🧿AI powering the Metaverse

AI powering the Metaverse

Artificial intelligence is one of the pillars on which the metaverse is being built. Starting with processing user-generated data, continuing with generative AI models that create photorealistic virtual environments and avatars that resemble users, and the ability to recognize body movements and thus make the metaverse experience more natural.

But AI will also breathe new life into the digital characters that populate virtual worlds, such as non-human characters and personal assistants, and allow everyone to understand each other in their own language by simultaneously translating speech.

Integration of the Metaverse with Eye-AI

Artificial intelligence will provide fundamental support for the metaverse, simplifying people's access to digital environments, as well as aiding in content generation and the interaction between humans and virtual worlds. Here are some of the points we will address:

Reconciling trends

For the metaverse to exist, servers and network systems need to be up and running. As companies that host MMORPGs (such as World of Warcraft or Elder Scrolls Online) are well aware, running an infrastructure that can simultaneously host over half a million users every day requires titanic efforts in terms of computing resources.

This is precisely why Meta recently unveiled the AI Research SuperCluster (RSC), one of the most powerful AI supercomputers in the world. As the company states, one of the tasks of the supercomputer will be to take care of the metaverse, that is, to keep digital worlds running and host the activities of millions of users, even simultaneously, without slowdowns or resource problems.

Artificial intelligence will also be used to scan and process in real time the enormous amount of data produced every second by the users' activities in the EYE-AI metaverse to enable other situations

Enabling you to make your own avatar

Although in the metaverse potentially no one knows who you are, there will be situations - such as business meetings hosted in the metaverse - where disguising yourself behind a nickname and a Salvador Dali mask may not be commonly accepted behavior. In these environments it will be necessary, and useful, to be present not only with one's real name, but also with an avatar that looks as much like us as possible. EYE-AI can help here too, with models that analyze our photos and recreate a 3D avatar in our image and likeness.

Facilitating simultaneous translations

Real-time translation is one of the use cases that will dedicate part of your supercomputer specifically for this activity. The idea here is to enable groups of people from different countries, each speaking a different language, to speak and understand each other in real time. To do this, the artificial intelligence model will first need to recognize the language spoken by one user, interpret each word and recognize the meaning, translate it correctly into the language spoken by the other interlocutor, and generate the translated text in audio format, perhaps with the same voice as the first interlocutor (an audio deepfake would need to be used to simulate the voice).

Moderating and identifying harmful behavior

As already reported in some news stories, the metaverse is not free from typically human problems, such as harassment or bullying. These are challenges that all platforms need to address, because they don't want their great project to be ruined by the harasser next door.

Artificial intelligence already helps human moderators intercept and examine suspicious behavior; in the metaverse, these controls will only increase. Let's not forget that in virtual reality every movement of our avatar can be easily recorded and documented, as can every word we say or hear. As the immersion and sophistication of the devices increase - think of the body trackers we referred to earlier - the data points that can be intercepted and analyzed by AI will only increase.

With this amount of information, it would not be impossible to create models that calculate the probability that harassment is happening (or is about to happen). If enough data were available, it would be enough to analyze all the behaviors occurring before, during, and after reports of harassment to create a model that could recognize or predict them with good accuracy.

A system, hypothetical at the moment, that would potentially be very useful in allowing everyone to enjoy a digital experience without disruption or offense, but which also raises several questions, such as how much intrusion we are willing to allow in our private digital interactions.