The rise of GenAI models has reframed the discussion around synthetic data. You'll explore what AI-generated synthetic data is, its use today, benefits, limitations, and privacy-preserving aspects with tabular data, alongside a hands-on experience with an open-source tool to create tabular synthetic data.
Discover insights into AI-assisted development tools, understanding lessons learned, common use cases, critical evaluation factors like compliance and future product roadmaps. Learn prompt engineering as a key skill for optimizing AI interactions.
Delve into the advancements in learning-based methodologies in robotics, focusing on scalability and deployability to open-world problems. Explore reinforcement learning and imitation learning paradigms driving the forefront of robot learning systems.
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