Is Virtual Time Travel Possible With Machine Learning and Mixed Reality?

Is Virtual Time Travel Possible With Machine Learning and Mixed Reality?

Naveen Joshi 05/10/2022
Is Virtual Time Travel Possible With Machine Learning and Mixed Reality?

The concept of virtual time travel sounds like a far-off fantasy, doesn’t it?

But what if, for a brief period, you were able to live in the past without the need for teleportation? This may be viable in the near future, according to researchers, due to advancements that can enable time travel through machine learning and mixed reality technology.

A group of over 225 European academic institutes from 32 different nations is working to create a virtual time machine despite the fact that real-time travel is inconceivable as of now. This time machine is envisioned to be a substantial database that can hold, analyze and link many types of historical data, ranging from text and graphics via mapping and 3D models to music and other sensory stimuli. For this, machine learning and mixed reality need to be brought together. The project seeks to provide historical reconstructions at a degree of detail that is unprecedented.

Mixed reality combines the physical and digital realms allowing for more natural and intuitive 3D interactions between people, machines and their surroundings. The advent of computer vision, graphics processing, display technologies, interactive applications and cloud computing are the bedrock of this new world. 

The most popular mixed reality options available now are the augmented reality (AR) filters we find on social media platforms. The Instagram AR filters widely used today are actually mixed reality applications. The same technology that can today reshape our face to look a few years older or younger can potentially act like a time machine in a truer sense.

How Will The Time Machine Work?

Consider how, for instance, photorealistic rendering and 3D scanning are assisting in the preservation of our cultural heritage, how cameras enable us to capture priceless moments in 360-degree stereoscopic vision, and how volumetric video can even capture whole, dynamic worlds in 3D and 360-degrees. These technologies can be effective means of immersing ourselves in the past as well as simulating envisioned versions of the future because of the improvement in recording fidelity and the VR displays through which we see them. The role of the time machine is to link all the information and reconstruct plausible views of the past. Finally, it should allow us to navigate all this data in order to move in time and space as easily as we do on the internet today.

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Challenges to Time Travel Through Machine Learning

The project described above faces a number of challenges which can be categorized into three parts: data and digitalization, knowledge extraction and modeling, and the possibilities and constraints of such a digital epistemology.

Unsurprisingly, this consortium working on a time travel through machine learning currently includes large organizations like Ubisoft, well-known for its Assassin's Creed video game series. They have already come extremely close to fulfilling the Time Machine Project's objective with their time machine, the Animus, which allows users to experience the past firsthand by going back in time to the lives of their ancestors. Researchers working on the Time Machine Project think that while this objective is still far from being realized, it will revolutionize the historical study and spawn countless other beneficial applications.

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Naveen Joshi

Tech Expert

Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.

   
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