METAVERSE APPLICATIONS
Improve the intuitiveness of your metaverse with user-friendly blockchain-enabled applications. Several different factors are powering metaverse development. Understanding each of them and recognizing where they intersect is critical to innovation.
Use our best-in-class AR/VR and blockchain expertise for building a decentralized platform. Our team creates truly immersive virtual environments that allow users to interact, hang out, learn, or even work. We also implement integrations to add value to your custom metaverse project, from APIs to data and services.
AR and VR in the Metaverse
Virtual reality is one of the most prolific technologies moving the metaverse forward, but it has several limitations. Since these are emerging technologies, the world isn’t quite ready for widespread, easily accessible VR. First of all, this is due to limited mobility. To experience virtual reality, the user needs a special VR headset, which is quite bulky and doesn’t allow the head or body movements needed to get the full experience. Moreover, the cost of VR devices is relatively high, and there are no standards for virtual reality yet, so content created for one platform may not work with another.
AI In The Metaverse
Extended reality technologies like AR and VR have many limitations, but developers can overcome them with another advanced technology. This technology is artificial intelligence. Creating lifelike 3D spaces, delivering more realistic experiences, and running complex calculations necessary for AR face tracking and other tasks are best handled by AI. Artificial intelligence can complete these tasks more efficiently than humans in far less time. Self-supervised learning will greatly increase the efficiency of AI-powered systems.
Natural Language Processing
A subset of artificial intelligence that is important for the development of the metaverse is natural language processing. This is an advanced way for AI to interpret and emulate human speech. Not only will this be a great way for users and AI to interact in the form of customer service chatbots and virtual assistants, but it also can make the metaverse more accessible for diverse groups of people. For example, conversational artificial intelligence enables rich real-time language translation, even though it’s a challenging task.
In fact there is a non-monotonic relationship between the source speech and the target translations. It means that the words at the end of the speech can influence words at the beginning of the translations. So, there is no real real-time speech translation because there is always the need to check the translated text consistency against the original speech (so called re-translations). There is always a small delay even if you can’t see it. Therefore, you need advanced algorithms to stabilize the translation of live speech, as Google does in its Google Translate to reduce the number of re-translations.
Internally real-time speech translations may be organized as follows: user says something, the user’s speech turns into a text, the text is then translated into the other language. After the speech is paused/ended and the final re-translation is done, the text turns into a speech using speech-to-text technologies.
NLP also can provide live captions for users with hearing impairments. For example, AI technology can instantly transcribe the conversation of a group of people, making communication within a metaverse application accessible to users with hearing disabilities.
Virtual Assistant Technology
NLP also makes digital voice assistants and AI avatars possible that can help users with hands-free operation of their devices, as well as targeted suggestions. Meta is already developing a voice assistant that will be used in metaverse applications in coming years. Virtual assistants can perform language translation, financial management, and much more.
The representation of users in the metaverse as AI avatars or digital humans also relies on NLP. Conversational AI allows avatars to process and understand human language as well as respond to voice commands. Last year NVIDIA introduced the Omniverse Avatar avatar modeling platform. It allows you to create virtual versions of people who not only recognize speech, but also capture emotions on the faces of users.
Computer Vision
Computer vision can enable machines to better create digital copies of objects, recognize images and patterns, and even recognize the expressions and moods of users. One of the limitations of VR and AR experiences is control. Hardware controllers, gloves, or other kinds of physical devices can be used to input into the device. However, computer vision can help make this experience more natural by using hand tracking. By recognizing gestures and finger positions, users can interact with their devices more naturally and freely.
AR implementation includes the coordination of both the cell phone’s video camera and LiDAR. Video camera captures the image/video of the real world and the user’s hand. LiDAR estimates the distance between the real-world objects and the user’s hand. With that information we can correctly place some virtual objects on the phone screen, so from the user’s perspective the virtual object looks like a part of the real world.
