Category: Synthetic Data Applications

Synthetic Data, Technical Standards & the Metaverse

What role should standards play in the development of the Metaverse? That’s the question we’ll be tackling at our upcoming panel discussion, “Technical Standards for the MetaVerse” as part of the MetaBeat event taking place online and in San Francisco on October 4, 2022. Synthesis AI CEO and founder Yashar Behadi will be joined onstage by Rev Labaredian, NVIDIA; Neil Trevitt, Khronos Group; and Javier Bello Ruiz, IMVERSE. Dean Takahashi, lead writer for GamesBeat, moderates.

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How Synthetic data is used to build the Metaverse

As we discussed in part 1, the Metaverse has the potential to fundamentally alter just about every aspect of human existence. The way we work, play, interact with others, and more is going to move into a virtual reality sooner than many people imagine. With pixel-perfect labeling, synthetic data could be the key to unlocking the metaverse.

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Synthetic data can unlock the Metaverse

The Metaverse has been firmly established in the world of science fiction for decades now. With blockbuster titles like Neuromancer, The Matrix, Ready Player One, and other works of popular media, it is a concept that has long captured the public imagination. With the rapid advances of artificial intelligence and computer imaging technology, we appear to be on the cusp of making it a reality.

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Synthetic Data and the Metaverse

Today, we are talking about the Metaverse, a bold vision for the next iteration of the Internet consisting of interconnected virtual spaces. The Metaverse is a buzzword that had sounded entirely fantastical for a very long time. But lately, it looks like technology is catching up, and we may live to see the Metaverse in the near future. In this post, we discuss how modern artificial intelligence, especially computer vision, is enabling the Metaverse, and how synthetic data is enabling the relevant parts of computer vision.

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Synthetic Data for Safe Driving

The role of synthetic data in developing solutions for autonomous driving is hard to understate. In a recent post, I already touched upon virtual outdoor environments for training autonomous driving agents, and this is a huge topic that we will no doubt return to later. But today, I want to talk about a much more specialized topic in the same field: driver safety monitoring. It turns out that synthetic data can help here as well—and today we will understand how. This is a companion post for our recent press release.

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Synthetic Data Case Studies: It Just Works

In this (very) long post, we present an entire whitepaper on synthetic data, proving that synthetic data works even without complicated domain adaptation techniques in a wide variety of practical applications. We consider three specific problems, all related to human faces, show that synthetic data works for all three, and draw some other interesting and important conclusions.

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Top 5 Applications of Synthetic Data

It’s been a while since we last met on this blog. Today, we are having a brief interlude in the long series of posts on how to make machine learning models better with synthetic data (that’s a long and still unfinished series: Part I, Part II, Part III, Part IV, Part V, Part VI). I will give a brief overview of five primary fields where synthetic data can shine. You will see that most of them are related to computer vision, which is natural for synthetic data based on 3D models. Still, it makes sense to clarify where exactly synthetic data is already working well and where we expect synthetic data to shine in the nearest future.

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Synthesis AI speaking at the MetaBeat conference on Oct 4th

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