How is generative AI being used to create synthetic data in various industries, and what are the most promising applications you’ve observed or foreseen?
In what scenarios might synthetic data fall short compared to real-world data, and how does synthetic data complement real-world data in enhancing the robustness of AD algorithms?
What are the pros and cons of using multiple single-task AI models versus a single foundation model for various tasks?
How are advancements in AI, ML, and computer graphics contributing to more effective world simulation?
From proof-of-concepts to production, how to deploy generative AI applications at scale?
AI, Machine Learning, Reinforcement Learning, Deep Learning
Data Management, Fusion, Labelling, Annotation, Storage