Omar Maher provides a comprehensive look at the adoption, developments, and challenges in the world of Synthetic Data Generation.
Omar Maher is Director of Product Marketing at Parallel Domain, a startup that is advancing machine perception capabilities by harnessing the power of synthetic data. We delve into the growing adoption of synthetic data and the factors driving its use. We discuss major developments in synthetic data generation and its overlap with Generative AI. The conversation also covers data privacy, intellectual property, the generation of structured data like LiDAR, the current state of adoption, and key research directions to overcome existing challenges.
Interview highlights – key sections from the video version:
- Who’s using synthetic data, and what motivates AI teams to start using synthetic data?
- What are some of the major developments in the field of synthetic data?
- Why do teams need synthetic data, and what are some key features they ask for?
- Generating synthetic video data
- What is the overlap between tools for synthetic data generation and GenerativeAI?
- Digital twins and digital cousins
- Data privacy, intellectual property, and synthetic data
- Generating synthetic structured data (LiDAR)
- How mainstream is synthetic data today?
- Synthetic data generation: current challenges and key research directions
- A video version of this conversation is available on our YouTube channel.
- Jinsung Yoon and Sercan Arik: Generating high-fidelity and privacy-preserving synthetic data
- Jakub Zavrel: Uncovering and Highlighting AI Trends
- Peter Norvig and Alfred Spector: Data Science and AI in Context
- Yashar Behzadi: Synthetic data technologies can enable more capable and ethical AI
- Parisa Rashidi: Machine Learning in Healthcare
- Gabriela Zanfir-Fortuna and Andrew Burt: Preparing for the Implementation of the EU AI Act and Other AI Regulations
- Jian Pei: Pricing Data Products
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[Image: Synthetic Data Generation – by Ben Lorica, using images from Infogram.]