Generative XR: How Will AI and Spatial Computing Collide and What Will it Mean for Us? 

Facebook is undeniably one of the biggest culprits for fake content created with generative AI software. Log into Mark Zuckerberg’s social opium and witness the growing number of picture-based posts showing cataclysmic weather systems in the American mid-west, or creepy apparently abandoned Victorian houses of asylums, or beautiful, Thunderbirds style homes on gorgeous coasts. Regardless of how much the poster may try to convince an in-awe readership, little or none of it is real; it is all the product of the slew of Generative Fill AI tools that are now available.

Generative artificial intelligence, often known as GenAI, is a type of AI that has the ability to create new content, including text, photographs, videos, music, and a wide variety of other forms of audio and visual media from text inputs. A significant amount of data is used to train generative artificial intelligence models, which subsequently make use of that data to discover patterns and structure. They are then able to generate fresh data that consists of features that are comparable to the initial data. For instance, a generative artificial intelligence model that has been trained on the English language could use the words that it has learnt to compose a poem. 

It is now possible to employ generative AI for a wide range of applications, including chatbots, the production of media, the development of products, design, writing, research, and coding. A few examples of well-known generative artificial intelligence models are ChatGPT, which generates text, and DALL-E, which generates images. 

GenAI plainly has a lot of potential for content creation, but the technology behind the generation of images and written works is also starting to emerge as something that impacts XR and the development of virtual content. This is actually very exciting, because it occupies a different part of the market, and has the potential to change how we use and interact with the internet and Metaverse.

Currently, the virtual experiences that we engage with are painstakingly created by skilled and trained developers. People spend all day lovingly creating engaging experiences that thrill us with their depth and imagination. The XR experiences that we have are the result of developer teams who build them from the ground up. However, with Generative XR, there is the potential for the current tools to extend their scope, and actually create bespoke experiences in an instant from text prompts alone. That is exciting enough, but many industry commentators see the convergence of GenAI and XR technologies as not only essential, but the next most obvious step in the evolution of virtual technologies. 

Even though the notion of GenAI married to XR is still in its early stages, industry is already imagining a number of ways in which the two technologies could combine to create new functionalities, use cases, and points of value. Many developers see these possibilities being split between what are described as being user-facing and creator-facing features. The user-facing features would be the instant development of worlds and scenarios from a few text inputs, as described above. 

The creator-based inputs could comprise text-based commands that could be used to generate short how-to videos and 3D explainers such as how to tie shoe-laces or spatchcock a chicken. Search engines using creator-based inputs would become AI-generated, video-rich experiences that show you exactly what you are searching for. This is the most intriguing of the possibilities since it effectively becomes the first step towards truly virtual personal experiences, including:

• AI Virtual Assistants. Enhanced user experience can be achieved by the utilisation of GenAI-based virtual assistants in XR environments, which are able to offer real-time advice and direction.
• Adaptive Experiences. GenAI is able to personalise the XR experience to the interests and habits of each individual user by providing individualised material and interactions. These can range from films and computer-generated imagery (CGI) to virtual concerts and events.
• Predictive Visualisations. Utilising GenAI for the purpose of providing personalised client encounters, predictive visualisations are particularly useful in the healthcare industry.
• Virtual Learning. GenAI can enable virtual classrooms that adjust to the subject matter, hence improving the learning experience.

The melding of GenAI with XR experiences that are hyper-personalized, adaptable, and interactive are made possible by this integration, which serves as a game-changer for marketers, learning and development teams, and developers. It offers a multitude of benefits, including the ability to redefine possibilities in the area of digital engagement.

While generative artificial intelligence has the potential to be fascinating and thrilling, yet it is not necessarily trustworthy. The content that is created by generative artificial intelligence models are derived from the data that they have been provided with; nevertheless, there is no assurance that the information will be accurate. A further possibility is that the responses are skewed due to the fact that the model has employed information from the internet that is already AI generated and much of the input material may itself be previously generated content.

With a growing number of companies working on enabling GenAI within XR, there are already plenty of excitement over the results. We at Unity Developers are watching this with keen interest. This is a development that could potentially enrich the content that we create on a commercial basis.

If you are looking for the development of a game or App in Unity, why not contact us and see how we can help you create something truly magnificent.