Autonomous Systems
January 9, 2026
Explore synthetic data vs real data for robotics, including simulation, real-world datasets, and sim-to-real techniques for scalable robot training.
Discover how AI for renewable energy and waste management is creating cleaner and more efficient systems for a sustainable future.
Discover how model distillation makes large language models more efficient, affordable, and scalable for real-world AI applications.
Learn when a computer vision annotation tool adds value and when human review is needed to fix errors, refine labels, and ensure accuracy.
Learn what vector similarity search is, how it works, and why it's essential for AI systems handling text, image, and voice-based search queries.
Learn why AI agent evaluation depends on their trajectories, the actions and decisions they take, and how these pathways shape transparency and trust.
Learn how image annotation works, explore different types of image annotations, and see how accurate data labeling improves computer vision model performance.
Discover how to improve inter-rater reliability (IRR) in data annotation to enhance model accuracy, reduce inconsistencies, and build more reliable AI systems.
Learn how LiDAR and 3D point clouds go beyond autonomous vehicles to drive real-world innovation in urban planning, warehousing, construction, and farming.
