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Synthetic Data Will Enable Data-Centric AI and the Metaverse – What to Expect in 2022

By Yashar Behzadi, CEO and Founder of Synthesis AI

It is not surprising that 2021 was a year of evolution for society, business, and technology, due to the ever-changing impact of the COVID-19 global pandemic. Artificial Intelligence (AI) and other emerging technologies such as synthetic data have played a major role in enabling this transformation. A recent report from Synthesis AI found that 89% of decision-makers believe that synthetic data will be critical to the future of many industries and will lead to widespread change, indicating that these technologies will only continue to impact organizations in all sectors as we enter the new year.

Here are a few predictions for the evolution and adoption of AI and synthetic data technologies in 2022.

The Conversation Around Data for AI Will Be Prioritized

While it is true that data is the new “oil” and arguably the most valuable modern business asset, the lack of sufficiently diverse and high-quality data is often the catalyst to the downfall of many AI projects. Historically, the vast majority of the development effort is concentrated on the model itself, and as a result, hundreds of hours can be wasted on tuning a model built on low-quality data. If data is the most critical aspect for building AI systems, we need to continue the conversation around how we talk and think about the systems to acquire, prepare, and monitor data to ensure performance and lack of bias. Unlike “one and done” model-centric approaches, like oil, data for AI needs to be refined and put into a functioning engine in order to be useful.

At its core, data-centric AI optimization involves a paradigm shift over the way AI systems are developed, emphasizing the role of good data as the cause of good model performance as opposed to the specifics of the model. Organizations will have to prioritize a data-first approach within an enterprise architecture in 2022 to enable AI and analytics to solve problems and facilitate new revenue streams. This revolution – more simply a new line of thinking – will be the key to success for AI in the enterprise.

Synthetic Data Will Be a Requirement to Build the Metaverse

Talks of the metaverse have been dominating headlines–and for good reasons. The metaverse is a bold vision for the next iteration of the Internet consisting of interconnected virtual spaces, and it has the potential to revolutionize the way we work and play. Major players such as Facebook, Microsoft, and Apple, to name a few, have made significant investments in this digital world, indicating that it is not going away anytime soon. In order to recreate reality as a digital twin, it is necessary to deeply understand humans, objects, 3D environments, and their interactions with one another. Creating these AI capabilities requires tremendous amounts of high-quality labeled 3D data–data that is impossible for humans to label. We are incapable of labeling distance in 3D space, inferring material properties or labeling light sources needed to recreate spaces in high-fidelity.

Organizations need to invest heavily in the tools and technologies that will enable them to get to market quickly, and synthetic data is poised to rise to the challenge. Simply put, the metaverse cannot be built without the use of synthetic data. Using a combination of generative AI models and visual effects (VFX), synthetic data technologies will be a key enabler of the AI models required to power new metaverse applications.

As we enter 2022, there is no doubt that the momentum around AI and other technologies will continue to transform our lives. Each wave of AI innovation builds upon the last, and synthetic data’s opportunity to ensure data quality and mapping to the metaverse is no different.

Synthetic data will come to define a new paradigm in AI and enable the next generation of more capable models and products in 2022 and beyond.

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ABOUT THE AUTHOR

Yashar Behzadi, Ph.D., is the CEO and Founder of Synthesis AI. He is an experienced entrepreneur who has built transformative businesses in AI, medical technology, and IoT markets. He has spent the last 14 years in Silicon Valley building and scaling data-centric technology companies. Yashar has over 30 patents and patents pending and a Ph.D. from UCSD with a focus on spatial-temporal modeling of functional brain imaging.