Virtual agents are computer systems Supercharge Productivity with Taskade AI that can function in a complex dynamic environment and display intelligence similar to human beings. They can also interact with the environment in a natural way and respond to user input.

AI technology can enhance the realism of VR and AR experiences by recognizing and understanding images and objects, creating accurate 3D models, and generating more dynamic content. It can also enable personalized simulations and more interactive and engaging experiences.
Virtual Reality (VR)

VR is a virtual reality technology that allows users to immerse themselves in a 3D digital environment using headsets and peripherals. It provides a visual, auditory and tactile experience, similar to real life. It is an increasingly important tool for training and problem-solving in a wide range of fields, from medical simulations to firefighter training. It is also used in mental health therapy and education.

Artificial intelligence can be used to create more immersive and engaging virtual reality experiences for learners. For example, AI algorithms can personalize VR content by adapting the difficulty of a simulation based on the user’s skill level and preferences. This can lead to more effective learning and better problem-solving outcomes.

In addition, AI can be used to automate the process of creating VR content. This can reduce the time and cost associated with VR production, allowing researchers to focus on more important tasks. AI can also be used to make VR more interactive and immersive by incorporating intelligent agents that can respond to the actions of the user.

For example, in a recent study on interprofessional communication skills, nursing students were asked to interact with an AI doctor in a 2-hour virtual reality training session. They were then evaluated on their communication knowledge and self-efficacy via survey questionnaires and focus group discussions. The results showed that participants reported significant improvements in both measures following the training.

In the experiment, I used a two-neural network approach to train the AI agent. The first, referred to as the Guiding Agent, was trained to learn the voxel arrangement of the target 3D model. The second, called the Creator Agent, was rewarded for selecting and placing blocks within the design space, similar to a human VR user. The Creator Agent was then instructed to move its gaze toward the target block, as if it were being directed by the Guiding Agent. The Creator Agent was rewarded with the dot product of its head position and world position relative to the target block. This allowed the agent to learn to use its position to determine what blocks it should look for in order to complete its task.
Augmented Reality (AR)

Augmented reality (AR) is a real-time technology that superimposes digital information on top of existing objects in the user’s environment. AR is used for a wide variety of applications including consumer and business uses like product visualization, training and instruction, home design and architecture, retail sales, medical diagnostics, and many more. It’s important to differentiate AR from virtual reality, as VR immerses the user in a completely simulated world while AR is more like a hybrid of the physical and digital world.

Typically, enterprise augmented reality solutions use sensors to track the position of real-world objects and overlay them with digital information in order to display the result on screen. These can include text, video, simple diagrams, 3D models and other immersive simulations. These can be delivered as AR apps, head-mounted gear and smart glasses. There are four main types of AR: marker-less, marker-based, projector-based and superimposition based.

Marker-less AR technology is similar to the way Google Glass works. It can be displayed on screens, handheld devices and even mobile phones. This type of AR is also referred to as passive AR because the user doesn’t have to actively interact with the augmented content.

The most popular application of this type of AR is the Pokemon Go mobile game where users can see their surrounding map covered in animated characters. However, it can also be seen on a TV or movie screen when watching the NFL or NBA.

For industrial and manufacturing applications, augmented reality provides an excellent solution to help solve complex challenges. By reshaping how frontline workers perform their tasks, it improves productivity and helps companies meet modern customer demand for faster product development and delivery time. It’s an integral part of Industry 4.0, PTC’s vision for the next evolution of manufacturing that includes automation, machine learning, connected data and more.

For example, in quality control and assurance, AR can enable workers to quickly access information and instruction for any machine they’re working on. This ensures that they can repair or maintain the machine with minimal downtime and support production without disrupting the overall process. It can also help to identify defects, prevent issues in production and ensure consistent, high-quality products.
Artificial Intelligence (AI)

Artificial intelligence (AI) is the technology that gives computers the ability to perform tasks without being explicitly programmed. It can understand human language, learn and adapt, and act in a way that is rational and humane. It is often associated with robots, but there are many other applications for AI that can improve our lives.

One of the most important applications of AI is machine learning. This involves using algorithms to teach the computer to perform a task through repetition and feedback. This is accomplished through either a simulator or real-world environment. AI can also be used to analyze user preferences and behaviors to personalize content for AR and VR experiences.

Another use of AI in VR is predictive modeling. This allows the computer to predict what users will do next and create more dynamic and interactive experiences. This can also help overcome some of the challenges that VR and AR have faced with lag, latency, and cost.

Image and object recognition is another area of AI that can enhance the realism of VR and AR. By analyzing real-world objects and environments and generating accurate 3D models, AI can create more immersive and realistic experiences for users. Speech recognition is another example of AI that can be used in VR and AR to allow users to interact with virtual characters and environments using natural, intuitive gestures or voice commands.

Training and Simulation
AI-enhanced simulations can help train users for various industries, including medical procedures and aviation, in a safe and controlled environment. This can help them develop the skills and knowledge they need to succeed in their careers.

In addition, AI can be used to optimize simulations by adjusting parameters such as lighting and physics to simulate a more realistic experience. It can also be used to create individualized training programs for each user based on their unique needs.

AI is also being used to deliver more personalized and targeted marketing messages in VR and AR. By analyzing customer data, such as purchase history and browsing behavior, AI can deliver content that is more relevant and engaging to each individual user. This can result in higher conversion rates and improved customer satisfaction.
Training Simulations

Virtual reality and multi-agent systems are two powerful technologies that can be combined to create training simulations. This combination makes it possible to simulate complex situations that would be impossible or very expensive in real life. This technology is now widely used in the areas of videogames, education, human behavior, and staff training. It also allows for the development of new applications that could be very useful in countless fields.

Using AI, VR and AR can be used to train robots and other automated systems to perform in the real world. This can help to reduce the risk of human error and ensure that the system is working as it should. It can also be used to test the performance of a product before it is deployed to customers or employees.

The emergence of AI has made it possible to create more complex and dynamic environments for use in VR and AR applications. This is because artificial intelligence algorithms can learn from user interaction and modify the virtual world in real time. The result is more realistic and engaging applications that will appeal to a wide audience.

This can be seen in the way that augmented reality is being used for gaming. However, augmented reality can be used for more sophisticated applications as well. For example, medical students can use augmented reality to interact with virtual patients and practice procedures before they go into the field. This will make for a more effective and safer learning experience for them.

AI can also be used to improve the accuracy and speed of voice recognition in VR and AR. This is because AI can understand the context of a conversation and make better decisions about how to respond. It can also adapt to the user’s individual style of speech and tone of voice. This will make the user feel more comfortable and confident in the ability of the system to understand their needs.

Various research works have been done to integrate multi-agent systems into VR. Rincon et al. [42] have developed a framework for Intelligent Virtual Environments (IVEs) that uses a multi-agent architecture. Okresa et al. [43] proposed a MAM5 ontology for IVEs to support the knowledge representation and reasoning capabilities of agents. They also created an agent-based IVE that utilizes a chatbot. They found that users could request hints from the agents by name or as questions, and the agent could list out the available hints and dialogue options for them to choose from.