With the help of computer vision technologies we can recognize if the user tries to interact with the virtual object with the hand. Examples of such interactions can be putting the virtual object to a cart in a virtual shop or animating objects (useful for AR-interactive games).
Human Pose Estimation
Given that users interact with the metaverse in the form of digital avatars with bodies, it’s important that the posture of those characters be accounted for. Human pose estimation (HPE) uses motion sensing devices like controllers, gloves, and more to accomplish this. HPE recognizes body parts and their positions in an environment, while another practice called action recognition can identify more complex interactive activities like grabbing items or pushing buttons.
Internet of Things and the Metaverse
Artificial intelligence is just a part of the metaverse story and it’s usually not the answer to every problem that developers face when making metaverse projects. AI needs high quality data, and that data needs to come from somewhere. Internet of Things devices and sensors are critical for providing high-quality real-time data to AI systems for analysis.
One of the most useful applications of IoT in the metaverse are digital twins. This technique utilizes IoT sensors to create a digital version of an environment or system. With VR relying heavily on virtual environments, being able to create a virtual representation of an environment using sensors is in high demand.
The Blockchains Role in Web 3.0
As a global and decentralized system, blockchain platforms are in demand for use in metaverse projects. Centralized data storage is problematic in the metaverse because of the barriers to the flow of information. A more open solution like a blockchain can allow for a more fluid flow of information and proof of ownership for digital assets. Due to this, there is high demand for development of systems that can support cryptocurrencies and non-fungible tokens.
Non-fungible tokens or NFTs, today are the most promising way to develop the metaverse economy. Since each token is unique, it can be reliable proof of digital ownership recorded in the blockchain. For example, users can buy in-game assets and digital real estate in the form of non-fungible tokens representing the right to own these items.
3D MODELING
With the metaverse relying heavily on virtual worlds, 3D modeling is a skill that’s in high demand. From decorating homes to creating skins for avatars, modeling is something that virtual worlds can’t do without. With such a large number of objects that need to be digitized, it’s clear why IoT sensors need to be used to create digital twins of environments. Large databases need to be made of real world objects that have been ‘3D captured’ and digitized.
Use our best-in-class AR/VR and blockchain expertise for building a decentralized platform. Our team creates truly immersive virtual environments that allow users to interact, hang out, learn, or even work. We also implement integrations to add value to your custom metaverse project, from APIs to data and services.
AR and VR in the Metaverse
Virtual reality is one of the most prolific technologies moving the metaverse forward, but it has several limitations. Since these are emerging technologies, the world isn’t quite ready for widespread, easily accessible VR. First of all, this is due to limited mobility. To experience virtual reality, the user needs a special VR headset, which is quite bulky and doesn’t allow the head or body movements needed to get the full experience. Moreover, the cost of VR devices is relatively high, and there are no standards for virtual reality yet, so content created for one platform may not work with another.
AI In The Metaverse
Extended reality technologies like AR and VR have many limitations, but developers can overcome them with another advanced technology. This technology is artificial intelligence. Creating lifelike 3D spaces, delivering more realistic experiences, and running complex calculations necessary for AR face tracking and other tasks are best handled by AI. Artificial intelligence can complete these tasks more efficiently than humans in far less time. Self-supervised learning will greatly increase the efficiency of AI-powered systems.
Natural Language Processing
A subset of artificial intelligence that is important for the development of the metaverse is natural language processing. This is an advanced way for AI to interpret and emulate human speech. Not only will this be a great way for users and AI to interact in the form of customer service chatbots and virtual assistants, but it also can make the metaverse more accessible for diverse groups of people. For example, conversational artificial intelligence enables rich real-time language translation, even though it’s a challenging task.
In fact there is a non-monotonic relationship between the source speech and the target translations. It means that the words at the end of the speech can influence words at the beginning of the translations. So, there is no real real-time speech translation because there is always the need to check the translated text consistency against the original speech (so called re-translations). There is always a small delay even if you can’t see it. Therefore, you need advanced algorithms to stabilize the translation of live speech, as Google does in its Google Translate to reduce the number of re-translations.
