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Building Real-World Systems with Synthetic Data: Wise? | Intel Technology

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Can you trust “fake” data?

In this What That Means video, Camille talks with Selvakumar Panneer and Omesh Tickoo, Principal Engineers at Intel Labs. They get into why many industries are using synthetic data along with how synthetic data will change how future generations do things.

What Is Synthetic Data, and How It’s Used

Synthetic data is “fake” in that it has been artificially generated using a computer, but it’s very much based on data collected in the real world. It can be generated either by using AI or by using programming models. Selvakumar and Omesh share with Camille the many different ways synthetic data is used in a variety of industries, from industrial purposes to autonomous systems to entertainment media. All these industries use synthetic data to vastly improve the work they are already doing.

In the movie and video game industries, synthetic data is a valuable asset to train artificial intelligence with it for visual effects. Selvakumar gives some insight into how visual effects artists are using synthetic data-trained AI to create realistic-looking graphics for things like backgrounds or even digital twins of real people.

However, there are also unintended consequences of synthetic data related to ethical and responsible use. While using it allows for more control and flexibility when creating sophisticated models, users always need to update their systems and be aware of potential bias going into the data.

Building the Future with Synthetic Data

If this is what synthetic data looks like today, what does it mean for the future? Artists are increasingly going to use generative AI to improve their workflow and build their creativity on top of it, but that’s not all. Synthetic data will be more and more involved in generating visual effects, creating new content, and training autonomous models.

To fully get there, there are a few hurdles synthetic data will have to overcome. First is platform performance issues, which are currently bogged down at times from the massive computing power and memory required for handling synthetic data. A second challenge is exposing AI models to enough of the natural world to create more realistic data. One more area of concern is the growing inability to tell the difference between reality and synthetic data, such as deep fakes.

Even with these challenges, Selvakumar and Omesh see a bright future ahead. What’s being built today with synthetic data and artificial intelligence will be the foundation for the upcoming Gen Z and Gen Alpha to work off of and get even more creative with.

Omesh Tickoo, Intel Labs Principal Engineer

Omesh Tickoo synthetic data

Omesh Tickoo has spent almost two decades at Intel. Joining first in 2005 as a Senior Research Scientist and Engineering Manager, he has now been a Principal Engineer since 2015. Prior to Intel, Omesh received a Ph.D. in ECSE (Electrical, Computer, and Systems Engineering) from Rensselaer Polytechnic Institute. He now also volunteers as an instructor with Logical Minds to teach kids about programming fundamentals and logical thinking.

Selvakumar Panneer, Intel Labs Principal Engineer

Selvakumar Panneer synthetic data

Selvakumar is certainly an expert in synthetic data, having over 25 years in interactive graphics research, 3D graphics and gaming, and GPU driver development. His first period of time with Intel was as a Senior Software Engineer from 1999-2004. Selvakumar then re-joined Intel in 2009 as a Graphics Staff Engineer, working his way up to Senior Graphics SW Architect and now Principal Engineer in Graphics & AI.

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The views and opinions expressed are those of the guests and author and do not necessarily reflect the official policy or position of Intel Corporation.


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