Siggraph preview: How Nvidia envisions the omniverse as a powerful productivity tool

Disclosure: Nvidia is a client of the author.

Next week at Siggraph, Nvidia will be talking about its Omniverse offering, which contrasts sharply with the much-overhyped metaverse. What makes Nvidia’s effort powerful isn’t just that it’s being wrapped with services from companies like Siemens and used for cutting-edge autonomous factories like BMW’s latest, but its ability to anticipate and correct problems early on before they result in cost overruns or injuries. 

I also wish more companies understood is how much richer Nvidia’s presentations are in general because they use tools like Omniverse to create them. (This video of the last GTC keynote demonstrates the point.) Rather than relying on static word slides, the video experience from an Nvidia keynote better conveys the message while keeping the audience glued to the screen in a way that few speakers do today, proving you don’t need to be Steve Jobs if you have the right tools and spend the time on multimedia tools to entertain and inform. 

Nvidia at Siggraph

Nvidia is expected to talk about its progress with its Omniverse tool and the short-term future of these efforts. Much of what is driving the advance of Omniverse at the moment are the underlying concepts of digital twins and AI — one can’t reliably exist without the other. To be viable, digital twins not only have to initially emulate the real world but must stay connected to their physical counterparts to assure related simulations can accurately predict future events.  Without that connection, any variances between the physical element being emulated and the digital twin will introduce a growing number of unknown errors, which will reduce the accuracy of the result at an increasing rate because of the disconnect.

This is particularly problematic if, when used for factories and automobiles, the system attempts to come up with methodologies that blend these two elements. The result might not adequately predict future problems, and decision makers would have no way to understand the related risks in believing something that’s increasingly unreliable. 

AI is critical not only to making sure the physical world and its related digital twin remain connected (by bridging information gaps sensors can’t yet collect), but also by predicting the future behavior of these elements so problems can be identified early on. Nvidia’s approach to aggressively use AI in its Omniverse tool should provide a far higher degree of accuracy and reliability to any related metaverse simulation, which translates to more reliable outcomes.

Copyright © 2022 IDG Communications, Inc.

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