Comparing Generative AI Solutions for Extended Reality
It may seem like generative AI has stolen the spotlight from the metaverse and extended reality technologies for tech enthusiasts. However, there’s actually a significant symbiotic relationship between extended reality, AI solutions, and machine learning.
Generative AI, in particular, is helping to accelerate development cycles in the XR world. It’s helping companies to create more realistic, immersive environments and unique assets and enhancing the development of new XR hardware.
The rise of generative AI could help unlock new opportunities in the metaverse for all kinds of companies and end users and transform our immersive interactions. So, how do you choose the right extended reality AI software for your needs? Here’s your step-by-step guide.
Step 1: Consider Your Goals and Use Cases
The first step in comparing extended reality AI solutions is identifying your specific use cases and goals. The most common way companies leverage generative AI in extended reality is to streamline and support content development. Generative AI can create 3D content, assets, landscapes, and even non-playable characters (NPCs) for XR applications.
Companies like Snap and Meta even give developers access to generative AI tools that can reduce the time and effort involved in creating virtual experiences. However, there are various other ways companies can experiment with generative AI for XR.
For instance, generative AI solutions can be built into XR applications to give every user in an app access to a real-time coach, source of customer support, or coworker. For example, Copilot in Microsoft Mesh for Microsoft Teams can give each employee a real-time assistant to help them complete tasks.
Generative AI can also help generate digital twins of new products, ensuring teams can experiment with different ways to produce lighter and more comfortable virtual reality headsets or smart glasses.
Step 2: Examine Extended Reality AI Integration Options
If you’re using extended reality AI to streamline the development process or create content, integrations are essential. The best generative AI software should work seamlessly with the tools your teams already use, from content creation and development platforms like Unity and Unreal, to metaverse as a service platforms.
The ability to access AI alongside crucial CAD tools, software development kits, and even project management and analytical tools will help to enhance your workflows and boost productivity. If you’re using generative AI as a feature in an extended reality app, it’s important to ensure the technology you access can work seamlessly with the hardware your end users prefer.
For instance, you might want to ensure your app will work well on a device like the Apple Vision Pro, leveraging spatial computing features and gesture or voice recognition to improve user experiences. Your technology might need to integrate with certain solutions to enable specific capabilities. For instance, if your customers use generative AI to create realistic avatars, your tech will need to integrate with facial scanning tools.
Step 3: Prioritize Advanced AI Functionality
To take full advantage of extended reality AI, companies need access to the most advanced algorithms. Simple solutions like ChatGPT might help you create scripts and basic images for your XR applications. However, more advanced toolkits can assist with various aspects of the development process. For instance, Nvidia’s generative AI solutions can rapidly produce digital twins, or leverage perception algorithms for spatial mapping, object recognition, and more.
VirtualSpeech’s generative AI solutions can enable speech-to-text capabilities and learn over time to adapt training experiences to the needs of different users. Many generative AI solutions also offer exceptional customization options. They can adapt to serve users in different languages, speak in a specific tone of voice, or match the personality of a certain brand.
Some solutions even combine generative AI capabilities with other forms of artificial intelligence, such as conversational AI, or computer vision. Prioritize advanced features based on the specific use cases and goals you have for generative AI in XR.
Step 4: Consider Security and Compliance
Security and compliance are two major concerns for anyone investing in extended reality AI. Whether you’re purchasing a pre-built generative AI app for your team to use in virtual or augmented reality applications or building something new with gen AI, security is key.
Like most forms of AI, generative AI relies heavily on large volumes of data. This makes it crucial to ensure the software you’re using stores and collects data according to compliance standards. If you’re investing in an AI app for extended reality or you’re building a new metaverse environment with AI, make sure your data will be encrypted and protected.
It’s also worth considering how you can ensure your AI solution is ethical. Generative AI can create synthetic data that gives companies access to broader, more diverse data sets they can use to create highly accessible and user-friendly applications and tools. This can also allow for the creation of more ethical AI assistants for use in training and customer service.
Step 5: Look for Scalable Extended Reality AI
Finally, whenever you invest in extended reality AI for any purpose, you’ll have the ability to scale your solution as your business grows. If you’re purchasing generative AI applications for your team, you must ensure the solution can scale to support as many team members as possible. Ensure it works in various languages and is easily accessible on various devices, from smart glasses to mixed reality headsets like the Apple Vision Pro.
If you’re using generative AI for content development, make sure you can train and fine-tune your solution with proprietary data and insights. Look for machine-learning capabilities that will make your technology more efficient and effective over time.
Additionally, ensure you can add to the functionality of your generative AI system over time by integrating additional applications and software with the technology or customizing certain elements. This will help you get the most value out of your technology.
Comparing Extended Reality AI Solutions
AI and extended reality are a match made in heaven. Whether you’re looking for ways to get more value out of your immersive collaboration apps with an AI assistant or you want to accelerate your product development lifecycle, generative AI can help.
The key to choosing the right solution is identifying your specific use case and examining the available technology carefully to ensure your technology is secure, scalable, and innovative.
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