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

Disclosure: Nvidia is a customer of the author.

Next week in SiggraphNvidia will talk about it Omniverse proposal, which contrasts sharply with the much-hyped metaverse. What makes Nvidia’s effort powerful isn’t just that it’s wrapped in services from companies like Siemens and used for cutting-edge autonomous factories like BMW’s latest, but its ability to predict and fix problems at an early stage, before they lead to cost overruns or injuries.

I also wish more companies understood how much richer Nvidia presentations are in general because they use tools like Omniverse to create them. (This video from the latest GTC keynote demonstrates the point.) Instead of relying on static word slides, the video experience from Nvidia’s keynote better conveys the message while keeping the audience glued to the screen in a way that few speakers do today, proving that you don’t have to be Steve Job if you have the right tools and spend 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 near-term future of that effort. A big part of what’s driving Omniverse’s progress right now is the core concepts of digital twins and AI – one cannot reliably exist without the other. To be viable, digital twins must not only initially mimic the real world, but must remain connected to their physical counterparts to ensure that the linked simulations can accurately predict future events. Without this connection, any differences between the physical item being emulated and the digital twin will introduce an increasing number of unknown errors, reducing the accuracy of the result at an increasing rate due to the disconnection.

This is particularly problematic if, when used for factories and cars, the system tries to come up with methodologies that combine these two elements. The result may not adequately predict future problems, and decision makers will have no way of understanding the risks involved in believing something that is increasingly unreliable.

AI is critical not only to ensure that the physical world and its associated digital twin remain connected (by bridging information gaps that sensors cannot yet gather), but also by predicting the future behavior of these elements , so that problems can be identified at an early stage. Nvidia’s approach to aggressively using AI in its Omniverse tool should provide a much higher degree of accuracy and reliability to any associated metaverse simulation, which means more reliable results.