions, but marketing applications are perhaps the most common. One of the most significant benefits is the ability to create high-quality, engaging content at scale. For example, generative AI can be used to automatically generate property descriptions, virtual home tours, and even 3D floor plans. This saves real estate agents and marketers a significant amount of time and resources while also providing potential buyers with more immersive and interactive experiences.

Example: Utilizing ChatGPT to create a listing.

Let’s start with the applications for text generation. Tools like Jasper.ai, a marketing-focused product for AI-generated content, can produce blogs, social media posts, web copy, sales emails, ads, and other types of customer-facing content. The early adopters in the real estate industry are already using these tools to accomplish their work in a fraction of the time it would normally take to write this content.

However, it's not just the time saved; it's also the fact that new agents and property managers can easily produce high-quality and more accurate content about their properties, which can be difficult to do manually without significant effort and experience. Here are a few examples.

 

 

1. Automated Content Creation: automatically generate property descriptions, blog posts, and social media posts, saving real estate agents and marketers a significant amount of time and resources.

2. Personalized content: create personalized content for potential buyers, such as emails or property descriptions that are tailored to their preferences and search behavior to help buyers feel more engaged and interested in the properties being presented to them.

3. Market Analysis: analyze data on property and market trends, and then create informative and persuasive content that speaks to those trends to create more accurate and informative content that resonates with potential buyers.

4. Multilingual content: create content in multiple languages, which can be useful for real estate agents and marketers working in diverse markets or with international buyers.

So, as you can see, automated text generation will have a huge impact, but there’s more.

Generative AI image models can also play an incredibly valuable role in automating expensive and time-consuming tasks involved in selling and building a property.

Here are a few examples: 

1. Virtual Staging: create images of empty or unfurnished properties with furniture and decor that looks real.

2. Photo Editing: automatically enhances photos of properties, such as brightening the image, removing objects, or adding filters.

Example: Using Autoenhance.ai Sky Replacement feature

Example: Using Stable Diffusion + ControlNet with a photo of a home and a prompt for “light gray two-story house with dark shutters, a green lawn, and landscaping along the front”

3. Materials & Finishes: Image generation can be used to create realistic simulations of different materials and finishes, allowing interior designers to experiment with different combinations.

Example: Using Stable Diffusion + ControlNet with a photo of a kitchen and a prompt for “modern kitchen with white marble countertops”

4. Virtual Property Tours: create virtual tours of properties before they are built, helping architects and real estate developers showcase their designs to potential clients and investors.

"The adoption of generative AI technology will occur faster than cloud computing and smartphone adoption and significantly impact every industry, including real estate"

5. Design Visualization: create realistic 3D visualizations of architectural designs, helping architects and developers better visualize and design the final product.

6. Space Planning: 2D and 3D image generation can be used to create interactive design tools that allow users to create or manipulate floor plans and space layouts in real time.

Example: Maket.ai

7. Building Systems: 3D image generation can be used to create detailed 3D models of building systems, allowing engineers and architects to identify potential issues and optimize system design before construction begins.

8. Personalized content: create personalized content for potential buyers, such as virtual tours or images that show what a property would look like with different paint colors or furniture.

The generative AI market in the US is expected to reach over $110B by 2032, and the adoption of generative AI technology will occur faster than cloud computing and smartphone adoption and significantly impact every industry, including real estate. It's amazing to see the rapid evolution and development of these technologies, and we can expect even more exciting use cases to emerge in the near future.