Internally real-time speech translations may be organized as follows: user says something, the user’s speech turns into a text, the text is then translated into the other language. After the speech is paused/ended and the final re-translation is done, the text turns into a speech using speech-to-text technologies.
NLP also can provide live captions for users with hearing impairments. For example, AI technology can instantly transcribe the conversation of a group of people, making communication within a metaverse application accessible to users with hearing disabilities.
Virtual Assistant Technology
NLP also makes digital voice assistants and AI avatars possible that can help users with hands-free operation of their devices, as well as targeted suggestions. Meta is already developing a voice assistant that will be used in metaverse applications in coming years. Virtual assistants can perform language translation, financial management, and much more.
The representation of users in the metaverse as AI avatars or digital humans also relies on NLP. Conversational AI allows avatars to process and understand human language as well as respond to voice commands. Last year NVIDIA introduced the Omniverse Avatar avatar modeling platform. It allows you to create virtual versions of people who not only recognize speech, but also capture emotions on the faces of users.
Computer Vision
Computer vision can enable machines to better create digital copies of objects, recognize images and patterns, and even recognize the expressions and moods of users. One of the limitations of VR and AR experiences is control. Hardware controllers, gloves, or other kinds of physical devices can be used to input into the device. However, computer vision can help make this experience more natural by using hand tracking. By recognizing gestures and finger positions, users can interact with their devices more naturally and freely.
AR implementation includes the coordination of both the cell phone’s video camera and LiDAR. Video camera captures the image/video of the real world and the user’s hand. LiDAR estimates the distance between the real-world objects and the user’s hand. With that information we can correctly place some virtual objects on the phone screen, so from the user’s perspective the virtual object looks like a part of the real world.
With the help of computer vision technologies we can recognize if the user tries to interact with the virtual object with the hand. Examples of such interactions can be putting the virtual object to a cart in a virtual shop or animating objects (useful for AR-interactive games).
Human Pose Estimation
Given that users interact with the metaverse in the form of digital avatars with bodies, it’s important that the posture of those characters be accounted for. Human pose estimation (HPE) uses motion sensing devices like controllers, gloves, and more to accomplish this. HPE recognizes body parts and their positions in an environment, while another practice called action recognition can identify more complex interactive activities like grabbing items or pushing buttons.
Internet of Things and the Metaverse
Artificial intelligence is just a part of the metaverse story and it’s usually not the answer to every problem that developers face when making metaverse projects. AI needs high quality data, and that data needs to come from somewhere. Internet of Things devices and sensors are critical for providing high-quality real-time data to AI systems for analysis.
One of the most useful applications of IoT in the metaverse are digital twins. This technique utilizes IoT sensors to create a digital version of an environment or system. With VR relying heavily on virtual environments, being able to create a virtual representation of an environment using sensors is in high demand.
The Blockchains Role in Web 3.0
As a global and decentralized system, blockchain platforms are in demand for use in metaverse projects. Centralized data storage is problematic in the metaverse because of the barriers to the flow of information. A more open solution like a blockchain can allow for a more fluid flow of information and proof of ownership for digital assets. Due to this, there is high demand for development of systems that can support cryptocurrencies and non-fungible tokens.
Non-fungible tokens or NFTs, today are the most promising way to develop the metaverse economy. Since each token is unique, it can be reliable proof of digital ownership recorded in the blockchain. For example, users can buy in-game assets and digital real estate in the form of non-fungible tokens representing the right to own these items.
3D MODELING
With the metaverse relying heavily on virtual worlds, 3D modeling is a skill that’s in high demand. From decorating homes to creating skins for avatars, modeling is something that virtual worlds can’t do without. With such a large number of objects that need to be digitized, it’s clear why IoT sensors need to be used to create digital twins of environments. Large databases need to be made of real world objects that have been ‘3D captured’ and digitized.